html_url
stringlengths 48
51
| title
stringlengths 5
155
| comments
stringlengths 63
15.7k
| body
stringlengths 0
17.7k
| comment_length
int64 16
949
| text
stringlengths 164
23.7k
|
|---|---|---|---|---|---|
https://github.com/huggingface/datasets/issues/853 | concatenate_datasets support axis=0 or 1 ？ | @lhoestq, we have two Pull Requests to implement:
- Dataset.add_item: #1870
- Dataset.add_column: #2145
which add a single row or column, repectively.
The request here is to implement the concatenation of *multiple* rows/columns. Am I right?
We should agree on the API:
- `concatenate_datasets` with `axis`?
- other Dataset method name? | I want to achieve the following result
| 51 | concatenate_datasets support axis=0 or 1 ？
I want to achieve the following result
@lhoestq, we have two Pull Requests to implement:
- Dataset.add_item: #1870
- Dataset.add_column: #2145
which add a single row or column, repectively.
The request here is to implement the concatenation of *multiple* rows/columns. Am I right?
We should agree on the API:
- `concatenate_datasets` with `axis`?
- other Dataset method name? |
https://github.com/huggingface/datasets/issues/853 | concatenate_datasets support axis=0 or 1 ？ | For the API, I like `concatenate_datasets` with `axis` personally :)
From a list of `Dataset` objects, it would concatenate them to a new `Dataset` object backed by a `ConcatenationTable`, that is the concatenation of the tables of each input dataset. The concatenation is either on axis=0 (append rows) or on axis=1 (append columns).
Regarding what we need to implement:
The axis=0 is already supported and is the current behavior of `concatenate_datasets`.
Also `add_item` is not needed to implement axis=1 (though it's an awesome addition to this library).
To implement axis=1, we either need `add_column` or a `ConcatenationTable` constructor to concatenate tables horizontally.
I have a preference for using a `ConcatenationTable` constructor because this way we can end up with a `ConcatenationTable` with only 1 additional block per table, while `add_column` would add 1 block per new column.
Maybe we can simply have an equivalent of `ConcatenationTable.from_tables` but for axis=1 ?
`axis` could also be an argument of `ConcatenationTable.from_tables` | I want to achieve the following result
| 158 | concatenate_datasets support axis=0 or 1 ？
I want to achieve the following result
For the API, I like `concatenate_datasets` with `axis` personally :)
From a list of `Dataset` objects, it would concatenate them to a new `Dataset` object backed by a `ConcatenationTable`, that is the concatenation of the tables of each input dataset. The concatenation is either on axis=0 (append rows) or on axis=1 (append columns).
Regarding what we need to implement:
The axis=0 is already supported and is the current behavior of `concatenate_datasets`.
Also `add_item` is not needed to implement axis=1 (though it's an awesome addition to this library).
To implement axis=1, we either need `add_column` or a `ConcatenationTable` constructor to concatenate tables horizontally.
I have a preference for using a `ConcatenationTable` constructor because this way we can end up with a `ConcatenationTable` with only 1 additional block per table, while `add_column` would add 1 block per new column.
Maybe we can simply have an equivalent of `ConcatenationTable.from_tables` but for axis=1 ?
`axis` could also be an argument of `ConcatenationTable.from_tables` |
https://github.com/huggingface/datasets/issues/849 | Load amazon dataset | Thanks for reporting !
We plan to show information about the different configs of the datasets on the website, with the corresponding `load_dataset` calls.
Also I think the bullet points formatting has been fixed | Hi,
I was going through amazon_us_reviews dataset and found that example API usage given on website is different from the API usage while loading dataset.
Eg. what API usage is on the [website](https://huggingface.co/datasets/amazon_us_reviews)
```
from datasets import load_dataset
dataset = load_dataset("amazon_us_reviews")
```
How it is when I tried (the error generated does point me to the right direction though)
```
from datasets import load_dataset
dataset = load_dataset("amazon_us_reviews", 'Books_v1_00')
```
Also, there is some issue with formatting as it's not showing bullet list in description with new line. Can I work on it? | 34 | Load amazon dataset
Hi,
I was going through amazon_us_reviews dataset and found that example API usage given on website is different from the API usage while loading dataset.
Eg. what API usage is on the [website](https://huggingface.co/datasets/amazon_us_reviews)
```
from datasets import load_dataset
dataset = load_dataset("amazon_us_reviews")
```
How it is when I tried (the error generated does point me to the right direction though)
```
from datasets import load_dataset
dataset = load_dataset("amazon_us_reviews", 'Books_v1_00')
```
Also, there is some issue with formatting as it's not showing bullet list in description with new line. Can I work on it?
Thanks for reporting !
We plan to show information about the different configs of the datasets on the website, with the corresponding `load_dataset` calls.
Also I think the bullet points formatting has been fixed |
https://github.com/huggingface/datasets/issues/848 | Error when concatenate_datasets | As you can see in the error the test checks if `indices_mappings_in_memory` is True or not, which is different from the test you do in your script. In a dataset, both the data and the indices mapping can be either on disk or in memory.
The indices mapping correspond to a mapping on top of the data table that is used to re-order/select a sample of the original data table. For example if you do `dataset.train_test_split`, then the resulting train and test datasets will have both an indices mapping to tell which examples are in train and which ones in test.
Before saving your datasets on disk, you should call `dataset.flatten_indices()` to remove the indices mapping. It should fix your issue. Under the hood it will create a new data table using the indices mapping. The new data table is going to be a subset of the old one (for example taking only the test set examples), and since the indices mapping will be gone you'll be able to concatenate your datasets.
| Hello, when I concatenate two dataset loading from disk, I encountered a problem:
```
test_dataset = load_from_disk('data/test_dataset')
trn_dataset = load_from_disk('data/train_dataset')
train_dataset = concatenate_datasets([trn_dataset, test_dataset])
```
And it reported ValueError blow:
```
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-38-74fa525512ca> in <module>
----> 1 train_dataset = concatenate_datasets([trn_dataset, test_dataset])
/opt/miniconda3/lib/python3.7/site-packages/datasets/arrow_dataset.py in concatenate_datasets(dsets, info, split)
2547 "However datasets' indices {} come from memory and datasets' indices {} come from disk.".format(
2548 [i for i in range(len(dsets)) if indices_mappings_in_memory[i]],
-> 2549 [i for i in range(len(dsets)) if not indices_mappings_in_memory[i]],
2550 )
2551 )
ValueError: Datasets' indices should ALL come from memory, or should ALL come from disk.
However datasets' indices [1] come from memory and datasets' indices [0] come from disk.
```
But it's curious both of my datasets loading from disk, so I check the source code in `arrow_dataset.py` about the Error:
```
trn_dataset._data_files
# output
[{'filename': 'data/train_dataset/csv-train.arrow', 'skip': 0, 'take': 593264}]
test_dataset._data_files
# output
[{'filename': 'data/test_dataset/csv-test.arrow', 'skip': 0, 'take': 424383}]
print([not dset._data_files for dset in [trn_dataset, test_dataset]])
# [False, False]
# And I tested the code the same as arrow_dataset, but nothing happened
dsets = [trn_dataset, test_dataset]
dsets_in_memory = [not dset._data_files for dset in dsets]
if any(dset_in_memory != dsets_in_memory[0] for dset_in_memory in dsets_in_memory):
raise ValueError(
"Datasets should ALL come from memory, or should ALL come from disk.\n"
"However datasets {} come from memory and datasets {} come from disk.".format(
[i for i in range(len(dsets)) if dsets_in_memory[i]],
[i for i in range(len(dsets)) if not dsets_in_memory[i]],
)
)
```
Any suggestions would be greatly appreciated!
Thanks! | 172 | Error when concatenate_datasets
Hello, when I concatenate two dataset loading from disk, I encountered a problem:
```
test_dataset = load_from_disk('data/test_dataset')
trn_dataset = load_from_disk('data/train_dataset')
train_dataset = concatenate_datasets([trn_dataset, test_dataset])
```
And it reported ValueError blow:
```
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-38-74fa525512ca> in <module>
----> 1 train_dataset = concatenate_datasets([trn_dataset, test_dataset])
/opt/miniconda3/lib/python3.7/site-packages/datasets/arrow_dataset.py in concatenate_datasets(dsets, info, split)
2547 "However datasets' indices {} come from memory and datasets' indices {} come from disk.".format(
2548 [i for i in range(len(dsets)) if indices_mappings_in_memory[i]],
-> 2549 [i for i in range(len(dsets)) if not indices_mappings_in_memory[i]],
2550 )
2551 )
ValueError: Datasets' indices should ALL come from memory, or should ALL come from disk.
However datasets' indices [1] come from memory and datasets' indices [0] come from disk.
```
But it's curious both of my datasets loading from disk, so I check the source code in `arrow_dataset.py` about the Error:
```
trn_dataset._data_files
# output
[{'filename': 'data/train_dataset/csv-train.arrow', 'skip': 0, 'take': 593264}]
test_dataset._data_files
# output
[{'filename': 'data/test_dataset/csv-test.arrow', 'skip': 0, 'take': 424383}]
print([not dset._data_files for dset in [trn_dataset, test_dataset]])
# [False, False]
# And I tested the code the same as arrow_dataset, but nothing happened
dsets = [trn_dataset, test_dataset]
dsets_in_memory = [not dset._data_files for dset in dsets]
if any(dset_in_memory != dsets_in_memory[0] for dset_in_memory in dsets_in_memory):
raise ValueError(
"Datasets should ALL come from memory, or should ALL come from disk.\n"
"However datasets {} come from memory and datasets {} come from disk.".format(
[i for i in range(len(dsets)) if dsets_in_memory[i]],
[i for i in range(len(dsets)) if not dsets_in_memory[i]],
)
)
```
Any suggestions would be greatly appreciated!
Thanks!
As you can see in the error the test checks if `indices_mappings_in_memory` is True or not, which is different from the test you do in your script. In a dataset, both the data and the indices mapping can be either on disk or in memory.
The indices mapping correspond to a mapping on top of the data table that is used to re-order/select a sample of the original data table. For example if you do `dataset.train_test_split`, then the resulting train and test datasets will have both an indices mapping to tell which examples are in train and which ones in test.
Before saving your datasets on disk, you should call `dataset.flatten_indices()` to remove the indices mapping. It should fix your issue. Under the hood it will create a new data table using the indices mapping. The new data table is going to be a subset of the old one (for example taking only the test set examples), and since the indices mapping will be gone you'll be able to concatenate your datasets.
|
https://github.com/huggingface/datasets/issues/848 | Error when concatenate_datasets | > As you can see in the error the test checks if `indices_mappings_in_memory` is True or not, which is different from the test you do in your script. In a dataset, both the data and the indices mapping can be either on disk or in memory.
>
> The indices mapping correspond to a mapping on top of the data table that is used to re-order/select a sample of the original data table. For example if you do `dataset.train_test_split`, then the resulting train and test datasets will have both an indices mapping to tell which examples are in train and which ones in test.
>
> Before saving your datasets on disk, you should call `dataset.flatten_indices()` to remove the indices mapping. It should fix your issue. Under the hood it will create a new data table using the indices mapping. The new data table is going to be a subset of the old one (for example taking only the test set examples), and since the indices mapping will be gone you'll be able to concatenate your datasets.
`dataset.flatten_indices()` solved my problem, thanks so much! | Hello, when I concatenate two dataset loading from disk, I encountered a problem:
```
test_dataset = load_from_disk('data/test_dataset')
trn_dataset = load_from_disk('data/train_dataset')
train_dataset = concatenate_datasets([trn_dataset, test_dataset])
```
And it reported ValueError blow:
```
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-38-74fa525512ca> in <module>
----> 1 train_dataset = concatenate_datasets([trn_dataset, test_dataset])
/opt/miniconda3/lib/python3.7/site-packages/datasets/arrow_dataset.py in concatenate_datasets(dsets, info, split)
2547 "However datasets' indices {} come from memory and datasets' indices {} come from disk.".format(
2548 [i for i in range(len(dsets)) if indices_mappings_in_memory[i]],
-> 2549 [i for i in range(len(dsets)) if not indices_mappings_in_memory[i]],
2550 )
2551 )
ValueError: Datasets' indices should ALL come from memory, or should ALL come from disk.
However datasets' indices [1] come from memory and datasets' indices [0] come from disk.
```
But it's curious both of my datasets loading from disk, so I check the source code in `arrow_dataset.py` about the Error:
```
trn_dataset._data_files
# output
[{'filename': 'data/train_dataset/csv-train.arrow', 'skip': 0, 'take': 593264}]
test_dataset._data_files
# output
[{'filename': 'data/test_dataset/csv-test.arrow', 'skip': 0, 'take': 424383}]
print([not dset._data_files for dset in [trn_dataset, test_dataset]])
# [False, False]
# And I tested the code the same as arrow_dataset, but nothing happened
dsets = [trn_dataset, test_dataset]
dsets_in_memory = [not dset._data_files for dset in dsets]
if any(dset_in_memory != dsets_in_memory[0] for dset_in_memory in dsets_in_memory):
raise ValueError(
"Datasets should ALL come from memory, or should ALL come from disk.\n"
"However datasets {} come from memory and datasets {} come from disk.".format(
[i for i in range(len(dsets)) if dsets_in_memory[i]],
[i for i in range(len(dsets)) if not dsets_in_memory[i]],
)
)
```
Any suggestions would be greatly appreciated!
Thanks! | 184 | Error when concatenate_datasets
Hello, when I concatenate two dataset loading from disk, I encountered a problem:
```
test_dataset = load_from_disk('data/test_dataset')
trn_dataset = load_from_disk('data/train_dataset')
train_dataset = concatenate_datasets([trn_dataset, test_dataset])
```
And it reported ValueError blow:
```
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-38-74fa525512ca> in <module>
----> 1 train_dataset = concatenate_datasets([trn_dataset, test_dataset])
/opt/miniconda3/lib/python3.7/site-packages/datasets/arrow_dataset.py in concatenate_datasets(dsets, info, split)
2547 "However datasets' indices {} come from memory and datasets' indices {} come from disk.".format(
2548 [i for i in range(len(dsets)) if indices_mappings_in_memory[i]],
-> 2549 [i for i in range(len(dsets)) if not indices_mappings_in_memory[i]],
2550 )
2551 )
ValueError: Datasets' indices should ALL come from memory, or should ALL come from disk.
However datasets' indices [1] come from memory and datasets' indices [0] come from disk.
```
But it's curious both of my datasets loading from disk, so I check the source code in `arrow_dataset.py` about the Error:
```
trn_dataset._data_files
# output
[{'filename': 'data/train_dataset/csv-train.arrow', 'skip': 0, 'take': 593264}]
test_dataset._data_files
# output
[{'filename': 'data/test_dataset/csv-test.arrow', 'skip': 0, 'take': 424383}]
print([not dset._data_files for dset in [trn_dataset, test_dataset]])
# [False, False]
# And I tested the code the same as arrow_dataset, but nothing happened
dsets = [trn_dataset, test_dataset]
dsets_in_memory = [not dset._data_files for dset in dsets]
if any(dset_in_memory != dsets_in_memory[0] for dset_in_memory in dsets_in_memory):
raise ValueError(
"Datasets should ALL come from memory, or should ALL come from disk.\n"
"However datasets {} come from memory and datasets {} come from disk.".format(
[i for i in range(len(dsets)) if dsets_in_memory[i]],
[i for i in range(len(dsets)) if not dsets_in_memory[i]],
)
)
```
Any suggestions would be greatly appreciated!
Thanks!
> As you can see in the error the test checks if `indices_mappings_in_memory` is True or not, which is different from the test you do in your script. In a dataset, both the data and the indices mapping can be either on disk or in memory.
>
> The indices mapping correspond to a mapping on top of the data table that is used to re-order/select a sample of the original data table. For example if you do `dataset.train_test_split`, then the resulting train and test datasets will have both an indices mapping to tell which examples are in train and which ones in test.
>
> Before saving your datasets on disk, you should call `dataset.flatten_indices()` to remove the indices mapping. It should fix your issue. Under the hood it will create a new data table using the indices mapping. The new data table is going to be a subset of the old one (for example taking only the test set examples), and since the indices mapping will be gone you'll be able to concatenate your datasets.
`dataset.flatten_indices()` solved my problem, thanks so much! |
https://github.com/huggingface/datasets/issues/848 | Error when concatenate_datasets | @lhoestq we can add a mention of `dataset.flatten_indices()` in the error message (no rush, just put it on your TODO list or I can do it when I come at it) | Hello, when I concatenate two dataset loading from disk, I encountered a problem:
```
test_dataset = load_from_disk('data/test_dataset')
trn_dataset = load_from_disk('data/train_dataset')
train_dataset = concatenate_datasets([trn_dataset, test_dataset])
```
And it reported ValueError blow:
```
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-38-74fa525512ca> in <module>
----> 1 train_dataset = concatenate_datasets([trn_dataset, test_dataset])
/opt/miniconda3/lib/python3.7/site-packages/datasets/arrow_dataset.py in concatenate_datasets(dsets, info, split)
2547 "However datasets' indices {} come from memory and datasets' indices {} come from disk.".format(
2548 [i for i in range(len(dsets)) if indices_mappings_in_memory[i]],
-> 2549 [i for i in range(len(dsets)) if not indices_mappings_in_memory[i]],
2550 )
2551 )
ValueError: Datasets' indices should ALL come from memory, or should ALL come from disk.
However datasets' indices [1] come from memory and datasets' indices [0] come from disk.
```
But it's curious both of my datasets loading from disk, so I check the source code in `arrow_dataset.py` about the Error:
```
trn_dataset._data_files
# output
[{'filename': 'data/train_dataset/csv-train.arrow', 'skip': 0, 'take': 593264}]
test_dataset._data_files
# output
[{'filename': 'data/test_dataset/csv-test.arrow', 'skip': 0, 'take': 424383}]
print([not dset._data_files for dset in [trn_dataset, test_dataset]])
# [False, False]
# And I tested the code the same as arrow_dataset, but nothing happened
dsets = [trn_dataset, test_dataset]
dsets_in_memory = [not dset._data_files for dset in dsets]
if any(dset_in_memory != dsets_in_memory[0] for dset_in_memory in dsets_in_memory):
raise ValueError(
"Datasets should ALL come from memory, or should ALL come from disk.\n"
"However datasets {} come from memory and datasets {} come from disk.".format(
[i for i in range(len(dsets)) if dsets_in_memory[i]],
[i for i in range(len(dsets)) if not dsets_in_memory[i]],
)
)
```
Any suggestions would be greatly appreciated!
Thanks! | 31 | Error when concatenate_datasets
Hello, when I concatenate two dataset loading from disk, I encountered a problem:
```
test_dataset = load_from_disk('data/test_dataset')
trn_dataset = load_from_disk('data/train_dataset')
train_dataset = concatenate_datasets([trn_dataset, test_dataset])
```
And it reported ValueError blow:
```
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-38-74fa525512ca> in <module>
----> 1 train_dataset = concatenate_datasets([trn_dataset, test_dataset])
/opt/miniconda3/lib/python3.7/site-packages/datasets/arrow_dataset.py in concatenate_datasets(dsets, info, split)
2547 "However datasets' indices {} come from memory and datasets' indices {} come from disk.".format(
2548 [i for i in range(len(dsets)) if indices_mappings_in_memory[i]],
-> 2549 [i for i in range(len(dsets)) if not indices_mappings_in_memory[i]],
2550 )
2551 )
ValueError: Datasets' indices should ALL come from memory, or should ALL come from disk.
However datasets' indices [1] come from memory and datasets' indices [0] come from disk.
```
But it's curious both of my datasets loading from disk, so I check the source code in `arrow_dataset.py` about the Error:
```
trn_dataset._data_files
# output
[{'filename': 'data/train_dataset/csv-train.arrow', 'skip': 0, 'take': 593264}]
test_dataset._data_files
# output
[{'filename': 'data/test_dataset/csv-test.arrow', 'skip': 0, 'take': 424383}]
print([not dset._data_files for dset in [trn_dataset, test_dataset]])
# [False, False]
# And I tested the code the same as arrow_dataset, but nothing happened
dsets = [trn_dataset, test_dataset]
dsets_in_memory = [not dset._data_files for dset in dsets]
if any(dset_in_memory != dsets_in_memory[0] for dset_in_memory in dsets_in_memory):
raise ValueError(
"Datasets should ALL come from memory, or should ALL come from disk.\n"
"However datasets {} come from memory and datasets {} come from disk.".format(
[i for i in range(len(dsets)) if dsets_in_memory[i]],
[i for i in range(len(dsets)) if not dsets_in_memory[i]],
)
)
```
Any suggestions would be greatly appreciated!
Thanks!
@lhoestq we can add a mention of `dataset.flatten_indices()` in the error message (no rush, just put it on your TODO list or I can do it when I come at it) |
https://github.com/huggingface/datasets/issues/847 | multiprocessing in dataset map "can only test a child process" | It looks like an issue with wandb/tqdm here.
We're using the `multiprocess` library instead of the `multiprocessing` builtin python package to support various types of mapping functions. Maybe there's some sort of incompatibility.
Could you make a minimal script to reproduce or a google colab ? | Using a dataset with a single 'text' field and a fast tokenizer in a jupyter notebook.
```
def tokenizer_fn(example):
return tokenizer.batch_encode_plus(example['text'])
ds_tokenized = text_dataset.map(tokenizer_fn, batched=True, num_proc=6, remove_columns=['text'])
```
```
---------------------------------------------------------------------------
RemoteTraceback Traceback (most recent call last)
RemoteTraceback:
"""
Traceback (most recent call last):
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/multiprocess/pool.py", line 119, in worker
result = (True, func(*args, **kwds))
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/datasets/arrow_dataset.py", line 156, in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/datasets/fingerprint.py", line 163, in wrapper
out = func(self, *args, **kwargs)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/datasets/arrow_dataset.py", line 1510, in _map_single
for i in pbar:
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/notebook.py", line 228, in __iter__
for obj in super(tqdm_notebook, self).__iter__(*args, **kwargs):
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/std.py", line 1186, in __iter__
self.close()
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/notebook.py", line 251, in close
super(tqdm_notebook, self).close(*args, **kwargs)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/std.py", line 1291, in close
fp_write('')
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/std.py", line 1288, in fp_write
self.fp.write(_unicode(s))
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/lib/redirect.py", line 91, in new_write
cb(name, data)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/wandb_run.py", line 598, in _console_callback
self._backend.interface.publish_output(name, data)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 146, in publish_output
self._publish_output(o)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 151, in _publish_output
self._publish(rec)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 431, in _publish
if self._process and not self._process.is_alive():
File "/usr/lib/python3.6/multiprocessing/process.py", line 134, in is_alive
assert self._parent_pid == os.getpid(), 'can only test a child process'
AssertionError: can only test a child process
"""
``` | 46 | multiprocessing in dataset map "can only test a child process"
Using a dataset with a single 'text' field and a fast tokenizer in a jupyter notebook.
```
def tokenizer_fn(example):
return tokenizer.batch_encode_plus(example['text'])
ds_tokenized = text_dataset.map(tokenizer_fn, batched=True, num_proc=6, remove_columns=['text'])
```
```
---------------------------------------------------------------------------
RemoteTraceback Traceback (most recent call last)
RemoteTraceback:
"""
Traceback (most recent call last):
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/multiprocess/pool.py", line 119, in worker
result = (True, func(*args, **kwds))
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/datasets/arrow_dataset.py", line 156, in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/datasets/fingerprint.py", line 163, in wrapper
out = func(self, *args, **kwargs)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/datasets/arrow_dataset.py", line 1510, in _map_single
for i in pbar:
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/notebook.py", line 228, in __iter__
for obj in super(tqdm_notebook, self).__iter__(*args, **kwargs):
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/std.py", line 1186, in __iter__
self.close()
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/notebook.py", line 251, in close
super(tqdm_notebook, self).close(*args, **kwargs)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/std.py", line 1291, in close
fp_write('')
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/std.py", line 1288, in fp_write
self.fp.write(_unicode(s))
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/lib/redirect.py", line 91, in new_write
cb(name, data)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/wandb_run.py", line 598, in _console_callback
self._backend.interface.publish_output(name, data)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 146, in publish_output
self._publish_output(o)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 151, in _publish_output
self._publish(rec)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 431, in _publish
if self._process and not self._process.is_alive():
File "/usr/lib/python3.6/multiprocessing/process.py", line 134, in is_alive
assert self._parent_pid == os.getpid(), 'can only test a child process'
AssertionError: can only test a child process
"""
```
It looks like an issue with wandb/tqdm here.
We're using the `multiprocess` library instead of the `multiprocessing` builtin python package to support various types of mapping functions. Maybe there's some sort of incompatibility.
Could you make a minimal script to reproduce or a google colab ? |
https://github.com/huggingface/datasets/issues/847 | multiprocessing in dataset map "can only test a child process" | hi facing the same issue here -
`AssertionError: Caught AssertionError in DataLoader worker process 0.
Original Traceback (most recent call last):
File "/usr/lib/python3.6/logging/__init__.py", line 996, in emit
stream.write(msg)
File "/usr/local/lib/python3.6/dist-packages/wandb/sdk/lib/redirect.py", line 100, in new_write
cb(name, data)
File "/usr/local/lib/python3.6/dist-packages/wandb/sdk/wandb_run.py", line 723, in _console_callback
self._backend.interface.publish_output(name, data)
File "/usr/local/lib/python3.6/dist-packages/wandb/sdk/interface/interface.py", line 153, in publish_output
self._publish_output(o)
File "/usr/local/lib/python3.6/dist-packages/wandb/sdk/interface/interface.py", line 158, in _publish_output
self._publish(rec)
File "/usr/local/lib/python3.6/dist-packages/wandb/sdk/interface/interface.py", line 456, in _publish
if self._process and not self._process.is_alive():
File "/usr/lib/python3.6/multiprocessing/process.py", line 134, in is_alive
assert self._parent_pid == os.getpid(), 'can only test a child process'
AssertionError: can only test a child process
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/usr/local/lib/python3.6/dist-packages/torch/utils/data/_utils/worker.py", line 198, in _worker_loop
data = fetcher.fetch(index)
File "/usr/local/lib/python3.6/dist-packages/torch/utils/data/_utils/fetch.py", line 44, in fetch
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/usr/local/lib/python3.6/dist-packages/torch/utils/data/_utils/fetch.py", line 44, in <listcomp>
data = [self.dataset[idx] for idx in possibly_batched_index]
File "<ipython-input-8-a4d9a08d114e>", line 20, in __getitem__
return_token_type_ids=True
File "/usr/local/lib/python3.6/dist-packages/transformers/tokenization_utils_base.py", line 2405, in encode_plus
**kwargs,
File "/usr/local/lib/python3.6/dist-packages/transformers/tokenization_utils_base.py", line 2125, in _get_padding_truncation_strategies
"Truncation was not explicitly activated but `max_length` is provided a specific value, "
File "/usr/lib/python3.6/logging/__init__.py", line 1320, in warning
self._log(WARNING, msg, args, **kwargs)
File "/usr/lib/python3.6/logging/__init__.py", line 1444, in _log
self.handle(record)
File "/usr/lib/python3.6/logging/__init__.py", line 1454, in handle
self.callHandlers(record)
File "/usr/lib/python3.6/logging/__init__.py", line 1516, in callHandlers
hdlr.handle(record)
File "/usr/lib/python3.6/logging/__init__.py", line 865, in handle
self.emit(record)
File "/usr/lib/python3.6/logging/__init__.py", line 1000, in emit
self.handleError(record)
File "/usr/lib/python3.6/logging/__init__.py", line 917, in handleError
sys.stderr.write('--- Logging error ---\n')
File "/usr/local/lib/python3.6/dist-packages/wandb/sdk/lib/redirect.py", line 100, in new_write
cb(name, data)
File "/usr/local/lib/python3.6/dist-packages/wandb/sdk/wandb_run.py", line 723, in _console_callback
self._backend.interface.publish_output(name, data)
File "/usr/local/lib/python3.6/dist-packages/wandb/sdk/interface/interface.py", line 153, in publish_output
self._publish_output(o)
File "/usr/local/lib/python3.6/dist-packages/wandb/sdk/interface/interface.py", line 158, in _publish_output
self._publish(rec)
File "/usr/local/lib/python3.6/dist-packages/wandb/sdk/interface/interface.py", line 456, in _publish
if self._process and not self._process.is_alive():
File "/usr/lib/python3.6/multiprocessing/process.py", line 134, in is_alive
assert self._parent_pid == os.getpid(), 'can only test a child process'
AssertionError: can only test a child process`
| Using a dataset with a single 'text' field and a fast tokenizer in a jupyter notebook.
```
def tokenizer_fn(example):
return tokenizer.batch_encode_plus(example['text'])
ds_tokenized = text_dataset.map(tokenizer_fn, batched=True, num_proc=6, remove_columns=['text'])
```
```
---------------------------------------------------------------------------
RemoteTraceback Traceback (most recent call last)
RemoteTraceback:
"""
Traceback (most recent call last):
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/multiprocess/pool.py", line 119, in worker
result = (True, func(*args, **kwds))
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/datasets/arrow_dataset.py", line 156, in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/datasets/fingerprint.py", line 163, in wrapper
out = func(self, *args, **kwargs)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/datasets/arrow_dataset.py", line 1510, in _map_single
for i in pbar:
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/notebook.py", line 228, in __iter__
for obj in super(tqdm_notebook, self).__iter__(*args, **kwargs):
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/std.py", line 1186, in __iter__
self.close()
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/notebook.py", line 251, in close
super(tqdm_notebook, self).close(*args, **kwargs)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/std.py", line 1291, in close
fp_write('')
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/std.py", line 1288, in fp_write
self.fp.write(_unicode(s))
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/lib/redirect.py", line 91, in new_write
cb(name, data)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/wandb_run.py", line 598, in _console_callback
self._backend.interface.publish_output(name, data)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 146, in publish_output
self._publish_output(o)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 151, in _publish_output
self._publish(rec)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 431, in _publish
if self._process and not self._process.is_alive():
File "/usr/lib/python3.6/multiprocessing/process.py", line 134, in is_alive
assert self._parent_pid == os.getpid(), 'can only test a child process'
AssertionError: can only test a child process
"""
``` | 293 | multiprocessing in dataset map "can only test a child process"
Using a dataset with a single 'text' field and a fast tokenizer in a jupyter notebook.
```
def tokenizer_fn(example):
return tokenizer.batch_encode_plus(example['text'])
ds_tokenized = text_dataset.map(tokenizer_fn, batched=True, num_proc=6, remove_columns=['text'])
```
```
---------------------------------------------------------------------------
RemoteTraceback Traceback (most recent call last)
RemoteTraceback:
"""
Traceback (most recent call last):
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/multiprocess/pool.py", line 119, in worker
result = (True, func(*args, **kwds))
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/datasets/arrow_dataset.py", line 156, in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/datasets/fingerprint.py", line 163, in wrapper
out = func(self, *args, **kwargs)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/datasets/arrow_dataset.py", line 1510, in _map_single
for i in pbar:
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/notebook.py", line 228, in __iter__
for obj in super(tqdm_notebook, self).__iter__(*args, **kwargs):
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/std.py", line 1186, in __iter__
self.close()
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/notebook.py", line 251, in close
super(tqdm_notebook, self).close(*args, **kwargs)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/std.py", line 1291, in close
fp_write('')
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/std.py", line 1288, in fp_write
self.fp.write(_unicode(s))
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/lib/redirect.py", line 91, in new_write
cb(name, data)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/wandb_run.py", line 598, in _console_callback
self._backend.interface.publish_output(name, data)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 146, in publish_output
self._publish_output(o)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 151, in _publish_output
self._publish(rec)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 431, in _publish
if self._process and not self._process.is_alive():
File "/usr/lib/python3.6/multiprocessing/process.py", line 134, in is_alive
assert self._parent_pid == os.getpid(), 'can only test a child process'
AssertionError: can only test a child process
"""
```
hi facing the same issue here -
`AssertionError: Caught AssertionError in DataLoader worker process 0.
Original Traceback (most recent call last):
File "/usr/lib/python3.6/logging/__init__.py", line 996, in emit
stream.write(msg)
File "/usr/local/lib/python3.6/dist-packages/wandb/sdk/lib/redirect.py", line 100, in new_write
cb(name, data)
File "/usr/local/lib/python3.6/dist-packages/wandb/sdk/wandb_run.py", line 723, in _console_callback
self._backend.interface.publish_output(name, data)
File "/usr/local/lib/python3.6/dist-packages/wandb/sdk/interface/interface.py", line 153, in publish_output
self._publish_output(o)
File "/usr/local/lib/python3.6/dist-packages/wandb/sdk/interface/interface.py", line 158, in _publish_output
self._publish(rec)
File "/usr/local/lib/python3.6/dist-packages/wandb/sdk/interface/interface.py", line 456, in _publish
if self._process and not self._process.is_alive():
File "/usr/lib/python3.6/multiprocessing/process.py", line 134, in is_alive
assert self._parent_pid == os.getpid(), 'can only test a child process'
AssertionError: can only test a child process
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/usr/local/lib/python3.6/dist-packages/torch/utils/data/_utils/worker.py", line 198, in _worker_loop
data = fetcher.fetch(index)
File "/usr/local/lib/python3.6/dist-packages/torch/utils/data/_utils/fetch.py", line 44, in fetch
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/usr/local/lib/python3.6/dist-packages/torch/utils/data/_utils/fetch.py", line 44, in <listcomp>
data = [self.dataset[idx] for idx in possibly_batched_index]
File "<ipython-input-8-a4d9a08d114e>", line 20, in __getitem__
return_token_type_ids=True
File "/usr/local/lib/python3.6/dist-packages/transformers/tokenization_utils_base.py", line 2405, in encode_plus
**kwargs,
File "/usr/local/lib/python3.6/dist-packages/transformers/tokenization_utils_base.py", line 2125, in _get_padding_truncation_strategies
"Truncation was not explicitly activated but `max_length` is provided a specific value, "
File "/usr/lib/python3.6/logging/__init__.py", line 1320, in warning
self._log(WARNING, msg, args, **kwargs)
File "/usr/lib/python3.6/logging/__init__.py", line 1444, in _log
self.handle(record)
File "/usr/lib/python3.6/logging/__init__.py", line 1454, in handle
self.callHandlers(record)
File "/usr/lib/python3.6/logging/__init__.py", line 1516, in callHandlers
hdlr.handle(record)
File "/usr/lib/python3.6/logging/__init__.py", line 865, in handle
self.emit(record)
File "/usr/lib/python3.6/logging/__init__.py", line 1000, in emit
self.handleError(record)
File "/usr/lib/python3.6/logging/__init__.py", line 917, in handleError
sys.stderr.write('--- Logging error ---\n')
File "/usr/local/lib/python3.6/dist-packages/wandb/sdk/lib/redirect.py", line 100, in new_write
cb(name, data)
File "/usr/local/lib/python3.6/dist-packages/wandb/sdk/wandb_run.py", line 723, in _console_callback
self._backend.interface.publish_output(name, data)
File "/usr/local/lib/python3.6/dist-packages/wandb/sdk/interface/interface.py", line 153, in publish_output
self._publish_output(o)
File "/usr/local/lib/python3.6/dist-packages/wandb/sdk/interface/interface.py", line 158, in _publish_output
self._publish(rec)
File "/usr/local/lib/python3.6/dist-packages/wandb/sdk/interface/interface.py", line 456, in _publish
if self._process and not self._process.is_alive():
File "/usr/lib/python3.6/multiprocessing/process.py", line 134, in is_alive
assert self._parent_pid == os.getpid(), 'can only test a child process'
AssertionError: can only test a child process`
|
https://github.com/huggingface/datasets/issues/847 | multiprocessing in dataset map "can only test a child process" | It looks like this warning :
"Truncation was not explicitly activated but max_length is provided a specific value, "
is not handled well by wandb.
The error occurs when calling the tokenizer.
Maybe you can try to specify `truncation=True` when calling the tokenizer to remove the warning ?
Otherwise I don't know why wandb would fail on a warning. Maybe one of its logging handlers have some issues with the logging of tokenizers. Maybe @n1t0 knows more about this ? | Using a dataset with a single 'text' field and a fast tokenizer in a jupyter notebook.
```
def tokenizer_fn(example):
return tokenizer.batch_encode_plus(example['text'])
ds_tokenized = text_dataset.map(tokenizer_fn, batched=True, num_proc=6, remove_columns=['text'])
```
```
---------------------------------------------------------------------------
RemoteTraceback Traceback (most recent call last)
RemoteTraceback:
"""
Traceback (most recent call last):
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/multiprocess/pool.py", line 119, in worker
result = (True, func(*args, **kwds))
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/datasets/arrow_dataset.py", line 156, in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/datasets/fingerprint.py", line 163, in wrapper
out = func(self, *args, **kwargs)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/datasets/arrow_dataset.py", line 1510, in _map_single
for i in pbar:
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/notebook.py", line 228, in __iter__
for obj in super(tqdm_notebook, self).__iter__(*args, **kwargs):
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/std.py", line 1186, in __iter__
self.close()
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/notebook.py", line 251, in close
super(tqdm_notebook, self).close(*args, **kwargs)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/std.py", line 1291, in close
fp_write('')
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/std.py", line 1288, in fp_write
self.fp.write(_unicode(s))
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/lib/redirect.py", line 91, in new_write
cb(name, data)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/wandb_run.py", line 598, in _console_callback
self._backend.interface.publish_output(name, data)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 146, in publish_output
self._publish_output(o)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 151, in _publish_output
self._publish(rec)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 431, in _publish
if self._process and not self._process.is_alive():
File "/usr/lib/python3.6/multiprocessing/process.py", line 134, in is_alive
assert self._parent_pid == os.getpid(), 'can only test a child process'
AssertionError: can only test a child process
"""
``` | 80 | multiprocessing in dataset map "can only test a child process"
Using a dataset with a single 'text' field and a fast tokenizer in a jupyter notebook.
```
def tokenizer_fn(example):
return tokenizer.batch_encode_plus(example['text'])
ds_tokenized = text_dataset.map(tokenizer_fn, batched=True, num_proc=6, remove_columns=['text'])
```
```
---------------------------------------------------------------------------
RemoteTraceback Traceback (most recent call last)
RemoteTraceback:
"""
Traceback (most recent call last):
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/multiprocess/pool.py", line 119, in worker
result = (True, func(*args, **kwds))
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/datasets/arrow_dataset.py", line 156, in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/datasets/fingerprint.py", line 163, in wrapper
out = func(self, *args, **kwargs)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/datasets/arrow_dataset.py", line 1510, in _map_single
for i in pbar:
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/notebook.py", line 228, in __iter__
for obj in super(tqdm_notebook, self).__iter__(*args, **kwargs):
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/std.py", line 1186, in __iter__
self.close()
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/notebook.py", line 251, in close
super(tqdm_notebook, self).close(*args, **kwargs)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/std.py", line 1291, in close
fp_write('')
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/std.py", line 1288, in fp_write
self.fp.write(_unicode(s))
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/lib/redirect.py", line 91, in new_write
cb(name, data)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/wandb_run.py", line 598, in _console_callback
self._backend.interface.publish_output(name, data)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 146, in publish_output
self._publish_output(o)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 151, in _publish_output
self._publish(rec)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 431, in _publish
if self._process and not self._process.is_alive():
File "/usr/lib/python3.6/multiprocessing/process.py", line 134, in is_alive
assert self._parent_pid == os.getpid(), 'can only test a child process'
AssertionError: can only test a child process
"""
```
It looks like this warning :
"Truncation was not explicitly activated but max_length is provided a specific value, "
is not handled well by wandb.
The error occurs when calling the tokenizer.
Maybe you can try to specify `truncation=True` when calling the tokenizer to remove the warning ?
Otherwise I don't know why wandb would fail on a warning. Maybe one of its logging handlers have some issues with the logging of tokenizers. Maybe @n1t0 knows more about this ? |
https://github.com/huggingface/datasets/issues/847 | multiprocessing in dataset map "can only test a child process" | I'm having a similar issue but when I try to do multiprocessing with the `DataLoader`
Code to reproduce:
```
from datasets import load_dataset
book_corpus = load_dataset('bookcorpus', 'plain_text', cache_dir='/home/ad/Desktop/bookcorpus', split='train[:1%]')
book_corpus = book_corpus.map(encode, batched=True, num_proc=20, load_from_cache_file=True, batch_size=5000)
book_corpus.set_format(type='torch', columns=['text', "input_ids", "attention_mask", "token_type_ids"])
from transformers import DataCollatorForWholeWordMask
from transformers import Trainer, TrainingArguments
data_collator = DataCollatorForWholeWordMask(
tokenizer=tokenizer, mlm=True, mlm_probability=0.15)
training_args = TrainingArguments(
output_dir="./mobile_linear_att_8L_128_128_03layerdrop_shared",
overwrite_output_dir=True,
num_train_epochs=1,
per_device_train_batch_size=64,
save_steps=50,
save_total_limit=2,
logging_first_step=True,
warmup_steps=100,
logging_steps=50,
gradient_accumulation_steps=1,
fp16=True,
**dataloader_num_workers=10**,
)
trainer = Trainer(
model=model,
args=training_args,
data_collator=data_collator,
train_dataset=book_corpus,
tokenizer=tokenizer)
trainer.train()
```
```
---------------------------------------------------------------------------
AssertionError Traceback (most recent call last)
<timed eval> in <module>
~/anaconda3/envs/tfm/lib/python3.6/site-packages/transformers/trainer.py in train(self, model_path, trial)
869 self.control = self.callback_handler.on_epoch_begin(self.args, self.state, self.control)
870
--> 871 for step, inputs in enumerate(epoch_iterator):
872
873 # Skip past any already trained steps if resuming training
~/anaconda3/envs/tfm/lib/python3.6/site-packages/torch/utils/data/dataloader.py in __next__(self)
433 if self._sampler_iter is None:
434 self._reset()
--> 435 data = self._next_data()
436 self._num_yielded += 1
437 if self._dataset_kind == _DatasetKind.Iterable and \
~/anaconda3/envs/tfm/lib/python3.6/site-packages/torch/utils/data/dataloader.py in _next_data(self)
1083 else:
1084 del self._task_info[idx]
-> 1085 return self._process_data(data)
1086
1087 def _try_put_index(self):
~/anaconda3/envs/tfm/lib/python3.6/site-packages/torch/utils/data/dataloader.py in _process_data(self, data)
1109 self._try_put_index()
1110 if isinstance(data, ExceptionWrapper):
-> 1111 data.reraise()
1112 return data
1113
~/anaconda3/envs/tfm/lib/python3.6/site-packages/torch/_utils.py in reraise(self)
426 # have message field
427 raise self.exc_type(message=msg)
--> 428 raise self.exc_type(msg)
429
430
AssertionError: Caught AssertionError in DataLoader worker process 0.
Original Traceback (most recent call last):
File "/home/ad/anaconda3/envs/tfm/lib/python3.6/site-packages/torch/utils/data/_utils/worker.py", line 198, in _worker_loop
data = fetcher.fetch(index)
File "/home/ad/anaconda3/envs/tfm/lib/python3.6/site-packages/torch/utils/data/_utils/fetch.py", line 44, in fetch
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/home/ad/anaconda3/envs/tfm/lib/python3.6/site-packages/torch/utils/data/_utils/fetch.py", line 44, in <listcomp>
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/home/ad/anaconda3/envs/tfm/lib/python3.6/site-packages/datasets/arrow_dataset.py", line 1087, in __getitem__
format_kwargs=self._format_kwargs,
File "/home/ad/anaconda3/envs/tfm/lib/python3.6/site-packages/datasets/arrow_dataset.py", line 1074, in _getitem
format_kwargs=format_kwargs,
File "/home/ad/anaconda3/envs/tfm/lib/python3.6/site-packages/datasets/arrow_dataset.py", line 890, in _convert_outputs
v = map_nested(command, v, **map_nested_kwargs)
File "/home/ad/anaconda3/envs/tfm/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 225, in map_nested
return function(data_struct)
File "/home/ad/anaconda3/envs/tfm/lib/python3.6/site-packages/datasets/arrow_dataset.py", line 851, in command
return torch.tensor(x, **format_kwargs)
File "/home/ad/anaconda3/envs/tfm/lib/python3.6/warnings.py", line 101, in _showwarnmsg
_showwarnmsg_impl(msg)
File "/home/ad/anaconda3/envs/tfm/lib/python3.6/warnings.py", line 30, in _showwarnmsg_impl
file.write(text)
File "/home/ad/anaconda3/envs/tfm/lib/python3.6/site-packages/wandb/sdk/lib/redirect.py", line 100, in new_write
cb(name, data)
File "/home/ad/anaconda3/envs/tfm/lib/python3.6/site-packages/wandb/sdk/wandb_run.py", line 723, in _console_callback
self._backend.interface.publish_output(name, data)
File "/home/ad/anaconda3/envs/tfm/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 153, in publish_output
self._publish_output(o)
File "/home/ad/anaconda3/envs/tfm/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 158, in _publish_output
self._publish(rec)
File "/home/ad/anaconda3/envs/tfm/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 456, in _publish
if self._process and not self._process.is_alive():
File "/home/ad/anaconda3/envs/tfm/lib/python3.6/multiprocessing/process.py", line 134, in is_alive
assert self._parent_pid == os.getpid(), 'can only test a child process'
AssertionError: can only test a child process
```
As a workaround I have commented line 456 and 457 in `/home/ad/anaconda3/envs/tfm/lib/python3.6/site-packages/wandb/sdk/interface/interface.py` | Using a dataset with a single 'text' field and a fast tokenizer in a jupyter notebook.
```
def tokenizer_fn(example):
return tokenizer.batch_encode_plus(example['text'])
ds_tokenized = text_dataset.map(tokenizer_fn, batched=True, num_proc=6, remove_columns=['text'])
```
```
---------------------------------------------------------------------------
RemoteTraceback Traceback (most recent call last)
RemoteTraceback:
"""
Traceback (most recent call last):
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/multiprocess/pool.py", line 119, in worker
result = (True, func(*args, **kwds))
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/datasets/arrow_dataset.py", line 156, in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/datasets/fingerprint.py", line 163, in wrapper
out = func(self, *args, **kwargs)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/datasets/arrow_dataset.py", line 1510, in _map_single
for i in pbar:
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/notebook.py", line 228, in __iter__
for obj in super(tqdm_notebook, self).__iter__(*args, **kwargs):
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/std.py", line 1186, in __iter__
self.close()
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/notebook.py", line 251, in close
super(tqdm_notebook, self).close(*args, **kwargs)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/std.py", line 1291, in close
fp_write('')
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/std.py", line 1288, in fp_write
self.fp.write(_unicode(s))
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/lib/redirect.py", line 91, in new_write
cb(name, data)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/wandb_run.py", line 598, in _console_callback
self._backend.interface.publish_output(name, data)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 146, in publish_output
self._publish_output(o)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 151, in _publish_output
self._publish(rec)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 431, in _publish
if self._process and not self._process.is_alive():
File "/usr/lib/python3.6/multiprocessing/process.py", line 134, in is_alive
assert self._parent_pid == os.getpid(), 'can only test a child process'
AssertionError: can only test a child process
"""
``` | 383 | multiprocessing in dataset map "can only test a child process"
Using a dataset with a single 'text' field and a fast tokenizer in a jupyter notebook.
```
def tokenizer_fn(example):
return tokenizer.batch_encode_plus(example['text'])
ds_tokenized = text_dataset.map(tokenizer_fn, batched=True, num_proc=6, remove_columns=['text'])
```
```
---------------------------------------------------------------------------
RemoteTraceback Traceback (most recent call last)
RemoteTraceback:
"""
Traceback (most recent call last):
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/multiprocess/pool.py", line 119, in worker
result = (True, func(*args, **kwds))
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/datasets/arrow_dataset.py", line 156, in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/datasets/fingerprint.py", line 163, in wrapper
out = func(self, *args, **kwargs)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/datasets/arrow_dataset.py", line 1510, in _map_single
for i in pbar:
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/notebook.py", line 228, in __iter__
for obj in super(tqdm_notebook, self).__iter__(*args, **kwargs):
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/std.py", line 1186, in __iter__
self.close()
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/notebook.py", line 251, in close
super(tqdm_notebook, self).close(*args, **kwargs)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/std.py", line 1291, in close
fp_write('')
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/std.py", line 1288, in fp_write
self.fp.write(_unicode(s))
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/lib/redirect.py", line 91, in new_write
cb(name, data)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/wandb_run.py", line 598, in _console_callback
self._backend.interface.publish_output(name, data)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 146, in publish_output
self._publish_output(o)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 151, in _publish_output
self._publish(rec)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 431, in _publish
if self._process and not self._process.is_alive():
File "/usr/lib/python3.6/multiprocessing/process.py", line 134, in is_alive
assert self._parent_pid == os.getpid(), 'can only test a child process'
AssertionError: can only test a child process
"""
```
I'm having a similar issue but when I try to do multiprocessing with the `DataLoader`
Code to reproduce:
```
from datasets import load_dataset
book_corpus = load_dataset('bookcorpus', 'plain_text', cache_dir='/home/ad/Desktop/bookcorpus', split='train[:1%]')
book_corpus = book_corpus.map(encode, batched=True, num_proc=20, load_from_cache_file=True, batch_size=5000)
book_corpus.set_format(type='torch', columns=['text', "input_ids", "attention_mask", "token_type_ids"])
from transformers import DataCollatorForWholeWordMask
from transformers import Trainer, TrainingArguments
data_collator = DataCollatorForWholeWordMask(
tokenizer=tokenizer, mlm=True, mlm_probability=0.15)
training_args = TrainingArguments(
output_dir="./mobile_linear_att_8L_128_128_03layerdrop_shared",
overwrite_output_dir=True,
num_train_epochs=1,
per_device_train_batch_size=64,
save_steps=50,
save_total_limit=2,
logging_first_step=True,
warmup_steps=100,
logging_steps=50,
gradient_accumulation_steps=1,
fp16=True,
**dataloader_num_workers=10**,
)
trainer = Trainer(
model=model,
args=training_args,
data_collator=data_collator,
train_dataset=book_corpus,
tokenizer=tokenizer)
trainer.train()
```
```
---------------------------------------------------------------------------
AssertionError Traceback (most recent call last)
<timed eval> in <module>
~/anaconda3/envs/tfm/lib/python3.6/site-packages/transformers/trainer.py in train(self, model_path, trial)
869 self.control = self.callback_handler.on_epoch_begin(self.args, self.state, self.control)
870
--> 871 for step, inputs in enumerate(epoch_iterator):
872
873 # Skip past any already trained steps if resuming training
~/anaconda3/envs/tfm/lib/python3.6/site-packages/torch/utils/data/dataloader.py in __next__(self)
433 if self._sampler_iter is None:
434 self._reset()
--> 435 data = self._next_data()
436 self._num_yielded += 1
437 if self._dataset_kind == _DatasetKind.Iterable and \
~/anaconda3/envs/tfm/lib/python3.6/site-packages/torch/utils/data/dataloader.py in _next_data(self)
1083 else:
1084 del self._task_info[idx]
-> 1085 return self._process_data(data)
1086
1087 def _try_put_index(self):
~/anaconda3/envs/tfm/lib/python3.6/site-packages/torch/utils/data/dataloader.py in _process_data(self, data)
1109 self._try_put_index()
1110 if isinstance(data, ExceptionWrapper):
-> 1111 data.reraise()
1112 return data
1113
~/anaconda3/envs/tfm/lib/python3.6/site-packages/torch/_utils.py in reraise(self)
426 # have message field
427 raise self.exc_type(message=msg)
--> 428 raise self.exc_type(msg)
429
430
AssertionError: Caught AssertionError in DataLoader worker process 0.
Original Traceback (most recent call last):
File "/home/ad/anaconda3/envs/tfm/lib/python3.6/site-packages/torch/utils/data/_utils/worker.py", line 198, in _worker_loop
data = fetcher.fetch(index)
File "/home/ad/anaconda3/envs/tfm/lib/python3.6/site-packages/torch/utils/data/_utils/fetch.py", line 44, in fetch
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/home/ad/anaconda3/envs/tfm/lib/python3.6/site-packages/torch/utils/data/_utils/fetch.py", line 44, in <listcomp>
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/home/ad/anaconda3/envs/tfm/lib/python3.6/site-packages/datasets/arrow_dataset.py", line 1087, in __getitem__
format_kwargs=self._format_kwargs,
File "/home/ad/anaconda3/envs/tfm/lib/python3.6/site-packages/datasets/arrow_dataset.py", line 1074, in _getitem
format_kwargs=format_kwargs,
File "/home/ad/anaconda3/envs/tfm/lib/python3.6/site-packages/datasets/arrow_dataset.py", line 890, in _convert_outputs
v = map_nested(command, v, **map_nested_kwargs)
File "/home/ad/anaconda3/envs/tfm/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 225, in map_nested
return function(data_struct)
File "/home/ad/anaconda3/envs/tfm/lib/python3.6/site-packages/datasets/arrow_dataset.py", line 851, in command
return torch.tensor(x, **format_kwargs)
File "/home/ad/anaconda3/envs/tfm/lib/python3.6/warnings.py", line 101, in _showwarnmsg
_showwarnmsg_impl(msg)
File "/home/ad/anaconda3/envs/tfm/lib/python3.6/warnings.py", line 30, in _showwarnmsg_impl
file.write(text)
File "/home/ad/anaconda3/envs/tfm/lib/python3.6/site-packages/wandb/sdk/lib/redirect.py", line 100, in new_write
cb(name, data)
File "/home/ad/anaconda3/envs/tfm/lib/python3.6/site-packages/wandb/sdk/wandb_run.py", line 723, in _console_callback
self._backend.interface.publish_output(name, data)
File "/home/ad/anaconda3/envs/tfm/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 153, in publish_output
self._publish_output(o)
File "/home/ad/anaconda3/envs/tfm/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 158, in _publish_output
self._publish(rec)
File "/home/ad/anaconda3/envs/tfm/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 456, in _publish
if self._process and not self._process.is_alive():
File "/home/ad/anaconda3/envs/tfm/lib/python3.6/multiprocessing/process.py", line 134, in is_alive
assert self._parent_pid == os.getpid(), 'can only test a child process'
AssertionError: can only test a child process
```
As a workaround I have commented line 456 and 457 in `/home/ad/anaconda3/envs/tfm/lib/python3.6/site-packages/wandb/sdk/interface/interface.py` |
https://github.com/huggingface/datasets/issues/847 | multiprocessing in dataset map "can only test a child process" | Isn't it more the pytorch warning on the use of non-writable memory for tensor that trigger this here @lhoestq? (since it seems to be a warning triggered in `torch.tensor()` | Using a dataset with a single 'text' field and a fast tokenizer in a jupyter notebook.
```
def tokenizer_fn(example):
return tokenizer.batch_encode_plus(example['text'])
ds_tokenized = text_dataset.map(tokenizer_fn, batched=True, num_proc=6, remove_columns=['text'])
```
```
---------------------------------------------------------------------------
RemoteTraceback Traceback (most recent call last)
RemoteTraceback:
"""
Traceback (most recent call last):
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/multiprocess/pool.py", line 119, in worker
result = (True, func(*args, **kwds))
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/datasets/arrow_dataset.py", line 156, in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/datasets/fingerprint.py", line 163, in wrapper
out = func(self, *args, **kwargs)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/datasets/arrow_dataset.py", line 1510, in _map_single
for i in pbar:
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/notebook.py", line 228, in __iter__
for obj in super(tqdm_notebook, self).__iter__(*args, **kwargs):
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/std.py", line 1186, in __iter__
self.close()
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/notebook.py", line 251, in close
super(tqdm_notebook, self).close(*args, **kwargs)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/std.py", line 1291, in close
fp_write('')
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/std.py", line 1288, in fp_write
self.fp.write(_unicode(s))
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/lib/redirect.py", line 91, in new_write
cb(name, data)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/wandb_run.py", line 598, in _console_callback
self._backend.interface.publish_output(name, data)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 146, in publish_output
self._publish_output(o)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 151, in _publish_output
self._publish(rec)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 431, in _publish
if self._process and not self._process.is_alive():
File "/usr/lib/python3.6/multiprocessing/process.py", line 134, in is_alive
assert self._parent_pid == os.getpid(), 'can only test a child process'
AssertionError: can only test a child process
"""
``` | 29 | multiprocessing in dataset map "can only test a child process"
Using a dataset with a single 'text' field and a fast tokenizer in a jupyter notebook.
```
def tokenizer_fn(example):
return tokenizer.batch_encode_plus(example['text'])
ds_tokenized = text_dataset.map(tokenizer_fn, batched=True, num_proc=6, remove_columns=['text'])
```
```
---------------------------------------------------------------------------
RemoteTraceback Traceback (most recent call last)
RemoteTraceback:
"""
Traceback (most recent call last):
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/multiprocess/pool.py", line 119, in worker
result = (True, func(*args, **kwds))
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/datasets/arrow_dataset.py", line 156, in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/datasets/fingerprint.py", line 163, in wrapper
out = func(self, *args, **kwargs)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/datasets/arrow_dataset.py", line 1510, in _map_single
for i in pbar:
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/notebook.py", line 228, in __iter__
for obj in super(tqdm_notebook, self).__iter__(*args, **kwargs):
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/std.py", line 1186, in __iter__
self.close()
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/notebook.py", line 251, in close
super(tqdm_notebook, self).close(*args, **kwargs)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/std.py", line 1291, in close
fp_write('')
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/std.py", line 1288, in fp_write
self.fp.write(_unicode(s))
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/lib/redirect.py", line 91, in new_write
cb(name, data)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/wandb_run.py", line 598, in _console_callback
self._backend.interface.publish_output(name, data)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 146, in publish_output
self._publish_output(o)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 151, in _publish_output
self._publish(rec)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 431, in _publish
if self._process and not self._process.is_alive():
File "/usr/lib/python3.6/multiprocessing/process.py", line 134, in is_alive
assert self._parent_pid == os.getpid(), 'can only test a child process'
AssertionError: can only test a child process
"""
```
Isn't it more the pytorch warning on the use of non-writable memory for tensor that trigger this here @lhoestq? (since it seems to be a warning triggered in `torch.tensor()` |
https://github.com/huggingface/datasets/issues/847 | multiprocessing in dataset map "can only test a child process" | Yep this time this is a warning from pytorch that causes wandb to not work properly.
Could this by a wandb issue ? | Using a dataset with a single 'text' field and a fast tokenizer in a jupyter notebook.
```
def tokenizer_fn(example):
return tokenizer.batch_encode_plus(example['text'])
ds_tokenized = text_dataset.map(tokenizer_fn, batched=True, num_proc=6, remove_columns=['text'])
```
```
---------------------------------------------------------------------------
RemoteTraceback Traceback (most recent call last)
RemoteTraceback:
"""
Traceback (most recent call last):
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/multiprocess/pool.py", line 119, in worker
result = (True, func(*args, **kwds))
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/datasets/arrow_dataset.py", line 156, in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/datasets/fingerprint.py", line 163, in wrapper
out = func(self, *args, **kwargs)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/datasets/arrow_dataset.py", line 1510, in _map_single
for i in pbar:
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/notebook.py", line 228, in __iter__
for obj in super(tqdm_notebook, self).__iter__(*args, **kwargs):
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/std.py", line 1186, in __iter__
self.close()
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/notebook.py", line 251, in close
super(tqdm_notebook, self).close(*args, **kwargs)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/std.py", line 1291, in close
fp_write('')
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/std.py", line 1288, in fp_write
self.fp.write(_unicode(s))
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/lib/redirect.py", line 91, in new_write
cb(name, data)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/wandb_run.py", line 598, in _console_callback
self._backend.interface.publish_output(name, data)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 146, in publish_output
self._publish_output(o)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 151, in _publish_output
self._publish(rec)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 431, in _publish
if self._process and not self._process.is_alive():
File "/usr/lib/python3.6/multiprocessing/process.py", line 134, in is_alive
assert self._parent_pid == os.getpid(), 'can only test a child process'
AssertionError: can only test a child process
"""
``` | 23 | multiprocessing in dataset map "can only test a child process"
Using a dataset with a single 'text' field and a fast tokenizer in a jupyter notebook.
```
def tokenizer_fn(example):
return tokenizer.batch_encode_plus(example['text'])
ds_tokenized = text_dataset.map(tokenizer_fn, batched=True, num_proc=6, remove_columns=['text'])
```
```
---------------------------------------------------------------------------
RemoteTraceback Traceback (most recent call last)
RemoteTraceback:
"""
Traceback (most recent call last):
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/multiprocess/pool.py", line 119, in worker
result = (True, func(*args, **kwds))
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/datasets/arrow_dataset.py", line 156, in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/datasets/fingerprint.py", line 163, in wrapper
out = func(self, *args, **kwargs)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/datasets/arrow_dataset.py", line 1510, in _map_single
for i in pbar:
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/notebook.py", line 228, in __iter__
for obj in super(tqdm_notebook, self).__iter__(*args, **kwargs):
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/std.py", line 1186, in __iter__
self.close()
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/notebook.py", line 251, in close
super(tqdm_notebook, self).close(*args, **kwargs)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/std.py", line 1291, in close
fp_write('')
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/std.py", line 1288, in fp_write
self.fp.write(_unicode(s))
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/lib/redirect.py", line 91, in new_write
cb(name, data)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/wandb_run.py", line 598, in _console_callback
self._backend.interface.publish_output(name, data)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 146, in publish_output
self._publish_output(o)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 151, in _publish_output
self._publish(rec)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 431, in _publish
if self._process and not self._process.is_alive():
File "/usr/lib/python3.6/multiprocessing/process.py", line 134, in is_alive
assert self._parent_pid == os.getpid(), 'can only test a child process'
AssertionError: can only test a child process
"""
```
Yep this time this is a warning from pytorch that causes wandb to not work properly.
Could this by a wandb issue ? |
https://github.com/huggingface/datasets/issues/847 | multiprocessing in dataset map "can only test a child process" | Hi @timothyjlaurent @gaceladri
If you're running `transformers` from `master` you can try setting the env var `WAND_DISABLE=true` (from https://github.com/huggingface/transformers/pull/9896) and try again ?
This issue might be related to https://github.com/huggingface/transformers/issues/9623 | Using a dataset with a single 'text' field and a fast tokenizer in a jupyter notebook.
```
def tokenizer_fn(example):
return tokenizer.batch_encode_plus(example['text'])
ds_tokenized = text_dataset.map(tokenizer_fn, batched=True, num_proc=6, remove_columns=['text'])
```
```
---------------------------------------------------------------------------
RemoteTraceback Traceback (most recent call last)
RemoteTraceback:
"""
Traceback (most recent call last):
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/multiprocess/pool.py", line 119, in worker
result = (True, func(*args, **kwds))
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/datasets/arrow_dataset.py", line 156, in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/datasets/fingerprint.py", line 163, in wrapper
out = func(self, *args, **kwargs)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/datasets/arrow_dataset.py", line 1510, in _map_single
for i in pbar:
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/notebook.py", line 228, in __iter__
for obj in super(tqdm_notebook, self).__iter__(*args, **kwargs):
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/std.py", line 1186, in __iter__
self.close()
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/notebook.py", line 251, in close
super(tqdm_notebook, self).close(*args, **kwargs)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/std.py", line 1291, in close
fp_write('')
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/std.py", line 1288, in fp_write
self.fp.write(_unicode(s))
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/lib/redirect.py", line 91, in new_write
cb(name, data)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/wandb_run.py", line 598, in _console_callback
self._backend.interface.publish_output(name, data)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 146, in publish_output
self._publish_output(o)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 151, in _publish_output
self._publish(rec)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 431, in _publish
if self._process and not self._process.is_alive():
File "/usr/lib/python3.6/multiprocessing/process.py", line 134, in is_alive
assert self._parent_pid == os.getpid(), 'can only test a child process'
AssertionError: can only test a child process
"""
``` | 30 | multiprocessing in dataset map "can only test a child process"
Using a dataset with a single 'text' field and a fast tokenizer in a jupyter notebook.
```
def tokenizer_fn(example):
return tokenizer.batch_encode_plus(example['text'])
ds_tokenized = text_dataset.map(tokenizer_fn, batched=True, num_proc=6, remove_columns=['text'])
```
```
---------------------------------------------------------------------------
RemoteTraceback Traceback (most recent call last)
RemoteTraceback:
"""
Traceback (most recent call last):
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/multiprocess/pool.py", line 119, in worker
result = (True, func(*args, **kwds))
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/datasets/arrow_dataset.py", line 156, in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/datasets/fingerprint.py", line 163, in wrapper
out = func(self, *args, **kwargs)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/datasets/arrow_dataset.py", line 1510, in _map_single
for i in pbar:
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/notebook.py", line 228, in __iter__
for obj in super(tqdm_notebook, self).__iter__(*args, **kwargs):
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/std.py", line 1186, in __iter__
self.close()
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/notebook.py", line 251, in close
super(tqdm_notebook, self).close(*args, **kwargs)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/std.py", line 1291, in close
fp_write('')
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/std.py", line 1288, in fp_write
self.fp.write(_unicode(s))
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/lib/redirect.py", line 91, in new_write
cb(name, data)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/wandb_run.py", line 598, in _console_callback
self._backend.interface.publish_output(name, data)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 146, in publish_output
self._publish_output(o)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 151, in _publish_output
self._publish(rec)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 431, in _publish
if self._process and not self._process.is_alive():
File "/usr/lib/python3.6/multiprocessing/process.py", line 134, in is_alive
assert self._parent_pid == os.getpid(), 'can only test a child process'
AssertionError: can only test a child process
"""
```
Hi @timothyjlaurent @gaceladri
If you're running `transformers` from `master` you can try setting the env var `WAND_DISABLE=true` (from https://github.com/huggingface/transformers/pull/9896) and try again ?
This issue might be related to https://github.com/huggingface/transformers/issues/9623 |
https://github.com/huggingface/datasets/issues/847 | multiprocessing in dataset map "can only test a child process" | I have commented the lines that cause my code break. I'm now seeing my reports on Wandb and my code does not break. I am training now, so I will check probably in 6 hours. I suppose that setting wandb disable will work as well. | Using a dataset with a single 'text' field and a fast tokenizer in a jupyter notebook.
```
def tokenizer_fn(example):
return tokenizer.batch_encode_plus(example['text'])
ds_tokenized = text_dataset.map(tokenizer_fn, batched=True, num_proc=6, remove_columns=['text'])
```
```
---------------------------------------------------------------------------
RemoteTraceback Traceback (most recent call last)
RemoteTraceback:
"""
Traceback (most recent call last):
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/multiprocess/pool.py", line 119, in worker
result = (True, func(*args, **kwds))
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/datasets/arrow_dataset.py", line 156, in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/datasets/fingerprint.py", line 163, in wrapper
out = func(self, *args, **kwargs)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/datasets/arrow_dataset.py", line 1510, in _map_single
for i in pbar:
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/notebook.py", line 228, in __iter__
for obj in super(tqdm_notebook, self).__iter__(*args, **kwargs):
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/std.py", line 1186, in __iter__
self.close()
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/notebook.py", line 251, in close
super(tqdm_notebook, self).close(*args, **kwargs)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/std.py", line 1291, in close
fp_write('')
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/std.py", line 1288, in fp_write
self.fp.write(_unicode(s))
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/lib/redirect.py", line 91, in new_write
cb(name, data)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/wandb_run.py", line 598, in _console_callback
self._backend.interface.publish_output(name, data)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 146, in publish_output
self._publish_output(o)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 151, in _publish_output
self._publish(rec)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 431, in _publish
if self._process and not self._process.is_alive():
File "/usr/lib/python3.6/multiprocessing/process.py", line 134, in is_alive
assert self._parent_pid == os.getpid(), 'can only test a child process'
AssertionError: can only test a child process
"""
``` | 45 | multiprocessing in dataset map "can only test a child process"
Using a dataset with a single 'text' field and a fast tokenizer in a jupyter notebook.
```
def tokenizer_fn(example):
return tokenizer.batch_encode_plus(example['text'])
ds_tokenized = text_dataset.map(tokenizer_fn, batched=True, num_proc=6, remove_columns=['text'])
```
```
---------------------------------------------------------------------------
RemoteTraceback Traceback (most recent call last)
RemoteTraceback:
"""
Traceback (most recent call last):
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/multiprocess/pool.py", line 119, in worker
result = (True, func(*args, **kwds))
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/datasets/arrow_dataset.py", line 156, in wrapper
out: Union["Dataset", "DatasetDict"] = func(self, *args, **kwargs)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/datasets/fingerprint.py", line 163, in wrapper
out = func(self, *args, **kwargs)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/datasets/arrow_dataset.py", line 1510, in _map_single
for i in pbar:
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/notebook.py", line 228, in __iter__
for obj in super(tqdm_notebook, self).__iter__(*args, **kwargs):
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/std.py", line 1186, in __iter__
self.close()
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/notebook.py", line 251, in close
super(tqdm_notebook, self).close(*args, **kwargs)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/std.py", line 1291, in close
fp_write('')
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/tqdm/std.py", line 1288, in fp_write
self.fp.write(_unicode(s))
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/lib/redirect.py", line 91, in new_write
cb(name, data)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/wandb_run.py", line 598, in _console_callback
self._backend.interface.publish_output(name, data)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 146, in publish_output
self._publish_output(o)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 151, in _publish_output
self._publish(rec)
File "/home/jovyan/share/users/tlaurent/invitae-bert/ve/lib/python3.6/site-packages/wandb/sdk/interface/interface.py", line 431, in _publish
if self._process and not self._process.is_alive():
File "/usr/lib/python3.6/multiprocessing/process.py", line 134, in is_alive
assert self._parent_pid == os.getpid(), 'can only test a child process'
AssertionError: can only test a child process
"""
```
I have commented the lines that cause my code break. I'm now seeing my reports on Wandb and my code does not break. I am training now, so I will check probably in 6 hours. I suppose that setting wandb disable will work as well. |
https://github.com/huggingface/datasets/issues/846 | Add HoVer multi-hop fact verification dataset | Hi @yjernite I'm new but wanted to contribute. Has anyone already taken this problem and do you think it is suitable for newbies? | ## Adding a Dataset
- **Name:** HoVer
- **Description:** https://twitter.com/YichenJiang9/status/1326954363806429186 contains 20K claim verification examples
- **Paper:** https://arxiv.org/abs/2011.03088
- **Data:** https://hover-nlp.github.io/
- **Motivation:** There are still few multi-hop information extraction benchmarks (HotpotQA, which dataset wase based off, notwithstanding)
Instructions to add a new dataset can be found [here](https://huggingface.co/docs/datasets/share_dataset.html).
| 23 | Add HoVer multi-hop fact verification dataset
## Adding a Dataset
- **Name:** HoVer
- **Description:** https://twitter.com/YichenJiang9/status/1326954363806429186 contains 20K claim verification examples
- **Paper:** https://arxiv.org/abs/2011.03088
- **Data:** https://hover-nlp.github.io/
- **Motivation:** There are still few multi-hop information extraction benchmarks (HotpotQA, which dataset wase based off, notwithstanding)
Instructions to add a new dataset can be found [here](https://huggingface.co/docs/datasets/share_dataset.html).
Hi @yjernite I'm new but wanted to contribute. Has anyone already taken this problem and do you think it is suitable for newbies? |
https://github.com/huggingface/datasets/issues/846 | Add HoVer multi-hop fact verification dataset | Hi @tenjjin! This dataset is still up for grabs! Here's the link with the guide to add it. You should play around with the library first (download and look at a few datasets), then follow the steps here:
https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md | ## Adding a Dataset
- **Name:** HoVer
- **Description:** https://twitter.com/YichenJiang9/status/1326954363806429186 contains 20K claim verification examples
- **Paper:** https://arxiv.org/abs/2011.03088
- **Data:** https://hover-nlp.github.io/
- **Motivation:** There are still few multi-hop information extraction benchmarks (HotpotQA, which dataset wase based off, notwithstanding)
Instructions to add a new dataset can be found [here](https://huggingface.co/docs/datasets/share_dataset.html).
| 39 | Add HoVer multi-hop fact verification dataset
## Adding a Dataset
- **Name:** HoVer
- **Description:** https://twitter.com/YichenJiang9/status/1326954363806429186 contains 20K claim verification examples
- **Paper:** https://arxiv.org/abs/2011.03088
- **Data:** https://hover-nlp.github.io/
- **Motivation:** There are still few multi-hop information extraction benchmarks (HotpotQA, which dataset wase based off, notwithstanding)
Instructions to add a new dataset can be found [here](https://huggingface.co/docs/datasets/share_dataset.html).
Hi @tenjjin! This dataset is still up for grabs! Here's the link with the guide to add it. You should play around with the library first (download and look at a few datasets), then follow the steps here:
https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md |
https://github.com/huggingface/datasets/issues/843 | use_custom_baseline still produces errors for bertscore | Thanks for reporting ! That's a bug indeed
If you want to contribute, feel free to fix this issue and open a PR :) | `metric = load_metric('bertscore')`
`a1 = "random sentences"`
`b1 = "random sentences"`
`metric.compute(predictions = [a1], references = [b1], lang = 'en')`
`Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/stephen_chan/.local/lib/python3.6/site-packages/datasets/metric.py", line 393, in compute
output = self._compute(predictions=predictions, references=references, **kwargs)
File "/home/stephen_chan/.cache/huggingface/modules/datasets_modules/metrics/bertscore/361e597a01a41d6cf95d94bbfb01dea16261687abc0c6c74cc9930f80488f363/bertscore.py", line 108, in _compute
hashcode = bert_score.utils.get_hash(model_type, num_layers, idf, rescale_with_baseline)
TypeError: get_hash() missing 1 required positional argument: 'use_custom_baseline'`
Adding 'use_custom_baseline = False' as an argument produces this error
`Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/stephen_chan/.local/lib/python3.6/site-packages/datasets/metric.py", line 393, in compute
output = self._compute(predictions=predictions, references=references, **kwargs)
TypeError: _compute() got an unexpected keyword argument 'use_custom_baseline'`
This is on Ubuntu 18.04, Python 3.6.9, datasets version 1.1.2 | 24 | use_custom_baseline still produces errors for bertscore
`metric = load_metric('bertscore')`
`a1 = "random sentences"`
`b1 = "random sentences"`
`metric.compute(predictions = [a1], references = [b1], lang = 'en')`
`Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/stephen_chan/.local/lib/python3.6/site-packages/datasets/metric.py", line 393, in compute
output = self._compute(predictions=predictions, references=references, **kwargs)
File "/home/stephen_chan/.cache/huggingface/modules/datasets_modules/metrics/bertscore/361e597a01a41d6cf95d94bbfb01dea16261687abc0c6c74cc9930f80488f363/bertscore.py", line 108, in _compute
hashcode = bert_score.utils.get_hash(model_type, num_layers, idf, rescale_with_baseline)
TypeError: get_hash() missing 1 required positional argument: 'use_custom_baseline'`
Adding 'use_custom_baseline = False' as an argument produces this error
`Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/stephen_chan/.local/lib/python3.6/site-packages/datasets/metric.py", line 393, in compute
output = self._compute(predictions=predictions, references=references, **kwargs)
TypeError: _compute() got an unexpected keyword argument 'use_custom_baseline'`
This is on Ubuntu 18.04, Python 3.6.9, datasets version 1.1.2
Thanks for reporting ! That's a bug indeed
If you want to contribute, feel free to fix this issue and open a PR :) |
https://github.com/huggingface/datasets/issues/843 | use_custom_baseline still produces errors for bertscore | This error is because of a mismatch between `datasets` and `bert_score`. With `datasets=1.1.2` and `bert_score>=0.3.6` it works ok. So `pip install -U bert_score` should fix the problem. | `metric = load_metric('bertscore')`
`a1 = "random sentences"`
`b1 = "random sentences"`
`metric.compute(predictions = [a1], references = [b1], lang = 'en')`
`Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/stephen_chan/.local/lib/python3.6/site-packages/datasets/metric.py", line 393, in compute
output = self._compute(predictions=predictions, references=references, **kwargs)
File "/home/stephen_chan/.cache/huggingface/modules/datasets_modules/metrics/bertscore/361e597a01a41d6cf95d94bbfb01dea16261687abc0c6c74cc9930f80488f363/bertscore.py", line 108, in _compute
hashcode = bert_score.utils.get_hash(model_type, num_layers, idf, rescale_with_baseline)
TypeError: get_hash() missing 1 required positional argument: 'use_custom_baseline'`
Adding 'use_custom_baseline = False' as an argument produces this error
`Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/stephen_chan/.local/lib/python3.6/site-packages/datasets/metric.py", line 393, in compute
output = self._compute(predictions=predictions, references=references, **kwargs)
TypeError: _compute() got an unexpected keyword argument 'use_custom_baseline'`
This is on Ubuntu 18.04, Python 3.6.9, datasets version 1.1.2 | 27 | use_custom_baseline still produces errors for bertscore
`metric = load_metric('bertscore')`
`a1 = "random sentences"`
`b1 = "random sentences"`
`metric.compute(predictions = [a1], references = [b1], lang = 'en')`
`Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/stephen_chan/.local/lib/python3.6/site-packages/datasets/metric.py", line 393, in compute
output = self._compute(predictions=predictions, references=references, **kwargs)
File "/home/stephen_chan/.cache/huggingface/modules/datasets_modules/metrics/bertscore/361e597a01a41d6cf95d94bbfb01dea16261687abc0c6c74cc9930f80488f363/bertscore.py", line 108, in _compute
hashcode = bert_score.utils.get_hash(model_type, num_layers, idf, rescale_with_baseline)
TypeError: get_hash() missing 1 required positional argument: 'use_custom_baseline'`
Adding 'use_custom_baseline = False' as an argument produces this error
`Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/stephen_chan/.local/lib/python3.6/site-packages/datasets/metric.py", line 393, in compute
output = self._compute(predictions=predictions, references=references, **kwargs)
TypeError: _compute() got an unexpected keyword argument 'use_custom_baseline'`
This is on Ubuntu 18.04, Python 3.6.9, datasets version 1.1.2
This error is because of a mismatch between `datasets` and `bert_score`. With `datasets=1.1.2` and `bert_score>=0.3.6` it works ok. So `pip install -U bert_score` should fix the problem. |
https://github.com/huggingface/datasets/issues/843 | use_custom_baseline still produces errors for bertscore | Hello everyone,
I think the problem is not solved:
```
from datasets import load_metric
metric=load_metric('bertscore')
metric.compute(
predictions=predictions,
references=references,
lang='fr',
rescale_with_baseline=True
)
TypeError: get_hash() missing 2 required positional arguments: 'use_custom_baseline' and 'use_fast_tokenizer'
```
This code is produced using `Python 3.6.9 datasets==1.1.2 and bert_score==0.3.10` | `metric = load_metric('bertscore')`
`a1 = "random sentences"`
`b1 = "random sentences"`
`metric.compute(predictions = [a1], references = [b1], lang = 'en')`
`Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/stephen_chan/.local/lib/python3.6/site-packages/datasets/metric.py", line 393, in compute
output = self._compute(predictions=predictions, references=references, **kwargs)
File "/home/stephen_chan/.cache/huggingface/modules/datasets_modules/metrics/bertscore/361e597a01a41d6cf95d94bbfb01dea16261687abc0c6c74cc9930f80488f363/bertscore.py", line 108, in _compute
hashcode = bert_score.utils.get_hash(model_type, num_layers, idf, rescale_with_baseline)
TypeError: get_hash() missing 1 required positional argument: 'use_custom_baseline'`
Adding 'use_custom_baseline = False' as an argument produces this error
`Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/stephen_chan/.local/lib/python3.6/site-packages/datasets/metric.py", line 393, in compute
output = self._compute(predictions=predictions, references=references, **kwargs)
TypeError: _compute() got an unexpected keyword argument 'use_custom_baseline'`
This is on Ubuntu 18.04, Python 3.6.9, datasets version 1.1.2 | 42 | use_custom_baseline still produces errors for bertscore
`metric = load_metric('bertscore')`
`a1 = "random sentences"`
`b1 = "random sentences"`
`metric.compute(predictions = [a1], references = [b1], lang = 'en')`
`Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/stephen_chan/.local/lib/python3.6/site-packages/datasets/metric.py", line 393, in compute
output = self._compute(predictions=predictions, references=references, **kwargs)
File "/home/stephen_chan/.cache/huggingface/modules/datasets_modules/metrics/bertscore/361e597a01a41d6cf95d94bbfb01dea16261687abc0c6c74cc9930f80488f363/bertscore.py", line 108, in _compute
hashcode = bert_score.utils.get_hash(model_type, num_layers, idf, rescale_with_baseline)
TypeError: get_hash() missing 1 required positional argument: 'use_custom_baseline'`
Adding 'use_custom_baseline = False' as an argument produces this error
`Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/stephen_chan/.local/lib/python3.6/site-packages/datasets/metric.py", line 393, in compute
output = self._compute(predictions=predictions, references=references, **kwargs)
TypeError: _compute() got an unexpected keyword argument 'use_custom_baseline'`
This is on Ubuntu 18.04, Python 3.6.9, datasets version 1.1.2
Hello everyone,
I think the problem is not solved:
```
from datasets import load_metric
metric=load_metric('bertscore')
metric.compute(
predictions=predictions,
references=references,
lang='fr',
rescale_with_baseline=True
)
TypeError: get_hash() missing 2 required positional arguments: 'use_custom_baseline' and 'use_fast_tokenizer'
```
This code is produced using `Python 3.6.9 datasets==1.1.2 and bert_score==0.3.10` |
https://github.com/huggingface/datasets/issues/843 | use_custom_baseline still produces errors for bertscore | Hi ! This has been fixed by https://github.com/huggingface/datasets/pull/2770, we'll do a new release soon to make the fix available :)
In the meantime please use an older version of `bert_score` | `metric = load_metric('bertscore')`
`a1 = "random sentences"`
`b1 = "random sentences"`
`metric.compute(predictions = [a1], references = [b1], lang = 'en')`
`Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/stephen_chan/.local/lib/python3.6/site-packages/datasets/metric.py", line 393, in compute
output = self._compute(predictions=predictions, references=references, **kwargs)
File "/home/stephen_chan/.cache/huggingface/modules/datasets_modules/metrics/bertscore/361e597a01a41d6cf95d94bbfb01dea16261687abc0c6c74cc9930f80488f363/bertscore.py", line 108, in _compute
hashcode = bert_score.utils.get_hash(model_type, num_layers, idf, rescale_with_baseline)
TypeError: get_hash() missing 1 required positional argument: 'use_custom_baseline'`
Adding 'use_custom_baseline = False' as an argument produces this error
`Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/stephen_chan/.local/lib/python3.6/site-packages/datasets/metric.py", line 393, in compute
output = self._compute(predictions=predictions, references=references, **kwargs)
TypeError: _compute() got an unexpected keyword argument 'use_custom_baseline'`
This is on Ubuntu 18.04, Python 3.6.9, datasets version 1.1.2 | 30 | use_custom_baseline still produces errors for bertscore
`metric = load_metric('bertscore')`
`a1 = "random sentences"`
`b1 = "random sentences"`
`metric.compute(predictions = [a1], references = [b1], lang = 'en')`
`Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/stephen_chan/.local/lib/python3.6/site-packages/datasets/metric.py", line 393, in compute
output = self._compute(predictions=predictions, references=references, **kwargs)
File "/home/stephen_chan/.cache/huggingface/modules/datasets_modules/metrics/bertscore/361e597a01a41d6cf95d94bbfb01dea16261687abc0c6c74cc9930f80488f363/bertscore.py", line 108, in _compute
hashcode = bert_score.utils.get_hash(model_type, num_layers, idf, rescale_with_baseline)
TypeError: get_hash() missing 1 required positional argument: 'use_custom_baseline'`
Adding 'use_custom_baseline = False' as an argument produces this error
`Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/stephen_chan/.local/lib/python3.6/site-packages/datasets/metric.py", line 393, in compute
output = self._compute(predictions=predictions, references=references, **kwargs)
TypeError: _compute() got an unexpected keyword argument 'use_custom_baseline'`
This is on Ubuntu 18.04, Python 3.6.9, datasets version 1.1.2
Hi ! This has been fixed by https://github.com/huggingface/datasets/pull/2770, we'll do a new release soon to make the fix available :)
In the meantime please use an older version of `bert_score` |
https://github.com/huggingface/datasets/issues/842 | How to enable `.map()` pre-processing pipelines to support multi-node parallelism? | Right now multiprocessing only runs on single node.
However it's probably possible to extend it to support multi nodes. Indeed we're using the `multiprocess` library from the `pathos` project to do multiprocessing in `datasets`, and `pathos` is made to support parallelism on several nodes. More info about pathos [on the pathos repo](https://github.com/uqfoundation/pathos).
If you're familiar with pathos or if you want to give it a try, it could be a nice addition to the library :) | Hi,
Currently, multiprocessing can be enabled for the `.map()` stages on a single node. However, in the case of multi-node training, (since more than one node would be available) I'm wondering if it's possible to extend the parallel processing among nodes, instead of only 1 node running the `.map()` while the other node is waiting for it to finish?
Thanks! | 76 | How to enable `.map()` pre-processing pipelines to support multi-node parallelism?
Hi,
Currently, multiprocessing can be enabled for the `.map()` stages on a single node. However, in the case of multi-node training, (since more than one node would be available) I'm wondering if it's possible to extend the parallel processing among nodes, instead of only 1 node running the `.map()` while the other node is waiting for it to finish?
Thanks!
Right now multiprocessing only runs on single node.
However it's probably possible to extend it to support multi nodes. Indeed we're using the `multiprocess` library from the `pathos` project to do multiprocessing in `datasets`, and `pathos` is made to support parallelism on several nodes. More info about pathos [on the pathos repo](https://github.com/uqfoundation/pathos).
If you're familiar with pathos or if you want to give it a try, it could be a nice addition to the library :) |
https://github.com/huggingface/datasets/issues/842 | How to enable `.map()` pre-processing pipelines to support multi-node parallelism? | Curious to hear if anything on that side changed or if you suggestions to do it changed @lhoestq :)
For our use-case, we are entering the regime where trading a few more instances to save a few days would be nice :) | Hi,
Currently, multiprocessing can be enabled for the `.map()` stages on a single node. However, in the case of multi-node training, (since more than one node would be available) I'm wondering if it's possible to extend the parallel processing among nodes, instead of only 1 node running the `.map()` while the other node is waiting for it to finish?
Thanks! | 42 | How to enable `.map()` pre-processing pipelines to support multi-node parallelism?
Hi,
Currently, multiprocessing can be enabled for the `.map()` stages on a single node. However, in the case of multi-node training, (since more than one node would be available) I'm wondering if it's possible to extend the parallel processing among nodes, instead of only 1 node running the `.map()` while the other node is waiting for it to finish?
Thanks!
Curious to hear if anything on that side changed or if you suggestions to do it changed @lhoestq :)
For our use-case, we are entering the regime where trading a few more instances to save a few days would be nice :) |
https://github.com/huggingface/datasets/issues/842 | How to enable `.map()` pre-processing pipelines to support multi-node parallelism? | Currently for multi-node setups we're mostly going towards a nice integration with Dask. But I wouldn't exclude exploring `pathos` more at one point | Hi,
Currently, multiprocessing can be enabled for the `.map()` stages on a single node. However, in the case of multi-node training, (since more than one node would be available) I'm wondering if it's possible to extend the parallel processing among nodes, instead of only 1 node running the `.map()` while the other node is waiting for it to finish?
Thanks! | 23 | How to enable `.map()` pre-processing pipelines to support multi-node parallelism?
Hi,
Currently, multiprocessing can be enabled for the `.map()` stages on a single node. However, in the case of multi-node training, (since more than one node would be available) I'm wondering if it's possible to extend the parallel processing among nodes, instead of only 1 node running the `.map()` while the other node is waiting for it to finish?
Thanks!
Currently for multi-node setups we're mostly going towards a nice integration with Dask. But I wouldn't exclude exploring `pathos` more at one point |
https://github.com/huggingface/datasets/issues/841 | Can not reuse datasets already downloaded | It seems the process needs '/datasets.huggingface.co/datasets/datasets/wikipedia/wikipedia.py'
Where and how to assign this ```wikipedia.py``` after I manually download it ? | Hello,
I need to connect to a frontal node (with http proxy, no gpu) before connecting to a gpu node (but no http proxy, so can not use wget so on).
I successfully downloaded and reuse the wikipedia datasets in a frontal node.
When I connect to the gpu node, I supposed to use the downloaded datasets from cache, but failed and end with time out error.
On frontal node:
```
>>> from datasets import load_dataset
>>> dataset = load_dataset('wikipedia', '20200501.en')
Reusing dataset wikipedia (/linkhome/rech/genini01/uua34ms/.cache/huggingface/datasets/wikipedia/20200501.en/1.0.0/f92599dfccab29832c442b82870fa8f6983e5b4ebbf5e6e2dcbe894e325339cd)
/linkhome/rech/genini01/uua34ms/work/anaconda3/envs/pytorch_pip170_cuda102/lib/python3.6/site-packages/torch/cuda/__init__.py:52: UserWarning: CUDA initialization: Found no NVIDIA driver on your system. Please check that you have an NVIDIA GPU and installed a driver from http://www.nvidia.com/Download/index.aspx (Triggered internally at /pytorch/c10/cuda/CUDAFunctions.cpp:100.)
return torch._C._cuda_getDeviceCount() > 0
```
On gpu node:
```
>>> from datasets import load_dataset
>>> dataset = load_dataset('wikipedia', '20200501.en')
Traceback (most recent call last):
File "/linkhome/rech/genini01/uua34ms/work/anaconda3/envs/pytorch_pip170_cuda102/lib/python3.6/site-packages/urllib3/connection.py", line 160, in _new_conn
(self._dns_host, self.port), self.timeout, **extra_kw
File "/linkhome/rech/genini01/uua34ms/work/anaconda3/envs/pytorch_pip170_cuda102/lib/python3.6/site-packages/urllib3/util/connection.py", line 84, in create_connection
raise err
File "/linkhome/rech/genini01/uua34ms/work/anaconda3/envs/pytorch_pip170_cuda102/lib/python3.6/site-packages/urllib3/util/connection.py", line 74, in create_connection
sock.connect(sa)
TimeoutError: [Errno 110] Connection timed out
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/linkhome/rech/genini01/uua34ms/work/anaconda3/envs/pytorch_pip170_cuda102/lib/python3.6/site-packages/urllib3/connectionpool.py", line 677, in urlopen
chunked=chunked,
File "/linkhome/rech/genini01/uua34ms/work/anaconda3/envs/pytorch_pip170_cuda102/lib/python3.6/site-packages/urllib3/connectionpool.py", line 381, in _make_request
self._validate_conn(conn)
File "/linkhome/rech/genini01/uua34ms/work/anaconda3/envs/pytorch_pip170_cuda102/lib/python3.6/site-packages/urllib3/connectionpool.py", line 978, in _validate_conn
conn.connect()
File "/linkhome/rech/genini01/uua34ms/work/anaconda3/envs/pytorch_pip170_cuda102/lib/python3.6/site-packages/urllib3/connection.py", line 309, in connect
conn = self._new_conn()
File "/linkhome/rech/genini01/uua34ms/work/anaconda3/envs/pytorch_pip170_cuda102/lib/python3.6/site-packages/urllib3/connection.py", line 172, in _new_conn
self, "Failed to establish a new connection: %s" % e
urllib3.exceptions.NewConnectionError: <urllib3.connection.HTTPSConnection object at 0x14b7b73e4908>: Failed to establish a new connection: [Errno 110] Connection timed out
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/linkhome/rech/genini01/uua34ms/work/anaconda3/envs/pytorch_pip170_cuda102/lib/python3.6/site-packages/requests/adapters.py", line 449, in send
timeout=timeout
File "/linkhome/rech/genini01/uua34ms/work/anaconda3/envs/pytorch_pip170_cuda102/lib/python3.6/site-packages/urllib3/connectionpool.py", line 727, in urlopen
method, url, error=e, _pool=self, _stacktrace=sys.exc_info()[2]
File "/linkhome/rech/genini01/uua34ms/work/anaconda3/envs/pytorch_pip170_cuda102/lib/python3.6/site-packages/urllib3/util/retry.py", line 446, in increment
raise MaxRetryError(_pool, url, error or ResponseError(cause))
urllib3.exceptions.MaxRetryError: HTTPSConnectionPool(host='s3.amazonaws.com', port=443): Max retries exceeded with url: /datasets.huggingface.co/datasets/datasets/wikipedia/wikipedia.py (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x14b7b73e4908>: Failed to establish a new connection: [Errno 110] Connection timed out',))
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/linkhome/rech/genini01/uua34ms/work/anaconda3/envs/pytorch_pip170_cuda102/lib/python3.6/site-packages/datasets/load.py", line 590, in load_dataset
path, script_version=script_version, download_config=download_config, download_mode=download_mode, dataset=True
File "/linkhome/rech/genini01/uua34ms/work/anaconda3/envs/pytorch_pip170_cuda102/lib/python3.6/site-packages/datasets/load.py", line 264, in prepare_module
head_hf_s3(path, filename=name, dataset=dataset)
File "/linkhome/rech/genini01/uua34ms/work/anaconda3/envs/pytorch_pip170_cuda102/lib/python3.6/site-packages/datasets/utils/file_utils.py", line 200, in head_hf_s3
return requests.head(hf_bucket_url(identifier=identifier, filename=filename, use_cdn=use_cdn, dataset=dataset))
File "/linkhome/rech/genini01/uua34ms/work/anaconda3/envs/pytorch_pip170_cuda102/lib/python3.6/site-packages/requests/api.py", line 104, in head
return request('head', url, **kwargs)
File "/linkhome/rech/genini01/uua34ms/work/anaconda3/envs/pytorch_pip170_cuda102/lib/python3.6/site-packages/requests/api.py", line 61, in request
return session.request(method=method, url=url, **kwargs)
File "/linkhome/rech/genini01/uua34ms/work/anaconda3/envs/pytorch_pip170_cuda102/lib/python3.6/site-packages/requests/sessions.py", line 530, in request
resp = self.send(prep, **send_kwargs)
File "/linkhome/rech/genini01/uua34ms/work/anaconda3/envs/pytorch_pip170_cuda102/lib/python3.6/site-packages/requests/sessions.py", line 643, in send
r = adapter.send(request, **kwargs)
File "/linkhome/rech/genini01/uua34ms/work/anaconda3/envs/pytorch_pip170_cuda102/lib/python3.6/site-packages/requests/adapters.py", line 516, in send
raise ConnectionError(e, request=request)
requests.exceptions.ConnectionError: HTTPSConnectionPool(host='s3.amazonaws.com', port=443): Max retries exceeded with url: /datasets.huggingface.co/datasets/datasets/wikipedia/wikipedia.py (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x14b7b73e4908>: Failed to establish a new connection: [Errno 110] Connection timed out',))
```
Any advice?Thanks!
| 19 | Can not reuse datasets already downloaded
Hello,
I need to connect to a frontal node (with http proxy, no gpu) before connecting to a gpu node (but no http proxy, so can not use wget so on).
I successfully downloaded and reuse the wikipedia datasets in a frontal node.
When I connect to the gpu node, I supposed to use the downloaded datasets from cache, but failed and end with time out error.
On frontal node:
```
>>> from datasets import load_dataset
>>> dataset = load_dataset('wikipedia', '20200501.en')
Reusing dataset wikipedia (/linkhome/rech/genini01/uua34ms/.cache/huggingface/datasets/wikipedia/20200501.en/1.0.0/f92599dfccab29832c442b82870fa8f6983e5b4ebbf5e6e2dcbe894e325339cd)
/linkhome/rech/genini01/uua34ms/work/anaconda3/envs/pytorch_pip170_cuda102/lib/python3.6/site-packages/torch/cuda/__init__.py:52: UserWarning: CUDA initialization: Found no NVIDIA driver on your system. Please check that you have an NVIDIA GPU and installed a driver from http://www.nvidia.com/Download/index.aspx (Triggered internally at /pytorch/c10/cuda/CUDAFunctions.cpp:100.)
return torch._C._cuda_getDeviceCount() > 0
```
On gpu node:
```
>>> from datasets import load_dataset
>>> dataset = load_dataset('wikipedia', '20200501.en')
Traceback (most recent call last):
File "/linkhome/rech/genini01/uua34ms/work/anaconda3/envs/pytorch_pip170_cuda102/lib/python3.6/site-packages/urllib3/connection.py", line 160, in _new_conn
(self._dns_host, self.port), self.timeout, **extra_kw
File "/linkhome/rech/genini01/uua34ms/work/anaconda3/envs/pytorch_pip170_cuda102/lib/python3.6/site-packages/urllib3/util/connection.py", line 84, in create_connection
raise err
File "/linkhome/rech/genini01/uua34ms/work/anaconda3/envs/pytorch_pip170_cuda102/lib/python3.6/site-packages/urllib3/util/connection.py", line 74, in create_connection
sock.connect(sa)
TimeoutError: [Errno 110] Connection timed out
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/linkhome/rech/genini01/uua34ms/work/anaconda3/envs/pytorch_pip170_cuda102/lib/python3.6/site-packages/urllib3/connectionpool.py", line 677, in urlopen
chunked=chunked,
File "/linkhome/rech/genini01/uua34ms/work/anaconda3/envs/pytorch_pip170_cuda102/lib/python3.6/site-packages/urllib3/connectionpool.py", line 381, in _make_request
self._validate_conn(conn)
File "/linkhome/rech/genini01/uua34ms/work/anaconda3/envs/pytorch_pip170_cuda102/lib/python3.6/site-packages/urllib3/connectionpool.py", line 978, in _validate_conn
conn.connect()
File "/linkhome/rech/genini01/uua34ms/work/anaconda3/envs/pytorch_pip170_cuda102/lib/python3.6/site-packages/urllib3/connection.py", line 309, in connect
conn = self._new_conn()
File "/linkhome/rech/genini01/uua34ms/work/anaconda3/envs/pytorch_pip170_cuda102/lib/python3.6/site-packages/urllib3/connection.py", line 172, in _new_conn
self, "Failed to establish a new connection: %s" % e
urllib3.exceptions.NewConnectionError: <urllib3.connection.HTTPSConnection object at 0x14b7b73e4908>: Failed to establish a new connection: [Errno 110] Connection timed out
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/linkhome/rech/genini01/uua34ms/work/anaconda3/envs/pytorch_pip170_cuda102/lib/python3.6/site-packages/requests/adapters.py", line 449, in send
timeout=timeout
File "/linkhome/rech/genini01/uua34ms/work/anaconda3/envs/pytorch_pip170_cuda102/lib/python3.6/site-packages/urllib3/connectionpool.py", line 727, in urlopen
method, url, error=e, _pool=self, _stacktrace=sys.exc_info()[2]
File "/linkhome/rech/genini01/uua34ms/work/anaconda3/envs/pytorch_pip170_cuda102/lib/python3.6/site-packages/urllib3/util/retry.py", line 446, in increment
raise MaxRetryError(_pool, url, error or ResponseError(cause))
urllib3.exceptions.MaxRetryError: HTTPSConnectionPool(host='s3.amazonaws.com', port=443): Max retries exceeded with url: /datasets.huggingface.co/datasets/datasets/wikipedia/wikipedia.py (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x14b7b73e4908>: Failed to establish a new connection: [Errno 110] Connection timed out',))
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/linkhome/rech/genini01/uua34ms/work/anaconda3/envs/pytorch_pip170_cuda102/lib/python3.6/site-packages/datasets/load.py", line 590, in load_dataset
path, script_version=script_version, download_config=download_config, download_mode=download_mode, dataset=True
File "/linkhome/rech/genini01/uua34ms/work/anaconda3/envs/pytorch_pip170_cuda102/lib/python3.6/site-packages/datasets/load.py", line 264, in prepare_module
head_hf_s3(path, filename=name, dataset=dataset)
File "/linkhome/rech/genini01/uua34ms/work/anaconda3/envs/pytorch_pip170_cuda102/lib/python3.6/site-packages/datasets/utils/file_utils.py", line 200, in head_hf_s3
return requests.head(hf_bucket_url(identifier=identifier, filename=filename, use_cdn=use_cdn, dataset=dataset))
File "/linkhome/rech/genini01/uua34ms/work/anaconda3/envs/pytorch_pip170_cuda102/lib/python3.6/site-packages/requests/api.py", line 104, in head
return request('head', url, **kwargs)
File "/linkhome/rech/genini01/uua34ms/work/anaconda3/envs/pytorch_pip170_cuda102/lib/python3.6/site-packages/requests/api.py", line 61, in request
return session.request(method=method, url=url, **kwargs)
File "/linkhome/rech/genini01/uua34ms/work/anaconda3/envs/pytorch_pip170_cuda102/lib/python3.6/site-packages/requests/sessions.py", line 530, in request
resp = self.send(prep, **send_kwargs)
File "/linkhome/rech/genini01/uua34ms/work/anaconda3/envs/pytorch_pip170_cuda102/lib/python3.6/site-packages/requests/sessions.py", line 643, in send
r = adapter.send(request, **kwargs)
File "/linkhome/rech/genini01/uua34ms/work/anaconda3/envs/pytorch_pip170_cuda102/lib/python3.6/site-packages/requests/adapters.py", line 516, in send
raise ConnectionError(e, request=request)
requests.exceptions.ConnectionError: HTTPSConnectionPool(host='s3.amazonaws.com', port=443): Max retries exceeded with url: /datasets.huggingface.co/datasets/datasets/wikipedia/wikipedia.py (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x14b7b73e4908>: Failed to establish a new connection: [Errno 110] Connection timed out',))
```
Any advice?Thanks!
It seems the process needs '/datasets.huggingface.co/datasets/datasets/wikipedia/wikipedia.py'
Where and how to assign this ```wikipedia.py``` after I manually download it ? |
https://github.com/huggingface/datasets/issues/836 | load_dataset with 'csv' is not working. while the same file is loading with 'text' mode or with pandas | Which version of pyarrow do you have ? Could you try to update pyarrow and try again ? | Hi All
I am trying to load a custom dataset and I am trying to load a single file to make sure the file is loading correctly:
dataset = load_dataset('csv', data_files=files)
When I run it I get:
Downloading and preparing dataset csv/default-35575a1051604c88 (download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size) tocache/huggingface/datasets/csv/default-35575a1051604c88/0.0.0/49187751790fa4d820300fd4d0707896e5b941f1a9c644652645b866716a4ac4...
I am getting this error:
6a4ac4/csv.py in _generate_tables(self, files)
78 def _generate_tables(self, files):
79 for i, file in enumerate(files):
---> 80 pa_table = pac.read_csv(
81 file,
82 read_options=self.config.pa_read_options,
~/anaconda2/envs/nlp/lib/python3.8/site-packages/pyarrow/_csv.pyx in pyarrow._csv.read_csv()
~/anaconda2/envs/nlp/lib/python3.8/site-packages/pyarrow/error.pxi in pyarrow.lib.pyarrow_internal_check_status()
~/anaconda2/envs/nlp/lib/python3.8/site-packages/pyarrow/error.pxi in pyarrow.lib.check_status()
**ArrowInvalid: straddling object straddles two block boundaries (try to increase block size?)**
The size of the file is 3.5 GB. When I try smaller files I do not have an issue. When I load it with 'text' parser I can see all data but it is not what I need.
There is no issue reading the file with pandas. any idea what could be the issue?
When I am running a different CSV I do not get this line:
(download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size)
Any ideas?
| 18 | load_dataset with 'csv' is not working. while the same file is loading with 'text' mode or with pandas
Hi All
I am trying to load a custom dataset and I am trying to load a single file to make sure the file is loading correctly:
dataset = load_dataset('csv', data_files=files)
When I run it I get:
Downloading and preparing dataset csv/default-35575a1051604c88 (download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size) tocache/huggingface/datasets/csv/default-35575a1051604c88/0.0.0/49187751790fa4d820300fd4d0707896e5b941f1a9c644652645b866716a4ac4...
I am getting this error:
6a4ac4/csv.py in _generate_tables(self, files)
78 def _generate_tables(self, files):
79 for i, file in enumerate(files):
---> 80 pa_table = pac.read_csv(
81 file,
82 read_options=self.config.pa_read_options,
~/anaconda2/envs/nlp/lib/python3.8/site-packages/pyarrow/_csv.pyx in pyarrow._csv.read_csv()
~/anaconda2/envs/nlp/lib/python3.8/site-packages/pyarrow/error.pxi in pyarrow.lib.pyarrow_internal_check_status()
~/anaconda2/envs/nlp/lib/python3.8/site-packages/pyarrow/error.pxi in pyarrow.lib.check_status()
**ArrowInvalid: straddling object straddles two block boundaries (try to increase block size?)**
The size of the file is 3.5 GB. When I try smaller files I do not have an issue. When I load it with 'text' parser I can see all data but it is not what I need.
There is no issue reading the file with pandas. any idea what could be the issue?
When I am running a different CSV I do not get this line:
(download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size)
Any ideas?
Which version of pyarrow do you have ? Could you try to update pyarrow and try again ? |
https://github.com/huggingface/datasets/issues/836 | load_dataset with 'csv' is not working. while the same file is loading with 'text' mode or with pandas | Thanks for the fast response. I have the latest version '2.0.0' (I tried to update)
I am working with Python 3.8.5 | Hi All
I am trying to load a custom dataset and I am trying to load a single file to make sure the file is loading correctly:
dataset = load_dataset('csv', data_files=files)
When I run it I get:
Downloading and preparing dataset csv/default-35575a1051604c88 (download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size) tocache/huggingface/datasets/csv/default-35575a1051604c88/0.0.0/49187751790fa4d820300fd4d0707896e5b941f1a9c644652645b866716a4ac4...
I am getting this error:
6a4ac4/csv.py in _generate_tables(self, files)
78 def _generate_tables(self, files):
79 for i, file in enumerate(files):
---> 80 pa_table = pac.read_csv(
81 file,
82 read_options=self.config.pa_read_options,
~/anaconda2/envs/nlp/lib/python3.8/site-packages/pyarrow/_csv.pyx in pyarrow._csv.read_csv()
~/anaconda2/envs/nlp/lib/python3.8/site-packages/pyarrow/error.pxi in pyarrow.lib.pyarrow_internal_check_status()
~/anaconda2/envs/nlp/lib/python3.8/site-packages/pyarrow/error.pxi in pyarrow.lib.check_status()
**ArrowInvalid: straddling object straddles two block boundaries (try to increase block size?)**
The size of the file is 3.5 GB. When I try smaller files I do not have an issue. When I load it with 'text' parser I can see all data but it is not what I need.
There is no issue reading the file with pandas. any idea what could be the issue?
When I am running a different CSV I do not get this line:
(download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size)
Any ideas?
| 21 | load_dataset with 'csv' is not working. while the same file is loading with 'text' mode or with pandas
Hi All
I am trying to load a custom dataset and I am trying to load a single file to make sure the file is loading correctly:
dataset = load_dataset('csv', data_files=files)
When I run it I get:
Downloading and preparing dataset csv/default-35575a1051604c88 (download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size) tocache/huggingface/datasets/csv/default-35575a1051604c88/0.0.0/49187751790fa4d820300fd4d0707896e5b941f1a9c644652645b866716a4ac4...
I am getting this error:
6a4ac4/csv.py in _generate_tables(self, files)
78 def _generate_tables(self, files):
79 for i, file in enumerate(files):
---> 80 pa_table = pac.read_csv(
81 file,
82 read_options=self.config.pa_read_options,
~/anaconda2/envs/nlp/lib/python3.8/site-packages/pyarrow/_csv.pyx in pyarrow._csv.read_csv()
~/anaconda2/envs/nlp/lib/python3.8/site-packages/pyarrow/error.pxi in pyarrow.lib.pyarrow_internal_check_status()
~/anaconda2/envs/nlp/lib/python3.8/site-packages/pyarrow/error.pxi in pyarrow.lib.check_status()
**ArrowInvalid: straddling object straddles two block boundaries (try to increase block size?)**
The size of the file is 3.5 GB. When I try smaller files I do not have an issue. When I load it with 'text' parser I can see all data but it is not what I need.
There is no issue reading the file with pandas. any idea what could be the issue?
When I am running a different CSV I do not get this line:
(download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size)
Any ideas?
Thanks for the fast response. I have the latest version '2.0.0' (I tried to update)
I am working with Python 3.8.5 |
https://github.com/huggingface/datasets/issues/836 | load_dataset with 'csv' is not working. while the same file is loading with 'text' mode or with pandas | I think that the issue is similar to this one:https://issues.apache.org/jira/browse/ARROW-9612
The problem is in arrow when the column data contains long strings.
Any ideas on how to bypass this? | Hi All
I am trying to load a custom dataset and I am trying to load a single file to make sure the file is loading correctly:
dataset = load_dataset('csv', data_files=files)
When I run it I get:
Downloading and preparing dataset csv/default-35575a1051604c88 (download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size) tocache/huggingface/datasets/csv/default-35575a1051604c88/0.0.0/49187751790fa4d820300fd4d0707896e5b941f1a9c644652645b866716a4ac4...
I am getting this error:
6a4ac4/csv.py in _generate_tables(self, files)
78 def _generate_tables(self, files):
79 for i, file in enumerate(files):
---> 80 pa_table = pac.read_csv(
81 file,
82 read_options=self.config.pa_read_options,
~/anaconda2/envs/nlp/lib/python3.8/site-packages/pyarrow/_csv.pyx in pyarrow._csv.read_csv()
~/anaconda2/envs/nlp/lib/python3.8/site-packages/pyarrow/error.pxi in pyarrow.lib.pyarrow_internal_check_status()
~/anaconda2/envs/nlp/lib/python3.8/site-packages/pyarrow/error.pxi in pyarrow.lib.check_status()
**ArrowInvalid: straddling object straddles two block boundaries (try to increase block size?)**
The size of the file is 3.5 GB. When I try smaller files I do not have an issue. When I load it with 'text' parser I can see all data but it is not what I need.
There is no issue reading the file with pandas. any idea what could be the issue?
When I am running a different CSV I do not get this line:
(download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size)
Any ideas?
| 29 | load_dataset with 'csv' is not working. while the same file is loading with 'text' mode or with pandas
Hi All
I am trying to load a custom dataset and I am trying to load a single file to make sure the file is loading correctly:
dataset = load_dataset('csv', data_files=files)
When I run it I get:
Downloading and preparing dataset csv/default-35575a1051604c88 (download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size) tocache/huggingface/datasets/csv/default-35575a1051604c88/0.0.0/49187751790fa4d820300fd4d0707896e5b941f1a9c644652645b866716a4ac4...
I am getting this error:
6a4ac4/csv.py in _generate_tables(self, files)
78 def _generate_tables(self, files):
79 for i, file in enumerate(files):
---> 80 pa_table = pac.read_csv(
81 file,
82 read_options=self.config.pa_read_options,
~/anaconda2/envs/nlp/lib/python3.8/site-packages/pyarrow/_csv.pyx in pyarrow._csv.read_csv()
~/anaconda2/envs/nlp/lib/python3.8/site-packages/pyarrow/error.pxi in pyarrow.lib.pyarrow_internal_check_status()
~/anaconda2/envs/nlp/lib/python3.8/site-packages/pyarrow/error.pxi in pyarrow.lib.check_status()
**ArrowInvalid: straddling object straddles two block boundaries (try to increase block size?)**
The size of the file is 3.5 GB. When I try smaller files I do not have an issue. When I load it with 'text' parser I can see all data but it is not what I need.
There is no issue reading the file with pandas. any idea what could be the issue?
When I am running a different CSV I do not get this line:
(download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size)
Any ideas?
I think that the issue is similar to this one:https://issues.apache.org/jira/browse/ARROW-9612
The problem is in arrow when the column data contains long strings.
Any ideas on how to bypass this? |
https://github.com/huggingface/datasets/issues/836 | load_dataset with 'csv' is not working. while the same file is loading with 'text' mode or with pandas | We should expose the [`block_size` argument](https://arrow.apache.org/docs/python/generated/pyarrow.csv.ReadOptions.html#pyarrow.csv.ReadOptions) of Apache Arrow csv `ReadOptions` in the [script](https://github.com/huggingface/datasets/blob/master/datasets/csv/csv.py).
In the meantime you can specify yourself the `ReadOptions` config like this:
```python
import pyarrow.csv as pac # PyArrow is installed with `datasets`
read_options = pac.ReadOptions(block_size=1e9) # try to find the right value for your use-case
dataset = load_dataset('csv', data_files=files, read_options=read_options)
```
| Hi All
I am trying to load a custom dataset and I am trying to load a single file to make sure the file is loading correctly:
dataset = load_dataset('csv', data_files=files)
When I run it I get:
Downloading and preparing dataset csv/default-35575a1051604c88 (download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size) tocache/huggingface/datasets/csv/default-35575a1051604c88/0.0.0/49187751790fa4d820300fd4d0707896e5b941f1a9c644652645b866716a4ac4...
I am getting this error:
6a4ac4/csv.py in _generate_tables(self, files)
78 def _generate_tables(self, files):
79 for i, file in enumerate(files):
---> 80 pa_table = pac.read_csv(
81 file,
82 read_options=self.config.pa_read_options,
~/anaconda2/envs/nlp/lib/python3.8/site-packages/pyarrow/_csv.pyx in pyarrow._csv.read_csv()
~/anaconda2/envs/nlp/lib/python3.8/site-packages/pyarrow/error.pxi in pyarrow.lib.pyarrow_internal_check_status()
~/anaconda2/envs/nlp/lib/python3.8/site-packages/pyarrow/error.pxi in pyarrow.lib.check_status()
**ArrowInvalid: straddling object straddles two block boundaries (try to increase block size?)**
The size of the file is 3.5 GB. When I try smaller files I do not have an issue. When I load it with 'text' parser I can see all data but it is not what I need.
There is no issue reading the file with pandas. any idea what could be the issue?
When I am running a different CSV I do not get this line:
(download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size)
Any ideas?
| 56 | load_dataset with 'csv' is not working. while the same file is loading with 'text' mode or with pandas
Hi All
I am trying to load a custom dataset and I am trying to load a single file to make sure the file is loading correctly:
dataset = load_dataset('csv', data_files=files)
When I run it I get:
Downloading and preparing dataset csv/default-35575a1051604c88 (download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size) tocache/huggingface/datasets/csv/default-35575a1051604c88/0.0.0/49187751790fa4d820300fd4d0707896e5b941f1a9c644652645b866716a4ac4...
I am getting this error:
6a4ac4/csv.py in _generate_tables(self, files)
78 def _generate_tables(self, files):
79 for i, file in enumerate(files):
---> 80 pa_table = pac.read_csv(
81 file,
82 read_options=self.config.pa_read_options,
~/anaconda2/envs/nlp/lib/python3.8/site-packages/pyarrow/_csv.pyx in pyarrow._csv.read_csv()
~/anaconda2/envs/nlp/lib/python3.8/site-packages/pyarrow/error.pxi in pyarrow.lib.pyarrow_internal_check_status()
~/anaconda2/envs/nlp/lib/python3.8/site-packages/pyarrow/error.pxi in pyarrow.lib.check_status()
**ArrowInvalid: straddling object straddles two block boundaries (try to increase block size?)**
The size of the file is 3.5 GB. When I try smaller files I do not have an issue. When I load it with 'text' parser I can see all data but it is not what I need.
There is no issue reading the file with pandas. any idea what could be the issue?
When I am running a different CSV I do not get this line:
(download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size)
Any ideas?
We should expose the [`block_size` argument](https://arrow.apache.org/docs/python/generated/pyarrow.csv.ReadOptions.html#pyarrow.csv.ReadOptions) of Apache Arrow csv `ReadOptions` in the [script](https://github.com/huggingface/datasets/blob/master/datasets/csv/csv.py).
In the meantime you can specify yourself the `ReadOptions` config like this:
```python
import pyarrow.csv as pac # PyArrow is installed with `datasets`
read_options = pac.ReadOptions(block_size=1e9) # try to find the right value for your use-case
dataset = load_dataset('csv', data_files=files, read_options=read_options)
```
|
https://github.com/huggingface/datasets/issues/836 | load_dataset with 'csv' is not working. while the same file is loading with 'text' mode or with pandas | This did help to load the data. But the problem now is that I get:
ArrowInvalid: CSV parse error: Expected 5 columns, got 187
It seems that this change the parsing so I changed the table to tab-separated and tried to load it directly from pyarrow
But I got a similar error, again it loaded fine in pandas so I am not sure what to do.
| Hi All
I am trying to load a custom dataset and I am trying to load a single file to make sure the file is loading correctly:
dataset = load_dataset('csv', data_files=files)
When I run it I get:
Downloading and preparing dataset csv/default-35575a1051604c88 (download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size) tocache/huggingface/datasets/csv/default-35575a1051604c88/0.0.0/49187751790fa4d820300fd4d0707896e5b941f1a9c644652645b866716a4ac4...
I am getting this error:
6a4ac4/csv.py in _generate_tables(self, files)
78 def _generate_tables(self, files):
79 for i, file in enumerate(files):
---> 80 pa_table = pac.read_csv(
81 file,
82 read_options=self.config.pa_read_options,
~/anaconda2/envs/nlp/lib/python3.8/site-packages/pyarrow/_csv.pyx in pyarrow._csv.read_csv()
~/anaconda2/envs/nlp/lib/python3.8/site-packages/pyarrow/error.pxi in pyarrow.lib.pyarrow_internal_check_status()
~/anaconda2/envs/nlp/lib/python3.8/site-packages/pyarrow/error.pxi in pyarrow.lib.check_status()
**ArrowInvalid: straddling object straddles two block boundaries (try to increase block size?)**
The size of the file is 3.5 GB. When I try smaller files I do not have an issue. When I load it with 'text' parser I can see all data but it is not what I need.
There is no issue reading the file with pandas. any idea what could be the issue?
When I am running a different CSV I do not get this line:
(download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size)
Any ideas?
| 66 | load_dataset with 'csv' is not working. while the same file is loading with 'text' mode or with pandas
Hi All
I am trying to load a custom dataset and I am trying to load a single file to make sure the file is loading correctly:
dataset = load_dataset('csv', data_files=files)
When I run it I get:
Downloading and preparing dataset csv/default-35575a1051604c88 (download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size) tocache/huggingface/datasets/csv/default-35575a1051604c88/0.0.0/49187751790fa4d820300fd4d0707896e5b941f1a9c644652645b866716a4ac4...
I am getting this error:
6a4ac4/csv.py in _generate_tables(self, files)
78 def _generate_tables(self, files):
79 for i, file in enumerate(files):
---> 80 pa_table = pac.read_csv(
81 file,
82 read_options=self.config.pa_read_options,
~/anaconda2/envs/nlp/lib/python3.8/site-packages/pyarrow/_csv.pyx in pyarrow._csv.read_csv()
~/anaconda2/envs/nlp/lib/python3.8/site-packages/pyarrow/error.pxi in pyarrow.lib.pyarrow_internal_check_status()
~/anaconda2/envs/nlp/lib/python3.8/site-packages/pyarrow/error.pxi in pyarrow.lib.check_status()
**ArrowInvalid: straddling object straddles two block boundaries (try to increase block size?)**
The size of the file is 3.5 GB. When I try smaller files I do not have an issue. When I load it with 'text' parser I can see all data but it is not what I need.
There is no issue reading the file with pandas. any idea what could be the issue?
When I am running a different CSV I do not get this line:
(download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size)
Any ideas?
This did help to load the data. But the problem now is that I get:
ArrowInvalid: CSV parse error: Expected 5 columns, got 187
It seems that this change the parsing so I changed the table to tab-separated and tried to load it directly from pyarrow
But I got a similar error, again it loaded fine in pandas so I am not sure what to do.
|
https://github.com/huggingface/datasets/issues/836 | load_dataset with 'csv' is not working. while the same file is loading with 'text' mode or with pandas | Got almost the same error loading a ~5GB TSV file, first got the same error as OP, then tried giving it my own ReadOptions and also got the same CSV parse error. | Hi All
I am trying to load a custom dataset and I am trying to load a single file to make sure the file is loading correctly:
dataset = load_dataset('csv', data_files=files)
When I run it I get:
Downloading and preparing dataset csv/default-35575a1051604c88 (download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size) tocache/huggingface/datasets/csv/default-35575a1051604c88/0.0.0/49187751790fa4d820300fd4d0707896e5b941f1a9c644652645b866716a4ac4...
I am getting this error:
6a4ac4/csv.py in _generate_tables(self, files)
78 def _generate_tables(self, files):
79 for i, file in enumerate(files):
---> 80 pa_table = pac.read_csv(
81 file,
82 read_options=self.config.pa_read_options,
~/anaconda2/envs/nlp/lib/python3.8/site-packages/pyarrow/_csv.pyx in pyarrow._csv.read_csv()
~/anaconda2/envs/nlp/lib/python3.8/site-packages/pyarrow/error.pxi in pyarrow.lib.pyarrow_internal_check_status()
~/anaconda2/envs/nlp/lib/python3.8/site-packages/pyarrow/error.pxi in pyarrow.lib.check_status()
**ArrowInvalid: straddling object straddles two block boundaries (try to increase block size?)**
The size of the file is 3.5 GB. When I try smaller files I do not have an issue. When I load it with 'text' parser I can see all data but it is not what I need.
There is no issue reading the file with pandas. any idea what could be the issue?
When I am running a different CSV I do not get this line:
(download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size)
Any ideas?
| 32 | load_dataset with 'csv' is not working. while the same file is loading with 'text' mode or with pandas
Hi All
I am trying to load a custom dataset and I am trying to load a single file to make sure the file is loading correctly:
dataset = load_dataset('csv', data_files=files)
When I run it I get:
Downloading and preparing dataset csv/default-35575a1051604c88 (download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size) tocache/huggingface/datasets/csv/default-35575a1051604c88/0.0.0/49187751790fa4d820300fd4d0707896e5b941f1a9c644652645b866716a4ac4...
I am getting this error:
6a4ac4/csv.py in _generate_tables(self, files)
78 def _generate_tables(self, files):
79 for i, file in enumerate(files):
---> 80 pa_table = pac.read_csv(
81 file,
82 read_options=self.config.pa_read_options,
~/anaconda2/envs/nlp/lib/python3.8/site-packages/pyarrow/_csv.pyx in pyarrow._csv.read_csv()
~/anaconda2/envs/nlp/lib/python3.8/site-packages/pyarrow/error.pxi in pyarrow.lib.pyarrow_internal_check_status()
~/anaconda2/envs/nlp/lib/python3.8/site-packages/pyarrow/error.pxi in pyarrow.lib.check_status()
**ArrowInvalid: straddling object straddles two block boundaries (try to increase block size?)**
The size of the file is 3.5 GB. When I try smaller files I do not have an issue. When I load it with 'text' parser I can see all data but it is not what I need.
There is no issue reading the file with pandas. any idea what could be the issue?
When I am running a different CSV I do not get this line:
(download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size)
Any ideas?
Got almost the same error loading a ~5GB TSV file, first got the same error as OP, then tried giving it my own ReadOptions and also got the same CSV parse error. |
https://github.com/huggingface/datasets/issues/836 | load_dataset with 'csv' is not working. while the same file is loading with 'text' mode or with pandas | > We should expose the [`block_size` argument](https://arrow.apache.org/docs/python/generated/pyarrow.csv.ReadOptions.html#pyarrow.csv.ReadOptions) of Apache Arrow csv `ReadOptions` in the [script](https://github.com/huggingface/datasets/blob/master/datasets/csv/csv.py).
>
> In the meantime you can specify yourself the `ReadOptions` config like this:
>
> ```python
> import pyarrow.csv as pac # PyArrow is installed with `datasets`
>
> read_options = pac.ReadOptions(block_size=1e9) # try to find the right value for your use-case
> dataset = load_dataset('csv', data_files=files, read_options=read_options)
> ```
This did not work for me, I got
`TypeError: __init__() got an unexpected keyword argument 'read_options'` | Hi All
I am trying to load a custom dataset and I am trying to load a single file to make sure the file is loading correctly:
dataset = load_dataset('csv', data_files=files)
When I run it I get:
Downloading and preparing dataset csv/default-35575a1051604c88 (download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size) tocache/huggingface/datasets/csv/default-35575a1051604c88/0.0.0/49187751790fa4d820300fd4d0707896e5b941f1a9c644652645b866716a4ac4...
I am getting this error:
6a4ac4/csv.py in _generate_tables(self, files)
78 def _generate_tables(self, files):
79 for i, file in enumerate(files):
---> 80 pa_table = pac.read_csv(
81 file,
82 read_options=self.config.pa_read_options,
~/anaconda2/envs/nlp/lib/python3.8/site-packages/pyarrow/_csv.pyx in pyarrow._csv.read_csv()
~/anaconda2/envs/nlp/lib/python3.8/site-packages/pyarrow/error.pxi in pyarrow.lib.pyarrow_internal_check_status()
~/anaconda2/envs/nlp/lib/python3.8/site-packages/pyarrow/error.pxi in pyarrow.lib.check_status()
**ArrowInvalid: straddling object straddles two block boundaries (try to increase block size?)**
The size of the file is 3.5 GB. When I try smaller files I do not have an issue. When I load it with 'text' parser I can see all data but it is not what I need.
There is no issue reading the file with pandas. any idea what could be the issue?
When I am running a different CSV I do not get this line:
(download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size)
Any ideas?
| 82 | load_dataset with 'csv' is not working. while the same file is loading with 'text' mode or with pandas
Hi All
I am trying to load a custom dataset and I am trying to load a single file to make sure the file is loading correctly:
dataset = load_dataset('csv', data_files=files)
When I run it I get:
Downloading and preparing dataset csv/default-35575a1051604c88 (download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size) tocache/huggingface/datasets/csv/default-35575a1051604c88/0.0.0/49187751790fa4d820300fd4d0707896e5b941f1a9c644652645b866716a4ac4...
I am getting this error:
6a4ac4/csv.py in _generate_tables(self, files)
78 def _generate_tables(self, files):
79 for i, file in enumerate(files):
---> 80 pa_table = pac.read_csv(
81 file,
82 read_options=self.config.pa_read_options,
~/anaconda2/envs/nlp/lib/python3.8/site-packages/pyarrow/_csv.pyx in pyarrow._csv.read_csv()
~/anaconda2/envs/nlp/lib/python3.8/site-packages/pyarrow/error.pxi in pyarrow.lib.pyarrow_internal_check_status()
~/anaconda2/envs/nlp/lib/python3.8/site-packages/pyarrow/error.pxi in pyarrow.lib.check_status()
**ArrowInvalid: straddling object straddles two block boundaries (try to increase block size?)**
The size of the file is 3.5 GB. When I try smaller files I do not have an issue. When I load it with 'text' parser I can see all data but it is not what I need.
There is no issue reading the file with pandas. any idea what could be the issue?
When I am running a different CSV I do not get this line:
(download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size)
Any ideas?
> We should expose the [`block_size` argument](https://arrow.apache.org/docs/python/generated/pyarrow.csv.ReadOptions.html#pyarrow.csv.ReadOptions) of Apache Arrow csv `ReadOptions` in the [script](https://github.com/huggingface/datasets/blob/master/datasets/csv/csv.py).
>
> In the meantime you can specify yourself the `ReadOptions` config like this:
>
> ```python
> import pyarrow.csv as pac # PyArrow is installed with `datasets`
>
> read_options = pac.ReadOptions(block_size=1e9) # try to find the right value for your use-case
> dataset = load_dataset('csv', data_files=files, read_options=read_options)
> ```
This did not work for me, I got
`TypeError: __init__() got an unexpected keyword argument 'read_options'` |
https://github.com/huggingface/datasets/issues/836 | load_dataset with 'csv' is not working. while the same file is loading with 'text' mode or with pandas | Hi ! Yes because of issues with PyArrow's CSV reader we switched to using the Pandas CSV reader. In particular the `read_options` argument is not supported anymore, but you can pass any parameter of Pandas' `read_csv` function (see the list here in [Pandas documentation](https://pandas.pydata.org/docs/reference/api/pandas.read_csv.html)) | Hi All
I am trying to load a custom dataset and I am trying to load a single file to make sure the file is loading correctly:
dataset = load_dataset('csv', data_files=files)
When I run it I get:
Downloading and preparing dataset csv/default-35575a1051604c88 (download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size) tocache/huggingface/datasets/csv/default-35575a1051604c88/0.0.0/49187751790fa4d820300fd4d0707896e5b941f1a9c644652645b866716a4ac4...
I am getting this error:
6a4ac4/csv.py in _generate_tables(self, files)
78 def _generate_tables(self, files):
79 for i, file in enumerate(files):
---> 80 pa_table = pac.read_csv(
81 file,
82 read_options=self.config.pa_read_options,
~/anaconda2/envs/nlp/lib/python3.8/site-packages/pyarrow/_csv.pyx in pyarrow._csv.read_csv()
~/anaconda2/envs/nlp/lib/python3.8/site-packages/pyarrow/error.pxi in pyarrow.lib.pyarrow_internal_check_status()
~/anaconda2/envs/nlp/lib/python3.8/site-packages/pyarrow/error.pxi in pyarrow.lib.check_status()
**ArrowInvalid: straddling object straddles two block boundaries (try to increase block size?)**
The size of the file is 3.5 GB. When I try smaller files I do not have an issue. When I load it with 'text' parser I can see all data but it is not what I need.
There is no issue reading the file with pandas. any idea what could be the issue?
When I am running a different CSV I do not get this line:
(download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size)
Any ideas?
| 44 | load_dataset with 'csv' is not working. while the same file is loading with 'text' mode or with pandas
Hi All
I am trying to load a custom dataset and I am trying to load a single file to make sure the file is loading correctly:
dataset = load_dataset('csv', data_files=files)
When I run it I get:
Downloading and preparing dataset csv/default-35575a1051604c88 (download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size) tocache/huggingface/datasets/csv/default-35575a1051604c88/0.0.0/49187751790fa4d820300fd4d0707896e5b941f1a9c644652645b866716a4ac4...
I am getting this error:
6a4ac4/csv.py in _generate_tables(self, files)
78 def _generate_tables(self, files):
79 for i, file in enumerate(files):
---> 80 pa_table = pac.read_csv(
81 file,
82 read_options=self.config.pa_read_options,
~/anaconda2/envs/nlp/lib/python3.8/site-packages/pyarrow/_csv.pyx in pyarrow._csv.read_csv()
~/anaconda2/envs/nlp/lib/python3.8/site-packages/pyarrow/error.pxi in pyarrow.lib.pyarrow_internal_check_status()
~/anaconda2/envs/nlp/lib/python3.8/site-packages/pyarrow/error.pxi in pyarrow.lib.check_status()
**ArrowInvalid: straddling object straddles two block boundaries (try to increase block size?)**
The size of the file is 3.5 GB. When I try smaller files I do not have an issue. When I load it with 'text' parser I can see all data but it is not what I need.
There is no issue reading the file with pandas. any idea what could be the issue?
When I am running a different CSV I do not get this line:
(download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size)
Any ideas?
Hi ! Yes because of issues with PyArrow's CSV reader we switched to using the Pandas CSV reader. In particular the `read_options` argument is not supported anymore, but you can pass any parameter of Pandas' `read_csv` function (see the list here in [Pandas documentation](https://pandas.pydata.org/docs/reference/api/pandas.read_csv.html)) |
https://github.com/huggingface/datasets/issues/835 | Wikipedia postprocessing | Hi @bminixhofer ! Parsing WikiMedia is notoriously difficult: this processing used [mwparserfromhell](https://github.com/earwig/mwparserfromhell) which is pretty good but not perfect.
As an alternative, you can also use the Wiki40b dataset which was pre-processed using an un-released Google internal tool | Hi, thanks for this library!
Running this code:
```py
import datasets
wikipedia = datasets.load_dataset("wikipedia", "20200501.de")
print(wikipedia['train']['text'][0])
```
I get:
```
mini|Ricardo Flores Magón
mini|Mexikanische Revolutionäre, Magón in der Mitte anführend, gegen die Diktatur von Porfirio Diaz, Ausschnitt des Gemälde „Tierra y Libertad“ von Idelfonso Carrara (?) von 1930.
Ricardo Flores Magón (* 16. September 1874 in San Antonio Eloxochitlán im mexikanischen Bundesstaat Oaxaca; † 22. November 1922 im Bundesgefängnis Leavenworth im US-amerikanischen Bundesstaat Kansas) war als Journalist, Gewerkschafter und Literat ein führender anarchistischer Theoretiker und Aktivist, der die revolutionäre mexikanische Bewegung radikal beeinflusste. Magón war Gründer der Partido Liberal Mexicano und Mitglied der Industrial Workers of the World.
Politische Biografie
Journalistisch und politisch kämpfte er und sein Bruder sehr kompromisslos gegen die Diktatur Porfirio Diaz. Philosophisch und politisch orientiert an radikal anarchistischen Idealen und den Erfahrungen seiner indigenen Vorfahren bei der gemeinschaftlichen Bewirtschaftung des Gemeindelandes, machte er die Forderung „Land und Freiheit“ (Tierra y Libertad) populär. Besonders Francisco Villa und Emiliano Zapata griffen die Forderung Land und Freiheit auf. Seine Philosophie hatte großen Einfluss auf die Landarbeiter. 1904 floh er in die USA und gründete 1906 die Partido Liberal Mexicano. Im Exil lernte er u. a. Emma Goldman kennen. Er verbrachte die meiste Zeit seines Lebens in Gefängnissen und im Exil und wurde 1918 in den USA wegen „Behinderung der Kriegsanstrengungen“ zu zwanzig Jahren Gefängnis verurteilt. Zu seinem Tod gibt es drei verschiedene Theorien. Offiziell starb er an Herzversagen. Librado Rivera, der die Leiche mit eigenen Augen gesehen hat, geht davon aus, dass Magón von einem Mitgefangenen erdrosselt wurde. Die staatstreue Gewerkschaftszeitung CROM veröffentlichte 1923 einen Beitrag, nachdem Magón von einem Gefängniswärter erschlagen wurde.
mini|Die Brüder Ricardo (links) und Enrique Flores Magón (rechts) vor dem Los Angeles County Jail, 1917
[...]
```
so some Markup like `mini|` is still left. Should I run another parser on this text before feeding it to an ML model or is this a known imperfection of parsing Wiki markup?
Apologies if this has been asked before. | 38 | Wikipedia postprocessing
Hi, thanks for this library!
Running this code:
```py
import datasets
wikipedia = datasets.load_dataset("wikipedia", "20200501.de")
print(wikipedia['train']['text'][0])
```
I get:
```
mini|Ricardo Flores Magón
mini|Mexikanische Revolutionäre, Magón in der Mitte anführend, gegen die Diktatur von Porfirio Diaz, Ausschnitt des Gemälde „Tierra y Libertad“ von Idelfonso Carrara (?) von 1930.
Ricardo Flores Magón (* 16. September 1874 in San Antonio Eloxochitlán im mexikanischen Bundesstaat Oaxaca; † 22. November 1922 im Bundesgefängnis Leavenworth im US-amerikanischen Bundesstaat Kansas) war als Journalist, Gewerkschafter und Literat ein führender anarchistischer Theoretiker und Aktivist, der die revolutionäre mexikanische Bewegung radikal beeinflusste. Magón war Gründer der Partido Liberal Mexicano und Mitglied der Industrial Workers of the World.
Politische Biografie
Journalistisch und politisch kämpfte er und sein Bruder sehr kompromisslos gegen die Diktatur Porfirio Diaz. Philosophisch und politisch orientiert an radikal anarchistischen Idealen und den Erfahrungen seiner indigenen Vorfahren bei der gemeinschaftlichen Bewirtschaftung des Gemeindelandes, machte er die Forderung „Land und Freiheit“ (Tierra y Libertad) populär. Besonders Francisco Villa und Emiliano Zapata griffen die Forderung Land und Freiheit auf. Seine Philosophie hatte großen Einfluss auf die Landarbeiter. 1904 floh er in die USA und gründete 1906 die Partido Liberal Mexicano. Im Exil lernte er u. a. Emma Goldman kennen. Er verbrachte die meiste Zeit seines Lebens in Gefängnissen und im Exil und wurde 1918 in den USA wegen „Behinderung der Kriegsanstrengungen“ zu zwanzig Jahren Gefängnis verurteilt. Zu seinem Tod gibt es drei verschiedene Theorien. Offiziell starb er an Herzversagen. Librado Rivera, der die Leiche mit eigenen Augen gesehen hat, geht davon aus, dass Magón von einem Mitgefangenen erdrosselt wurde. Die staatstreue Gewerkschaftszeitung CROM veröffentlichte 1923 einen Beitrag, nachdem Magón von einem Gefängniswärter erschlagen wurde.
mini|Die Brüder Ricardo (links) und Enrique Flores Magón (rechts) vor dem Los Angeles County Jail, 1917
[...]
```
so some Markup like `mini|` is still left. Should I run another parser on this text before feeding it to an ML model or is this a known imperfection of parsing Wiki markup?
Apologies if this has been asked before.
Hi @bminixhofer ! Parsing WikiMedia is notoriously difficult: this processing used [mwparserfromhell](https://github.com/earwig/mwparserfromhell) which is pretty good but not perfect.
As an alternative, you can also use the Wiki40b dataset which was pre-processed using an un-released Google internal tool |
https://github.com/huggingface/datasets/issues/834 | [GEM] add WikiLingua cross-lingual abstractive summarization dataset | Hey @yjernite. This is a very interesting dataset. Would love to work on adding it but I see that the link to the data is to a gdrive folder. Can I just confirm wether dlmanager can handle gdrive urls or would this have to be a manual dl? | ## Adding a Dataset
- **Name:** WikiLingua
- **Description:** The dataset includes ~770k article and summary pairs in 18 languages from WikiHow. The gold-standard article-summary alignments across languages were extracted by aligning the images that are used to describe each how-to step in an article.
- **Paper:** https://arxiv.org/pdf/2010.03093.pdf
- **Data:** https://github.com/esdurmus/Wikilingua
- **Motivation:** Included in the GEM shared task. Multilingual.
Instructions to add a new dataset can be found [here](https://huggingface.co/docs/datasets/share_dataset.html).
| 48 | [GEM] add WikiLingua cross-lingual abstractive summarization dataset
## Adding a Dataset
- **Name:** WikiLingua
- **Description:** The dataset includes ~770k article and summary pairs in 18 languages from WikiHow. The gold-standard article-summary alignments across languages were extracted by aligning the images that are used to describe each how-to step in an article.
- **Paper:** https://arxiv.org/pdf/2010.03093.pdf
- **Data:** https://github.com/esdurmus/Wikilingua
- **Motivation:** Included in the GEM shared task. Multilingual.
Instructions to add a new dataset can be found [here](https://huggingface.co/docs/datasets/share_dataset.html).
Hey @yjernite. This is a very interesting dataset. Would love to work on adding it but I see that the link to the data is to a gdrive folder. Can I just confirm wether dlmanager can handle gdrive urls or would this have to be a manual dl? |
https://github.com/huggingface/datasets/issues/834 | [GEM] add WikiLingua cross-lingual abstractive summarization dataset | Hi @KMFODA ! A version of WikiLingua is actually already accessible in the [GEM dataset](https://huggingface.co/datasets/gem)
You can use it for example to load the French to English translation with:
```python
from datasets import load_dataset
wikilingua = load_dataset("gem", "wiki_lingua_french_fr")
```
Closed by https://github.com/huggingface/datasets/pull/1807 | ## Adding a Dataset
- **Name:** WikiLingua
- **Description:** The dataset includes ~770k article and summary pairs in 18 languages from WikiHow. The gold-standard article-summary alignments across languages were extracted by aligning the images that are used to describe each how-to step in an article.
- **Paper:** https://arxiv.org/pdf/2010.03093.pdf
- **Data:** https://github.com/esdurmus/Wikilingua
- **Motivation:** Included in the GEM shared task. Multilingual.
Instructions to add a new dataset can be found [here](https://huggingface.co/docs/datasets/share_dataset.html).
| 42 | [GEM] add WikiLingua cross-lingual abstractive summarization dataset
## Adding a Dataset
- **Name:** WikiLingua
- **Description:** The dataset includes ~770k article and summary pairs in 18 languages from WikiHow. The gold-standard article-summary alignments across languages were extracted by aligning the images that are used to describe each how-to step in an article.
- **Paper:** https://arxiv.org/pdf/2010.03093.pdf
- **Data:** https://github.com/esdurmus/Wikilingua
- **Motivation:** Included in the GEM shared task. Multilingual.
Instructions to add a new dataset can be found [here](https://huggingface.co/docs/datasets/share_dataset.html).
Hi @KMFODA ! A version of WikiLingua is actually already accessible in the [GEM dataset](https://huggingface.co/datasets/gem)
You can use it for example to load the French to English translation with:
```python
from datasets import load_dataset
wikilingua = load_dataset("gem", "wiki_lingua_french_fr")
```
Closed by https://github.com/huggingface/datasets/pull/1807 |
https://github.com/huggingface/datasets/issues/827 | [GEM] MultiWOZ dialogue dataset | Hi @yjernite can I help in adding this dataset?
I am excited about this because this will be my first contribution to the datasets library as well as to hugginface. | ## Adding a Dataset
- **Name:** MultiWOZ (Multi-Domain Wizard-of-Oz)
- **Description:** 10k annotated human-human dialogues. Each dialogue consists of a goal, multiple user and system utterances as well as a belief state. Only system utterances are annotated with dialogue acts – there are no annotations from the user side.
- **Paper:** https://arxiv.org/pdf/2007.12720.pdf
- **Data:** https://github.com/budzianowski/multiwoz
- **Motivation:** Will likely be part of the GEM shared task
Instructions to add a new dataset can be found [here](https://huggingface.co/docs/datasets/share_dataset.html).
| 30 | [GEM] MultiWOZ dialogue dataset
## Adding a Dataset
- **Name:** MultiWOZ (Multi-Domain Wizard-of-Oz)
- **Description:** 10k annotated human-human dialogues. Each dialogue consists of a goal, multiple user and system utterances as well as a belief state. Only system utterances are annotated with dialogue acts – there are no annotations from the user side.
- **Paper:** https://arxiv.org/pdf/2007.12720.pdf
- **Data:** https://github.com/budzianowski/multiwoz
- **Motivation:** Will likely be part of the GEM shared task
Instructions to add a new dataset can be found [here](https://huggingface.co/docs/datasets/share_dataset.html).
Hi @yjernite can I help in adding this dataset?
I am excited about this because this will be my first contribution to the datasets library as well as to hugginface. |
https://github.com/huggingface/datasets/issues/824 | Discussion using datasets in offline mode | I think it would be very cool. I'm currently working on a cluster from Compute Canada, and I have internet access only when I'm not in the nodes where I run the scripts. So I was expecting to be able to use the wmt14 dataset until I realized I needed internet connection even if I downloaded the data already. I'm going to try option 2 you mention for now though! Thanks ;) | `datasets.load_dataset("csv", ...)` breaks if you have no connection (There is already this issue https://github.com/huggingface/datasets/issues/761 about it). It seems to be the same for metrics too.
I create this ticket to discuss a bit and gather what you have in mind or other propositions.
Here are some points to open discussion:
- if you want to prepare your code/datasets on your machine (having internet connexion) but run it on another offline machine (not having internet connexion), it won't work as is, even if you have all files locally on this machine.
- AFAIK, you can make it work if you manually put the python files (csv.py for example) on this offline machine and change your code to `datasets.load_dataset("MY_PATH/csv.py", ...)`. But it would be much better if you could run ths same code without modification if files are available locally.
- I've also been considering the requirement of downloading Python code and execute on your machine to use datasets. This can be an issue in a professional context. Downloading a CSV/H5 file is acceptable, downloading an executable script can open many security issues. We certainly need a mechanism to at least "freeze" the dataset code you retrieved once so that you can review it if you want and then be sure you use this one everywhere and not a version dowloaded from internet.
WDYT? (thks)
| 72 | Discussion using datasets in offline mode
`datasets.load_dataset("csv", ...)` breaks if you have no connection (There is already this issue https://github.com/huggingface/datasets/issues/761 about it). It seems to be the same for metrics too.
I create this ticket to discuss a bit and gather what you have in mind or other propositions.
Here are some points to open discussion:
- if you want to prepare your code/datasets on your machine (having internet connexion) but run it on another offline machine (not having internet connexion), it won't work as is, even if you have all files locally on this machine.
- AFAIK, you can make it work if you manually put the python files (csv.py for example) on this offline machine and change your code to `datasets.load_dataset("MY_PATH/csv.py", ...)`. But it would be much better if you could run ths same code without modification if files are available locally.
- I've also been considering the requirement of downloading Python code and execute on your machine to use datasets. This can be an issue in a professional context. Downloading a CSV/H5 file is acceptable, downloading an executable script can open many security issues. We certainly need a mechanism to at least "freeze" the dataset code you retrieved once so that you can review it if you want and then be sure you use this one everywhere and not a version dowloaded from internet.
WDYT? (thks)
I think it would be very cool. I'm currently working on a cluster from Compute Canada, and I have internet access only when I'm not in the nodes where I run the scripts. So I was expecting to be able to use the wmt14 dataset until I realized I needed internet connection even if I downloaded the data already. I'm going to try option 2 you mention for now though! Thanks ;) |
https://github.com/huggingface/datasets/issues/824 | Discussion using datasets in offline mode | Requiring online connection is a deal breaker in some cases unfortunately so it'd be great if offline mode is added similar to how `transformers` loads models offline fine.
@mandubian's second bullet point suggests that there's a workaround allowing you to use your offline (custom?) dataset with `datasets`. Could you please elaborate on how that should look like? | `datasets.load_dataset("csv", ...)` breaks if you have no connection (There is already this issue https://github.com/huggingface/datasets/issues/761 about it). It seems to be the same for metrics too.
I create this ticket to discuss a bit and gather what you have in mind or other propositions.
Here are some points to open discussion:
- if you want to prepare your code/datasets on your machine (having internet connexion) but run it on another offline machine (not having internet connexion), it won't work as is, even if you have all files locally on this machine.
- AFAIK, you can make it work if you manually put the python files (csv.py for example) on this offline machine and change your code to `datasets.load_dataset("MY_PATH/csv.py", ...)`. But it would be much better if you could run ths same code without modification if files are available locally.
- I've also been considering the requirement of downloading Python code and execute on your machine to use datasets. This can be an issue in a professional context. Downloading a CSV/H5 file is acceptable, downloading an executable script can open many security issues. We certainly need a mechanism to at least "freeze" the dataset code you retrieved once so that you can review it if you want and then be sure you use this one everywhere and not a version dowloaded from internet.
WDYT? (thks)
| 57 | Discussion using datasets in offline mode
`datasets.load_dataset("csv", ...)` breaks if you have no connection (There is already this issue https://github.com/huggingface/datasets/issues/761 about it). It seems to be the same for metrics too.
I create this ticket to discuss a bit and gather what you have in mind or other propositions.
Here are some points to open discussion:
- if you want to prepare your code/datasets on your machine (having internet connexion) but run it on another offline machine (not having internet connexion), it won't work as is, even if you have all files locally on this machine.
- AFAIK, you can make it work if you manually put the python files (csv.py for example) on this offline machine and change your code to `datasets.load_dataset("MY_PATH/csv.py", ...)`. But it would be much better if you could run ths same code without modification if files are available locally.
- I've also been considering the requirement of downloading Python code and execute on your machine to use datasets. This can be an issue in a professional context. Downloading a CSV/H5 file is acceptable, downloading an executable script can open many security issues. We certainly need a mechanism to at least "freeze" the dataset code you retrieved once so that you can review it if you want and then be sure you use this one everywhere and not a version dowloaded from internet.
WDYT? (thks)
Requiring online connection is a deal breaker in some cases unfortunately so it'd be great if offline mode is added similar to how `transformers` loads models offline fine.
@mandubian's second bullet point suggests that there's a workaround allowing you to use your offline (custom?) dataset with `datasets`. Could you please elaborate on how that should look like? |
https://github.com/huggingface/datasets/issues/824 | Discussion using datasets in offline mode | here is my way to load a dataset offline, but it **requires** an online machine
1. (online machine)
```
import datasets
data = datasets.load_dataset(...)
data.save_to_disk(/YOUR/DATASET/DIR)
```
2. copy the dir from online to the offline machine
3. (offline machine)
```
import datasets
data = datasets.load_from_disk(/SAVED/DATA/DIR)
```
HTH. | `datasets.load_dataset("csv", ...)` breaks if you have no connection (There is already this issue https://github.com/huggingface/datasets/issues/761 about it). It seems to be the same for metrics too.
I create this ticket to discuss a bit and gather what you have in mind or other propositions.
Here are some points to open discussion:
- if you want to prepare your code/datasets on your machine (having internet connexion) but run it on another offline machine (not having internet connexion), it won't work as is, even if you have all files locally on this machine.
- AFAIK, you can make it work if you manually put the python files (csv.py for example) on this offline machine and change your code to `datasets.load_dataset("MY_PATH/csv.py", ...)`. But it would be much better if you could run ths same code without modification if files are available locally.
- I've also been considering the requirement of downloading Python code and execute on your machine to use datasets. This can be an issue in a professional context. Downloading a CSV/H5 file is acceptable, downloading an executable script can open many security issues. We certainly need a mechanism to at least "freeze" the dataset code you retrieved once so that you can review it if you want and then be sure you use this one everywhere and not a version dowloaded from internet.
WDYT? (thks)
| 47 | Discussion using datasets in offline mode
`datasets.load_dataset("csv", ...)` breaks if you have no connection (There is already this issue https://github.com/huggingface/datasets/issues/761 about it). It seems to be the same for metrics too.
I create this ticket to discuss a bit and gather what you have in mind or other propositions.
Here are some points to open discussion:
- if you want to prepare your code/datasets on your machine (having internet connexion) but run it on another offline machine (not having internet connexion), it won't work as is, even if you have all files locally on this machine.
- AFAIK, you can make it work if you manually put the python files (csv.py for example) on this offline machine and change your code to `datasets.load_dataset("MY_PATH/csv.py", ...)`. But it would be much better if you could run ths same code without modification if files are available locally.
- I've also been considering the requirement of downloading Python code and execute on your machine to use datasets. This can be an issue in a professional context. Downloading a CSV/H5 file is acceptable, downloading an executable script can open many security issues. We certainly need a mechanism to at least "freeze" the dataset code you retrieved once so that you can review it if you want and then be sure you use this one everywhere and not a version dowloaded from internet.
WDYT? (thks)
here is my way to load a dataset offline, but it **requires** an online machine
1. (online machine)
```
import datasets
data = datasets.load_dataset(...)
data.save_to_disk(/YOUR/DATASET/DIR)
```
2. copy the dir from online to the offline machine
3. (offline machine)
```
import datasets
data = datasets.load_from_disk(/SAVED/DATA/DIR)
```
HTH. |
https://github.com/huggingface/datasets/issues/824 | Discussion using datasets in offline mode | > here is my way to load a dataset offline, but it **requires** an online machine
>
> 1. (online machine)
>
> ```
>
> import datasets
>
> data = datasets.load_dataset(...)
>
> data.save_to_disk(/YOUR/DATASET/DIR)
>
> ```
>
> 2. copy the dir from online to the offline machine
>
> 3. (offline machine)
>
> ```
>
> import datasets
>
> data = datasets.load_from_disk(/SAVED/DATA/DIR)
>
> ```
>
>
>
> HTH.
| `datasets.load_dataset("csv", ...)` breaks if you have no connection (There is already this issue https://github.com/huggingface/datasets/issues/761 about it). It seems to be the same for metrics too.
I create this ticket to discuss a bit and gather what you have in mind or other propositions.
Here are some points to open discussion:
- if you want to prepare your code/datasets on your machine (having internet connexion) but run it on another offline machine (not having internet connexion), it won't work as is, even if you have all files locally on this machine.
- AFAIK, you can make it work if you manually put the python files (csv.py for example) on this offline machine and change your code to `datasets.load_dataset("MY_PATH/csv.py", ...)`. But it would be much better if you could run ths same code without modification if files are available locally.
- I've also been considering the requirement of downloading Python code and execute on your machine to use datasets. This can be an issue in a professional context. Downloading a CSV/H5 file is acceptable, downloading an executable script can open many security issues. We certainly need a mechanism to at least "freeze" the dataset code you retrieved once so that you can review it if you want and then be sure you use this one everywhere and not a version dowloaded from internet.
WDYT? (thks)
| 76 | Discussion using datasets in offline mode
`datasets.load_dataset("csv", ...)` breaks if you have no connection (There is already this issue https://github.com/huggingface/datasets/issues/761 about it). It seems to be the same for metrics too.
I create this ticket to discuss a bit and gather what you have in mind or other propositions.
Here are some points to open discussion:
- if you want to prepare your code/datasets on your machine (having internet connexion) but run it on another offline machine (not having internet connexion), it won't work as is, even if you have all files locally on this machine.
- AFAIK, you can make it work if you manually put the python files (csv.py for example) on this offline machine and change your code to `datasets.load_dataset("MY_PATH/csv.py", ...)`. But it would be much better if you could run ths same code without modification if files are available locally.
- I've also been considering the requirement of downloading Python code and execute on your machine to use datasets. This can be an issue in a professional context. Downloading a CSV/H5 file is acceptable, downloading an executable script can open many security issues. We certainly need a mechanism to at least "freeze" the dataset code you retrieved once so that you can review it if you want and then be sure you use this one everywhere and not a version dowloaded from internet.
WDYT? (thks)
> here is my way to load a dataset offline, but it **requires** an online machine
>
> 1. (online machine)
>
> ```
>
> import datasets
>
> data = datasets.load_dataset(...)
>
> data.save_to_disk(/YOUR/DATASET/DIR)
>
> ```
>
> 2. copy the dir from online to the offline machine
>
> 3. (offline machine)
>
> ```
>
> import datasets
>
> data = datasets.load_from_disk(/SAVED/DATA/DIR)
>
> ```
>
>
>
> HTH.
|
https://github.com/huggingface/datasets/issues/824 | Discussion using datasets in offline mode | I opened a PR that allows to reload modules that have already been loaded once even if there's no internet.
Let me know if you know other ways that can make the offline mode experience better. I'd be happy to add them :)
I already note the "freeze" modules option, to prevent local modules updates. It would be a cool feature.
----------
> @mandubian's second bullet point suggests that there's a workaround allowing you to use your offline (custom?) dataset with `datasets`. Could you please elaborate on how that should look like?
Indeed `load_dataset` allows to load remote dataset script (squad, glue, etc.) but also you own local ones.
For example if you have a dataset script at `./my_dataset/my_dataset.py` then you can do
```python
load_dataset("./my_dataset")
```
and the dataset script will generate your dataset once and for all.
----------
About I'm looking into having `csv`, `json`, `text`, `pandas` dataset builders already included in the `datasets` package, so that they are available offline by default, as opposed to the other datasets that require the script to be downloaded.
cf #1724 | `datasets.load_dataset("csv", ...)` breaks if you have no connection (There is already this issue https://github.com/huggingface/datasets/issues/761 about it). It seems to be the same for metrics too.
I create this ticket to discuss a bit and gather what you have in mind or other propositions.
Here are some points to open discussion:
- if you want to prepare your code/datasets on your machine (having internet connexion) but run it on another offline machine (not having internet connexion), it won't work as is, even if you have all files locally on this machine.
- AFAIK, you can make it work if you manually put the python files (csv.py for example) on this offline machine and change your code to `datasets.load_dataset("MY_PATH/csv.py", ...)`. But it would be much better if you could run ths same code without modification if files are available locally.
- I've also been considering the requirement of downloading Python code and execute on your machine to use datasets. This can be an issue in a professional context. Downloading a CSV/H5 file is acceptable, downloading an executable script can open many security issues. We certainly need a mechanism to at least "freeze" the dataset code you retrieved once so that you can review it if you want and then be sure you use this one everywhere and not a version dowloaded from internet.
WDYT? (thks)
| 179 | Discussion using datasets in offline mode
`datasets.load_dataset("csv", ...)` breaks if you have no connection (There is already this issue https://github.com/huggingface/datasets/issues/761 about it). It seems to be the same for metrics too.
I create this ticket to discuss a bit and gather what you have in mind or other propositions.
Here are some points to open discussion:
- if you want to prepare your code/datasets on your machine (having internet connexion) but run it on another offline machine (not having internet connexion), it won't work as is, even if you have all files locally on this machine.
- AFAIK, you can make it work if you manually put the python files (csv.py for example) on this offline machine and change your code to `datasets.load_dataset("MY_PATH/csv.py", ...)`. But it would be much better if you could run ths same code without modification if files are available locally.
- I've also been considering the requirement of downloading Python code and execute on your machine to use datasets. This can be an issue in a professional context. Downloading a CSV/H5 file is acceptable, downloading an executable script can open many security issues. We certainly need a mechanism to at least "freeze" the dataset code you retrieved once so that you can review it if you want and then be sure you use this one everywhere and not a version dowloaded from internet.
WDYT? (thks)
I opened a PR that allows to reload modules that have already been loaded once even if there's no internet.
Let me know if you know other ways that can make the offline mode experience better. I'd be happy to add them :)
I already note the "freeze" modules option, to prevent local modules updates. It would be a cool feature.
----------
> @mandubian's second bullet point suggests that there's a workaround allowing you to use your offline (custom?) dataset with `datasets`. Could you please elaborate on how that should look like?
Indeed `load_dataset` allows to load remote dataset script (squad, glue, etc.) but also you own local ones.
For example if you have a dataset script at `./my_dataset/my_dataset.py` then you can do
```python
load_dataset("./my_dataset")
```
and the dataset script will generate your dataset once and for all.
----------
About I'm looking into having `csv`, `json`, `text`, `pandas` dataset builders already included in the `datasets` package, so that they are available offline by default, as opposed to the other datasets that require the script to be downloaded.
cf #1724 |
https://github.com/huggingface/datasets/issues/824 | Discussion using datasets in offline mode | The local dataset builders (csv, text , json and pandas) are now part of the `datasets` package since #1726 :)
You can now use them offline
```python
datasets = load_dataset('text', data_files=data_files)
```
We'll do a new release soon | `datasets.load_dataset("csv", ...)` breaks if you have no connection (There is already this issue https://github.com/huggingface/datasets/issues/761 about it). It seems to be the same for metrics too.
I create this ticket to discuss a bit and gather what you have in mind or other propositions.
Here are some points to open discussion:
- if you want to prepare your code/datasets on your machine (having internet connexion) but run it on another offline machine (not having internet connexion), it won't work as is, even if you have all files locally on this machine.
- AFAIK, you can make it work if you manually put the python files (csv.py for example) on this offline machine and change your code to `datasets.load_dataset("MY_PATH/csv.py", ...)`. But it would be much better if you could run ths same code without modification if files are available locally.
- I've also been considering the requirement of downloading Python code and execute on your machine to use datasets. This can be an issue in a professional context. Downloading a CSV/H5 file is acceptable, downloading an executable script can open many security issues. We certainly need a mechanism to at least "freeze" the dataset code you retrieved once so that you can review it if you want and then be sure you use this one everywhere and not a version dowloaded from internet.
WDYT? (thks)
| 38 | Discussion using datasets in offline mode
`datasets.load_dataset("csv", ...)` breaks if you have no connection (There is already this issue https://github.com/huggingface/datasets/issues/761 about it). It seems to be the same for metrics too.
I create this ticket to discuss a bit and gather what you have in mind or other propositions.
Here are some points to open discussion:
- if you want to prepare your code/datasets on your machine (having internet connexion) but run it on another offline machine (not having internet connexion), it won't work as is, even if you have all files locally on this machine.
- AFAIK, you can make it work if you manually put the python files (csv.py for example) on this offline machine and change your code to `datasets.load_dataset("MY_PATH/csv.py", ...)`. But it would be much better if you could run ths same code without modification if files are available locally.
- I've also been considering the requirement of downloading Python code and execute on your machine to use datasets. This can be an issue in a professional context. Downloading a CSV/H5 file is acceptable, downloading an executable script can open many security issues. We certainly need a mechanism to at least "freeze" the dataset code you retrieved once so that you can review it if you want and then be sure you use this one everywhere and not a version dowloaded from internet.
WDYT? (thks)
The local dataset builders (csv, text , json and pandas) are now part of the `datasets` package since #1726 :)
You can now use them offline
```python
datasets = load_dataset('text', data_files=data_files)
```
We'll do a new release soon |
https://github.com/huggingface/datasets/issues/823 | how processing in batch works in datasets | Hi I don’t think this is a request for a dataset like you labeled it.
I also think this would be better suited for the forum at https://discuss.huggingface.co. we try to keep the issue for the repo for bug reports and new features/dataset requests and have usage questions discussed on the forum. Thanks. | Hi,
I need to process my datasets before it is passed to dataloader in batch,
here is my codes
```
class AbstractTask(ABC):
task_name: str = NotImplemented
preprocessor: Callable = NotImplemented
split_to_data_split: Mapping[str, str] = NotImplemented
tokenizer: Callable = NotImplemented
max_source_length: str = NotImplemented
max_target_length: str = NotImplemented
# TODO: should not be a task item, but cannot see other ways.
tpu_num_cores: int = None
# The arguments set are for all tasks and needs to be kept common.
def __init__(self, config):
self.max_source_length = config['max_source_length']
self.max_target_length = config['max_target_length']
self.tokenizer = config['tokenizer']
self.tpu_num_cores = config['tpu_num_cores']
def _encode(self, batch) -> Dict[str, torch.Tensor]:
batch_encoding = self.tokenizer.prepare_seq2seq_batch(
[x["src_texts"] for x in batch],
tgt_texts=[x["tgt_texts"] for x in batch],
max_length=self.max_source_length,
max_target_length=self.max_target_length,
padding="max_length" if self.tpu_num_cores is not None else "longest", # TPU hack
return_tensors="pt"
)
return batch_encoding.data
def data_split(self, split):
return self.split_to_data_split[split]
def get_dataset(self, split, n_obs=None):
split = self.data_split(split)
if n_obs is not None:
split = split+"[:{}]".format(n_obs)
dataset = load_dataset(self.task_name, split=split)
dataset = dataset.map(self.preprocessor, remove_columns=dataset.column_names)
dataset = dataset.map(lambda batch: self._encode(batch), batched=True)
dataset.set_format(type="torch", columns=['input_ids', 'token_type_ids', 'attention_mask', 'label'])
return dataset
```
I call it like
`AutoTask.get(task, train_dataset_config).get_dataset(split="train", n_obs=data_args.n_train)
`
This gives the following error, to me because the data inside the dataset = dataset.map(lambda batch: self._encode(batch), batched=True) is not processed in batch, could you tell me how I can process dataset in batch inside my function? thanks
File "finetune_multitask_trainer.py", line 192, in main
if training_args.do_train else None
File "finetune_multitask_trainer.py", line 191, in <dictcomp>
split="train", n_obs=data_args.n_train) for task in data_args.task}
File "/remote/idiap.svm/user.active/rkarimi/dev/internship/seq2seq/tasks.py", line 56, in get_dataset
dataset = dataset.map(lambda batch: self._encode(batch), batched=True)
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/arrow_dataset.py", line 1236, in map
update_data = does_function_return_dict(test_inputs, test_indices)
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/arrow_dataset.py", line 1207, in does_function_return_dict
function(*fn_args, indices, **fn_kwargs) if with_indices else function(*fn_args, **fn_kwargs)
File "/remote/idiap.svm/user.active/rkarimi/dev/internship/seq2seq/tasks.py", line 56, in <lambda>
dataset = dataset.map(lambda batch: self._encode(batch), batched=True)
File "/remote/idiap.svm/user.active/rkarimi/dev/internship/seq2seq/tasks.py", line 37, in _encode
[x["src_texts"] for x in batch],
File "/remote/idiap.svm/user.active/rkarimi/dev/internship/seq2seq/tasks.py", line 37, in <listcomp>
[x["src_texts"] for x in batch],
TypeError: string indices must be integers
| 53 | how processing in batch works in datasets
Hi,
I need to process my datasets before it is passed to dataloader in batch,
here is my codes
```
class AbstractTask(ABC):
task_name: str = NotImplemented
preprocessor: Callable = NotImplemented
split_to_data_split: Mapping[str, str] = NotImplemented
tokenizer: Callable = NotImplemented
max_source_length: str = NotImplemented
max_target_length: str = NotImplemented
# TODO: should not be a task item, but cannot see other ways.
tpu_num_cores: int = None
# The arguments set are for all tasks and needs to be kept common.
def __init__(self, config):
self.max_source_length = config['max_source_length']
self.max_target_length = config['max_target_length']
self.tokenizer = config['tokenizer']
self.tpu_num_cores = config['tpu_num_cores']
def _encode(self, batch) -> Dict[str, torch.Tensor]:
batch_encoding = self.tokenizer.prepare_seq2seq_batch(
[x["src_texts"] for x in batch],
tgt_texts=[x["tgt_texts"] for x in batch],
max_length=self.max_source_length,
max_target_length=self.max_target_length,
padding="max_length" if self.tpu_num_cores is not None else "longest", # TPU hack
return_tensors="pt"
)
return batch_encoding.data
def data_split(self, split):
return self.split_to_data_split[split]
def get_dataset(self, split, n_obs=None):
split = self.data_split(split)
if n_obs is not None:
split = split+"[:{}]".format(n_obs)
dataset = load_dataset(self.task_name, split=split)
dataset = dataset.map(self.preprocessor, remove_columns=dataset.column_names)
dataset = dataset.map(lambda batch: self._encode(batch), batched=True)
dataset.set_format(type="torch", columns=['input_ids', 'token_type_ids', 'attention_mask', 'label'])
return dataset
```
I call it like
`AutoTask.get(task, train_dataset_config).get_dataset(split="train", n_obs=data_args.n_train)
`
This gives the following error, to me because the data inside the dataset = dataset.map(lambda batch: self._encode(batch), batched=True) is not processed in batch, could you tell me how I can process dataset in batch inside my function? thanks
File "finetune_multitask_trainer.py", line 192, in main
if training_args.do_train else None
File "finetune_multitask_trainer.py", line 191, in <dictcomp>
split="train", n_obs=data_args.n_train) for task in data_args.task}
File "/remote/idiap.svm/user.active/rkarimi/dev/internship/seq2seq/tasks.py", line 56, in get_dataset
dataset = dataset.map(lambda batch: self._encode(batch), batched=True)
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/arrow_dataset.py", line 1236, in map
update_data = does_function_return_dict(test_inputs, test_indices)
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/arrow_dataset.py", line 1207, in does_function_return_dict
function(*fn_args, indices, **fn_kwargs) if with_indices else function(*fn_args, **fn_kwargs)
File "/remote/idiap.svm/user.active/rkarimi/dev/internship/seq2seq/tasks.py", line 56, in <lambda>
dataset = dataset.map(lambda batch: self._encode(batch), batched=True)
File "/remote/idiap.svm/user.active/rkarimi/dev/internship/seq2seq/tasks.py", line 37, in _encode
[x["src_texts"] for x in batch],
File "/remote/idiap.svm/user.active/rkarimi/dev/internship/seq2seq/tasks.py", line 37, in <listcomp>
[x["src_texts"] for x in batch],
TypeError: string indices must be integers
Hi I don’t think this is a request for a dataset like you labeled it.
I also think this would be better suited for the forum at https://discuss.huggingface.co. we try to keep the issue for the repo for bug reports and new features/dataset requests and have usage questions discussed on the forum. Thanks. |
https://github.com/huggingface/datasets/issues/823 | how processing in batch works in datasets | Hi Thomas,
what I do not get from documentation is that why when you set batched=True,
this is processed in batch, while data is not divided to batched
beforehand, basically this is a question on the documentation and I do not
get the batched=True, but sure, if you think this is more appropriate in
forum I will post it there.
thanks
Best
Rabeeh
On Tue, Nov 10, 2020 at 12:21 PM Thomas Wolf <[email protected]>
wrote:
> Hi I don’t think this is a request for a dataset like you labeled it.
>
> I also think this would be better suited for the forum at
> https://discuss.huggingface.co. we try to keep the issue for the repo for
> bug reports and new features/dataset requests and have usage questions
> discussed on the forum. Thanks.
>
> —
> You are receiving this because you authored the thread.
> Reply to this email directly, view it on GitHub
> <https://github.com/huggingface/datasets/issues/823#issuecomment-724639476>,
> or unsubscribe
> <https://github.com/notifications/unsubscribe-auth/ARPXHH4FIPFHVVUHANAE4F3SPEO2JANCNFSM4TQQVEXQ>
> .
>
| Hi,
I need to process my datasets before it is passed to dataloader in batch,
here is my codes
```
class AbstractTask(ABC):
task_name: str = NotImplemented
preprocessor: Callable = NotImplemented
split_to_data_split: Mapping[str, str] = NotImplemented
tokenizer: Callable = NotImplemented
max_source_length: str = NotImplemented
max_target_length: str = NotImplemented
# TODO: should not be a task item, but cannot see other ways.
tpu_num_cores: int = None
# The arguments set are for all tasks and needs to be kept common.
def __init__(self, config):
self.max_source_length = config['max_source_length']
self.max_target_length = config['max_target_length']
self.tokenizer = config['tokenizer']
self.tpu_num_cores = config['tpu_num_cores']
def _encode(self, batch) -> Dict[str, torch.Tensor]:
batch_encoding = self.tokenizer.prepare_seq2seq_batch(
[x["src_texts"] for x in batch],
tgt_texts=[x["tgt_texts"] for x in batch],
max_length=self.max_source_length,
max_target_length=self.max_target_length,
padding="max_length" if self.tpu_num_cores is not None else "longest", # TPU hack
return_tensors="pt"
)
return batch_encoding.data
def data_split(self, split):
return self.split_to_data_split[split]
def get_dataset(self, split, n_obs=None):
split = self.data_split(split)
if n_obs is not None:
split = split+"[:{}]".format(n_obs)
dataset = load_dataset(self.task_name, split=split)
dataset = dataset.map(self.preprocessor, remove_columns=dataset.column_names)
dataset = dataset.map(lambda batch: self._encode(batch), batched=True)
dataset.set_format(type="torch", columns=['input_ids', 'token_type_ids', 'attention_mask', 'label'])
return dataset
```
I call it like
`AutoTask.get(task, train_dataset_config).get_dataset(split="train", n_obs=data_args.n_train)
`
This gives the following error, to me because the data inside the dataset = dataset.map(lambda batch: self._encode(batch), batched=True) is not processed in batch, could you tell me how I can process dataset in batch inside my function? thanks
File "finetune_multitask_trainer.py", line 192, in main
if training_args.do_train else None
File "finetune_multitask_trainer.py", line 191, in <dictcomp>
split="train", n_obs=data_args.n_train) for task in data_args.task}
File "/remote/idiap.svm/user.active/rkarimi/dev/internship/seq2seq/tasks.py", line 56, in get_dataset
dataset = dataset.map(lambda batch: self._encode(batch), batched=True)
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/arrow_dataset.py", line 1236, in map
update_data = does_function_return_dict(test_inputs, test_indices)
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/arrow_dataset.py", line 1207, in does_function_return_dict
function(*fn_args, indices, **fn_kwargs) if with_indices else function(*fn_args, **fn_kwargs)
File "/remote/idiap.svm/user.active/rkarimi/dev/internship/seq2seq/tasks.py", line 56, in <lambda>
dataset = dataset.map(lambda batch: self._encode(batch), batched=True)
File "/remote/idiap.svm/user.active/rkarimi/dev/internship/seq2seq/tasks.py", line 37, in _encode
[x["src_texts"] for x in batch],
File "/remote/idiap.svm/user.active/rkarimi/dev/internship/seq2seq/tasks.py", line 37, in <listcomp>
[x["src_texts"] for x in batch],
TypeError: string indices must be integers
| 167 | how processing in batch works in datasets
Hi,
I need to process my datasets before it is passed to dataloader in batch,
here is my codes
```
class AbstractTask(ABC):
task_name: str = NotImplemented
preprocessor: Callable = NotImplemented
split_to_data_split: Mapping[str, str] = NotImplemented
tokenizer: Callable = NotImplemented
max_source_length: str = NotImplemented
max_target_length: str = NotImplemented
# TODO: should not be a task item, but cannot see other ways.
tpu_num_cores: int = None
# The arguments set are for all tasks and needs to be kept common.
def __init__(self, config):
self.max_source_length = config['max_source_length']
self.max_target_length = config['max_target_length']
self.tokenizer = config['tokenizer']
self.tpu_num_cores = config['tpu_num_cores']
def _encode(self, batch) -> Dict[str, torch.Tensor]:
batch_encoding = self.tokenizer.prepare_seq2seq_batch(
[x["src_texts"] for x in batch],
tgt_texts=[x["tgt_texts"] for x in batch],
max_length=self.max_source_length,
max_target_length=self.max_target_length,
padding="max_length" if self.tpu_num_cores is not None else "longest", # TPU hack
return_tensors="pt"
)
return batch_encoding.data
def data_split(self, split):
return self.split_to_data_split[split]
def get_dataset(self, split, n_obs=None):
split = self.data_split(split)
if n_obs is not None:
split = split+"[:{}]".format(n_obs)
dataset = load_dataset(self.task_name, split=split)
dataset = dataset.map(self.preprocessor, remove_columns=dataset.column_names)
dataset = dataset.map(lambda batch: self._encode(batch), batched=True)
dataset.set_format(type="torch", columns=['input_ids', 'token_type_ids', 'attention_mask', 'label'])
return dataset
```
I call it like
`AutoTask.get(task, train_dataset_config).get_dataset(split="train", n_obs=data_args.n_train)
`
This gives the following error, to me because the data inside the dataset = dataset.map(lambda batch: self._encode(batch), batched=True) is not processed in batch, could you tell me how I can process dataset in batch inside my function? thanks
File "finetune_multitask_trainer.py", line 192, in main
if training_args.do_train else None
File "finetune_multitask_trainer.py", line 191, in <dictcomp>
split="train", n_obs=data_args.n_train) for task in data_args.task}
File "/remote/idiap.svm/user.active/rkarimi/dev/internship/seq2seq/tasks.py", line 56, in get_dataset
dataset = dataset.map(lambda batch: self._encode(batch), batched=True)
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/arrow_dataset.py", line 1236, in map
update_data = does_function_return_dict(test_inputs, test_indices)
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/arrow_dataset.py", line 1207, in does_function_return_dict
function(*fn_args, indices, **fn_kwargs) if with_indices else function(*fn_args, **fn_kwargs)
File "/remote/idiap.svm/user.active/rkarimi/dev/internship/seq2seq/tasks.py", line 56, in <lambda>
dataset = dataset.map(lambda batch: self._encode(batch), batched=True)
File "/remote/idiap.svm/user.active/rkarimi/dev/internship/seq2seq/tasks.py", line 37, in _encode
[x["src_texts"] for x in batch],
File "/remote/idiap.svm/user.active/rkarimi/dev/internship/seq2seq/tasks.py", line 37, in <listcomp>
[x["src_texts"] for x in batch],
TypeError: string indices must be integers
Hi Thomas,
what I do not get from documentation is that why when you set batched=True,
this is processed in batch, while data is not divided to batched
beforehand, basically this is a question on the documentation and I do not
get the batched=True, but sure, if you think this is more appropriate in
forum I will post it there.
thanks
Best
Rabeeh
On Tue, Nov 10, 2020 at 12:21 PM Thomas Wolf <[email protected]>
wrote:
> Hi I don’t think this is a request for a dataset like you labeled it.
>
> I also think this would be better suited for the forum at
> https://discuss.huggingface.co. we try to keep the issue for the repo for
> bug reports and new features/dataset requests and have usage questions
> discussed on the forum. Thanks.
>
> —
> You are receiving this because you authored the thread.
> Reply to this email directly, view it on GitHub
> <https://github.com/huggingface/datasets/issues/823#issuecomment-724639476>,
> or unsubscribe
> <https://github.com/notifications/unsubscribe-auth/ARPXHH4FIPFHVVUHANAE4F3SPEO2JANCNFSM4TQQVEXQ>
> .
>
|
https://github.com/huggingface/datasets/issues/823 | how processing in batch works in datasets | Yes the forum is perfect for that. You can post in the `datasets` section.
Thanks a lot! | Hi,
I need to process my datasets before it is passed to dataloader in batch,
here is my codes
```
class AbstractTask(ABC):
task_name: str = NotImplemented
preprocessor: Callable = NotImplemented
split_to_data_split: Mapping[str, str] = NotImplemented
tokenizer: Callable = NotImplemented
max_source_length: str = NotImplemented
max_target_length: str = NotImplemented
# TODO: should not be a task item, but cannot see other ways.
tpu_num_cores: int = None
# The arguments set are for all tasks and needs to be kept common.
def __init__(self, config):
self.max_source_length = config['max_source_length']
self.max_target_length = config['max_target_length']
self.tokenizer = config['tokenizer']
self.tpu_num_cores = config['tpu_num_cores']
def _encode(self, batch) -> Dict[str, torch.Tensor]:
batch_encoding = self.tokenizer.prepare_seq2seq_batch(
[x["src_texts"] for x in batch],
tgt_texts=[x["tgt_texts"] for x in batch],
max_length=self.max_source_length,
max_target_length=self.max_target_length,
padding="max_length" if self.tpu_num_cores is not None else "longest", # TPU hack
return_tensors="pt"
)
return batch_encoding.data
def data_split(self, split):
return self.split_to_data_split[split]
def get_dataset(self, split, n_obs=None):
split = self.data_split(split)
if n_obs is not None:
split = split+"[:{}]".format(n_obs)
dataset = load_dataset(self.task_name, split=split)
dataset = dataset.map(self.preprocessor, remove_columns=dataset.column_names)
dataset = dataset.map(lambda batch: self._encode(batch), batched=True)
dataset.set_format(type="torch", columns=['input_ids', 'token_type_ids', 'attention_mask', 'label'])
return dataset
```
I call it like
`AutoTask.get(task, train_dataset_config).get_dataset(split="train", n_obs=data_args.n_train)
`
This gives the following error, to me because the data inside the dataset = dataset.map(lambda batch: self._encode(batch), batched=True) is not processed in batch, could you tell me how I can process dataset in batch inside my function? thanks
File "finetune_multitask_trainer.py", line 192, in main
if training_args.do_train else None
File "finetune_multitask_trainer.py", line 191, in <dictcomp>
split="train", n_obs=data_args.n_train) for task in data_args.task}
File "/remote/idiap.svm/user.active/rkarimi/dev/internship/seq2seq/tasks.py", line 56, in get_dataset
dataset = dataset.map(lambda batch: self._encode(batch), batched=True)
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/arrow_dataset.py", line 1236, in map
update_data = does_function_return_dict(test_inputs, test_indices)
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/arrow_dataset.py", line 1207, in does_function_return_dict
function(*fn_args, indices, **fn_kwargs) if with_indices else function(*fn_args, **fn_kwargs)
File "/remote/idiap.svm/user.active/rkarimi/dev/internship/seq2seq/tasks.py", line 56, in <lambda>
dataset = dataset.map(lambda batch: self._encode(batch), batched=True)
File "/remote/idiap.svm/user.active/rkarimi/dev/internship/seq2seq/tasks.py", line 37, in _encode
[x["src_texts"] for x in batch],
File "/remote/idiap.svm/user.active/rkarimi/dev/internship/seq2seq/tasks.py", line 37, in <listcomp>
[x["src_texts"] for x in batch],
TypeError: string indices must be integers
| 17 | how processing in batch works in datasets
Hi,
I need to process my datasets before it is passed to dataloader in batch,
here is my codes
```
class AbstractTask(ABC):
task_name: str = NotImplemented
preprocessor: Callable = NotImplemented
split_to_data_split: Mapping[str, str] = NotImplemented
tokenizer: Callable = NotImplemented
max_source_length: str = NotImplemented
max_target_length: str = NotImplemented
# TODO: should not be a task item, but cannot see other ways.
tpu_num_cores: int = None
# The arguments set are for all tasks and needs to be kept common.
def __init__(self, config):
self.max_source_length = config['max_source_length']
self.max_target_length = config['max_target_length']
self.tokenizer = config['tokenizer']
self.tpu_num_cores = config['tpu_num_cores']
def _encode(self, batch) -> Dict[str, torch.Tensor]:
batch_encoding = self.tokenizer.prepare_seq2seq_batch(
[x["src_texts"] for x in batch],
tgt_texts=[x["tgt_texts"] for x in batch],
max_length=self.max_source_length,
max_target_length=self.max_target_length,
padding="max_length" if self.tpu_num_cores is not None else "longest", # TPU hack
return_tensors="pt"
)
return batch_encoding.data
def data_split(self, split):
return self.split_to_data_split[split]
def get_dataset(self, split, n_obs=None):
split = self.data_split(split)
if n_obs is not None:
split = split+"[:{}]".format(n_obs)
dataset = load_dataset(self.task_name, split=split)
dataset = dataset.map(self.preprocessor, remove_columns=dataset.column_names)
dataset = dataset.map(lambda batch: self._encode(batch), batched=True)
dataset.set_format(type="torch", columns=['input_ids', 'token_type_ids', 'attention_mask', 'label'])
return dataset
```
I call it like
`AutoTask.get(task, train_dataset_config).get_dataset(split="train", n_obs=data_args.n_train)
`
This gives the following error, to me because the data inside the dataset = dataset.map(lambda batch: self._encode(batch), batched=True) is not processed in batch, could you tell me how I can process dataset in batch inside my function? thanks
File "finetune_multitask_trainer.py", line 192, in main
if training_args.do_train else None
File "finetune_multitask_trainer.py", line 191, in <dictcomp>
split="train", n_obs=data_args.n_train) for task in data_args.task}
File "/remote/idiap.svm/user.active/rkarimi/dev/internship/seq2seq/tasks.py", line 56, in get_dataset
dataset = dataset.map(lambda batch: self._encode(batch), batched=True)
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/arrow_dataset.py", line 1236, in map
update_data = does_function_return_dict(test_inputs, test_indices)
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/arrow_dataset.py", line 1207, in does_function_return_dict
function(*fn_args, indices, **fn_kwargs) if with_indices else function(*fn_args, **fn_kwargs)
File "/remote/idiap.svm/user.active/rkarimi/dev/internship/seq2seq/tasks.py", line 56, in <lambda>
dataset = dataset.map(lambda batch: self._encode(batch), batched=True)
File "/remote/idiap.svm/user.active/rkarimi/dev/internship/seq2seq/tasks.py", line 37, in _encode
[x["src_texts"] for x in batch],
File "/remote/idiap.svm/user.active/rkarimi/dev/internship/seq2seq/tasks.py", line 37, in <listcomp>
[x["src_texts"] for x in batch],
TypeError: string indices must be integers
Yes the forum is perfect for that. You can post in the `datasets` section.
Thanks a lot! |
https://github.com/huggingface/datasets/issues/822 | datasets freezes | Pytorch is unable to convert strings to tensors unfortunately.
You can use `set_format(type="torch")` on columns that can be converted to tensors, such as token ids.
This makes me think that we should probably raise an error or at least a warning when one tries to create pytorch tensors out of text columns | Hi, I want to load these two datasets and convert them to Dataset format in torch and the code freezes for me, could you have a look please? thanks
dataset1 = load_dataset("squad", split="train[:10]")
dataset1 = dataset1.set_format(type='torch', columns=['context', 'answers', 'question'])
dataset2 = load_dataset("imdb", split="train[:10]")
dataset2 = dataset2.set_format(type="torch", columns=["text", "label"])
print(len(dataset1))
| 52 | datasets freezes
Hi, I want to load these two datasets and convert them to Dataset format in torch and the code freezes for me, could you have a look please? thanks
dataset1 = load_dataset("squad", split="train[:10]")
dataset1 = dataset1.set_format(type='torch', columns=['context', 'answers', 'question'])
dataset2 = load_dataset("imdb", split="train[:10]")
dataset2 = dataset2.set_format(type="torch", columns=["text", "label"])
print(len(dataset1))
Pytorch is unable to convert strings to tensors unfortunately.
You can use `set_format(type="torch")` on columns that can be converted to tensors, such as token ids.
This makes me think that we should probably raise an error or at least a warning when one tries to create pytorch tensors out of text columns |
https://github.com/huggingface/datasets/issues/822 | datasets freezes | Ultimately, we decided to return a list instead of an error when formatting a string column with the format type `"torch"`.
If you think an error would be more appropriate, please open a new issue. | Hi, I want to load these two datasets and convert them to Dataset format in torch and the code freezes for me, could you have a look please? thanks
dataset1 = load_dataset("squad", split="train[:10]")
dataset1 = dataset1.set_format(type='torch', columns=['context', 'answers', 'question'])
dataset2 = load_dataset("imdb", split="train[:10]")
dataset2 = dataset2.set_format(type="torch", columns=["text", "label"])
print(len(dataset1))
| 35 | datasets freezes
Hi, I want to load these two datasets and convert them to Dataset format in torch and the code freezes for me, could you have a look please? thanks
dataset1 = load_dataset("squad", split="train[:10]")
dataset1 = dataset1.set_format(type='torch', columns=['context', 'answers', 'question'])
dataset2 = load_dataset("imdb", split="train[:10]")
dataset2 = dataset2.set_format(type="torch", columns=["text", "label"])
print(len(dataset1))
Ultimately, we decided to return a list instead of an error when formatting a string column with the format type `"torch"`.
If you think an error would be more appropriate, please open a new issue. |
https://github.com/huggingface/datasets/issues/816 | [Caching] Dill globalvars() output order is not deterministic and can cause cache issues. | To show the issue:
```
python -c "from datasets.fingerprint import Hasher; a=[]; func = lambda : len(a); print(Hasher.hash(func))"
```
doesn't always return the same ouput since `globs` is a dictionary with "a" and "len" as keys but sometimes not in the same order | Dill uses `dill.detect.globalvars` to get the globals used by a function in a recursive dump. `globalvars` returns a dictionary of all the globals that a dumped function needs. However the order of the keys in this dict is not deterministic and can cause caching issues.
To fix that one could register an implementation of dill's `save_function` in the `datasets` pickler that sorts the globals keys before dumping a function. | 43 | [Caching] Dill globalvars() output order is not deterministic and can cause cache issues.
Dill uses `dill.detect.globalvars` to get the globals used by a function in a recursive dump. `globalvars` returns a dictionary of all the globals that a dumped function needs. However the order of the keys in this dict is not deterministic and can cause caching issues.
To fix that one could register an implementation of dill's `save_function` in the `datasets` pickler that sorts the globals keys before dumping a function.
To show the issue:
```
python -c "from datasets.fingerprint import Hasher; a=[]; func = lambda : len(a); print(Hasher.hash(func))"
```
doesn't always return the same ouput since `globs` is a dictionary with "a" and "len" as keys but sometimes not in the same order |
https://github.com/huggingface/datasets/issues/815 | Is dataset iterative or not? | Hello !
Could you give more details ?
If you mean iter through one dataset then yes, `Dataset` object does implement the `__iter__` method so you can use
```python
for example in dataset:
# do something
```
If you want to iter through several datasets you can first concatenate them
```python
from datasets import concatenate_datasets
new_dataset = concatenate_datasets([dataset1, dataset2])
```
Let me know if this helps ! | Hi
I want to use your library for large-scale training, I am not sure if this is implemented as iterative datasets or not?
could you provide me with example how I can use datasets as iterative datasets?
thanks | 67 | Is dataset iterative or not?
Hi
I want to use your library for large-scale training, I am not sure if this is implemented as iterative datasets or not?
could you provide me with example how I can use datasets as iterative datasets?
thanks
Hello !
Could you give more details ?
If you mean iter through one dataset then yes, `Dataset` object does implement the `__iter__` method so you can use
```python
for example in dataset:
# do something
```
If you want to iter through several datasets you can first concatenate them
```python
from datasets import concatenate_datasets
new_dataset = concatenate_datasets([dataset1, dataset2])
```
Let me know if this helps ! |
https://github.com/huggingface/datasets/issues/815 | Is dataset iterative or not? | Hi Huggingface/Datasets team,
I want to use the datasets inside Seq2SeqDataset here
https://github.com/huggingface/transformers/blob/master/examples/seq2seq/utils.py
and there I need to return back each line from the datasets and I am not
sure how to access each line and implement this?
It seems it also has get_item attribute? so I was not sure if this is
iterative dataset? or if this is non-iterable datasets?
thanks.
On Mon, Nov 9, 2020 at 10:18 AM Quentin Lhoest <[email protected]>
wrote:
> Hello !
> Could you give more details ?
>
> If you mean iter through one dataset then yes, Dataset object does
> implement the __iter__ method so you can use
>
> for example in dataset:
> # do something
>
> If you want to iter through several datasets you can first concatenate them
>
> from datasets import concatenate_datasets
> new_dataset = concatenate_datasets([dataset1, dataset2])
>
> Let me know if this helps !
>
> —
> You are receiving this because you authored the thread.
> Reply to this email directly, view it on GitHub
> <https://github.com/huggingface/datasets/issues/815#issuecomment-723881199>,
> or unsubscribe
> <https://github.com/notifications/unsubscribe-auth/ARPXHHYRLSSYW6NZN2HYDBTSO6XV5ANCNFSM4TPB7OWA>
> .
>
| Hi
I want to use your library for large-scale training, I am not sure if this is implemented as iterative datasets or not?
could you provide me with example how I can use datasets as iterative datasets?
thanks | 185 | Is dataset iterative or not?
Hi
I want to use your library for large-scale training, I am not sure if this is implemented as iterative datasets or not?
could you provide me with example how I can use datasets as iterative datasets?
thanks
Hi Huggingface/Datasets team,
I want to use the datasets inside Seq2SeqDataset here
https://github.com/huggingface/transformers/blob/master/examples/seq2seq/utils.py
and there I need to return back each line from the datasets and I am not
sure how to access each line and implement this?
It seems it also has get_item attribute? so I was not sure if this is
iterative dataset? or if this is non-iterable datasets?
thanks.
On Mon, Nov 9, 2020 at 10:18 AM Quentin Lhoest <[email protected]>
wrote:
> Hello !
> Could you give more details ?
>
> If you mean iter through one dataset then yes, Dataset object does
> implement the __iter__ method so you can use
>
> for example in dataset:
> # do something
>
> If you want to iter through several datasets you can first concatenate them
>
> from datasets import concatenate_datasets
> new_dataset = concatenate_datasets([dataset1, dataset2])
>
> Let me know if this helps !
>
> —
> You are receiving this because you authored the thread.
> Reply to this email directly, view it on GitHub
> <https://github.com/huggingface/datasets/issues/815#issuecomment-723881199>,
> or unsubscribe
> <https://github.com/notifications/unsubscribe-auth/ARPXHHYRLSSYW6NZN2HYDBTSO6XV5ANCNFSM4TPB7OWA>
> .
>
|
https://github.com/huggingface/datasets/issues/815 | Is dataset iterative or not? | could you tell me please if datasets also has __getitem__ any idea on how
to integrate it with Seq2SeqDataset is appreciated thanks
On Mon, Nov 9, 2020 at 10:22 AM Rabeeh Karimi Mahabadi <[email protected]>
wrote:
> Hi Huggingface/Datasets team,
> I want to use the datasets inside Seq2SeqDataset here
> https://github.com/huggingface/transformers/blob/master/examples/seq2seq/utils.py
> and there I need to return back each line from the datasets and I am not
> sure how to access each line and implement this?
> It seems it also has get_item attribute? so I was not sure if this is
> iterative dataset? or if this is non-iterable datasets?
> thanks.
>
>
>
> On Mon, Nov 9, 2020 at 10:18 AM Quentin Lhoest <[email protected]>
> wrote:
>
>> Hello !
>> Could you give more details ?
>>
>> If you mean iter through one dataset then yes, Dataset object does
>> implement the __iter__ method so you can use
>>
>> for example in dataset:
>> # do something
>>
>> If you want to iter through several datasets you can first concatenate
>> them
>>
>> from datasets import concatenate_datasets
>> new_dataset = concatenate_datasets([dataset1, dataset2])
>>
>> Let me know if this helps !
>>
>> —
>> You are receiving this because you authored the thread.
>> Reply to this email directly, view it on GitHub
>> <https://github.com/huggingface/datasets/issues/815#issuecomment-723881199>,
>> or unsubscribe
>> <https://github.com/notifications/unsubscribe-auth/ARPXHHYRLSSYW6NZN2HYDBTSO6XV5ANCNFSM4TPB7OWA>
>> .
>>
>
| Hi
I want to use your library for large-scale training, I am not sure if this is implemented as iterative datasets or not?
could you provide me with example how I can use datasets as iterative datasets?
thanks | 236 | Is dataset iterative or not?
Hi
I want to use your library for large-scale training, I am not sure if this is implemented as iterative datasets or not?
could you provide me with example how I can use datasets as iterative datasets?
thanks
could you tell me please if datasets also has __getitem__ any idea on how
to integrate it with Seq2SeqDataset is appreciated thanks
On Mon, Nov 9, 2020 at 10:22 AM Rabeeh Karimi Mahabadi <[email protected]>
wrote:
> Hi Huggingface/Datasets team,
> I want to use the datasets inside Seq2SeqDataset here
> https://github.com/huggingface/transformers/blob/master/examples/seq2seq/utils.py
> and there I need to return back each line from the datasets and I am not
> sure how to access each line and implement this?
> It seems it also has get_item attribute? so I was not sure if this is
> iterative dataset? or if this is non-iterable datasets?
> thanks.
>
>
>
> On Mon, Nov 9, 2020 at 10:18 AM Quentin Lhoest <[email protected]>
> wrote:
>
>> Hello !
>> Could you give more details ?
>>
>> If you mean iter through one dataset then yes, Dataset object does
>> implement the __iter__ method so you can use
>>
>> for example in dataset:
>> # do something
>>
>> If you want to iter through several datasets you can first concatenate
>> them
>>
>> from datasets import concatenate_datasets
>> new_dataset = concatenate_datasets([dataset1, dataset2])
>>
>> Let me know if this helps !
>>
>> —
>> You are receiving this because you authored the thread.
>> Reply to this email directly, view it on GitHub
>> <https://github.com/huggingface/datasets/issues/815#issuecomment-723881199>,
>> or unsubscribe
>> <https://github.com/notifications/unsubscribe-auth/ARPXHHYRLSSYW6NZN2HYDBTSO6XV5ANCNFSM4TPB7OWA>
>> .
>>
>
|
https://github.com/huggingface/datasets/issues/815 | Is dataset iterative or not? | `datasets.Dataset` objects implement indeed `__getitem__`. It returns a dictionary with one field per column.
We've not added the integration of the datasets library for the seq2seq utilities yet. The current seq2seq utilities are based on text files.
However as soon as you have a `datasets.Dataset` with columns "tgt_texts" (str), "src_texts" (str), and "id" (int) you should be able to implement your own Seq2SeqDataset class that wraps your dataset object. Does that make sense to you ? | Hi
I want to use your library for large-scale training, I am not sure if this is implemented as iterative datasets or not?
could you provide me with example how I can use datasets as iterative datasets?
thanks | 76 | Is dataset iterative or not?
Hi
I want to use your library for large-scale training, I am not sure if this is implemented as iterative datasets or not?
could you provide me with example how I can use datasets as iterative datasets?
thanks
`datasets.Dataset` objects implement indeed `__getitem__`. It returns a dictionary with one field per column.
We've not added the integration of the datasets library for the seq2seq utilities yet. The current seq2seq utilities are based on text files.
However as soon as you have a `datasets.Dataset` with columns "tgt_texts" (str), "src_texts" (str), and "id" (int) you should be able to implement your own Seq2SeqDataset class that wraps your dataset object. Does that make sense to you ? |
https://github.com/huggingface/datasets/issues/815 | Is dataset iterative or not? | Hi
I am sorry for asking it multiple times but I am not getting the dataloader
type, could you confirm if the dataset library returns back an iterable
type dataloader or a mapping type one where one has access to __getitem__,
in the former case, one can iterate with __iter__, and how I can configure
it to return the data back as the iterative type? I am dealing with
large-scale datasets and I do not want to bring all in memory
thanks for your help
Best regards
Rabeeh
On Mon, Nov 9, 2020 at 11:17 AM Quentin Lhoest <[email protected]>
wrote:
> datasets.Dataset objects implement indeed __getitem__. It returns a
> dictionary with one field per column.
>
> We've not added the integration of the datasets library for the seq2seq
> utilities yet. The current seq2seq utilities are based on text files.
>
> However as soon as you have a datasets.Dataset with columns "tgt_texts"
> (str), "src_texts" (str), and "id" (int) you should be able to implement
> your own Seq2SeqDataset class that wraps your dataset object. Does that
> make sense ?
>
> —
> You are receiving this because you authored the thread.
> Reply to this email directly, view it on GitHub
> <https://github.com/huggingface/datasets/issues/815#issuecomment-723915556>,
> or unsubscribe
> <https://github.com/notifications/unsubscribe-auth/ARPXHHYOC22EM7F666BZSOTSO66R3ANCNFSM4TPB7OWA>
> .
>
| Hi
I want to use your library for large-scale training, I am not sure if this is implemented as iterative datasets or not?
could you provide me with example how I can use datasets as iterative datasets?
thanks | 217 | Is dataset iterative or not?
Hi
I want to use your library for large-scale training, I am not sure if this is implemented as iterative datasets or not?
could you provide me with example how I can use datasets as iterative datasets?
thanks
Hi
I am sorry for asking it multiple times but I am not getting the dataloader
type, could you confirm if the dataset library returns back an iterable
type dataloader or a mapping type one where one has access to __getitem__,
in the former case, one can iterate with __iter__, and how I can configure
it to return the data back as the iterative type? I am dealing with
large-scale datasets and I do not want to bring all in memory
thanks for your help
Best regards
Rabeeh
On Mon, Nov 9, 2020 at 11:17 AM Quentin Lhoest <[email protected]>
wrote:
> datasets.Dataset objects implement indeed __getitem__. It returns a
> dictionary with one field per column.
>
> We've not added the integration of the datasets library for the seq2seq
> utilities yet. The current seq2seq utilities are based on text files.
>
> However as soon as you have a datasets.Dataset with columns "tgt_texts"
> (str), "src_texts" (str), and "id" (int) you should be able to implement
> your own Seq2SeqDataset class that wraps your dataset object. Does that
> make sense ?
>
> —
> You are receiving this because you authored the thread.
> Reply to this email directly, view it on GitHub
> <https://github.com/huggingface/datasets/issues/815#issuecomment-723915556>,
> or unsubscribe
> <https://github.com/notifications/unsubscribe-auth/ARPXHHYOC22EM7F666BZSOTSO66R3ANCNFSM4TPB7OWA>
> .
>
|
https://github.com/huggingface/datasets/issues/815 | Is dataset iterative or not? | `datasets.Dataset` objects are both iterative and mapping types: it has both `__iter__` and `__getitem__`
For example you can do
```python
for example in dataset:
# do something
```
or
```python
for i in range(len(dataset)):
example = dataset[i]
# do something
```
When you do that, one and only one example is loaded into memory at a time. | Hi
I want to use your library for large-scale training, I am not sure if this is implemented as iterative datasets or not?
could you provide me with example how I can use datasets as iterative datasets?
thanks | 57 | Is dataset iterative or not?
Hi
I want to use your library for large-scale training, I am not sure if this is implemented as iterative datasets or not?
could you provide me with example how I can use datasets as iterative datasets?
thanks
`datasets.Dataset` objects are both iterative and mapping types: it has both `__iter__` and `__getitem__`
For example you can do
```python
for example in dataset:
# do something
```
or
```python
for i in range(len(dataset)):
example = dataset[i]
# do something
```
When you do that, one and only one example is loaded into memory at a time. |
https://github.com/huggingface/datasets/issues/815 | Is dataset iterative or not? | Hi there,
Here is what I am trying, this is not working for me in map-style datasets, could you please tell me how to use datasets with being able to access ___getitem__ ? could you assist me please correcting this example? I need map-style datasets which is formed from concatenation of two datasets from your library. thanks
```
import datasets
dataset1 = load_dataset("squad", split="train[:10]")
dataset1 = dataset1.map(lambda example: {"src_texts": "question: {0} context: {1} ".format(
example["question"], example["context"]),
"tgt_texts": example["answers"]["text"][0]}, remove_columns=dataset1.column_names)
dataset2 = load_dataset("imdb", split="train[:10]")
dataset2 = dataset2.map(lambda example: {"src_texts": "imdb: " + example["text"],
"tgt_texts": str(example["label"])}, remove_columns=dataset2.column_names)
train_dataset = datasets.concatenate_datasets([dataset1, dataset2])
train_dataset.set_format(type='torch', columns=['src_texts', 'tgt_texts'])
dataloader = torch.utils.data.DataLoader(train_dataset, batch_size=32)
for id, batch in enumerate(dataloader):
print(batch)
``` | Hi
I want to use your library for large-scale training, I am not sure if this is implemented as iterative datasets or not?
could you provide me with example how I can use datasets as iterative datasets?
thanks | 113 | Is dataset iterative or not?
Hi
I want to use your library for large-scale training, I am not sure if this is implemented as iterative datasets or not?
could you provide me with example how I can use datasets as iterative datasets?
thanks
Hi there,
Here is what I am trying, this is not working for me in map-style datasets, could you please tell me how to use datasets with being able to access ___getitem__ ? could you assist me please correcting this example? I need map-style datasets which is formed from concatenation of two datasets from your library. thanks
```
import datasets
dataset1 = load_dataset("squad", split="train[:10]")
dataset1 = dataset1.map(lambda example: {"src_texts": "question: {0} context: {1} ".format(
example["question"], example["context"]),
"tgt_texts": example["answers"]["text"][0]}, remove_columns=dataset1.column_names)
dataset2 = load_dataset("imdb", split="train[:10]")
dataset2 = dataset2.map(lambda example: {"src_texts": "imdb: " + example["text"],
"tgt_texts": str(example["label"])}, remove_columns=dataset2.column_names)
train_dataset = datasets.concatenate_datasets([dataset1, dataset2])
train_dataset.set_format(type='torch', columns=['src_texts', 'tgt_texts'])
dataloader = torch.utils.data.DataLoader(train_dataset, batch_size=32)
for id, batch in enumerate(dataloader):
print(batch)
``` |
https://github.com/huggingface/datasets/issues/813 | How to implement DistributedSampler with datasets | Hi Apparently I need to shard the data and give one host a chunk, could you provide me please with examples on how to do it? I want to use it jointly with finetune_trainer.py in huggingface repo seq2seq examples. thanks. | Hi,
I am using your datasets to define my dataloaders, and I am training finetune_trainer.py in huggingface repo on them.
I need a distributedSampler to be able to train the models on TPUs being able to distribute the load across the TPU cores. Could you tell me how I can implement the distribued sampler when using datasets in which datasets are iterative? To give you more context, I have multiple of datasets and I need to write sampler for this case. thanks. | 40 | How to implement DistributedSampler with datasets
Hi,
I am using your datasets to define my dataloaders, and I am training finetune_trainer.py in huggingface repo on them.
I need a distributedSampler to be able to train the models on TPUs being able to distribute the load across the TPU cores. Could you tell me how I can implement the distribued sampler when using datasets in which datasets are iterative? To give you more context, I have multiple of datasets and I need to write sampler for this case. thanks.
Hi Apparently I need to shard the data and give one host a chunk, could you provide me please with examples on how to do it? I want to use it jointly with finetune_trainer.py in huggingface repo seq2seq examples. thanks. |
https://github.com/huggingface/datasets/issues/812 | Too much logging | Hi ! Thanks for reporting :)
I agree these one should be hidden when the logging level is warning, we'll fix that | I'm doing this in the beginning of my script:
from datasets.utils import logging as datasets_logging
datasets_logging.set_verbosity_warning()
but I'm still getting these logs:
[2020-11-07 15:45:41,908][filelock][INFO] - Lock 139958278886176 acquired on /home/username/.cache/huggingface/datasets/cfe20ffaa80ef1c145a0a210d5b9cdce2b60002831e6ed0edc7ab9275d6f0d48.1bd4ccbce9de3dad0698d84674a19d6cc66a84db736a6398110bd196795dde7e.py.lock
[2020-11-07 15:45:41,909][filelock][INFO] - Lock 139958278886176 released on /home/username/.cache/huggingface/datasets/cfe20ffaa80ef1c145a0a210d5b9cdce2b60002831e6ed0edc7ab9275d6f0d48.1bd4ccbce9de3dad0698d84674a19d6cc66a84db736a6398110bd196795dde7e.py.lock
using datasets version = 1.1.2 | 22 | Too much logging
I'm doing this in the beginning of my script:
from datasets.utils import logging as datasets_logging
datasets_logging.set_verbosity_warning()
but I'm still getting these logs:
[2020-11-07 15:45:41,908][filelock][INFO] - Lock 139958278886176 acquired on /home/username/.cache/huggingface/datasets/cfe20ffaa80ef1c145a0a210d5b9cdce2b60002831e6ed0edc7ab9275d6f0d48.1bd4ccbce9de3dad0698d84674a19d6cc66a84db736a6398110bd196795dde7e.py.lock
[2020-11-07 15:45:41,909][filelock][INFO] - Lock 139958278886176 released on /home/username/.cache/huggingface/datasets/cfe20ffaa80ef1c145a0a210d5b9cdce2b60002831e6ed0edc7ab9275d6f0d48.1bd4ccbce9de3dad0698d84674a19d6cc66a84db736a6398110bd196795dde7e.py.lock
using datasets version = 1.1.2
Hi ! Thanks for reporting :)
I agree these one should be hidden when the logging level is warning, we'll fix that |
https://github.com/huggingface/datasets/issues/812 | Too much logging | +1, the amount of logging is excessive.
Most of it indeed comes from `filelock.py`, though there are occasionally messages from other sources too. Below is an example (all of these messages were logged after I already called `datasets.logging.set_verbosity_error()`)
```
I1109 21:26:01.742688 139785006901056 filelock.py:318] Lock 139778216292192 released on /home/kitaev/.cache/huggingface/datasets/9ed4f2e133395826175a892c70611f68522c7bc61a35476e8b51a31afb76e4bf.e6f3e3f3e3875a07469d1cfd32e16e1d06b149616b11eef2d081c43d515b492d.py.lock
I1109 21:26:01.747898 139785006901056 filelock.py:274] Lock 139778216290176 acquired on /home/kitaev/.cache/huggingface/datasets/_home_kitaev_.cache_huggingface_datasets_glue_mnli_1.0.0_7c99657241149a24692c402a5c3f34d4c9f1df5ac2e4c3759fadea38f6cb29c4.lock
I1109 21:26:01.748258 139785006901056 filelock.py:318] Lock 139778216290176 released on /home/kitaev/.cache/huggingface/datasets/_home_kitaev_.cache_huggingface_datasets_glue_mnli_1.0.0_7c99657241149a24692c402a5c3f34d4c9f1df5ac2e4c3759fadea38f6cb29c4.lock
I1109 21:26:01.748412 139785006901056 filelock.py:274] Lock 139778215853024 acquired on /home/kitaev/.cache/huggingface/datasets/_home_kitaev_.cache_huggingface_datasets_glue_mnli_1.0.0_7c99657241149a24692c402a5c3f34d4c9f1df5ac2e4c3759fadea38f6cb29c4.lock
I1109 21:26:01.748497 139785006901056 filelock.py:318] Lock 139778215853024 released on /home/kitaev/.cache/huggingface/datasets/_home_kitaev_.cache_huggingface_datasets_glue_mnli_1.0.0_7c99657241149a24692c402a5c3f34d4c9f1df5ac2e4c3759fadea38f6cb29c4.lock
I1109 21:07:17.029001 140301730502464 filelock.py:274] Lock 140289479304360 acquired on /home/kitaev/.cache/huggingface/datasets/b16d3a04bf2cad1346896852bf120ba846ea1bebb1cd60255bb3a1a2bbcc3a67.ec871b06a00118091ec63eff0a641fddcb8d3c7cd52e855bbb2be28944df4b82.py.lock
I1109 21:07:17.029341 140301730502464 filelock.py:318] Lock 140289479304360 released on /home/kitaev/.cache/huggingface/datasets/b16d3a04bf2cad1346896852bf120ba846ea1bebb1cd60255bb3a1a2bbcc3a67.ec871b06a00118091ec63eff0a641fddcb8d3c7cd52e855bbb2be28944df4b82.py.lock
I1109 21:07:17.058964 140301730502464 filelock.py:274] Lock 140251889388120 acquired on /home/kitaev/.cache/huggingface/metrics/glue/mnli/default_experiment-1-0.arrow.lock
I1109 21:07:17.060933 140301730502464 filelock.py:318] Lock 140251889388120 released on /home/kitaev/.cache/huggingface/metrics/glue/mnli/default_experiment-1-0.arrow.lock
I1109 21:07:17.061067 140301730502464 filelock.py:274] Lock 140296072521488 acquired on /home/kitaev/.cache/huggingface/metrics/glue/mnli/default_experiment-1-0.arrow.lock
I1109 21:07:17.069736 140301730502464 metric.py:400] Removing /home/kitaev/.cache/huggingface/metrics/glue/mnli/default_experiment-1-0.arrow
I1109 21:07:17.069949 140301730502464 filelock.py:318] Lock 140296072521488 released on /home/kitaev/.cache/huggingface/metrics/glue/mnli/default_experiment-1-0.arrow.lock
``` | I'm doing this in the beginning of my script:
from datasets.utils import logging as datasets_logging
datasets_logging.set_verbosity_warning()
but I'm still getting these logs:
[2020-11-07 15:45:41,908][filelock][INFO] - Lock 139958278886176 acquired on /home/username/.cache/huggingface/datasets/cfe20ffaa80ef1c145a0a210d5b9cdce2b60002831e6ed0edc7ab9275d6f0d48.1bd4ccbce9de3dad0698d84674a19d6cc66a84db736a6398110bd196795dde7e.py.lock
[2020-11-07 15:45:41,909][filelock][INFO] - Lock 139958278886176 released on /home/username/.cache/huggingface/datasets/cfe20ffaa80ef1c145a0a210d5b9cdce2b60002831e6ed0edc7ab9275d6f0d48.1bd4ccbce9de3dad0698d84674a19d6cc66a84db736a6398110bd196795dde7e.py.lock
using datasets version = 1.1.2 | 145 | Too much logging
I'm doing this in the beginning of my script:
from datasets.utils import logging as datasets_logging
datasets_logging.set_verbosity_warning()
but I'm still getting these logs:
[2020-11-07 15:45:41,908][filelock][INFO] - Lock 139958278886176 acquired on /home/username/.cache/huggingface/datasets/cfe20ffaa80ef1c145a0a210d5b9cdce2b60002831e6ed0edc7ab9275d6f0d48.1bd4ccbce9de3dad0698d84674a19d6cc66a84db736a6398110bd196795dde7e.py.lock
[2020-11-07 15:45:41,909][filelock][INFO] - Lock 139958278886176 released on /home/username/.cache/huggingface/datasets/cfe20ffaa80ef1c145a0a210d5b9cdce2b60002831e6ed0edc7ab9275d6f0d48.1bd4ccbce9de3dad0698d84674a19d6cc66a84db736a6398110bd196795dde7e.py.lock
using datasets version = 1.1.2
+1, the amount of logging is excessive.
Most of it indeed comes from `filelock.py`, though there are occasionally messages from other sources too. Below is an example (all of these messages were logged after I already called `datasets.logging.set_verbosity_error()`)
```
I1109 21:26:01.742688 139785006901056 filelock.py:318] Lock 139778216292192 released on /home/kitaev/.cache/huggingface/datasets/9ed4f2e133395826175a892c70611f68522c7bc61a35476e8b51a31afb76e4bf.e6f3e3f3e3875a07469d1cfd32e16e1d06b149616b11eef2d081c43d515b492d.py.lock
I1109 21:26:01.747898 139785006901056 filelock.py:274] Lock 139778216290176 acquired on /home/kitaev/.cache/huggingface/datasets/_home_kitaev_.cache_huggingface_datasets_glue_mnli_1.0.0_7c99657241149a24692c402a5c3f34d4c9f1df5ac2e4c3759fadea38f6cb29c4.lock
I1109 21:26:01.748258 139785006901056 filelock.py:318] Lock 139778216290176 released on /home/kitaev/.cache/huggingface/datasets/_home_kitaev_.cache_huggingface_datasets_glue_mnli_1.0.0_7c99657241149a24692c402a5c3f34d4c9f1df5ac2e4c3759fadea38f6cb29c4.lock
I1109 21:26:01.748412 139785006901056 filelock.py:274] Lock 139778215853024 acquired on /home/kitaev/.cache/huggingface/datasets/_home_kitaev_.cache_huggingface_datasets_glue_mnli_1.0.0_7c99657241149a24692c402a5c3f34d4c9f1df5ac2e4c3759fadea38f6cb29c4.lock
I1109 21:26:01.748497 139785006901056 filelock.py:318] Lock 139778215853024 released on /home/kitaev/.cache/huggingface/datasets/_home_kitaev_.cache_huggingface_datasets_glue_mnli_1.0.0_7c99657241149a24692c402a5c3f34d4c9f1df5ac2e4c3759fadea38f6cb29c4.lock
I1109 21:07:17.029001 140301730502464 filelock.py:274] Lock 140289479304360 acquired on /home/kitaev/.cache/huggingface/datasets/b16d3a04bf2cad1346896852bf120ba846ea1bebb1cd60255bb3a1a2bbcc3a67.ec871b06a00118091ec63eff0a641fddcb8d3c7cd52e855bbb2be28944df4b82.py.lock
I1109 21:07:17.029341 140301730502464 filelock.py:318] Lock 140289479304360 released on /home/kitaev/.cache/huggingface/datasets/b16d3a04bf2cad1346896852bf120ba846ea1bebb1cd60255bb3a1a2bbcc3a67.ec871b06a00118091ec63eff0a641fddcb8d3c7cd52e855bbb2be28944df4b82.py.lock
I1109 21:07:17.058964 140301730502464 filelock.py:274] Lock 140251889388120 acquired on /home/kitaev/.cache/huggingface/metrics/glue/mnli/default_experiment-1-0.arrow.lock
I1109 21:07:17.060933 140301730502464 filelock.py:318] Lock 140251889388120 released on /home/kitaev/.cache/huggingface/metrics/glue/mnli/default_experiment-1-0.arrow.lock
I1109 21:07:17.061067 140301730502464 filelock.py:274] Lock 140296072521488 acquired on /home/kitaev/.cache/huggingface/metrics/glue/mnli/default_experiment-1-0.arrow.lock
I1109 21:07:17.069736 140301730502464 metric.py:400] Removing /home/kitaev/.cache/huggingface/metrics/glue/mnli/default_experiment-1-0.arrow
I1109 21:07:17.069949 140301730502464 filelock.py:318] Lock 140296072521488 released on /home/kitaev/.cache/huggingface/metrics/glue/mnli/default_experiment-1-0.arrow.lock
``` |
https://github.com/huggingface/datasets/issues/812 | Too much logging | In the latest version of the lib the logs about locks are at the DEBUG level so you won't see them by default.
Also `set_verbosity_warning` does take into account these logs now.
Can you try to update the lib ?
```
pip install --upgrade datasets
``` | I'm doing this in the beginning of my script:
from datasets.utils import logging as datasets_logging
datasets_logging.set_verbosity_warning()
but I'm still getting these logs:
[2020-11-07 15:45:41,908][filelock][INFO] - Lock 139958278886176 acquired on /home/username/.cache/huggingface/datasets/cfe20ffaa80ef1c145a0a210d5b9cdce2b60002831e6ed0edc7ab9275d6f0d48.1bd4ccbce9de3dad0698d84674a19d6cc66a84db736a6398110bd196795dde7e.py.lock
[2020-11-07 15:45:41,909][filelock][INFO] - Lock 139958278886176 released on /home/username/.cache/huggingface/datasets/cfe20ffaa80ef1c145a0a210d5b9cdce2b60002831e6ed0edc7ab9275d6f0d48.1bd4ccbce9de3dad0698d84674a19d6cc66a84db736a6398110bd196795dde7e.py.lock
using datasets version = 1.1.2 | 46 | Too much logging
I'm doing this in the beginning of my script:
from datasets.utils import logging as datasets_logging
datasets_logging.set_verbosity_warning()
but I'm still getting these logs:
[2020-11-07 15:45:41,908][filelock][INFO] - Lock 139958278886176 acquired on /home/username/.cache/huggingface/datasets/cfe20ffaa80ef1c145a0a210d5b9cdce2b60002831e6ed0edc7ab9275d6f0d48.1bd4ccbce9de3dad0698d84674a19d6cc66a84db736a6398110bd196795dde7e.py.lock
[2020-11-07 15:45:41,909][filelock][INFO] - Lock 139958278886176 released on /home/username/.cache/huggingface/datasets/cfe20ffaa80ef1c145a0a210d5b9cdce2b60002831e6ed0edc7ab9275d6f0d48.1bd4ccbce9de3dad0698d84674a19d6cc66a84db736a6398110bd196795dde7e.py.lock
using datasets version = 1.1.2
In the latest version of the lib the logs about locks are at the DEBUG level so you won't see them by default.
Also `set_verbosity_warning` does take into account these logs now.
Can you try to update the lib ?
```
pip install --upgrade datasets
``` |
https://github.com/huggingface/datasets/issues/812 | Too much logging | Thanks. For some reason I have to use the older version. Is that possible I can fix this by some surface-level trick?
I'm still using 1.13 version datasets. | I'm doing this in the beginning of my script:
from datasets.utils import logging as datasets_logging
datasets_logging.set_verbosity_warning()
but I'm still getting these logs:
[2020-11-07 15:45:41,908][filelock][INFO] - Lock 139958278886176 acquired on /home/username/.cache/huggingface/datasets/cfe20ffaa80ef1c145a0a210d5b9cdce2b60002831e6ed0edc7ab9275d6f0d48.1bd4ccbce9de3dad0698d84674a19d6cc66a84db736a6398110bd196795dde7e.py.lock
[2020-11-07 15:45:41,909][filelock][INFO] - Lock 139958278886176 released on /home/username/.cache/huggingface/datasets/cfe20ffaa80ef1c145a0a210d5b9cdce2b60002831e6ed0edc7ab9275d6f0d48.1bd4ccbce9de3dad0698d84674a19d6cc66a84db736a6398110bd196795dde7e.py.lock
using datasets version = 1.1.2 | 28 | Too much logging
I'm doing this in the beginning of my script:
from datasets.utils import logging as datasets_logging
datasets_logging.set_verbosity_warning()
but I'm still getting these logs:
[2020-11-07 15:45:41,908][filelock][INFO] - Lock 139958278886176 acquired on /home/username/.cache/huggingface/datasets/cfe20ffaa80ef1c145a0a210d5b9cdce2b60002831e6ed0edc7ab9275d6f0d48.1bd4ccbce9de3dad0698d84674a19d6cc66a84db736a6398110bd196795dde7e.py.lock
[2020-11-07 15:45:41,909][filelock][INFO] - Lock 139958278886176 released on /home/username/.cache/huggingface/datasets/cfe20ffaa80ef1c145a0a210d5b9cdce2b60002831e6ed0edc7ab9275d6f0d48.1bd4ccbce9de3dad0698d84674a19d6cc66a84db736a6398110bd196795dde7e.py.lock
using datasets version = 1.1.2
Thanks. For some reason I have to use the older version. Is that possible I can fix this by some surface-level trick?
I'm still using 1.13 version datasets. |
https://github.com/huggingface/datasets/issues/809 | Add Google Taskmaster dataset | Hey @yjernite. Was going to start working on this but found taskmaster 1,2 & 3 in the datasets library already so think this can be closed now? | ## Adding a Dataset
- **Name:** Taskmaster
- **Description:** A large dataset of task-oriented dialogue with annotated goals (55K dialogues covering entertainment and travel reservations)
- **Paper:** https://arxiv.org/abs/1909.05358
- **Data:** https://github.com/google-research-datasets/Taskmaster
- **Motivation:** One of few annotated datasets of this size for goal-oriented dialogue
Instructions to add a new dataset can be found [here](https://huggingface.co/docs/datasets/share_dataset.html).
| 27 | Add Google Taskmaster dataset
## Adding a Dataset
- **Name:** Taskmaster
- **Description:** A large dataset of task-oriented dialogue with annotated goals (55K dialogues covering entertainment and travel reservations)
- **Paper:** https://arxiv.org/abs/1909.05358
- **Data:** https://github.com/google-research-datasets/Taskmaster
- **Motivation:** One of few annotated datasets of this size for goal-oriented dialogue
Instructions to add a new dataset can be found [here](https://huggingface.co/docs/datasets/share_dataset.html).
Hey @yjernite. Was going to start working on this but found taskmaster 1,2 & 3 in the datasets library already so think this can be closed now? |
https://github.com/huggingface/datasets/issues/807 | load_dataset for LOCAL CSV files report CONNECTION ERROR | Hi !
The url works on my side.
Is the url working in your navigator ?
Are you connected to internet ? Does your network block access to `raw.githubusercontent.com` ? | ## load_dataset for LOCAL CSV files report CONNECTION ERROR
- **Description:**
A local demo csv file:
```
import pandas as pd
import numpy as np
from datasets import load_dataset
import torch
import transformers
df = pd.DataFrame(np.arange(1200).reshape(300,4))
df.to_csv('test.csv', header=False, index=False)
print('datasets version: ', datasets.__version__)
print('pytorch version: ', torch.__version__)
print('transformers version: ', transformers.__version__)
# output:
datasets version: 1.1.2
pytorch version: 1.5.0
transformers version: 3.2.0
```
when I load data through `dataset`:
```
dataset = load_dataset('csv', data_files='./test.csv', delimiter=',', autogenerate_column_names=False)
```
Error infos:
```
ConnectionError Traceback (most recent call last)
<ipython-input-17-bbdadb9a0c78> in <module>
----> 1 dataset = load_dataset('csv', data_files='./test.csv', delimiter=',', autogenerate_column_names=False)
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/load.py in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, save_infos, script_version, **config_kwargs)
588 # Download/copy dataset processing script
589 module_path, hash = prepare_module(
--> 590 path, script_version=script_version, download_config=download_config, download_mode=download_mode, dataset=True
591 )
592
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/load.py in prepare_module(path, script_version, download_config, download_mode, dataset, force_local_path, **download_kwargs)
266 file_path = hf_github_url(path=path, name=name, dataset=dataset, version=script_version)
267 try:
--> 268 local_path = cached_path(file_path, download_config=download_config)
269 except FileNotFoundError:
270 if script_version is not None:
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/utils/file_utils.py in cached_path(url_or_filename, download_config, **download_kwargs)
306 user_agent=download_config.user_agent,
307 local_files_only=download_config.local_files_only,
--> 308 use_etag=download_config.use_etag,
309 )
310 elif os.path.exists(url_or_filename):
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/utils/file_utils.py in get_from_cache(url, cache_dir, force_download, proxies, etag_timeout, resume_download, user_agent, local_files_only, use_etag)
473 elif response is not None and response.status_code == 404:
474 raise FileNotFoundError("Couldn't find file at {}".format(url))
--> 475 raise ConnectionError("Couldn't reach {}".format(url))
476
477 # Try a second time
ConnectionError: Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py
```
And I try to connect to the site with requests:
```
import requests
requests.head("https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py")
```
Similarly Error occurs:
```
---------------------------------------------------------------------------
ConnectionRefusedError Traceback (most recent call last)
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connection.py in _new_conn(self)
159 conn = connection.create_connection(
--> 160 (self._dns_host, self.port), self.timeout, **extra_kw
161 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/util/connection.py in create_connection(address, timeout, source_address, socket_options)
83 if err is not None:
---> 84 raise err
85
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/util/connection.py in create_connection(address, timeout, source_address, socket_options)
73 sock.bind(source_address)
---> 74 sock.connect(sa)
75 return sock
ConnectionRefusedError: [Errno 111] Connection refused
During handling of the above exception, another exception occurred:
NewConnectionError Traceback (most recent call last)
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)
676 headers=headers,
--> 677 chunked=chunked,
678 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in _make_request(self, conn, method, url, timeout, chunked, **httplib_request_kw)
380 try:
--> 381 self._validate_conn(conn)
382 except (SocketTimeout, BaseSSLError) as e:
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in _validate_conn(self, conn)
975 if not getattr(conn, "sock", None): # AppEngine might not have `.sock`
--> 976 conn.connect()
977
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connection.py in connect(self)
307 # Add certificate verification
--> 308 conn = self._new_conn()
309 hostname = self.host
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connection.py in _new_conn(self)
171 raise NewConnectionError(
--> 172 self, "Failed to establish a new connection: %s" % e
173 )
NewConnectionError: <urllib3.connection.HTTPSConnection object at 0x7f3cceda5e48>: Failed to establish a new connection: [Errno 111] Connection refused
During handling of the above exception, another exception occurred:
MaxRetryError Traceback (most recent call last)
~/.conda/envs/py36/lib/python3.6/site-packages/requests/adapters.py in send(self, request, stream, timeout, verify, cert, proxies)
448 retries=self.max_retries,
--> 449 timeout=timeout
450 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)
724 retries = retries.increment(
--> 725 method, url, error=e, _pool=self, _stacktrace=sys.exc_info()[2]
726 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/util/retry.py in increment(self, method, url, response, error, _pool, _stacktrace)
438 if new_retry.is_exhausted():
--> 439 raise MaxRetryError(_pool, url, error or ResponseError(cause))
440
MaxRetryError: HTTPSConnectionPool(host='raw.githubusercontent.com', port=443): Max retries exceeded with url: /huggingface/datasets/1.1.2/datasets/csv/csv.py (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x7f3cceda5e48>: Failed to establish a new connection: [Errno 111] Connection refused',))
During handling of the above exception, another exception occurred:
ConnectionError Traceback (most recent call last)
<ipython-input-20-18cc3eb4a049> in <module>
1 import requests
2
----> 3 requests.head("https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py")
~/.conda/envs/py36/lib/python3.6/site-packages/requests/api.py in head(url, **kwargs)
102
103 kwargs.setdefault('allow_redirects', False)
--> 104 return request('head', url, **kwargs)
105
106
~/.conda/envs/py36/lib/python3.6/site-packages/requests/api.py in request(method, url, **kwargs)
59 # cases, and look like a memory leak in others.
60 with sessions.Session() as session:
---> 61 return session.request(method=method, url=url, **kwargs)
62
63
~/.conda/envs/py36/lib/python3.6/site-packages/requests/sessions.py in request(self, method, url, params, data, headers, cookies, files, auth, timeout, allow_redirects, proxies, hooks, stream, verify, cert, json)
528 }
529 send_kwargs.update(settings)
--> 530 resp = self.send(prep, **send_kwargs)
531
532 return resp
~/.conda/envs/py36/lib/python3.6/site-packages/requests/sessions.py in send(self, request, **kwargs)
641
642 # Send the request
--> 643 r = adapter.send(request, **kwargs)
644
645 # Total elapsed time of the request (approximately)
~/.conda/envs/py36/lib/python3.6/site-packages/requests/adapters.py in send(self, request, stream, timeout, verify, cert, proxies)
514 raise SSLError(e, request=request)
515
--> 516 raise ConnectionError(e, request=request)
517
518 except ClosedPoolError as e:
ConnectionError: HTTPSConnectionPool(host='raw.githubusercontent.com', port=443): Max retries exceeded with url: /huggingface/datasets/1.1.2/datasets/csv/csv.py (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x7f3cceda5e48>: Failed to establish a new connection: [Errno 111] Connection refused',))
``` | 30 | load_dataset for LOCAL CSV files report CONNECTION ERROR
## load_dataset for LOCAL CSV files report CONNECTION ERROR
- **Description:**
A local demo csv file:
```
import pandas as pd
import numpy as np
from datasets import load_dataset
import torch
import transformers
df = pd.DataFrame(np.arange(1200).reshape(300,4))
df.to_csv('test.csv', header=False, index=False)
print('datasets version: ', datasets.__version__)
print('pytorch version: ', torch.__version__)
print('transformers version: ', transformers.__version__)
# output:
datasets version: 1.1.2
pytorch version: 1.5.0
transformers version: 3.2.0
```
when I load data through `dataset`:
```
dataset = load_dataset('csv', data_files='./test.csv', delimiter=',', autogenerate_column_names=False)
```
Error infos:
```
ConnectionError Traceback (most recent call last)
<ipython-input-17-bbdadb9a0c78> in <module>
----> 1 dataset = load_dataset('csv', data_files='./test.csv', delimiter=',', autogenerate_column_names=False)
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/load.py in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, save_infos, script_version, **config_kwargs)
588 # Download/copy dataset processing script
589 module_path, hash = prepare_module(
--> 590 path, script_version=script_version, download_config=download_config, download_mode=download_mode, dataset=True
591 )
592
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/load.py in prepare_module(path, script_version, download_config, download_mode, dataset, force_local_path, **download_kwargs)
266 file_path = hf_github_url(path=path, name=name, dataset=dataset, version=script_version)
267 try:
--> 268 local_path = cached_path(file_path, download_config=download_config)
269 except FileNotFoundError:
270 if script_version is not None:
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/utils/file_utils.py in cached_path(url_or_filename, download_config, **download_kwargs)
306 user_agent=download_config.user_agent,
307 local_files_only=download_config.local_files_only,
--> 308 use_etag=download_config.use_etag,
309 )
310 elif os.path.exists(url_or_filename):
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/utils/file_utils.py in get_from_cache(url, cache_dir, force_download, proxies, etag_timeout, resume_download, user_agent, local_files_only, use_etag)
473 elif response is not None and response.status_code == 404:
474 raise FileNotFoundError("Couldn't find file at {}".format(url))
--> 475 raise ConnectionError("Couldn't reach {}".format(url))
476
477 # Try a second time
ConnectionError: Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py
```
And I try to connect to the site with requests:
```
import requests
requests.head("https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py")
```
Similarly Error occurs:
```
---------------------------------------------------------------------------
ConnectionRefusedError Traceback (most recent call last)
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connection.py in _new_conn(self)
159 conn = connection.create_connection(
--> 160 (self._dns_host, self.port), self.timeout, **extra_kw
161 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/util/connection.py in create_connection(address, timeout, source_address, socket_options)
83 if err is not None:
---> 84 raise err
85
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/util/connection.py in create_connection(address, timeout, source_address, socket_options)
73 sock.bind(source_address)
---> 74 sock.connect(sa)
75 return sock
ConnectionRefusedError: [Errno 111] Connection refused
During handling of the above exception, another exception occurred:
NewConnectionError Traceback (most recent call last)
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)
676 headers=headers,
--> 677 chunked=chunked,
678 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in _make_request(self, conn, method, url, timeout, chunked, **httplib_request_kw)
380 try:
--> 381 self._validate_conn(conn)
382 except (SocketTimeout, BaseSSLError) as e:
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in _validate_conn(self, conn)
975 if not getattr(conn, "sock", None): # AppEngine might not have `.sock`
--> 976 conn.connect()
977
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connection.py in connect(self)
307 # Add certificate verification
--> 308 conn = self._new_conn()
309 hostname = self.host
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connection.py in _new_conn(self)
171 raise NewConnectionError(
--> 172 self, "Failed to establish a new connection: %s" % e
173 )
NewConnectionError: <urllib3.connection.HTTPSConnection object at 0x7f3cceda5e48>: Failed to establish a new connection: [Errno 111] Connection refused
During handling of the above exception, another exception occurred:
MaxRetryError Traceback (most recent call last)
~/.conda/envs/py36/lib/python3.6/site-packages/requests/adapters.py in send(self, request, stream, timeout, verify, cert, proxies)
448 retries=self.max_retries,
--> 449 timeout=timeout
450 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)
724 retries = retries.increment(
--> 725 method, url, error=e, _pool=self, _stacktrace=sys.exc_info()[2]
726 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/util/retry.py in increment(self, method, url, response, error, _pool, _stacktrace)
438 if new_retry.is_exhausted():
--> 439 raise MaxRetryError(_pool, url, error or ResponseError(cause))
440
MaxRetryError: HTTPSConnectionPool(host='raw.githubusercontent.com', port=443): Max retries exceeded with url: /huggingface/datasets/1.1.2/datasets/csv/csv.py (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x7f3cceda5e48>: Failed to establish a new connection: [Errno 111] Connection refused',))
During handling of the above exception, another exception occurred:
ConnectionError Traceback (most recent call last)
<ipython-input-20-18cc3eb4a049> in <module>
1 import requests
2
----> 3 requests.head("https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py")
~/.conda/envs/py36/lib/python3.6/site-packages/requests/api.py in head(url, **kwargs)
102
103 kwargs.setdefault('allow_redirects', False)
--> 104 return request('head', url, **kwargs)
105
106
~/.conda/envs/py36/lib/python3.6/site-packages/requests/api.py in request(method, url, **kwargs)
59 # cases, and look like a memory leak in others.
60 with sessions.Session() as session:
---> 61 return session.request(method=method, url=url, **kwargs)
62
63
~/.conda/envs/py36/lib/python3.6/site-packages/requests/sessions.py in request(self, method, url, params, data, headers, cookies, files, auth, timeout, allow_redirects, proxies, hooks, stream, verify, cert, json)
528 }
529 send_kwargs.update(settings)
--> 530 resp = self.send(prep, **send_kwargs)
531
532 return resp
~/.conda/envs/py36/lib/python3.6/site-packages/requests/sessions.py in send(self, request, **kwargs)
641
642 # Send the request
--> 643 r = adapter.send(request, **kwargs)
644
645 # Total elapsed time of the request (approximately)
~/.conda/envs/py36/lib/python3.6/site-packages/requests/adapters.py in send(self, request, stream, timeout, verify, cert, proxies)
514 raise SSLError(e, request=request)
515
--> 516 raise ConnectionError(e, request=request)
517
518 except ClosedPoolError as e:
ConnectionError: HTTPSConnectionPool(host='raw.githubusercontent.com', port=443): Max retries exceeded with url: /huggingface/datasets/1.1.2/datasets/csv/csv.py (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x7f3cceda5e48>: Failed to establish a new connection: [Errno 111] Connection refused',))
```
Hi !
The url works on my side.
Is the url working in your navigator ?
Are you connected to internet ? Does your network block access to `raw.githubusercontent.com` ? |
https://github.com/huggingface/datasets/issues/807 | load_dataset for LOCAL CSV files report CONNECTION ERROR | > Hi !
> The url works on my side.
>
> Is the url working in your navigator ?
> Are you connected to internet ? Does your network block access to `raw.githubusercontent.com` ?
I tried another server, it's working now. Thanks a lot.
And I'm curious about why download things from "github" when I load dataset from local files ? Dose datasets work if my network crashed? | ## load_dataset for LOCAL CSV files report CONNECTION ERROR
- **Description:**
A local demo csv file:
```
import pandas as pd
import numpy as np
from datasets import load_dataset
import torch
import transformers
df = pd.DataFrame(np.arange(1200).reshape(300,4))
df.to_csv('test.csv', header=False, index=False)
print('datasets version: ', datasets.__version__)
print('pytorch version: ', torch.__version__)
print('transformers version: ', transformers.__version__)
# output:
datasets version: 1.1.2
pytorch version: 1.5.0
transformers version: 3.2.0
```
when I load data through `dataset`:
```
dataset = load_dataset('csv', data_files='./test.csv', delimiter=',', autogenerate_column_names=False)
```
Error infos:
```
ConnectionError Traceback (most recent call last)
<ipython-input-17-bbdadb9a0c78> in <module>
----> 1 dataset = load_dataset('csv', data_files='./test.csv', delimiter=',', autogenerate_column_names=False)
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/load.py in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, save_infos, script_version, **config_kwargs)
588 # Download/copy dataset processing script
589 module_path, hash = prepare_module(
--> 590 path, script_version=script_version, download_config=download_config, download_mode=download_mode, dataset=True
591 )
592
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/load.py in prepare_module(path, script_version, download_config, download_mode, dataset, force_local_path, **download_kwargs)
266 file_path = hf_github_url(path=path, name=name, dataset=dataset, version=script_version)
267 try:
--> 268 local_path = cached_path(file_path, download_config=download_config)
269 except FileNotFoundError:
270 if script_version is not None:
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/utils/file_utils.py in cached_path(url_or_filename, download_config, **download_kwargs)
306 user_agent=download_config.user_agent,
307 local_files_only=download_config.local_files_only,
--> 308 use_etag=download_config.use_etag,
309 )
310 elif os.path.exists(url_or_filename):
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/utils/file_utils.py in get_from_cache(url, cache_dir, force_download, proxies, etag_timeout, resume_download, user_agent, local_files_only, use_etag)
473 elif response is not None and response.status_code == 404:
474 raise FileNotFoundError("Couldn't find file at {}".format(url))
--> 475 raise ConnectionError("Couldn't reach {}".format(url))
476
477 # Try a second time
ConnectionError: Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py
```
And I try to connect to the site with requests:
```
import requests
requests.head("https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py")
```
Similarly Error occurs:
```
---------------------------------------------------------------------------
ConnectionRefusedError Traceback (most recent call last)
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connection.py in _new_conn(self)
159 conn = connection.create_connection(
--> 160 (self._dns_host, self.port), self.timeout, **extra_kw
161 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/util/connection.py in create_connection(address, timeout, source_address, socket_options)
83 if err is not None:
---> 84 raise err
85
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/util/connection.py in create_connection(address, timeout, source_address, socket_options)
73 sock.bind(source_address)
---> 74 sock.connect(sa)
75 return sock
ConnectionRefusedError: [Errno 111] Connection refused
During handling of the above exception, another exception occurred:
NewConnectionError Traceback (most recent call last)
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)
676 headers=headers,
--> 677 chunked=chunked,
678 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in _make_request(self, conn, method, url, timeout, chunked, **httplib_request_kw)
380 try:
--> 381 self._validate_conn(conn)
382 except (SocketTimeout, BaseSSLError) as e:
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in _validate_conn(self, conn)
975 if not getattr(conn, "sock", None): # AppEngine might not have `.sock`
--> 976 conn.connect()
977
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connection.py in connect(self)
307 # Add certificate verification
--> 308 conn = self._new_conn()
309 hostname = self.host
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connection.py in _new_conn(self)
171 raise NewConnectionError(
--> 172 self, "Failed to establish a new connection: %s" % e
173 )
NewConnectionError: <urllib3.connection.HTTPSConnection object at 0x7f3cceda5e48>: Failed to establish a new connection: [Errno 111] Connection refused
During handling of the above exception, another exception occurred:
MaxRetryError Traceback (most recent call last)
~/.conda/envs/py36/lib/python3.6/site-packages/requests/adapters.py in send(self, request, stream, timeout, verify, cert, proxies)
448 retries=self.max_retries,
--> 449 timeout=timeout
450 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)
724 retries = retries.increment(
--> 725 method, url, error=e, _pool=self, _stacktrace=sys.exc_info()[2]
726 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/util/retry.py in increment(self, method, url, response, error, _pool, _stacktrace)
438 if new_retry.is_exhausted():
--> 439 raise MaxRetryError(_pool, url, error or ResponseError(cause))
440
MaxRetryError: HTTPSConnectionPool(host='raw.githubusercontent.com', port=443): Max retries exceeded with url: /huggingface/datasets/1.1.2/datasets/csv/csv.py (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x7f3cceda5e48>: Failed to establish a new connection: [Errno 111] Connection refused',))
During handling of the above exception, another exception occurred:
ConnectionError Traceback (most recent call last)
<ipython-input-20-18cc3eb4a049> in <module>
1 import requests
2
----> 3 requests.head("https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py")
~/.conda/envs/py36/lib/python3.6/site-packages/requests/api.py in head(url, **kwargs)
102
103 kwargs.setdefault('allow_redirects', False)
--> 104 return request('head', url, **kwargs)
105
106
~/.conda/envs/py36/lib/python3.6/site-packages/requests/api.py in request(method, url, **kwargs)
59 # cases, and look like a memory leak in others.
60 with sessions.Session() as session:
---> 61 return session.request(method=method, url=url, **kwargs)
62
63
~/.conda/envs/py36/lib/python3.6/site-packages/requests/sessions.py in request(self, method, url, params, data, headers, cookies, files, auth, timeout, allow_redirects, proxies, hooks, stream, verify, cert, json)
528 }
529 send_kwargs.update(settings)
--> 530 resp = self.send(prep, **send_kwargs)
531
532 return resp
~/.conda/envs/py36/lib/python3.6/site-packages/requests/sessions.py in send(self, request, **kwargs)
641
642 # Send the request
--> 643 r = adapter.send(request, **kwargs)
644
645 # Total elapsed time of the request (approximately)
~/.conda/envs/py36/lib/python3.6/site-packages/requests/adapters.py in send(self, request, stream, timeout, verify, cert, proxies)
514 raise SSLError(e, request=request)
515
--> 516 raise ConnectionError(e, request=request)
517
518 except ClosedPoolError as e:
ConnectionError: HTTPSConnectionPool(host='raw.githubusercontent.com', port=443): Max retries exceeded with url: /huggingface/datasets/1.1.2/datasets/csv/csv.py (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x7f3cceda5e48>: Failed to establish a new connection: [Errno 111] Connection refused',))
``` | 69 | load_dataset for LOCAL CSV files report CONNECTION ERROR
## load_dataset for LOCAL CSV files report CONNECTION ERROR
- **Description:**
A local demo csv file:
```
import pandas as pd
import numpy as np
from datasets import load_dataset
import torch
import transformers
df = pd.DataFrame(np.arange(1200).reshape(300,4))
df.to_csv('test.csv', header=False, index=False)
print('datasets version: ', datasets.__version__)
print('pytorch version: ', torch.__version__)
print('transformers version: ', transformers.__version__)
# output:
datasets version: 1.1.2
pytorch version: 1.5.0
transformers version: 3.2.0
```
when I load data through `dataset`:
```
dataset = load_dataset('csv', data_files='./test.csv', delimiter=',', autogenerate_column_names=False)
```
Error infos:
```
ConnectionError Traceback (most recent call last)
<ipython-input-17-bbdadb9a0c78> in <module>
----> 1 dataset = load_dataset('csv', data_files='./test.csv', delimiter=',', autogenerate_column_names=False)
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/load.py in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, save_infos, script_version, **config_kwargs)
588 # Download/copy dataset processing script
589 module_path, hash = prepare_module(
--> 590 path, script_version=script_version, download_config=download_config, download_mode=download_mode, dataset=True
591 )
592
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/load.py in prepare_module(path, script_version, download_config, download_mode, dataset, force_local_path, **download_kwargs)
266 file_path = hf_github_url(path=path, name=name, dataset=dataset, version=script_version)
267 try:
--> 268 local_path = cached_path(file_path, download_config=download_config)
269 except FileNotFoundError:
270 if script_version is not None:
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/utils/file_utils.py in cached_path(url_or_filename, download_config, **download_kwargs)
306 user_agent=download_config.user_agent,
307 local_files_only=download_config.local_files_only,
--> 308 use_etag=download_config.use_etag,
309 )
310 elif os.path.exists(url_or_filename):
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/utils/file_utils.py in get_from_cache(url, cache_dir, force_download, proxies, etag_timeout, resume_download, user_agent, local_files_only, use_etag)
473 elif response is not None and response.status_code == 404:
474 raise FileNotFoundError("Couldn't find file at {}".format(url))
--> 475 raise ConnectionError("Couldn't reach {}".format(url))
476
477 # Try a second time
ConnectionError: Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py
```
And I try to connect to the site with requests:
```
import requests
requests.head("https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py")
```
Similarly Error occurs:
```
---------------------------------------------------------------------------
ConnectionRefusedError Traceback (most recent call last)
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connection.py in _new_conn(self)
159 conn = connection.create_connection(
--> 160 (self._dns_host, self.port), self.timeout, **extra_kw
161 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/util/connection.py in create_connection(address, timeout, source_address, socket_options)
83 if err is not None:
---> 84 raise err
85
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/util/connection.py in create_connection(address, timeout, source_address, socket_options)
73 sock.bind(source_address)
---> 74 sock.connect(sa)
75 return sock
ConnectionRefusedError: [Errno 111] Connection refused
During handling of the above exception, another exception occurred:
NewConnectionError Traceback (most recent call last)
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)
676 headers=headers,
--> 677 chunked=chunked,
678 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in _make_request(self, conn, method, url, timeout, chunked, **httplib_request_kw)
380 try:
--> 381 self._validate_conn(conn)
382 except (SocketTimeout, BaseSSLError) as e:
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in _validate_conn(self, conn)
975 if not getattr(conn, "sock", None): # AppEngine might not have `.sock`
--> 976 conn.connect()
977
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connection.py in connect(self)
307 # Add certificate verification
--> 308 conn = self._new_conn()
309 hostname = self.host
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connection.py in _new_conn(self)
171 raise NewConnectionError(
--> 172 self, "Failed to establish a new connection: %s" % e
173 )
NewConnectionError: <urllib3.connection.HTTPSConnection object at 0x7f3cceda5e48>: Failed to establish a new connection: [Errno 111] Connection refused
During handling of the above exception, another exception occurred:
MaxRetryError Traceback (most recent call last)
~/.conda/envs/py36/lib/python3.6/site-packages/requests/adapters.py in send(self, request, stream, timeout, verify, cert, proxies)
448 retries=self.max_retries,
--> 449 timeout=timeout
450 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)
724 retries = retries.increment(
--> 725 method, url, error=e, _pool=self, _stacktrace=sys.exc_info()[2]
726 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/util/retry.py in increment(self, method, url, response, error, _pool, _stacktrace)
438 if new_retry.is_exhausted():
--> 439 raise MaxRetryError(_pool, url, error or ResponseError(cause))
440
MaxRetryError: HTTPSConnectionPool(host='raw.githubusercontent.com', port=443): Max retries exceeded with url: /huggingface/datasets/1.1.2/datasets/csv/csv.py (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x7f3cceda5e48>: Failed to establish a new connection: [Errno 111] Connection refused',))
During handling of the above exception, another exception occurred:
ConnectionError Traceback (most recent call last)
<ipython-input-20-18cc3eb4a049> in <module>
1 import requests
2
----> 3 requests.head("https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py")
~/.conda/envs/py36/lib/python3.6/site-packages/requests/api.py in head(url, **kwargs)
102
103 kwargs.setdefault('allow_redirects', False)
--> 104 return request('head', url, **kwargs)
105
106
~/.conda/envs/py36/lib/python3.6/site-packages/requests/api.py in request(method, url, **kwargs)
59 # cases, and look like a memory leak in others.
60 with sessions.Session() as session:
---> 61 return session.request(method=method, url=url, **kwargs)
62
63
~/.conda/envs/py36/lib/python3.6/site-packages/requests/sessions.py in request(self, method, url, params, data, headers, cookies, files, auth, timeout, allow_redirects, proxies, hooks, stream, verify, cert, json)
528 }
529 send_kwargs.update(settings)
--> 530 resp = self.send(prep, **send_kwargs)
531
532 return resp
~/.conda/envs/py36/lib/python3.6/site-packages/requests/sessions.py in send(self, request, **kwargs)
641
642 # Send the request
--> 643 r = adapter.send(request, **kwargs)
644
645 # Total elapsed time of the request (approximately)
~/.conda/envs/py36/lib/python3.6/site-packages/requests/adapters.py in send(self, request, stream, timeout, verify, cert, proxies)
514 raise SSLError(e, request=request)
515
--> 516 raise ConnectionError(e, request=request)
517
518 except ClosedPoolError as e:
ConnectionError: HTTPSConnectionPool(host='raw.githubusercontent.com', port=443): Max retries exceeded with url: /huggingface/datasets/1.1.2/datasets/csv/csv.py (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x7f3cceda5e48>: Failed to establish a new connection: [Errno 111] Connection refused',))
```
> Hi !
> The url works on my side.
>
> Is the url working in your navigator ?
> Are you connected to internet ? Does your network block access to `raw.githubusercontent.com` ?
I tried another server, it's working now. Thanks a lot.
And I'm curious about why download things from "github" when I load dataset from local files ? Dose datasets work if my network crashed? |
https://github.com/huggingface/datasets/issues/807 | load_dataset for LOCAL CSV files report CONNECTION ERROR |
> > Hi !
> > The url works on my side.
> > Is the url working in your navigator ?
> > Are you connected to internet ? Does your network block access to `raw.githubusercontent.com` ?
>
> I tried another server, it's working now. Thanks a lot.
>
> And I'm curious about why download things from "github" when I load dataset from local files ? Dose datasets work if my network crashed?
I download the scripts `https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py` and move it to the package dir `*/datasets/` solved the problem. Could you please put the file `datasets/datasets/csv/csv.py` to `datasets/src/datasets/`？
Thanks :D | ## load_dataset for LOCAL CSV files report CONNECTION ERROR
- **Description:**
A local demo csv file:
```
import pandas as pd
import numpy as np
from datasets import load_dataset
import torch
import transformers
df = pd.DataFrame(np.arange(1200).reshape(300,4))
df.to_csv('test.csv', header=False, index=False)
print('datasets version: ', datasets.__version__)
print('pytorch version: ', torch.__version__)
print('transformers version: ', transformers.__version__)
# output:
datasets version: 1.1.2
pytorch version: 1.5.0
transformers version: 3.2.0
```
when I load data through `dataset`:
```
dataset = load_dataset('csv', data_files='./test.csv', delimiter=',', autogenerate_column_names=False)
```
Error infos:
```
ConnectionError Traceback (most recent call last)
<ipython-input-17-bbdadb9a0c78> in <module>
----> 1 dataset = load_dataset('csv', data_files='./test.csv', delimiter=',', autogenerate_column_names=False)
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/load.py in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, save_infos, script_version, **config_kwargs)
588 # Download/copy dataset processing script
589 module_path, hash = prepare_module(
--> 590 path, script_version=script_version, download_config=download_config, download_mode=download_mode, dataset=True
591 )
592
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/load.py in prepare_module(path, script_version, download_config, download_mode, dataset, force_local_path, **download_kwargs)
266 file_path = hf_github_url(path=path, name=name, dataset=dataset, version=script_version)
267 try:
--> 268 local_path = cached_path(file_path, download_config=download_config)
269 except FileNotFoundError:
270 if script_version is not None:
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/utils/file_utils.py in cached_path(url_or_filename, download_config, **download_kwargs)
306 user_agent=download_config.user_agent,
307 local_files_only=download_config.local_files_only,
--> 308 use_etag=download_config.use_etag,
309 )
310 elif os.path.exists(url_or_filename):
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/utils/file_utils.py in get_from_cache(url, cache_dir, force_download, proxies, etag_timeout, resume_download, user_agent, local_files_only, use_etag)
473 elif response is not None and response.status_code == 404:
474 raise FileNotFoundError("Couldn't find file at {}".format(url))
--> 475 raise ConnectionError("Couldn't reach {}".format(url))
476
477 # Try a second time
ConnectionError: Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py
```
And I try to connect to the site with requests:
```
import requests
requests.head("https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py")
```
Similarly Error occurs:
```
---------------------------------------------------------------------------
ConnectionRefusedError Traceback (most recent call last)
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connection.py in _new_conn(self)
159 conn = connection.create_connection(
--> 160 (self._dns_host, self.port), self.timeout, **extra_kw
161 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/util/connection.py in create_connection(address, timeout, source_address, socket_options)
83 if err is not None:
---> 84 raise err
85
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/util/connection.py in create_connection(address, timeout, source_address, socket_options)
73 sock.bind(source_address)
---> 74 sock.connect(sa)
75 return sock
ConnectionRefusedError: [Errno 111] Connection refused
During handling of the above exception, another exception occurred:
NewConnectionError Traceback (most recent call last)
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)
676 headers=headers,
--> 677 chunked=chunked,
678 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in _make_request(self, conn, method, url, timeout, chunked, **httplib_request_kw)
380 try:
--> 381 self._validate_conn(conn)
382 except (SocketTimeout, BaseSSLError) as e:
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in _validate_conn(self, conn)
975 if not getattr(conn, "sock", None): # AppEngine might not have `.sock`
--> 976 conn.connect()
977
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connection.py in connect(self)
307 # Add certificate verification
--> 308 conn = self._new_conn()
309 hostname = self.host
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connection.py in _new_conn(self)
171 raise NewConnectionError(
--> 172 self, "Failed to establish a new connection: %s" % e
173 )
NewConnectionError: <urllib3.connection.HTTPSConnection object at 0x7f3cceda5e48>: Failed to establish a new connection: [Errno 111] Connection refused
During handling of the above exception, another exception occurred:
MaxRetryError Traceback (most recent call last)
~/.conda/envs/py36/lib/python3.6/site-packages/requests/adapters.py in send(self, request, stream, timeout, verify, cert, proxies)
448 retries=self.max_retries,
--> 449 timeout=timeout
450 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)
724 retries = retries.increment(
--> 725 method, url, error=e, _pool=self, _stacktrace=sys.exc_info()[2]
726 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/util/retry.py in increment(self, method, url, response, error, _pool, _stacktrace)
438 if new_retry.is_exhausted():
--> 439 raise MaxRetryError(_pool, url, error or ResponseError(cause))
440
MaxRetryError: HTTPSConnectionPool(host='raw.githubusercontent.com', port=443): Max retries exceeded with url: /huggingface/datasets/1.1.2/datasets/csv/csv.py (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x7f3cceda5e48>: Failed to establish a new connection: [Errno 111] Connection refused',))
During handling of the above exception, another exception occurred:
ConnectionError Traceback (most recent call last)
<ipython-input-20-18cc3eb4a049> in <module>
1 import requests
2
----> 3 requests.head("https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py")
~/.conda/envs/py36/lib/python3.6/site-packages/requests/api.py in head(url, **kwargs)
102
103 kwargs.setdefault('allow_redirects', False)
--> 104 return request('head', url, **kwargs)
105
106
~/.conda/envs/py36/lib/python3.6/site-packages/requests/api.py in request(method, url, **kwargs)
59 # cases, and look like a memory leak in others.
60 with sessions.Session() as session:
---> 61 return session.request(method=method, url=url, **kwargs)
62
63
~/.conda/envs/py36/lib/python3.6/site-packages/requests/sessions.py in request(self, method, url, params, data, headers, cookies, files, auth, timeout, allow_redirects, proxies, hooks, stream, verify, cert, json)
528 }
529 send_kwargs.update(settings)
--> 530 resp = self.send(prep, **send_kwargs)
531
532 return resp
~/.conda/envs/py36/lib/python3.6/site-packages/requests/sessions.py in send(self, request, **kwargs)
641
642 # Send the request
--> 643 r = adapter.send(request, **kwargs)
644
645 # Total elapsed time of the request (approximately)
~/.conda/envs/py36/lib/python3.6/site-packages/requests/adapters.py in send(self, request, stream, timeout, verify, cert, proxies)
514 raise SSLError(e, request=request)
515
--> 516 raise ConnectionError(e, request=request)
517
518 except ClosedPoolError as e:
ConnectionError: HTTPSConnectionPool(host='raw.githubusercontent.com', port=443): Max retries exceeded with url: /huggingface/datasets/1.1.2/datasets/csv/csv.py (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x7f3cceda5e48>: Failed to establish a new connection: [Errno 111] Connection refused',))
``` | 103 | load_dataset for LOCAL CSV files report CONNECTION ERROR
## load_dataset for LOCAL CSV files report CONNECTION ERROR
- **Description:**
A local demo csv file:
```
import pandas as pd
import numpy as np
from datasets import load_dataset
import torch
import transformers
df = pd.DataFrame(np.arange(1200).reshape(300,4))
df.to_csv('test.csv', header=False, index=False)
print('datasets version: ', datasets.__version__)
print('pytorch version: ', torch.__version__)
print('transformers version: ', transformers.__version__)
# output:
datasets version: 1.1.2
pytorch version: 1.5.0
transformers version: 3.2.0
```
when I load data through `dataset`:
```
dataset = load_dataset('csv', data_files='./test.csv', delimiter=',', autogenerate_column_names=False)
```
Error infos:
```
ConnectionError Traceback (most recent call last)
<ipython-input-17-bbdadb9a0c78> in <module>
----> 1 dataset = load_dataset('csv', data_files='./test.csv', delimiter=',', autogenerate_column_names=False)
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/load.py in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, save_infos, script_version, **config_kwargs)
588 # Download/copy dataset processing script
589 module_path, hash = prepare_module(
--> 590 path, script_version=script_version, download_config=download_config, download_mode=download_mode, dataset=True
591 )
592
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/load.py in prepare_module(path, script_version, download_config, download_mode, dataset, force_local_path, **download_kwargs)
266 file_path = hf_github_url(path=path, name=name, dataset=dataset, version=script_version)
267 try:
--> 268 local_path = cached_path(file_path, download_config=download_config)
269 except FileNotFoundError:
270 if script_version is not None:
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/utils/file_utils.py in cached_path(url_or_filename, download_config, **download_kwargs)
306 user_agent=download_config.user_agent,
307 local_files_only=download_config.local_files_only,
--> 308 use_etag=download_config.use_etag,
309 )
310 elif os.path.exists(url_or_filename):
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/utils/file_utils.py in get_from_cache(url, cache_dir, force_download, proxies, etag_timeout, resume_download, user_agent, local_files_only, use_etag)
473 elif response is not None and response.status_code == 404:
474 raise FileNotFoundError("Couldn't find file at {}".format(url))
--> 475 raise ConnectionError("Couldn't reach {}".format(url))
476
477 # Try a second time
ConnectionError: Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py
```
And I try to connect to the site with requests:
```
import requests
requests.head("https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py")
```
Similarly Error occurs:
```
---------------------------------------------------------------------------
ConnectionRefusedError Traceback (most recent call last)
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connection.py in _new_conn(self)
159 conn = connection.create_connection(
--> 160 (self._dns_host, self.port), self.timeout, **extra_kw
161 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/util/connection.py in create_connection(address, timeout, source_address, socket_options)
83 if err is not None:
---> 84 raise err
85
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/util/connection.py in create_connection(address, timeout, source_address, socket_options)
73 sock.bind(source_address)
---> 74 sock.connect(sa)
75 return sock
ConnectionRefusedError: [Errno 111] Connection refused
During handling of the above exception, another exception occurred:
NewConnectionError Traceback (most recent call last)
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)
676 headers=headers,
--> 677 chunked=chunked,
678 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in _make_request(self, conn, method, url, timeout, chunked, **httplib_request_kw)
380 try:
--> 381 self._validate_conn(conn)
382 except (SocketTimeout, BaseSSLError) as e:
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in _validate_conn(self, conn)
975 if not getattr(conn, "sock", None): # AppEngine might not have `.sock`
--> 976 conn.connect()
977
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connection.py in connect(self)
307 # Add certificate verification
--> 308 conn = self._new_conn()
309 hostname = self.host
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connection.py in _new_conn(self)
171 raise NewConnectionError(
--> 172 self, "Failed to establish a new connection: %s" % e
173 )
NewConnectionError: <urllib3.connection.HTTPSConnection object at 0x7f3cceda5e48>: Failed to establish a new connection: [Errno 111] Connection refused
During handling of the above exception, another exception occurred:
MaxRetryError Traceback (most recent call last)
~/.conda/envs/py36/lib/python3.6/site-packages/requests/adapters.py in send(self, request, stream, timeout, verify, cert, proxies)
448 retries=self.max_retries,
--> 449 timeout=timeout
450 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)
724 retries = retries.increment(
--> 725 method, url, error=e, _pool=self, _stacktrace=sys.exc_info()[2]
726 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/util/retry.py in increment(self, method, url, response, error, _pool, _stacktrace)
438 if new_retry.is_exhausted():
--> 439 raise MaxRetryError(_pool, url, error or ResponseError(cause))
440
MaxRetryError: HTTPSConnectionPool(host='raw.githubusercontent.com', port=443): Max retries exceeded with url: /huggingface/datasets/1.1.2/datasets/csv/csv.py (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x7f3cceda5e48>: Failed to establish a new connection: [Errno 111] Connection refused',))
During handling of the above exception, another exception occurred:
ConnectionError Traceback (most recent call last)
<ipython-input-20-18cc3eb4a049> in <module>
1 import requests
2
----> 3 requests.head("https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py")
~/.conda/envs/py36/lib/python3.6/site-packages/requests/api.py in head(url, **kwargs)
102
103 kwargs.setdefault('allow_redirects', False)
--> 104 return request('head', url, **kwargs)
105
106
~/.conda/envs/py36/lib/python3.6/site-packages/requests/api.py in request(method, url, **kwargs)
59 # cases, and look like a memory leak in others.
60 with sessions.Session() as session:
---> 61 return session.request(method=method, url=url, **kwargs)
62
63
~/.conda/envs/py36/lib/python3.6/site-packages/requests/sessions.py in request(self, method, url, params, data, headers, cookies, files, auth, timeout, allow_redirects, proxies, hooks, stream, verify, cert, json)
528 }
529 send_kwargs.update(settings)
--> 530 resp = self.send(prep, **send_kwargs)
531
532 return resp
~/.conda/envs/py36/lib/python3.6/site-packages/requests/sessions.py in send(self, request, **kwargs)
641
642 # Send the request
--> 643 r = adapter.send(request, **kwargs)
644
645 # Total elapsed time of the request (approximately)
~/.conda/envs/py36/lib/python3.6/site-packages/requests/adapters.py in send(self, request, stream, timeout, verify, cert, proxies)
514 raise SSLError(e, request=request)
515
--> 516 raise ConnectionError(e, request=request)
517
518 except ClosedPoolError as e:
ConnectionError: HTTPSConnectionPool(host='raw.githubusercontent.com', port=443): Max retries exceeded with url: /huggingface/datasets/1.1.2/datasets/csv/csv.py (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x7f3cceda5e48>: Failed to establish a new connection: [Errno 111] Connection refused',))
```
> > Hi !
> > The url works on my side.
> > Is the url working in your navigator ?
> > Are you connected to internet ? Does your network block access to `raw.githubusercontent.com` ?
>
> I tried another server, it's working now. Thanks a lot.
>
> And I'm curious about why download things from "github" when I load dataset from local files ? Dose datasets work if my network crashed?
I download the scripts `https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py` and move it to the package dir `*/datasets/` solved the problem. Could you please put the file `datasets/datasets/csv/csv.py` to `datasets/src/datasets/`？
Thanks :D |
https://github.com/huggingface/datasets/issues/807 | load_dataset for LOCAL CSV files report CONNECTION ERROR | hello, how did you solve this problems?
> > > Hi !
> > > The url works on my side.
> > > Is the url working in your navigator ?
> > > Are you connected to internet ? Does your network block access to `raw.githubusercontent.com` ?
> >
> >
> > I tried another server, it's working now. Thanks a lot.
> > And I'm curious about why download things from "github" when I load dataset from local files ? Dose datasets work if my network crashed?
>
> I download the scripts `https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py` and move it to the package dir `*/datasets/` solved the problem. Could you please put the file `datasets/datasets/csv/csv.py` to `datasets/src/datasets/`？
>
> Thanks :D
hello, I tried this. but it still failed. how do you fix this error? | ## load_dataset for LOCAL CSV files report CONNECTION ERROR
- **Description:**
A local demo csv file:
```
import pandas as pd
import numpy as np
from datasets import load_dataset
import torch
import transformers
df = pd.DataFrame(np.arange(1200).reshape(300,4))
df.to_csv('test.csv', header=False, index=False)
print('datasets version: ', datasets.__version__)
print('pytorch version: ', torch.__version__)
print('transformers version: ', transformers.__version__)
# output:
datasets version: 1.1.2
pytorch version: 1.5.0
transformers version: 3.2.0
```
when I load data through `dataset`:
```
dataset = load_dataset('csv', data_files='./test.csv', delimiter=',', autogenerate_column_names=False)
```
Error infos:
```
ConnectionError Traceback (most recent call last)
<ipython-input-17-bbdadb9a0c78> in <module>
----> 1 dataset = load_dataset('csv', data_files='./test.csv', delimiter=',', autogenerate_column_names=False)
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/load.py in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, save_infos, script_version, **config_kwargs)
588 # Download/copy dataset processing script
589 module_path, hash = prepare_module(
--> 590 path, script_version=script_version, download_config=download_config, download_mode=download_mode, dataset=True
591 )
592
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/load.py in prepare_module(path, script_version, download_config, download_mode, dataset, force_local_path, **download_kwargs)
266 file_path = hf_github_url(path=path, name=name, dataset=dataset, version=script_version)
267 try:
--> 268 local_path = cached_path(file_path, download_config=download_config)
269 except FileNotFoundError:
270 if script_version is not None:
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/utils/file_utils.py in cached_path(url_or_filename, download_config, **download_kwargs)
306 user_agent=download_config.user_agent,
307 local_files_only=download_config.local_files_only,
--> 308 use_etag=download_config.use_etag,
309 )
310 elif os.path.exists(url_or_filename):
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/utils/file_utils.py in get_from_cache(url, cache_dir, force_download, proxies, etag_timeout, resume_download, user_agent, local_files_only, use_etag)
473 elif response is not None and response.status_code == 404:
474 raise FileNotFoundError("Couldn't find file at {}".format(url))
--> 475 raise ConnectionError("Couldn't reach {}".format(url))
476
477 # Try a second time
ConnectionError: Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py
```
And I try to connect to the site with requests:
```
import requests
requests.head("https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py")
```
Similarly Error occurs:
```
---------------------------------------------------------------------------
ConnectionRefusedError Traceback (most recent call last)
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connection.py in _new_conn(self)
159 conn = connection.create_connection(
--> 160 (self._dns_host, self.port), self.timeout, **extra_kw
161 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/util/connection.py in create_connection(address, timeout, source_address, socket_options)
83 if err is not None:
---> 84 raise err
85
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/util/connection.py in create_connection(address, timeout, source_address, socket_options)
73 sock.bind(source_address)
---> 74 sock.connect(sa)
75 return sock
ConnectionRefusedError: [Errno 111] Connection refused
During handling of the above exception, another exception occurred:
NewConnectionError Traceback (most recent call last)
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)
676 headers=headers,
--> 677 chunked=chunked,
678 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in _make_request(self, conn, method, url, timeout, chunked, **httplib_request_kw)
380 try:
--> 381 self._validate_conn(conn)
382 except (SocketTimeout, BaseSSLError) as e:
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in _validate_conn(self, conn)
975 if not getattr(conn, "sock", None): # AppEngine might not have `.sock`
--> 976 conn.connect()
977
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connection.py in connect(self)
307 # Add certificate verification
--> 308 conn = self._new_conn()
309 hostname = self.host
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connection.py in _new_conn(self)
171 raise NewConnectionError(
--> 172 self, "Failed to establish a new connection: %s" % e
173 )
NewConnectionError: <urllib3.connection.HTTPSConnection object at 0x7f3cceda5e48>: Failed to establish a new connection: [Errno 111] Connection refused
During handling of the above exception, another exception occurred:
MaxRetryError Traceback (most recent call last)
~/.conda/envs/py36/lib/python3.6/site-packages/requests/adapters.py in send(self, request, stream, timeout, verify, cert, proxies)
448 retries=self.max_retries,
--> 449 timeout=timeout
450 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)
724 retries = retries.increment(
--> 725 method, url, error=e, _pool=self, _stacktrace=sys.exc_info()[2]
726 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/util/retry.py in increment(self, method, url, response, error, _pool, _stacktrace)
438 if new_retry.is_exhausted():
--> 439 raise MaxRetryError(_pool, url, error or ResponseError(cause))
440
MaxRetryError: HTTPSConnectionPool(host='raw.githubusercontent.com', port=443): Max retries exceeded with url: /huggingface/datasets/1.1.2/datasets/csv/csv.py (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x7f3cceda5e48>: Failed to establish a new connection: [Errno 111] Connection refused',))
During handling of the above exception, another exception occurred:
ConnectionError Traceback (most recent call last)
<ipython-input-20-18cc3eb4a049> in <module>
1 import requests
2
----> 3 requests.head("https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py")
~/.conda/envs/py36/lib/python3.6/site-packages/requests/api.py in head(url, **kwargs)
102
103 kwargs.setdefault('allow_redirects', False)
--> 104 return request('head', url, **kwargs)
105
106
~/.conda/envs/py36/lib/python3.6/site-packages/requests/api.py in request(method, url, **kwargs)
59 # cases, and look like a memory leak in others.
60 with sessions.Session() as session:
---> 61 return session.request(method=method, url=url, **kwargs)
62
63
~/.conda/envs/py36/lib/python3.6/site-packages/requests/sessions.py in request(self, method, url, params, data, headers, cookies, files, auth, timeout, allow_redirects, proxies, hooks, stream, verify, cert, json)
528 }
529 send_kwargs.update(settings)
--> 530 resp = self.send(prep, **send_kwargs)
531
532 return resp
~/.conda/envs/py36/lib/python3.6/site-packages/requests/sessions.py in send(self, request, **kwargs)
641
642 # Send the request
--> 643 r = adapter.send(request, **kwargs)
644
645 # Total elapsed time of the request (approximately)
~/.conda/envs/py36/lib/python3.6/site-packages/requests/adapters.py in send(self, request, stream, timeout, verify, cert, proxies)
514 raise SSLError(e, request=request)
515
--> 516 raise ConnectionError(e, request=request)
517
518 except ClosedPoolError as e:
ConnectionError: HTTPSConnectionPool(host='raw.githubusercontent.com', port=443): Max retries exceeded with url: /huggingface/datasets/1.1.2/datasets/csv/csv.py (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x7f3cceda5e48>: Failed to establish a new connection: [Errno 111] Connection refused',))
``` | 136 | load_dataset for LOCAL CSV files report CONNECTION ERROR
## load_dataset for LOCAL CSV files report CONNECTION ERROR
- **Description:**
A local demo csv file:
```
import pandas as pd
import numpy as np
from datasets import load_dataset
import torch
import transformers
df = pd.DataFrame(np.arange(1200).reshape(300,4))
df.to_csv('test.csv', header=False, index=False)
print('datasets version: ', datasets.__version__)
print('pytorch version: ', torch.__version__)
print('transformers version: ', transformers.__version__)
# output:
datasets version: 1.1.2
pytorch version: 1.5.0
transformers version: 3.2.0
```
when I load data through `dataset`:
```
dataset = load_dataset('csv', data_files='./test.csv', delimiter=',', autogenerate_column_names=False)
```
Error infos:
```
ConnectionError Traceback (most recent call last)
<ipython-input-17-bbdadb9a0c78> in <module>
----> 1 dataset = load_dataset('csv', data_files='./test.csv', delimiter=',', autogenerate_column_names=False)
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/load.py in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, save_infos, script_version, **config_kwargs)
588 # Download/copy dataset processing script
589 module_path, hash = prepare_module(
--> 590 path, script_version=script_version, download_config=download_config, download_mode=download_mode, dataset=True
591 )
592
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/load.py in prepare_module(path, script_version, download_config, download_mode, dataset, force_local_path, **download_kwargs)
266 file_path = hf_github_url(path=path, name=name, dataset=dataset, version=script_version)
267 try:
--> 268 local_path = cached_path(file_path, download_config=download_config)
269 except FileNotFoundError:
270 if script_version is not None:
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/utils/file_utils.py in cached_path(url_or_filename, download_config, **download_kwargs)
306 user_agent=download_config.user_agent,
307 local_files_only=download_config.local_files_only,
--> 308 use_etag=download_config.use_etag,
309 )
310 elif os.path.exists(url_or_filename):
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/utils/file_utils.py in get_from_cache(url, cache_dir, force_download, proxies, etag_timeout, resume_download, user_agent, local_files_only, use_etag)
473 elif response is not None and response.status_code == 404:
474 raise FileNotFoundError("Couldn't find file at {}".format(url))
--> 475 raise ConnectionError("Couldn't reach {}".format(url))
476
477 # Try a second time
ConnectionError: Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py
```
And I try to connect to the site with requests:
```
import requests
requests.head("https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py")
```
Similarly Error occurs:
```
---------------------------------------------------------------------------
ConnectionRefusedError Traceback (most recent call last)
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connection.py in _new_conn(self)
159 conn = connection.create_connection(
--> 160 (self._dns_host, self.port), self.timeout, **extra_kw
161 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/util/connection.py in create_connection(address, timeout, source_address, socket_options)
83 if err is not None:
---> 84 raise err
85
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/util/connection.py in create_connection(address, timeout, source_address, socket_options)
73 sock.bind(source_address)
---> 74 sock.connect(sa)
75 return sock
ConnectionRefusedError: [Errno 111] Connection refused
During handling of the above exception, another exception occurred:
NewConnectionError Traceback (most recent call last)
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)
676 headers=headers,
--> 677 chunked=chunked,
678 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in _make_request(self, conn, method, url, timeout, chunked, **httplib_request_kw)
380 try:
--> 381 self._validate_conn(conn)
382 except (SocketTimeout, BaseSSLError) as e:
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in _validate_conn(self, conn)
975 if not getattr(conn, "sock", None): # AppEngine might not have `.sock`
--> 976 conn.connect()
977
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connection.py in connect(self)
307 # Add certificate verification
--> 308 conn = self._new_conn()
309 hostname = self.host
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connection.py in _new_conn(self)
171 raise NewConnectionError(
--> 172 self, "Failed to establish a new connection: %s" % e
173 )
NewConnectionError: <urllib3.connection.HTTPSConnection object at 0x7f3cceda5e48>: Failed to establish a new connection: [Errno 111] Connection refused
During handling of the above exception, another exception occurred:
MaxRetryError Traceback (most recent call last)
~/.conda/envs/py36/lib/python3.6/site-packages/requests/adapters.py in send(self, request, stream, timeout, verify, cert, proxies)
448 retries=self.max_retries,
--> 449 timeout=timeout
450 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)
724 retries = retries.increment(
--> 725 method, url, error=e, _pool=self, _stacktrace=sys.exc_info()[2]
726 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/util/retry.py in increment(self, method, url, response, error, _pool, _stacktrace)
438 if new_retry.is_exhausted():
--> 439 raise MaxRetryError(_pool, url, error or ResponseError(cause))
440
MaxRetryError: HTTPSConnectionPool(host='raw.githubusercontent.com', port=443): Max retries exceeded with url: /huggingface/datasets/1.1.2/datasets/csv/csv.py (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x7f3cceda5e48>: Failed to establish a new connection: [Errno 111] Connection refused',))
During handling of the above exception, another exception occurred:
ConnectionError Traceback (most recent call last)
<ipython-input-20-18cc3eb4a049> in <module>
1 import requests
2
----> 3 requests.head("https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py")
~/.conda/envs/py36/lib/python3.6/site-packages/requests/api.py in head(url, **kwargs)
102
103 kwargs.setdefault('allow_redirects', False)
--> 104 return request('head', url, **kwargs)
105
106
~/.conda/envs/py36/lib/python3.6/site-packages/requests/api.py in request(method, url, **kwargs)
59 # cases, and look like a memory leak in others.
60 with sessions.Session() as session:
---> 61 return session.request(method=method, url=url, **kwargs)
62
63
~/.conda/envs/py36/lib/python3.6/site-packages/requests/sessions.py in request(self, method, url, params, data, headers, cookies, files, auth, timeout, allow_redirects, proxies, hooks, stream, verify, cert, json)
528 }
529 send_kwargs.update(settings)
--> 530 resp = self.send(prep, **send_kwargs)
531
532 return resp
~/.conda/envs/py36/lib/python3.6/site-packages/requests/sessions.py in send(self, request, **kwargs)
641
642 # Send the request
--> 643 r = adapter.send(request, **kwargs)
644
645 # Total elapsed time of the request (approximately)
~/.conda/envs/py36/lib/python3.6/site-packages/requests/adapters.py in send(self, request, stream, timeout, verify, cert, proxies)
514 raise SSLError(e, request=request)
515
--> 516 raise ConnectionError(e, request=request)
517
518 except ClosedPoolError as e:
ConnectionError: HTTPSConnectionPool(host='raw.githubusercontent.com', port=443): Max retries exceeded with url: /huggingface/datasets/1.1.2/datasets/csv/csv.py (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x7f3cceda5e48>: Failed to establish a new connection: [Errno 111] Connection refused',))
```
hello, how did you solve this problems?
> > > Hi !
> > > The url works on my side.
> > > Is the url working in your navigator ?
> > > Are you connected to internet ? Does your network block access to `raw.githubusercontent.com` ?
> >
> >
> > I tried another server, it's working now. Thanks a lot.
> > And I'm curious about why download things from "github" when I load dataset from local files ? Dose datasets work if my network crashed?
>
> I download the scripts `https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py` and move it to the package dir `*/datasets/` solved the problem. Could you please put the file `datasets/datasets/csv/csv.py` to `datasets/src/datasets/`？
>
> Thanks :D
hello, I tried this. but it still failed. how do you fix this error? |
https://github.com/huggingface/datasets/issues/807 | load_dataset for LOCAL CSV files report CONNECTION ERROR | > hello, how did you solve this problems?
>
> > > > Hi !
> > > > The url works on my side.
> > > > Is the url working in your navigator ?
> > > > Are you connected to internet ? Does your network block access to `raw.githubusercontent.com` ?
> > >
> > >
> > > I tried another server, it's working now. Thanks a lot.
> > > And I'm curious about why download things from "github" when I load dataset from local files ? Dose datasets work if my network crashed?
> >
> >
> > I download the scripts `https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py` and move it to the package dir `*/datasets/` solved the problem. Could you please put the file `datasets/datasets/csv/csv.py` to `datasets/src/datasets/`？
> > Thanks :D
>
> hello, I tried this. but it still failed. how do you fix this error?
你把那个脚本下载到你本地安装目录下，然后 `load_dataset(csv_script_path, data_fiels)`
| ## load_dataset for LOCAL CSV files report CONNECTION ERROR
- **Description:**
A local demo csv file:
```
import pandas as pd
import numpy as np
from datasets import load_dataset
import torch
import transformers
df = pd.DataFrame(np.arange(1200).reshape(300,4))
df.to_csv('test.csv', header=False, index=False)
print('datasets version: ', datasets.__version__)
print('pytorch version: ', torch.__version__)
print('transformers version: ', transformers.__version__)
# output:
datasets version: 1.1.2
pytorch version: 1.5.0
transformers version: 3.2.0
```
when I load data through `dataset`:
```
dataset = load_dataset('csv', data_files='./test.csv', delimiter=',', autogenerate_column_names=False)
```
Error infos:
```
ConnectionError Traceback (most recent call last)
<ipython-input-17-bbdadb9a0c78> in <module>
----> 1 dataset = load_dataset('csv', data_files='./test.csv', delimiter=',', autogenerate_column_names=False)
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/load.py in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, save_infos, script_version, **config_kwargs)
588 # Download/copy dataset processing script
589 module_path, hash = prepare_module(
--> 590 path, script_version=script_version, download_config=download_config, download_mode=download_mode, dataset=True
591 )
592
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/load.py in prepare_module(path, script_version, download_config, download_mode, dataset, force_local_path, **download_kwargs)
266 file_path = hf_github_url(path=path, name=name, dataset=dataset, version=script_version)
267 try:
--> 268 local_path = cached_path(file_path, download_config=download_config)
269 except FileNotFoundError:
270 if script_version is not None:
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/utils/file_utils.py in cached_path(url_or_filename, download_config, **download_kwargs)
306 user_agent=download_config.user_agent,
307 local_files_only=download_config.local_files_only,
--> 308 use_etag=download_config.use_etag,
309 )
310 elif os.path.exists(url_or_filename):
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/utils/file_utils.py in get_from_cache(url, cache_dir, force_download, proxies, etag_timeout, resume_download, user_agent, local_files_only, use_etag)
473 elif response is not None and response.status_code == 404:
474 raise FileNotFoundError("Couldn't find file at {}".format(url))
--> 475 raise ConnectionError("Couldn't reach {}".format(url))
476
477 # Try a second time
ConnectionError: Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py
```
And I try to connect to the site with requests:
```
import requests
requests.head("https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py")
```
Similarly Error occurs:
```
---------------------------------------------------------------------------
ConnectionRefusedError Traceback (most recent call last)
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connection.py in _new_conn(self)
159 conn = connection.create_connection(
--> 160 (self._dns_host, self.port), self.timeout, **extra_kw
161 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/util/connection.py in create_connection(address, timeout, source_address, socket_options)
83 if err is not None:
---> 84 raise err
85
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/util/connection.py in create_connection(address, timeout, source_address, socket_options)
73 sock.bind(source_address)
---> 74 sock.connect(sa)
75 return sock
ConnectionRefusedError: [Errno 111] Connection refused
During handling of the above exception, another exception occurred:
NewConnectionError Traceback (most recent call last)
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)
676 headers=headers,
--> 677 chunked=chunked,
678 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in _make_request(self, conn, method, url, timeout, chunked, **httplib_request_kw)
380 try:
--> 381 self._validate_conn(conn)
382 except (SocketTimeout, BaseSSLError) as e:
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in _validate_conn(self, conn)
975 if not getattr(conn, "sock", None): # AppEngine might not have `.sock`
--> 976 conn.connect()
977
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connection.py in connect(self)
307 # Add certificate verification
--> 308 conn = self._new_conn()
309 hostname = self.host
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connection.py in _new_conn(self)
171 raise NewConnectionError(
--> 172 self, "Failed to establish a new connection: %s" % e
173 )
NewConnectionError: <urllib3.connection.HTTPSConnection object at 0x7f3cceda5e48>: Failed to establish a new connection: [Errno 111] Connection refused
During handling of the above exception, another exception occurred:
MaxRetryError Traceback (most recent call last)
~/.conda/envs/py36/lib/python3.6/site-packages/requests/adapters.py in send(self, request, stream, timeout, verify, cert, proxies)
448 retries=self.max_retries,
--> 449 timeout=timeout
450 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)
724 retries = retries.increment(
--> 725 method, url, error=e, _pool=self, _stacktrace=sys.exc_info()[2]
726 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/util/retry.py in increment(self, method, url, response, error, _pool, _stacktrace)
438 if new_retry.is_exhausted():
--> 439 raise MaxRetryError(_pool, url, error or ResponseError(cause))
440
MaxRetryError: HTTPSConnectionPool(host='raw.githubusercontent.com', port=443): Max retries exceeded with url: /huggingface/datasets/1.1.2/datasets/csv/csv.py (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x7f3cceda5e48>: Failed to establish a new connection: [Errno 111] Connection refused',))
During handling of the above exception, another exception occurred:
ConnectionError Traceback (most recent call last)
<ipython-input-20-18cc3eb4a049> in <module>
1 import requests
2
----> 3 requests.head("https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py")
~/.conda/envs/py36/lib/python3.6/site-packages/requests/api.py in head(url, **kwargs)
102
103 kwargs.setdefault('allow_redirects', False)
--> 104 return request('head', url, **kwargs)
105
106
~/.conda/envs/py36/lib/python3.6/site-packages/requests/api.py in request(method, url, **kwargs)
59 # cases, and look like a memory leak in others.
60 with sessions.Session() as session:
---> 61 return session.request(method=method, url=url, **kwargs)
62
63
~/.conda/envs/py36/lib/python3.6/site-packages/requests/sessions.py in request(self, method, url, params, data, headers, cookies, files, auth, timeout, allow_redirects, proxies, hooks, stream, verify, cert, json)
528 }
529 send_kwargs.update(settings)
--> 530 resp = self.send(prep, **send_kwargs)
531
532 return resp
~/.conda/envs/py36/lib/python3.6/site-packages/requests/sessions.py in send(self, request, **kwargs)
641
642 # Send the request
--> 643 r = adapter.send(request, **kwargs)
644
645 # Total elapsed time of the request (approximately)
~/.conda/envs/py36/lib/python3.6/site-packages/requests/adapters.py in send(self, request, stream, timeout, verify, cert, proxies)
514 raise SSLError(e, request=request)
515
--> 516 raise ConnectionError(e, request=request)
517
518 except ClosedPoolError as e:
ConnectionError: HTTPSConnectionPool(host='raw.githubusercontent.com', port=443): Max retries exceeded with url: /huggingface/datasets/1.1.2/datasets/csv/csv.py (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x7f3cceda5e48>: Failed to establish a new connection: [Errno 111] Connection refused',))
``` | 155 | load_dataset for LOCAL CSV files report CONNECTION ERROR
## load_dataset for LOCAL CSV files report CONNECTION ERROR
- **Description:**
A local demo csv file:
```
import pandas as pd
import numpy as np
from datasets import load_dataset
import torch
import transformers
df = pd.DataFrame(np.arange(1200).reshape(300,4))
df.to_csv('test.csv', header=False, index=False)
print('datasets version: ', datasets.__version__)
print('pytorch version: ', torch.__version__)
print('transformers version: ', transformers.__version__)
# output:
datasets version: 1.1.2
pytorch version: 1.5.0
transformers version: 3.2.0
```
when I load data through `dataset`:
```
dataset = load_dataset('csv', data_files='./test.csv', delimiter=',', autogenerate_column_names=False)
```
Error infos:
```
ConnectionError Traceback (most recent call last)
<ipython-input-17-bbdadb9a0c78> in <module>
----> 1 dataset = load_dataset('csv', data_files='./test.csv', delimiter=',', autogenerate_column_names=False)
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/load.py in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, save_infos, script_version, **config_kwargs)
588 # Download/copy dataset processing script
589 module_path, hash = prepare_module(
--> 590 path, script_version=script_version, download_config=download_config, download_mode=download_mode, dataset=True
591 )
592
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/load.py in prepare_module(path, script_version, download_config, download_mode, dataset, force_local_path, **download_kwargs)
266 file_path = hf_github_url(path=path, name=name, dataset=dataset, version=script_version)
267 try:
--> 268 local_path = cached_path(file_path, download_config=download_config)
269 except FileNotFoundError:
270 if script_version is not None:
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/utils/file_utils.py in cached_path(url_or_filename, download_config, **download_kwargs)
306 user_agent=download_config.user_agent,
307 local_files_only=download_config.local_files_only,
--> 308 use_etag=download_config.use_etag,
309 )
310 elif os.path.exists(url_or_filename):
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/utils/file_utils.py in get_from_cache(url, cache_dir, force_download, proxies, etag_timeout, resume_download, user_agent, local_files_only, use_etag)
473 elif response is not None and response.status_code == 404:
474 raise FileNotFoundError("Couldn't find file at {}".format(url))
--> 475 raise ConnectionError("Couldn't reach {}".format(url))
476
477 # Try a second time
ConnectionError: Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py
```
And I try to connect to the site with requests:
```
import requests
requests.head("https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py")
```
Similarly Error occurs:
```
---------------------------------------------------------------------------
ConnectionRefusedError Traceback (most recent call last)
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connection.py in _new_conn(self)
159 conn = connection.create_connection(
--> 160 (self._dns_host, self.port), self.timeout, **extra_kw
161 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/util/connection.py in create_connection(address, timeout, source_address, socket_options)
83 if err is not None:
---> 84 raise err
85
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/util/connection.py in create_connection(address, timeout, source_address, socket_options)
73 sock.bind(source_address)
---> 74 sock.connect(sa)
75 return sock
ConnectionRefusedError: [Errno 111] Connection refused
During handling of the above exception, another exception occurred:
NewConnectionError Traceback (most recent call last)
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)
676 headers=headers,
--> 677 chunked=chunked,
678 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in _make_request(self, conn, method, url, timeout, chunked, **httplib_request_kw)
380 try:
--> 381 self._validate_conn(conn)
382 except (SocketTimeout, BaseSSLError) as e:
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in _validate_conn(self, conn)
975 if not getattr(conn, "sock", None): # AppEngine might not have `.sock`
--> 976 conn.connect()
977
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connection.py in connect(self)
307 # Add certificate verification
--> 308 conn = self._new_conn()
309 hostname = self.host
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connection.py in _new_conn(self)
171 raise NewConnectionError(
--> 172 self, "Failed to establish a new connection: %s" % e
173 )
NewConnectionError: <urllib3.connection.HTTPSConnection object at 0x7f3cceda5e48>: Failed to establish a new connection: [Errno 111] Connection refused
During handling of the above exception, another exception occurred:
MaxRetryError Traceback (most recent call last)
~/.conda/envs/py36/lib/python3.6/site-packages/requests/adapters.py in send(self, request, stream, timeout, verify, cert, proxies)
448 retries=self.max_retries,
--> 449 timeout=timeout
450 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)
724 retries = retries.increment(
--> 725 method, url, error=e, _pool=self, _stacktrace=sys.exc_info()[2]
726 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/util/retry.py in increment(self, method, url, response, error, _pool, _stacktrace)
438 if new_retry.is_exhausted():
--> 439 raise MaxRetryError(_pool, url, error or ResponseError(cause))
440
MaxRetryError: HTTPSConnectionPool(host='raw.githubusercontent.com', port=443): Max retries exceeded with url: /huggingface/datasets/1.1.2/datasets/csv/csv.py (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x7f3cceda5e48>: Failed to establish a new connection: [Errno 111] Connection refused',))
During handling of the above exception, another exception occurred:
ConnectionError Traceback (most recent call last)
<ipython-input-20-18cc3eb4a049> in <module>
1 import requests
2
----> 3 requests.head("https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py")
~/.conda/envs/py36/lib/python3.6/site-packages/requests/api.py in head(url, **kwargs)
102
103 kwargs.setdefault('allow_redirects', False)
--> 104 return request('head', url, **kwargs)
105
106
~/.conda/envs/py36/lib/python3.6/site-packages/requests/api.py in request(method, url, **kwargs)
59 # cases, and look like a memory leak in others.
60 with sessions.Session() as session:
---> 61 return session.request(method=method, url=url, **kwargs)
62
63
~/.conda/envs/py36/lib/python3.6/site-packages/requests/sessions.py in request(self, method, url, params, data, headers, cookies, files, auth, timeout, allow_redirects, proxies, hooks, stream, verify, cert, json)
528 }
529 send_kwargs.update(settings)
--> 530 resp = self.send(prep, **send_kwargs)
531
532 return resp
~/.conda/envs/py36/lib/python3.6/site-packages/requests/sessions.py in send(self, request, **kwargs)
641
642 # Send the request
--> 643 r = adapter.send(request, **kwargs)
644
645 # Total elapsed time of the request (approximately)
~/.conda/envs/py36/lib/python3.6/site-packages/requests/adapters.py in send(self, request, stream, timeout, verify, cert, proxies)
514 raise SSLError(e, request=request)
515
--> 516 raise ConnectionError(e, request=request)
517
518 except ClosedPoolError as e:
ConnectionError: HTTPSConnectionPool(host='raw.githubusercontent.com', port=443): Max retries exceeded with url: /huggingface/datasets/1.1.2/datasets/csv/csv.py (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x7f3cceda5e48>: Failed to establish a new connection: [Errno 111] Connection refused',))
```
> hello, how did you solve this problems?
>
> > > > Hi !
> > > > The url works on my side.
> > > > Is the url working in your navigator ?
> > > > Are you connected to internet ? Does your network block access to `raw.githubusercontent.com` ?
> > >
> > >
> > > I tried another server, it's working now. Thanks a lot.
> > > And I'm curious about why download things from "github" when I load dataset from local files ? Dose datasets work if my network crashed?
> >
> >
> > I download the scripts `https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py` and move it to the package dir `*/datasets/` solved the problem. Could you please put the file `datasets/datasets/csv/csv.py` to `datasets/src/datasets/`？
> > Thanks :D
>
> hello, I tried this. but it still failed. how do you fix this error?
你把那个脚本下载到你本地安装目录下，然后 `load_dataset(csv_script_path, data_fiels)`
|
https://github.com/huggingface/datasets/issues/807 | load_dataset for LOCAL CSV files report CONNECTION ERROR | > > hello, how did you solve this problems?
> > > > > Hi !
> > > > > The url works on my side.
> > > > > Is the url working in your navigator ?
> > > > > Are you connected to internet ? Does your network block access to `raw.githubusercontent.com` ?
> > > >
> > > >
> > > > I tried another server, it's working now. Thanks a lot.
> > > > And I'm curious about why download things from "github" when I load dataset from local files ? Dose datasets work if my network crashed?
> > >
> > >
> > > I download the scripts `https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py` and move it to the package dir `*/datasets/` solved the problem. Could you please put the file `datasets/datasets/csv/csv.py` to `datasets/src/datasets/`？
> > > Thanks :D
> >
> >
> > hello, I tried this. but it still failed. how do you fix this error?
>
> 你把那个脚本下载到你本地安装目录下，然后 `load_dataset(csv_script_path, data_fiels)`
好的好的！解决了，感谢感谢！！！ | ## load_dataset for LOCAL CSV files report CONNECTION ERROR
- **Description:**
A local demo csv file:
```
import pandas as pd
import numpy as np
from datasets import load_dataset
import torch
import transformers
df = pd.DataFrame(np.arange(1200).reshape(300,4))
df.to_csv('test.csv', header=False, index=False)
print('datasets version: ', datasets.__version__)
print('pytorch version: ', torch.__version__)
print('transformers version: ', transformers.__version__)
# output:
datasets version: 1.1.2
pytorch version: 1.5.0
transformers version: 3.2.0
```
when I load data through `dataset`:
```
dataset = load_dataset('csv', data_files='./test.csv', delimiter=',', autogenerate_column_names=False)
```
Error infos:
```
ConnectionError Traceback (most recent call last)
<ipython-input-17-bbdadb9a0c78> in <module>
----> 1 dataset = load_dataset('csv', data_files='./test.csv', delimiter=',', autogenerate_column_names=False)
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/load.py in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, save_infos, script_version, **config_kwargs)
588 # Download/copy dataset processing script
589 module_path, hash = prepare_module(
--> 590 path, script_version=script_version, download_config=download_config, download_mode=download_mode, dataset=True
591 )
592
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/load.py in prepare_module(path, script_version, download_config, download_mode, dataset, force_local_path, **download_kwargs)
266 file_path = hf_github_url(path=path, name=name, dataset=dataset, version=script_version)
267 try:
--> 268 local_path = cached_path(file_path, download_config=download_config)
269 except FileNotFoundError:
270 if script_version is not None:
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/utils/file_utils.py in cached_path(url_or_filename, download_config, **download_kwargs)
306 user_agent=download_config.user_agent,
307 local_files_only=download_config.local_files_only,
--> 308 use_etag=download_config.use_etag,
309 )
310 elif os.path.exists(url_or_filename):
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/utils/file_utils.py in get_from_cache(url, cache_dir, force_download, proxies, etag_timeout, resume_download, user_agent, local_files_only, use_etag)
473 elif response is not None and response.status_code == 404:
474 raise FileNotFoundError("Couldn't find file at {}".format(url))
--> 475 raise ConnectionError("Couldn't reach {}".format(url))
476
477 # Try a second time
ConnectionError: Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py
```
And I try to connect to the site with requests:
```
import requests
requests.head("https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py")
```
Similarly Error occurs:
```
---------------------------------------------------------------------------
ConnectionRefusedError Traceback (most recent call last)
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connection.py in _new_conn(self)
159 conn = connection.create_connection(
--> 160 (self._dns_host, self.port), self.timeout, **extra_kw
161 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/util/connection.py in create_connection(address, timeout, source_address, socket_options)
83 if err is not None:
---> 84 raise err
85
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/util/connection.py in create_connection(address, timeout, source_address, socket_options)
73 sock.bind(source_address)
---> 74 sock.connect(sa)
75 return sock
ConnectionRefusedError: [Errno 111] Connection refused
During handling of the above exception, another exception occurred:
NewConnectionError Traceback (most recent call last)
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)
676 headers=headers,
--> 677 chunked=chunked,
678 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in _make_request(self, conn, method, url, timeout, chunked, **httplib_request_kw)
380 try:
--> 381 self._validate_conn(conn)
382 except (SocketTimeout, BaseSSLError) as e:
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in _validate_conn(self, conn)
975 if not getattr(conn, "sock", None): # AppEngine might not have `.sock`
--> 976 conn.connect()
977
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connection.py in connect(self)
307 # Add certificate verification
--> 308 conn = self._new_conn()
309 hostname = self.host
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connection.py in _new_conn(self)
171 raise NewConnectionError(
--> 172 self, "Failed to establish a new connection: %s" % e
173 )
NewConnectionError: <urllib3.connection.HTTPSConnection object at 0x7f3cceda5e48>: Failed to establish a new connection: [Errno 111] Connection refused
During handling of the above exception, another exception occurred:
MaxRetryError Traceback (most recent call last)
~/.conda/envs/py36/lib/python3.6/site-packages/requests/adapters.py in send(self, request, stream, timeout, verify, cert, proxies)
448 retries=self.max_retries,
--> 449 timeout=timeout
450 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)
724 retries = retries.increment(
--> 725 method, url, error=e, _pool=self, _stacktrace=sys.exc_info()[2]
726 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/util/retry.py in increment(self, method, url, response, error, _pool, _stacktrace)
438 if new_retry.is_exhausted():
--> 439 raise MaxRetryError(_pool, url, error or ResponseError(cause))
440
MaxRetryError: HTTPSConnectionPool(host='raw.githubusercontent.com', port=443): Max retries exceeded with url: /huggingface/datasets/1.1.2/datasets/csv/csv.py (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x7f3cceda5e48>: Failed to establish a new connection: [Errno 111] Connection refused',))
During handling of the above exception, another exception occurred:
ConnectionError Traceback (most recent call last)
<ipython-input-20-18cc3eb4a049> in <module>
1 import requests
2
----> 3 requests.head("https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py")
~/.conda/envs/py36/lib/python3.6/site-packages/requests/api.py in head(url, **kwargs)
102
103 kwargs.setdefault('allow_redirects', False)
--> 104 return request('head', url, **kwargs)
105
106
~/.conda/envs/py36/lib/python3.6/site-packages/requests/api.py in request(method, url, **kwargs)
59 # cases, and look like a memory leak in others.
60 with sessions.Session() as session:
---> 61 return session.request(method=method, url=url, **kwargs)
62
63
~/.conda/envs/py36/lib/python3.6/site-packages/requests/sessions.py in request(self, method, url, params, data, headers, cookies, files, auth, timeout, allow_redirects, proxies, hooks, stream, verify, cert, json)
528 }
529 send_kwargs.update(settings)
--> 530 resp = self.send(prep, **send_kwargs)
531
532 return resp
~/.conda/envs/py36/lib/python3.6/site-packages/requests/sessions.py in send(self, request, **kwargs)
641
642 # Send the request
--> 643 r = adapter.send(request, **kwargs)
644
645 # Total elapsed time of the request (approximately)
~/.conda/envs/py36/lib/python3.6/site-packages/requests/adapters.py in send(self, request, stream, timeout, verify, cert, proxies)
514 raise SSLError(e, request=request)
515
--> 516 raise ConnectionError(e, request=request)
517
518 except ClosedPoolError as e:
ConnectionError: HTTPSConnectionPool(host='raw.githubusercontent.com', port=443): Max retries exceeded with url: /huggingface/datasets/1.1.2/datasets/csv/csv.py (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x7f3cceda5e48>: Failed to establish a new connection: [Errno 111] Connection refused',))
``` | 174 | load_dataset for LOCAL CSV files report CONNECTION ERROR
## load_dataset for LOCAL CSV files report CONNECTION ERROR
- **Description:**
A local demo csv file:
```
import pandas as pd
import numpy as np
from datasets import load_dataset
import torch
import transformers
df = pd.DataFrame(np.arange(1200).reshape(300,4))
df.to_csv('test.csv', header=False, index=False)
print('datasets version: ', datasets.__version__)
print('pytorch version: ', torch.__version__)
print('transformers version: ', transformers.__version__)
# output:
datasets version: 1.1.2
pytorch version: 1.5.0
transformers version: 3.2.0
```
when I load data through `dataset`:
```
dataset = load_dataset('csv', data_files='./test.csv', delimiter=',', autogenerate_column_names=False)
```
Error infos:
```
ConnectionError Traceback (most recent call last)
<ipython-input-17-bbdadb9a0c78> in <module>
----> 1 dataset = load_dataset('csv', data_files='./test.csv', delimiter=',', autogenerate_column_names=False)
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/load.py in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, save_infos, script_version, **config_kwargs)
588 # Download/copy dataset processing script
589 module_path, hash = prepare_module(
--> 590 path, script_version=script_version, download_config=download_config, download_mode=download_mode, dataset=True
591 )
592
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/load.py in prepare_module(path, script_version, download_config, download_mode, dataset, force_local_path, **download_kwargs)
266 file_path = hf_github_url(path=path, name=name, dataset=dataset, version=script_version)
267 try:
--> 268 local_path = cached_path(file_path, download_config=download_config)
269 except FileNotFoundError:
270 if script_version is not None:
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/utils/file_utils.py in cached_path(url_or_filename, download_config, **download_kwargs)
306 user_agent=download_config.user_agent,
307 local_files_only=download_config.local_files_only,
--> 308 use_etag=download_config.use_etag,
309 )
310 elif os.path.exists(url_or_filename):
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/utils/file_utils.py in get_from_cache(url, cache_dir, force_download, proxies, etag_timeout, resume_download, user_agent, local_files_only, use_etag)
473 elif response is not None and response.status_code == 404:
474 raise FileNotFoundError("Couldn't find file at {}".format(url))
--> 475 raise ConnectionError("Couldn't reach {}".format(url))
476
477 # Try a second time
ConnectionError: Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py
```
And I try to connect to the site with requests:
```
import requests
requests.head("https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py")
```
Similarly Error occurs:
```
---------------------------------------------------------------------------
ConnectionRefusedError Traceback (most recent call last)
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connection.py in _new_conn(self)
159 conn = connection.create_connection(
--> 160 (self._dns_host, self.port), self.timeout, **extra_kw
161 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/util/connection.py in create_connection(address, timeout, source_address, socket_options)
83 if err is not None:
---> 84 raise err
85
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/util/connection.py in create_connection(address, timeout, source_address, socket_options)
73 sock.bind(source_address)
---> 74 sock.connect(sa)
75 return sock
ConnectionRefusedError: [Errno 111] Connection refused
During handling of the above exception, another exception occurred:
NewConnectionError Traceback (most recent call last)
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)
676 headers=headers,
--> 677 chunked=chunked,
678 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in _make_request(self, conn, method, url, timeout, chunked, **httplib_request_kw)
380 try:
--> 381 self._validate_conn(conn)
382 except (SocketTimeout, BaseSSLError) as e:
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in _validate_conn(self, conn)
975 if not getattr(conn, "sock", None): # AppEngine might not have `.sock`
--> 976 conn.connect()
977
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connection.py in connect(self)
307 # Add certificate verification
--> 308 conn = self._new_conn()
309 hostname = self.host
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connection.py in _new_conn(self)
171 raise NewConnectionError(
--> 172 self, "Failed to establish a new connection: %s" % e
173 )
NewConnectionError: <urllib3.connection.HTTPSConnection object at 0x7f3cceda5e48>: Failed to establish a new connection: [Errno 111] Connection refused
During handling of the above exception, another exception occurred:
MaxRetryError Traceback (most recent call last)
~/.conda/envs/py36/lib/python3.6/site-packages/requests/adapters.py in send(self, request, stream, timeout, verify, cert, proxies)
448 retries=self.max_retries,
--> 449 timeout=timeout
450 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)
724 retries = retries.increment(
--> 725 method, url, error=e, _pool=self, _stacktrace=sys.exc_info()[2]
726 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/util/retry.py in increment(self, method, url, response, error, _pool, _stacktrace)
438 if new_retry.is_exhausted():
--> 439 raise MaxRetryError(_pool, url, error or ResponseError(cause))
440
MaxRetryError: HTTPSConnectionPool(host='raw.githubusercontent.com', port=443): Max retries exceeded with url: /huggingface/datasets/1.1.2/datasets/csv/csv.py (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x7f3cceda5e48>: Failed to establish a new connection: [Errno 111] Connection refused',))
During handling of the above exception, another exception occurred:
ConnectionError Traceback (most recent call last)
<ipython-input-20-18cc3eb4a049> in <module>
1 import requests
2
----> 3 requests.head("https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py")
~/.conda/envs/py36/lib/python3.6/site-packages/requests/api.py in head(url, **kwargs)
102
103 kwargs.setdefault('allow_redirects', False)
--> 104 return request('head', url, **kwargs)
105
106
~/.conda/envs/py36/lib/python3.6/site-packages/requests/api.py in request(method, url, **kwargs)
59 # cases, and look like a memory leak in others.
60 with sessions.Session() as session:
---> 61 return session.request(method=method, url=url, **kwargs)
62
63
~/.conda/envs/py36/lib/python3.6/site-packages/requests/sessions.py in request(self, method, url, params, data, headers, cookies, files, auth, timeout, allow_redirects, proxies, hooks, stream, verify, cert, json)
528 }
529 send_kwargs.update(settings)
--> 530 resp = self.send(prep, **send_kwargs)
531
532 return resp
~/.conda/envs/py36/lib/python3.6/site-packages/requests/sessions.py in send(self, request, **kwargs)
641
642 # Send the request
--> 643 r = adapter.send(request, **kwargs)
644
645 # Total elapsed time of the request (approximately)
~/.conda/envs/py36/lib/python3.6/site-packages/requests/adapters.py in send(self, request, stream, timeout, verify, cert, proxies)
514 raise SSLError(e, request=request)
515
--> 516 raise ConnectionError(e, request=request)
517
518 except ClosedPoolError as e:
ConnectionError: HTTPSConnectionPool(host='raw.githubusercontent.com', port=443): Max retries exceeded with url: /huggingface/datasets/1.1.2/datasets/csv/csv.py (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x7f3cceda5e48>: Failed to establish a new connection: [Errno 111] Connection refused',))
```
> > hello, how did you solve this problems?
> > > > > Hi !
> > > > > The url works on my side.
> > > > > Is the url working in your navigator ?
> > > > > Are you connected to internet ? Does your network block access to `raw.githubusercontent.com` ?
> > > >
> > > >
> > > > I tried another server, it's working now. Thanks a lot.
> > > > And I'm curious about why download things from "github" when I load dataset from local files ? Dose datasets work if my network crashed?
> > >
> > >
> > > I download the scripts `https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py` and move it to the package dir `*/datasets/` solved the problem. Could you please put the file `datasets/datasets/csv/csv.py` to `datasets/src/datasets/`？
> > > Thanks :D
> >
> >
> > hello, I tried this. but it still failed. how do you fix this error?
>
> 你把那个脚本下载到你本地安装目录下，然后 `load_dataset(csv_script_path, data_fiels)`
好的好的！解决了，感谢感谢！！！ |
https://github.com/huggingface/datasets/issues/807 | load_dataset for LOCAL CSV files report CONNECTION ERROR | >
>
> > hello, how did you solve this problems?
> > > > > Hi !
> > > > > The url works on my side.
> > > > > Is the url working in your navigator ?
> > > > > Are you connected to internet ? Does your network block access to `raw.githubusercontent.com` ?
> > > >
> > > >
> > > > I tried another server, it's working now. Thanks a lot.
> > > > And I'm curious about why download things from "github" when I load dataset from local files ? Dose datasets work if my network crashed?
> > >
> > >
> > > I download the scripts `https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py` and move it to the package dir `*/datasets/` solved the problem. Could you please put the file `datasets/datasets/csv/csv.py` to `datasets/src/datasets/`？
> > > Thanks :D
> >
> >
> > hello, I tried this. but it still failed. how do you fix this error?
>
> 你把那个脚本下载到你本地安装目录下，然后 `load_dataset(csv_script_path, data_fiels)`
我照着做了，然后报错。
ValueError: unable to parse C:/Software/Anaconda/envs/ptk_gpu2/Lib/site-packages/datasets\dataset_infos.json as a URL or as a local path
`---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-5-fd2106a3f053> in <module>
----> 1 dataset = load_dataset('C:/Software/Anaconda/envs/ptk_gpu2/Lib/site-packages/datasets/csv.py', data_files='./test.csv', delimiter=',', autogenerate_column_names=False)
C:\Software\Anaconda\envs\ptk_gpu2\lib\site-packages\datasets\load.py in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, save_infos, script_version, **config_kwargs)
588 # Download/copy dataset processing script
589 module_path, hash = prepare_module(
--> 590 path, script_version=script_version, download_config=download_config, download_mode=download_mode, dataset=True
591 )
592
C:\Software\Anaconda\envs\ptk_gpu2\lib\site-packages\datasets\load.py in prepare_module(path, script_version, download_config, download_mode, dataset, force_local_path, **download_kwargs)
296 local_dataset_infos_path = cached_path(
297 dataset_infos,
--> 298 download_config=download_config,
299 )
300 except (FileNotFoundError, ConnectionError):
C:\Software\Anaconda\envs\ptk_gpu2\lib\site-packages\datasets\utils\file_utils.py in cached_path(url_or_filename, download_config, **download_kwargs)
316 else:
317 # Something unknown
--> 318 raise ValueError("unable to parse {} as a URL or as a local path".format(url_or_filename))
319
320 if download_config.extract_compressed_file and output_path is not None:
ValueError: unable to parse C:/Software/Anaconda/envs/ptk_gpu2/Lib/site-packages/datasets\dataset_infos.json as a URL or as a local path
` | ## load_dataset for LOCAL CSV files report CONNECTION ERROR
- **Description:**
A local demo csv file:
```
import pandas as pd
import numpy as np
from datasets import load_dataset
import torch
import transformers
df = pd.DataFrame(np.arange(1200).reshape(300,4))
df.to_csv('test.csv', header=False, index=False)
print('datasets version: ', datasets.__version__)
print('pytorch version: ', torch.__version__)
print('transformers version: ', transformers.__version__)
# output:
datasets version: 1.1.2
pytorch version: 1.5.0
transformers version: 3.2.0
```
when I load data through `dataset`:
```
dataset = load_dataset('csv', data_files='./test.csv', delimiter=',', autogenerate_column_names=False)
```
Error infos:
```
ConnectionError Traceback (most recent call last)
<ipython-input-17-bbdadb9a0c78> in <module>
----> 1 dataset = load_dataset('csv', data_files='./test.csv', delimiter=',', autogenerate_column_names=False)
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/load.py in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, save_infos, script_version, **config_kwargs)
588 # Download/copy dataset processing script
589 module_path, hash = prepare_module(
--> 590 path, script_version=script_version, download_config=download_config, download_mode=download_mode, dataset=True
591 )
592
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/load.py in prepare_module(path, script_version, download_config, download_mode, dataset, force_local_path, **download_kwargs)
266 file_path = hf_github_url(path=path, name=name, dataset=dataset, version=script_version)
267 try:
--> 268 local_path = cached_path(file_path, download_config=download_config)
269 except FileNotFoundError:
270 if script_version is not None:
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/utils/file_utils.py in cached_path(url_or_filename, download_config, **download_kwargs)
306 user_agent=download_config.user_agent,
307 local_files_only=download_config.local_files_only,
--> 308 use_etag=download_config.use_etag,
309 )
310 elif os.path.exists(url_or_filename):
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/utils/file_utils.py in get_from_cache(url, cache_dir, force_download, proxies, etag_timeout, resume_download, user_agent, local_files_only, use_etag)
473 elif response is not None and response.status_code == 404:
474 raise FileNotFoundError("Couldn't find file at {}".format(url))
--> 475 raise ConnectionError("Couldn't reach {}".format(url))
476
477 # Try a second time
ConnectionError: Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py
```
And I try to connect to the site with requests:
```
import requests
requests.head("https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py")
```
Similarly Error occurs:
```
---------------------------------------------------------------------------
ConnectionRefusedError Traceback (most recent call last)
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connection.py in _new_conn(self)
159 conn = connection.create_connection(
--> 160 (self._dns_host, self.port), self.timeout, **extra_kw
161 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/util/connection.py in create_connection(address, timeout, source_address, socket_options)
83 if err is not None:
---> 84 raise err
85
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/util/connection.py in create_connection(address, timeout, source_address, socket_options)
73 sock.bind(source_address)
---> 74 sock.connect(sa)
75 return sock
ConnectionRefusedError: [Errno 111] Connection refused
During handling of the above exception, another exception occurred:
NewConnectionError Traceback (most recent call last)
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)
676 headers=headers,
--> 677 chunked=chunked,
678 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in _make_request(self, conn, method, url, timeout, chunked, **httplib_request_kw)
380 try:
--> 381 self._validate_conn(conn)
382 except (SocketTimeout, BaseSSLError) as e:
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in _validate_conn(self, conn)
975 if not getattr(conn, "sock", None): # AppEngine might not have `.sock`
--> 976 conn.connect()
977
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connection.py in connect(self)
307 # Add certificate verification
--> 308 conn = self._new_conn()
309 hostname = self.host
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connection.py in _new_conn(self)
171 raise NewConnectionError(
--> 172 self, "Failed to establish a new connection: %s" % e
173 )
NewConnectionError: <urllib3.connection.HTTPSConnection object at 0x7f3cceda5e48>: Failed to establish a new connection: [Errno 111] Connection refused
During handling of the above exception, another exception occurred:
MaxRetryError Traceback (most recent call last)
~/.conda/envs/py36/lib/python3.6/site-packages/requests/adapters.py in send(self, request, stream, timeout, verify, cert, proxies)
448 retries=self.max_retries,
--> 449 timeout=timeout
450 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)
724 retries = retries.increment(
--> 725 method, url, error=e, _pool=self, _stacktrace=sys.exc_info()[2]
726 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/util/retry.py in increment(self, method, url, response, error, _pool, _stacktrace)
438 if new_retry.is_exhausted():
--> 439 raise MaxRetryError(_pool, url, error or ResponseError(cause))
440
MaxRetryError: HTTPSConnectionPool(host='raw.githubusercontent.com', port=443): Max retries exceeded with url: /huggingface/datasets/1.1.2/datasets/csv/csv.py (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x7f3cceda5e48>: Failed to establish a new connection: [Errno 111] Connection refused',))
During handling of the above exception, another exception occurred:
ConnectionError Traceback (most recent call last)
<ipython-input-20-18cc3eb4a049> in <module>
1 import requests
2
----> 3 requests.head("https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py")
~/.conda/envs/py36/lib/python3.6/site-packages/requests/api.py in head(url, **kwargs)
102
103 kwargs.setdefault('allow_redirects', False)
--> 104 return request('head', url, **kwargs)
105
106
~/.conda/envs/py36/lib/python3.6/site-packages/requests/api.py in request(method, url, **kwargs)
59 # cases, and look like a memory leak in others.
60 with sessions.Session() as session:
---> 61 return session.request(method=method, url=url, **kwargs)
62
63
~/.conda/envs/py36/lib/python3.6/site-packages/requests/sessions.py in request(self, method, url, params, data, headers, cookies, files, auth, timeout, allow_redirects, proxies, hooks, stream, verify, cert, json)
528 }
529 send_kwargs.update(settings)
--> 530 resp = self.send(prep, **send_kwargs)
531
532 return resp
~/.conda/envs/py36/lib/python3.6/site-packages/requests/sessions.py in send(self, request, **kwargs)
641
642 # Send the request
--> 643 r = adapter.send(request, **kwargs)
644
645 # Total elapsed time of the request (approximately)
~/.conda/envs/py36/lib/python3.6/site-packages/requests/adapters.py in send(self, request, stream, timeout, verify, cert, proxies)
514 raise SSLError(e, request=request)
515
--> 516 raise ConnectionError(e, request=request)
517
518 except ClosedPoolError as e:
ConnectionError: HTTPSConnectionPool(host='raw.githubusercontent.com', port=443): Max retries exceeded with url: /huggingface/datasets/1.1.2/datasets/csv/csv.py (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x7f3cceda5e48>: Failed to establish a new connection: [Errno 111] Connection refused',))
``` | 316 | load_dataset for LOCAL CSV files report CONNECTION ERROR
## load_dataset for LOCAL CSV files report CONNECTION ERROR
- **Description:**
A local demo csv file:
```
import pandas as pd
import numpy as np
from datasets import load_dataset
import torch
import transformers
df = pd.DataFrame(np.arange(1200).reshape(300,4))
df.to_csv('test.csv', header=False, index=False)
print('datasets version: ', datasets.__version__)
print('pytorch version: ', torch.__version__)
print('transformers version: ', transformers.__version__)
# output:
datasets version: 1.1.2
pytorch version: 1.5.0
transformers version: 3.2.0
```
when I load data through `dataset`:
```
dataset = load_dataset('csv', data_files='./test.csv', delimiter=',', autogenerate_column_names=False)
```
Error infos:
```
ConnectionError Traceback (most recent call last)
<ipython-input-17-bbdadb9a0c78> in <module>
----> 1 dataset = load_dataset('csv', data_files='./test.csv', delimiter=',', autogenerate_column_names=False)
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/load.py in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, save_infos, script_version, **config_kwargs)
588 # Download/copy dataset processing script
589 module_path, hash = prepare_module(
--> 590 path, script_version=script_version, download_config=download_config, download_mode=download_mode, dataset=True
591 )
592
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/load.py in prepare_module(path, script_version, download_config, download_mode, dataset, force_local_path, **download_kwargs)
266 file_path = hf_github_url(path=path, name=name, dataset=dataset, version=script_version)
267 try:
--> 268 local_path = cached_path(file_path, download_config=download_config)
269 except FileNotFoundError:
270 if script_version is not None:
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/utils/file_utils.py in cached_path(url_or_filename, download_config, **download_kwargs)
306 user_agent=download_config.user_agent,
307 local_files_only=download_config.local_files_only,
--> 308 use_etag=download_config.use_etag,
309 )
310 elif os.path.exists(url_or_filename):
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/utils/file_utils.py in get_from_cache(url, cache_dir, force_download, proxies, etag_timeout, resume_download, user_agent, local_files_only, use_etag)
473 elif response is not None and response.status_code == 404:
474 raise FileNotFoundError("Couldn't find file at {}".format(url))
--> 475 raise ConnectionError("Couldn't reach {}".format(url))
476
477 # Try a second time
ConnectionError: Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py
```
And I try to connect to the site with requests:
```
import requests
requests.head("https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py")
```
Similarly Error occurs:
```
---------------------------------------------------------------------------
ConnectionRefusedError Traceback (most recent call last)
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connection.py in _new_conn(self)
159 conn = connection.create_connection(
--> 160 (self._dns_host, self.port), self.timeout, **extra_kw
161 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/util/connection.py in create_connection(address, timeout, source_address, socket_options)
83 if err is not None:
---> 84 raise err
85
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/util/connection.py in create_connection(address, timeout, source_address, socket_options)
73 sock.bind(source_address)
---> 74 sock.connect(sa)
75 return sock
ConnectionRefusedError: [Errno 111] Connection refused
During handling of the above exception, another exception occurred:
NewConnectionError Traceback (most recent call last)
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)
676 headers=headers,
--> 677 chunked=chunked,
678 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in _make_request(self, conn, method, url, timeout, chunked, **httplib_request_kw)
380 try:
--> 381 self._validate_conn(conn)
382 except (SocketTimeout, BaseSSLError) as e:
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in _validate_conn(self, conn)
975 if not getattr(conn, "sock", None): # AppEngine might not have `.sock`
--> 976 conn.connect()
977
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connection.py in connect(self)
307 # Add certificate verification
--> 308 conn = self._new_conn()
309 hostname = self.host
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connection.py in _new_conn(self)
171 raise NewConnectionError(
--> 172 self, "Failed to establish a new connection: %s" % e
173 )
NewConnectionError: <urllib3.connection.HTTPSConnection object at 0x7f3cceda5e48>: Failed to establish a new connection: [Errno 111] Connection refused
During handling of the above exception, another exception occurred:
MaxRetryError Traceback (most recent call last)
~/.conda/envs/py36/lib/python3.6/site-packages/requests/adapters.py in send(self, request, stream, timeout, verify, cert, proxies)
448 retries=self.max_retries,
--> 449 timeout=timeout
450 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)
724 retries = retries.increment(
--> 725 method, url, error=e, _pool=self, _stacktrace=sys.exc_info()[2]
726 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/util/retry.py in increment(self, method, url, response, error, _pool, _stacktrace)
438 if new_retry.is_exhausted():
--> 439 raise MaxRetryError(_pool, url, error or ResponseError(cause))
440
MaxRetryError: HTTPSConnectionPool(host='raw.githubusercontent.com', port=443): Max retries exceeded with url: /huggingface/datasets/1.1.2/datasets/csv/csv.py (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x7f3cceda5e48>: Failed to establish a new connection: [Errno 111] Connection refused',))
During handling of the above exception, another exception occurred:
ConnectionError Traceback (most recent call last)
<ipython-input-20-18cc3eb4a049> in <module>
1 import requests
2
----> 3 requests.head("https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py")
~/.conda/envs/py36/lib/python3.6/site-packages/requests/api.py in head(url, **kwargs)
102
103 kwargs.setdefault('allow_redirects', False)
--> 104 return request('head', url, **kwargs)
105
106
~/.conda/envs/py36/lib/python3.6/site-packages/requests/api.py in request(method, url, **kwargs)
59 # cases, and look like a memory leak in others.
60 with sessions.Session() as session:
---> 61 return session.request(method=method, url=url, **kwargs)
62
63
~/.conda/envs/py36/lib/python3.6/site-packages/requests/sessions.py in request(self, method, url, params, data, headers, cookies, files, auth, timeout, allow_redirects, proxies, hooks, stream, verify, cert, json)
528 }
529 send_kwargs.update(settings)
--> 530 resp = self.send(prep, **send_kwargs)
531
532 return resp
~/.conda/envs/py36/lib/python3.6/site-packages/requests/sessions.py in send(self, request, **kwargs)
641
642 # Send the request
--> 643 r = adapter.send(request, **kwargs)
644
645 # Total elapsed time of the request (approximately)
~/.conda/envs/py36/lib/python3.6/site-packages/requests/adapters.py in send(self, request, stream, timeout, verify, cert, proxies)
514 raise SSLError(e, request=request)
515
--> 516 raise ConnectionError(e, request=request)
517
518 except ClosedPoolError as e:
ConnectionError: HTTPSConnectionPool(host='raw.githubusercontent.com', port=443): Max retries exceeded with url: /huggingface/datasets/1.1.2/datasets/csv/csv.py (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x7f3cceda5e48>: Failed to establish a new connection: [Errno 111] Connection refused',))
```
>
>
> > hello, how did you solve this problems?
> > > > > Hi !
> > > > > The url works on my side.
> > > > > Is the url working in your navigator ?
> > > > > Are you connected to internet ? Does your network block access to `raw.githubusercontent.com` ?
> > > >
> > > >
> > > > I tried another server, it's working now. Thanks a lot.
> > > > And I'm curious about why download things from "github" when I load dataset from local files ? Dose datasets work if my network crashed?
> > >
> > >
> > > I download the scripts `https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py` and move it to the package dir `*/datasets/` solved the problem. Could you please put the file `datasets/datasets/csv/csv.py` to `datasets/src/datasets/`？
> > > Thanks :D
> >
> >
> > hello, I tried this. but it still failed. how do you fix this error?
>
> 你把那个脚本下载到你本地安装目录下，然后 `load_dataset(csv_script_path, data_fiels)`
我照着做了，然后报错。
ValueError: unable to parse C:/Software/Anaconda/envs/ptk_gpu2/Lib/site-packages/datasets\dataset_infos.json as a URL or as a local path
`---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-5-fd2106a3f053> in <module>
----> 1 dataset = load_dataset('C:/Software/Anaconda/envs/ptk_gpu2/Lib/site-packages/datasets/csv.py', data_files='./test.csv', delimiter=',', autogenerate_column_names=False)
C:\Software\Anaconda\envs\ptk_gpu2\lib\site-packages\datasets\load.py in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, save_infos, script_version, **config_kwargs)
588 # Download/copy dataset processing script
589 module_path, hash = prepare_module(
--> 590 path, script_version=script_version, download_config=download_config, download_mode=download_mode, dataset=True
591 )
592
C:\Software\Anaconda\envs\ptk_gpu2\lib\site-packages\datasets\load.py in prepare_module(path, script_version, download_config, download_mode, dataset, force_local_path, **download_kwargs)
296 local_dataset_infos_path = cached_path(
297 dataset_infos,
--> 298 download_config=download_config,
299 )
300 except (FileNotFoundError, ConnectionError):
C:\Software\Anaconda\envs\ptk_gpu2\lib\site-packages\datasets\utils\file_utils.py in cached_path(url_or_filename, download_config, **download_kwargs)
316 else:
317 # Something unknown
--> 318 raise ValueError("unable to parse {} as a URL or as a local path".format(url_or_filename))
319
320 if download_config.extract_compressed_file and output_path is not None:
ValueError: unable to parse C:/Software/Anaconda/envs/ptk_gpu2/Lib/site-packages/datasets\dataset_infos.json as a URL or as a local path
` |
https://github.com/huggingface/datasets/issues/807 | load_dataset for LOCAL CSV files report CONNECTION ERROR | I also experienced this issue this morning. Looks like something specific to windows.
I'm working on a fix | ## load_dataset for LOCAL CSV files report CONNECTION ERROR
- **Description:**
A local demo csv file:
```
import pandas as pd
import numpy as np
from datasets import load_dataset
import torch
import transformers
df = pd.DataFrame(np.arange(1200).reshape(300,4))
df.to_csv('test.csv', header=False, index=False)
print('datasets version: ', datasets.__version__)
print('pytorch version: ', torch.__version__)
print('transformers version: ', transformers.__version__)
# output:
datasets version: 1.1.2
pytorch version: 1.5.0
transformers version: 3.2.0
```
when I load data through `dataset`:
```
dataset = load_dataset('csv', data_files='./test.csv', delimiter=',', autogenerate_column_names=False)
```
Error infos:
```
ConnectionError Traceback (most recent call last)
<ipython-input-17-bbdadb9a0c78> in <module>
----> 1 dataset = load_dataset('csv', data_files='./test.csv', delimiter=',', autogenerate_column_names=False)
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/load.py in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, save_infos, script_version, **config_kwargs)
588 # Download/copy dataset processing script
589 module_path, hash = prepare_module(
--> 590 path, script_version=script_version, download_config=download_config, download_mode=download_mode, dataset=True
591 )
592
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/load.py in prepare_module(path, script_version, download_config, download_mode, dataset, force_local_path, **download_kwargs)
266 file_path = hf_github_url(path=path, name=name, dataset=dataset, version=script_version)
267 try:
--> 268 local_path = cached_path(file_path, download_config=download_config)
269 except FileNotFoundError:
270 if script_version is not None:
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/utils/file_utils.py in cached_path(url_or_filename, download_config, **download_kwargs)
306 user_agent=download_config.user_agent,
307 local_files_only=download_config.local_files_only,
--> 308 use_etag=download_config.use_etag,
309 )
310 elif os.path.exists(url_or_filename):
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/utils/file_utils.py in get_from_cache(url, cache_dir, force_download, proxies, etag_timeout, resume_download, user_agent, local_files_only, use_etag)
473 elif response is not None and response.status_code == 404:
474 raise FileNotFoundError("Couldn't find file at {}".format(url))
--> 475 raise ConnectionError("Couldn't reach {}".format(url))
476
477 # Try a second time
ConnectionError: Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py
```
And I try to connect to the site with requests:
```
import requests
requests.head("https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py")
```
Similarly Error occurs:
```
---------------------------------------------------------------------------
ConnectionRefusedError Traceback (most recent call last)
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connection.py in _new_conn(self)
159 conn = connection.create_connection(
--> 160 (self._dns_host, self.port), self.timeout, **extra_kw
161 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/util/connection.py in create_connection(address, timeout, source_address, socket_options)
83 if err is not None:
---> 84 raise err
85
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/util/connection.py in create_connection(address, timeout, source_address, socket_options)
73 sock.bind(source_address)
---> 74 sock.connect(sa)
75 return sock
ConnectionRefusedError: [Errno 111] Connection refused
During handling of the above exception, another exception occurred:
NewConnectionError Traceback (most recent call last)
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)
676 headers=headers,
--> 677 chunked=chunked,
678 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in _make_request(self, conn, method, url, timeout, chunked, **httplib_request_kw)
380 try:
--> 381 self._validate_conn(conn)
382 except (SocketTimeout, BaseSSLError) as e:
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in _validate_conn(self, conn)
975 if not getattr(conn, "sock", None): # AppEngine might not have `.sock`
--> 976 conn.connect()
977
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connection.py in connect(self)
307 # Add certificate verification
--> 308 conn = self._new_conn()
309 hostname = self.host
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connection.py in _new_conn(self)
171 raise NewConnectionError(
--> 172 self, "Failed to establish a new connection: %s" % e
173 )
NewConnectionError: <urllib3.connection.HTTPSConnection object at 0x7f3cceda5e48>: Failed to establish a new connection: [Errno 111] Connection refused
During handling of the above exception, another exception occurred:
MaxRetryError Traceback (most recent call last)
~/.conda/envs/py36/lib/python3.6/site-packages/requests/adapters.py in send(self, request, stream, timeout, verify, cert, proxies)
448 retries=self.max_retries,
--> 449 timeout=timeout
450 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)
724 retries = retries.increment(
--> 725 method, url, error=e, _pool=self, _stacktrace=sys.exc_info()[2]
726 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/util/retry.py in increment(self, method, url, response, error, _pool, _stacktrace)
438 if new_retry.is_exhausted():
--> 439 raise MaxRetryError(_pool, url, error or ResponseError(cause))
440
MaxRetryError: HTTPSConnectionPool(host='raw.githubusercontent.com', port=443): Max retries exceeded with url: /huggingface/datasets/1.1.2/datasets/csv/csv.py (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x7f3cceda5e48>: Failed to establish a new connection: [Errno 111] Connection refused',))
During handling of the above exception, another exception occurred:
ConnectionError Traceback (most recent call last)
<ipython-input-20-18cc3eb4a049> in <module>
1 import requests
2
----> 3 requests.head("https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py")
~/.conda/envs/py36/lib/python3.6/site-packages/requests/api.py in head(url, **kwargs)
102
103 kwargs.setdefault('allow_redirects', False)
--> 104 return request('head', url, **kwargs)
105
106
~/.conda/envs/py36/lib/python3.6/site-packages/requests/api.py in request(method, url, **kwargs)
59 # cases, and look like a memory leak in others.
60 with sessions.Session() as session:
---> 61 return session.request(method=method, url=url, **kwargs)
62
63
~/.conda/envs/py36/lib/python3.6/site-packages/requests/sessions.py in request(self, method, url, params, data, headers, cookies, files, auth, timeout, allow_redirects, proxies, hooks, stream, verify, cert, json)
528 }
529 send_kwargs.update(settings)
--> 530 resp = self.send(prep, **send_kwargs)
531
532 return resp
~/.conda/envs/py36/lib/python3.6/site-packages/requests/sessions.py in send(self, request, **kwargs)
641
642 # Send the request
--> 643 r = adapter.send(request, **kwargs)
644
645 # Total elapsed time of the request (approximately)
~/.conda/envs/py36/lib/python3.6/site-packages/requests/adapters.py in send(self, request, stream, timeout, verify, cert, proxies)
514 raise SSLError(e, request=request)
515
--> 516 raise ConnectionError(e, request=request)
517
518 except ClosedPoolError as e:
ConnectionError: HTTPSConnectionPool(host='raw.githubusercontent.com', port=443): Max retries exceeded with url: /huggingface/datasets/1.1.2/datasets/csv/csv.py (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x7f3cceda5e48>: Failed to establish a new connection: [Errno 111] Connection refused',))
``` | 18 | load_dataset for LOCAL CSV files report CONNECTION ERROR
## load_dataset for LOCAL CSV files report CONNECTION ERROR
- **Description:**
A local demo csv file:
```
import pandas as pd
import numpy as np
from datasets import load_dataset
import torch
import transformers
df = pd.DataFrame(np.arange(1200).reshape(300,4))
df.to_csv('test.csv', header=False, index=False)
print('datasets version: ', datasets.__version__)
print('pytorch version: ', torch.__version__)
print('transformers version: ', transformers.__version__)
# output:
datasets version: 1.1.2
pytorch version: 1.5.0
transformers version: 3.2.0
```
when I load data through `dataset`:
```
dataset = load_dataset('csv', data_files='./test.csv', delimiter=',', autogenerate_column_names=False)
```
Error infos:
```
ConnectionError Traceback (most recent call last)
<ipython-input-17-bbdadb9a0c78> in <module>
----> 1 dataset = load_dataset('csv', data_files='./test.csv', delimiter=',', autogenerate_column_names=False)
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/load.py in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, save_infos, script_version, **config_kwargs)
588 # Download/copy dataset processing script
589 module_path, hash = prepare_module(
--> 590 path, script_version=script_version, download_config=download_config, download_mode=download_mode, dataset=True
591 )
592
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/load.py in prepare_module(path, script_version, download_config, download_mode, dataset, force_local_path, **download_kwargs)
266 file_path = hf_github_url(path=path, name=name, dataset=dataset, version=script_version)
267 try:
--> 268 local_path = cached_path(file_path, download_config=download_config)
269 except FileNotFoundError:
270 if script_version is not None:
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/utils/file_utils.py in cached_path(url_or_filename, download_config, **download_kwargs)
306 user_agent=download_config.user_agent,
307 local_files_only=download_config.local_files_only,
--> 308 use_etag=download_config.use_etag,
309 )
310 elif os.path.exists(url_or_filename):
~/.conda/envs/py36/lib/python3.6/site-packages/datasets/utils/file_utils.py in get_from_cache(url, cache_dir, force_download, proxies, etag_timeout, resume_download, user_agent, local_files_only, use_etag)
473 elif response is not None and response.status_code == 404:
474 raise FileNotFoundError("Couldn't find file at {}".format(url))
--> 475 raise ConnectionError("Couldn't reach {}".format(url))
476
477 # Try a second time
ConnectionError: Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py
```
And I try to connect to the site with requests:
```
import requests
requests.head("https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py")
```
Similarly Error occurs:
```
---------------------------------------------------------------------------
ConnectionRefusedError Traceback (most recent call last)
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connection.py in _new_conn(self)
159 conn = connection.create_connection(
--> 160 (self._dns_host, self.port), self.timeout, **extra_kw
161 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/util/connection.py in create_connection(address, timeout, source_address, socket_options)
83 if err is not None:
---> 84 raise err
85
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/util/connection.py in create_connection(address, timeout, source_address, socket_options)
73 sock.bind(source_address)
---> 74 sock.connect(sa)
75 return sock
ConnectionRefusedError: [Errno 111] Connection refused
During handling of the above exception, another exception occurred:
NewConnectionError Traceback (most recent call last)
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)
676 headers=headers,
--> 677 chunked=chunked,
678 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in _make_request(self, conn, method, url, timeout, chunked, **httplib_request_kw)
380 try:
--> 381 self._validate_conn(conn)
382 except (SocketTimeout, BaseSSLError) as e:
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in _validate_conn(self, conn)
975 if not getattr(conn, "sock", None): # AppEngine might not have `.sock`
--> 976 conn.connect()
977
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connection.py in connect(self)
307 # Add certificate verification
--> 308 conn = self._new_conn()
309 hostname = self.host
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connection.py in _new_conn(self)
171 raise NewConnectionError(
--> 172 self, "Failed to establish a new connection: %s" % e
173 )
NewConnectionError: <urllib3.connection.HTTPSConnection object at 0x7f3cceda5e48>: Failed to establish a new connection: [Errno 111] Connection refused
During handling of the above exception, another exception occurred:
MaxRetryError Traceback (most recent call last)
~/.conda/envs/py36/lib/python3.6/site-packages/requests/adapters.py in send(self, request, stream, timeout, verify, cert, proxies)
448 retries=self.max_retries,
--> 449 timeout=timeout
450 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/connectionpool.py in urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)
724 retries = retries.increment(
--> 725 method, url, error=e, _pool=self, _stacktrace=sys.exc_info()[2]
726 )
~/.conda/envs/py36/lib/python3.6/site-packages/urllib3/util/retry.py in increment(self, method, url, response, error, _pool, _stacktrace)
438 if new_retry.is_exhausted():
--> 439 raise MaxRetryError(_pool, url, error or ResponseError(cause))
440
MaxRetryError: HTTPSConnectionPool(host='raw.githubusercontent.com', port=443): Max retries exceeded with url: /huggingface/datasets/1.1.2/datasets/csv/csv.py (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x7f3cceda5e48>: Failed to establish a new connection: [Errno 111] Connection refused',))
During handling of the above exception, another exception occurred:
ConnectionError Traceback (most recent call last)
<ipython-input-20-18cc3eb4a049> in <module>
1 import requests
2
----> 3 requests.head("https://raw.githubusercontent.com/huggingface/datasets/1.1.2/datasets/csv/csv.py")
~/.conda/envs/py36/lib/python3.6/site-packages/requests/api.py in head(url, **kwargs)
102
103 kwargs.setdefault('allow_redirects', False)
--> 104 return request('head', url, **kwargs)
105
106
~/.conda/envs/py36/lib/python3.6/site-packages/requests/api.py in request(method, url, **kwargs)
59 # cases, and look like a memory leak in others.
60 with sessions.Session() as session:
---> 61 return session.request(method=method, url=url, **kwargs)
62
63
~/.conda/envs/py36/lib/python3.6/site-packages/requests/sessions.py in request(self, method, url, params, data, headers, cookies, files, auth, timeout, allow_redirects, proxies, hooks, stream, verify, cert, json)
528 }
529 send_kwargs.update(settings)
--> 530 resp = self.send(prep, **send_kwargs)
531
532 return resp
~/.conda/envs/py36/lib/python3.6/site-packages/requests/sessions.py in send(self, request, **kwargs)
641
642 # Send the request
--> 643 r = adapter.send(request, **kwargs)
644
645 # Total elapsed time of the request (approximately)
~/.conda/envs/py36/lib/python3.6/site-packages/requests/adapters.py in send(self, request, stream, timeout, verify, cert, proxies)
514 raise SSLError(e, request=request)
515
--> 516 raise ConnectionError(e, request=request)
517
518 except ClosedPoolError as e:
ConnectionError: HTTPSConnectionPool(host='raw.githubusercontent.com', port=443): Max retries exceeded with url: /huggingface/datasets/1.1.2/datasets/csv/csv.py (Caused by NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x7f3cceda5e48>: Failed to establish a new connection: [Errno 111] Connection refused',))
```
I also experienced this issue this morning. Looks like something specific to windows.
I'm working on a fix |
https://github.com/huggingface/datasets/issues/806 | Quail dataset urls are out of date | Hi ! Thanks for reporting.
We should fix the urls and use quail 1.3.
If you want to contribute feel free to fix the urls and open a PR :) | <h3>Code</h3>
```
from datasets import load_dataset
quail = load_dataset('quail')
```
<h3>Error</h3>
```
FileNotFoundError: Couldn't find file at https://raw.githubusercontent.com/text-machine-lab/quail/master/quail_v1.2/xml/ordered/quail_1.2_train.xml
```
As per [quail v1.3 commit](https://github.com/text-machine-lab/quail/commit/506501cfa34d9ec6c042d31026ba6fea6bcec8ff) it looks like the location and suggested ordering has changed. In [https://github.com/huggingface/datasets/blob/master/datasets/quail/quail.py#L52-L58](https://github.com/huggingface/datasets/blob/master/datasets/quail/quail.py#L52-L58) the quail v1.2 datasets are being pointed to, which don't exist anymore. | 30 | Quail dataset urls are out of date
<h3>Code</h3>
```
from datasets import load_dataset
quail = load_dataset('quail')
```
<h3>Error</h3>
```
FileNotFoundError: Couldn't find file at https://raw.githubusercontent.com/text-machine-lab/quail/master/quail_v1.2/xml/ordered/quail_1.2_train.xml
```
As per [quail v1.3 commit](https://github.com/text-machine-lab/quail/commit/506501cfa34d9ec6c042d31026ba6fea6bcec8ff) it looks like the location and suggested ordering has changed. In [https://github.com/huggingface/datasets/blob/master/datasets/quail/quail.py#L52-L58](https://github.com/huggingface/datasets/blob/master/datasets/quail/quail.py#L52-L58) the quail v1.2 datasets are being pointed to, which don't exist anymore.
Hi ! Thanks for reporting.
We should fix the urls and use quail 1.3.
If you want to contribute feel free to fix the urls and open a PR :) |
https://github.com/huggingface/datasets/issues/806 | Quail dataset urls are out of date | Done! PR [https://github.com/huggingface/datasets/pull/820](https://github.com/huggingface/datasets/pull/820)
Updated links and also regenerated the metadata and dummy data for v1.3 in order to pass verifications as described here: [https://huggingface.co/docs/datasets/share_dataset.html#adding-tests-and-metadata-to-the-dataset](https://huggingface.co/docs/datasets/share_dataset.html#adding-tests-and-metadata-to-the-dataset). | <h3>Code</h3>
```
from datasets import load_dataset
quail = load_dataset('quail')
```
<h3>Error</h3>
```
FileNotFoundError: Couldn't find file at https://raw.githubusercontent.com/text-machine-lab/quail/master/quail_v1.2/xml/ordered/quail_1.2_train.xml
```
As per [quail v1.3 commit](https://github.com/text-machine-lab/quail/commit/506501cfa34d9ec6c042d31026ba6fea6bcec8ff) it looks like the location and suggested ordering has changed. In [https://github.com/huggingface/datasets/blob/master/datasets/quail/quail.py#L52-L58](https://github.com/huggingface/datasets/blob/master/datasets/quail/quail.py#L52-L58) the quail v1.2 datasets are being pointed to, which don't exist anymore. | 24 | Quail dataset urls are out of date
<h3>Code</h3>
```
from datasets import load_dataset
quail = load_dataset('quail')
```
<h3>Error</h3>
```
FileNotFoundError: Couldn't find file at https://raw.githubusercontent.com/text-machine-lab/quail/master/quail_v1.2/xml/ordered/quail_1.2_train.xml
```
As per [quail v1.3 commit](https://github.com/text-machine-lab/quail/commit/506501cfa34d9ec6c042d31026ba6fea6bcec8ff) it looks like the location and suggested ordering has changed. In [https://github.com/huggingface/datasets/blob/master/datasets/quail/quail.py#L52-L58](https://github.com/huggingface/datasets/blob/master/datasets/quail/quail.py#L52-L58) the quail v1.2 datasets are being pointed to, which don't exist anymore.
Done! PR [https://github.com/huggingface/datasets/pull/820](https://github.com/huggingface/datasets/pull/820)
Updated links and also regenerated the metadata and dummy data for v1.3 in order to pass verifications as described here: [https://huggingface.co/docs/datasets/share_dataset.html#adding-tests-and-metadata-to-the-dataset](https://huggingface.co/docs/datasets/share_dataset.html#adding-tests-and-metadata-to-the-dataset). |
https://github.com/huggingface/datasets/issues/805 | On loading a metric from datasets, I get the following error | Hi ! We support only pyarrow > 0.17.1 so that we have access to the `PyExtensionType` object.
Could you update pyarrow and try again ?
```
pip install --upgrade pyarrow
``` | `from datasets import load_metric`
`metric = load_metric('bleurt')`
Traceback:
210 class _ArrayXDExtensionType(pa.PyExtensionType):
211
212 ndims: int = None
AttributeError: module 'pyarrow' has no attribute 'PyExtensionType'
Any help will be appreciated. Thank you. | 31 | On loading a metric from datasets, I get the following error
`from datasets import load_metric`
`metric = load_metric('bleurt')`
Traceback:
210 class _ArrayXDExtensionType(pa.PyExtensionType):
211
212 ndims: int = None
AttributeError: module 'pyarrow' has no attribute 'PyExtensionType'
Any help will be appreciated. Thank you.
Hi ! We support only pyarrow > 0.17.1 so that we have access to the `PyExtensionType` object.
Could you update pyarrow and try again ?
```
pip install --upgrade pyarrow
``` |
https://github.com/huggingface/datasets/issues/804 | Empty output/answer in TriviaQA test set (both in 'kilt_tasks' and 'trivia_qa') | Yes: TriviaQA has a private test set for the leaderboard [here](https://competitions.codalab.org/competitions/17208)
For the KILT training and validation portions, you need to link the examples from the TriviaQA dataset as detailed here:
https://github.com/huggingface/datasets/blob/master/datasets/kilt_tasks/README.md | # The issue
It's all in the title, it appears to be fine on the train and validation sets.
Is there some kind of mapping to do like for the questions (see https://github.com/huggingface/datasets/blob/master/datasets/kilt_tasks/README.md) ?
# How to reproduce
```py
from datasets import load_dataset
kilt_tasks = load_dataset("kilt_tasks")
trivia_qa = load_dataset('trivia_qa', 'unfiltered.nocontext')
# both in "kilt_tasks"
In [18]: any([output['answer'] for output in kilt_tasks['test_triviaqa']['output']])
Out[18]: False
# and "trivia_qa"
In [13]: all([answer['value'] == '<unk>' for answer in trivia_qa['test']['answer']])
Out[13]: True
# appears to be fine on the train and validation sets.
In [14]: all([answer['value'] == '<unk>' for answer in trivia_qa['train']['answer']])
Out[14]: False
In [15]: all([answer['value'] == '<unk>' for answer in trivia_qa['validation']['answer']])
Out[15]: False
In [16]: any([output['answer'] for output in kilt_tasks['train_triviaqa']['output']])
Out[16]: True
In [17]: any([output['answer'] for output in kilt_tasks['validation_triviaqa']['output']])
Out[17]: True
``` | 32 | Empty output/answer in TriviaQA test set (both in 'kilt_tasks' and 'trivia_qa')
# The issue
It's all in the title, it appears to be fine on the train and validation sets.
Is there some kind of mapping to do like for the questions (see https://github.com/huggingface/datasets/blob/master/datasets/kilt_tasks/README.md) ?
# How to reproduce
```py
from datasets import load_dataset
kilt_tasks = load_dataset("kilt_tasks")
trivia_qa = load_dataset('trivia_qa', 'unfiltered.nocontext')
# both in "kilt_tasks"
In [18]: any([output['answer'] for output in kilt_tasks['test_triviaqa']['output']])
Out[18]: False
# and "trivia_qa"
In [13]: all([answer['value'] == '<unk>' for answer in trivia_qa['test']['answer']])
Out[13]: True
# appears to be fine on the train and validation sets.
In [14]: all([answer['value'] == '<unk>' for answer in trivia_qa['train']['answer']])
Out[14]: False
In [15]: all([answer['value'] == '<unk>' for answer in trivia_qa['validation']['answer']])
Out[15]: False
In [16]: any([output['answer'] for output in kilt_tasks['train_triviaqa']['output']])
Out[16]: True
In [17]: any([output['answer'] for output in kilt_tasks['validation_triviaqa']['output']])
Out[17]: True
```
Yes: TriviaQA has a private test set for the leaderboard [here](https://competitions.codalab.org/competitions/17208)
For the KILT training and validation portions, you need to link the examples from the TriviaQA dataset as detailed here:
https://github.com/huggingface/datasets/blob/master/datasets/kilt_tasks/README.md |
https://github.com/huggingface/datasets/issues/804 | Empty output/answer in TriviaQA test set (both in 'kilt_tasks' and 'trivia_qa') | Oh ok, I guess I read the paper too fast 😅, thank you for your answer! | # The issue
It's all in the title, it appears to be fine on the train and validation sets.
Is there some kind of mapping to do like for the questions (see https://github.com/huggingface/datasets/blob/master/datasets/kilt_tasks/README.md) ?
# How to reproduce
```py
from datasets import load_dataset
kilt_tasks = load_dataset("kilt_tasks")
trivia_qa = load_dataset('trivia_qa', 'unfiltered.nocontext')
# both in "kilt_tasks"
In [18]: any([output['answer'] for output in kilt_tasks['test_triviaqa']['output']])
Out[18]: False
# and "trivia_qa"
In [13]: all([answer['value'] == '<unk>' for answer in trivia_qa['test']['answer']])
Out[13]: True
# appears to be fine on the train and validation sets.
In [14]: all([answer['value'] == '<unk>' for answer in trivia_qa['train']['answer']])
Out[14]: False
In [15]: all([answer['value'] == '<unk>' for answer in trivia_qa['validation']['answer']])
Out[15]: False
In [16]: any([output['answer'] for output in kilt_tasks['train_triviaqa']['output']])
Out[16]: True
In [17]: any([output['answer'] for output in kilt_tasks['validation_triviaqa']['output']])
Out[17]: True
``` | 16 | Empty output/answer in TriviaQA test set (both in 'kilt_tasks' and 'trivia_qa')
# The issue
It's all in the title, it appears to be fine on the train and validation sets.
Is there some kind of mapping to do like for the questions (see https://github.com/huggingface/datasets/blob/master/datasets/kilt_tasks/README.md) ?
# How to reproduce
```py
from datasets import load_dataset
kilt_tasks = load_dataset("kilt_tasks")
trivia_qa = load_dataset('trivia_qa', 'unfiltered.nocontext')
# both in "kilt_tasks"
In [18]: any([output['answer'] for output in kilt_tasks['test_triviaqa']['output']])
Out[18]: False
# and "trivia_qa"
In [13]: all([answer['value'] == '<unk>' for answer in trivia_qa['test']['answer']])
Out[13]: True
# appears to be fine on the train and validation sets.
In [14]: all([answer['value'] == '<unk>' for answer in trivia_qa['train']['answer']])
Out[14]: False
In [15]: all([answer['value'] == '<unk>' for answer in trivia_qa['validation']['answer']])
Out[15]: False
In [16]: any([output['answer'] for output in kilt_tasks['train_triviaqa']['output']])
Out[16]: True
In [17]: any([output['answer'] for output in kilt_tasks['validation_triviaqa']['output']])
Out[17]: True
```
Oh ok, I guess I read the paper too fast 😅, thank you for your answer! |
https://github.com/huggingface/datasets/issues/801 | How to join two datasets? | Hi ! Currently the only way to add new fields to a dataset is by using `.map` and picking items from the other dataset
| Hi,
I'm wondering if it's possible to join two (preprocessed) datasets with the same number of rows but different labels?
I'm currently trying to create paired sentences for BERT from `wikipedia/'20200501.en`, and I couldn't figure out a way to create a paired sentence using `.map()` where the second sentence is **not** the next sentence (i.e., from a different article) of the first sentence.
Thanks! | 24 | How to join two datasets?
Hi,
I'm wondering if it's possible to join two (preprocessed) datasets with the same number of rows but different labels?
I'm currently trying to create paired sentences for BERT from `wikipedia/'20200501.en`, and I couldn't figure out a way to create a paired sentence using `.map()` where the second sentence is **not** the next sentence (i.e., from a different article) of the first sentence.
Thanks!
Hi ! Currently the only way to add new fields to a dataset is by using `.map` and picking items from the other dataset
|
https://github.com/huggingface/datasets/issues/801 | How to join two datasets? | Closing this one. Feel free to re-open if you have other questions about this issue.
Also linking another discussion about joining datasets: #853 | Hi,
I'm wondering if it's possible to join two (preprocessed) datasets with the same number of rows but different labels?
I'm currently trying to create paired sentences for BERT from `wikipedia/'20200501.en`, and I couldn't figure out a way to create a paired sentence using `.map()` where the second sentence is **not** the next sentence (i.e., from a different article) of the first sentence.
Thanks! | 23 | How to join two datasets?
Hi,
I'm wondering if it's possible to join two (preprocessed) datasets with the same number of rows but different labels?
I'm currently trying to create paired sentences for BERT from `wikipedia/'20200501.en`, and I couldn't figure out a way to create a paired sentence using `.map()` where the second sentence is **not** the next sentence (i.e., from a different article) of the first sentence.
Thanks!
Closing this one. Feel free to re-open if you have other questions about this issue.
Also linking another discussion about joining datasets: #853 |
https://github.com/huggingface/datasets/issues/798 | Cannot load TREC dataset: ConnectionError | Hi ! Indeed there's an issue with those links.
We should probably use the target urls of the redirections instead | ## Problem
I cannot load "trec" dataset, it results with ConnectionError as shown below. I've tried on both Google Colab and locally.
* `requests.head('http://cogcomp.org/Data/QA/QC/train_5500.label')` returns <Response [302]>.
* `requests.head('http://cogcomp.org/Data/QA/QC/train_5500.label', allow_redirects=True)` raises `requests.exceptions.TooManyRedirects: Exceeded 30 redirects.`
* Opening `http://cogcomp.org/Data/QA/QC/train_5500.label' in a browser works, but opens a different address
* Increasing max_redirects to 100 doesn't help
Also, while debugging I've seen that requesting 'https://storage.googleapis.com/huggingface-nlp/cache/datasets/trec/default/1.1.0/dataset_info.json' returns <Response [404]> before, but it doesn't raise any errors. Not sure if that's relevant.
* datasets.__version__ == '1.1.2'
* requests.__version__ == '2.24.0'
## Error trace
```
>>> import datasets
>>> datasets.__version__
'1.1.2'
>>> dataset = load_dataset("trec", split="train")
Using custom data configuration default
Downloading and preparing dataset trec/default (download: 350.79 KiB, generated: 403.39 KiB, post-processed: Unknown size, total: 754.18 KiB) to /home/przemyslaw/.cache/huggingface/datasets/trec/default/1.1.0/ca4248481ad244f235f4cf277186cad2ee8769f975119a2bbfc41b8932b88bd7...
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/load.py", line 611, in load_dataset
ignore_verifications=ignore_verifications,
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/builder.py", line 476, in download_and_prepare
dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/builder.py", line 531, in _download_and_prepare
split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
File "/home/przemyslaw/.cache/huggingface/modules/datasets_modules/datasets/trec/ca4248481ad244f235f4cf277186cad2ee8769f975119a2bbfc41b8932b88bd7/trec.py", line 140, in _split_generators
dl_files = dl_manager.download_and_extract(_URLs)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/download_manager.py", line 254, in download_and_extract
return self.extract(self.download(url_or_urls))
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/download_manager.py", line 179, in download
num_proc=download_config.num_proc,
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 225, in map_nested
_single_map_nested((function, obj, types, None, True)) for obj in tqdm(iterable, disable=disable_tqdm)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 225, in <listcomp>
_single_map_nested((function, obj, types, None, True)) for obj in tqdm(iterable, disable=disable_tqdm)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 163, in _single_map_nested
return function(data_struct)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/file_utils.py", line 308, in cached_path
use_etag=download_config.use_etag,
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/file_utils.py", line 475, in get_from_cache
raise ConnectionError("Couldn't reach {}".format(url))
ConnectionError: Couldn't reach http://cogcomp.org/Data/QA/QC/train_5500.label
```
I would appreciate some suggestions here. | 20 | Cannot load TREC dataset: ConnectionError
## Problem
I cannot load "trec" dataset, it results with ConnectionError as shown below. I've tried on both Google Colab and locally.
* `requests.head('http://cogcomp.org/Data/QA/QC/train_5500.label')` returns <Response [302]>.
* `requests.head('http://cogcomp.org/Data/QA/QC/train_5500.label', allow_redirects=True)` raises `requests.exceptions.TooManyRedirects: Exceeded 30 redirects.`
* Opening `http://cogcomp.org/Data/QA/QC/train_5500.label' in a browser works, but opens a different address
* Increasing max_redirects to 100 doesn't help
Also, while debugging I've seen that requesting 'https://storage.googleapis.com/huggingface-nlp/cache/datasets/trec/default/1.1.0/dataset_info.json' returns <Response [404]> before, but it doesn't raise any errors. Not sure if that's relevant.
* datasets.__version__ == '1.1.2'
* requests.__version__ == '2.24.0'
## Error trace
```
>>> import datasets
>>> datasets.__version__
'1.1.2'
>>> dataset = load_dataset("trec", split="train")
Using custom data configuration default
Downloading and preparing dataset trec/default (download: 350.79 KiB, generated: 403.39 KiB, post-processed: Unknown size, total: 754.18 KiB) to /home/przemyslaw/.cache/huggingface/datasets/trec/default/1.1.0/ca4248481ad244f235f4cf277186cad2ee8769f975119a2bbfc41b8932b88bd7...
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/load.py", line 611, in load_dataset
ignore_verifications=ignore_verifications,
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/builder.py", line 476, in download_and_prepare
dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/builder.py", line 531, in _download_and_prepare
split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
File "/home/przemyslaw/.cache/huggingface/modules/datasets_modules/datasets/trec/ca4248481ad244f235f4cf277186cad2ee8769f975119a2bbfc41b8932b88bd7/trec.py", line 140, in _split_generators
dl_files = dl_manager.download_and_extract(_URLs)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/download_manager.py", line 254, in download_and_extract
return self.extract(self.download(url_or_urls))
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/download_manager.py", line 179, in download
num_proc=download_config.num_proc,
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 225, in map_nested
_single_map_nested((function, obj, types, None, True)) for obj in tqdm(iterable, disable=disable_tqdm)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 225, in <listcomp>
_single_map_nested((function, obj, types, None, True)) for obj in tqdm(iterable, disable=disable_tqdm)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 163, in _single_map_nested
return function(data_struct)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/file_utils.py", line 308, in cached_path
use_etag=download_config.use_etag,
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/file_utils.py", line 475, in get_from_cache
raise ConnectionError("Couldn't reach {}".format(url))
ConnectionError: Couldn't reach http://cogcomp.org/Data/QA/QC/train_5500.label
```
I would appreciate some suggestions here.
Hi ! Indeed there's an issue with those links.
We should probably use the target urls of the redirections instead |
https://github.com/huggingface/datasets/issues/798 | Cannot load TREC dataset: ConnectionError | Hi, the same issue here, could you tell me how to download it through datasets? thanks | ## Problem
I cannot load "trec" dataset, it results with ConnectionError as shown below. I've tried on both Google Colab and locally.
* `requests.head('http://cogcomp.org/Data/QA/QC/train_5500.label')` returns <Response [302]>.
* `requests.head('http://cogcomp.org/Data/QA/QC/train_5500.label', allow_redirects=True)` raises `requests.exceptions.TooManyRedirects: Exceeded 30 redirects.`
* Opening `http://cogcomp.org/Data/QA/QC/train_5500.label' in a browser works, but opens a different address
* Increasing max_redirects to 100 doesn't help
Also, while debugging I've seen that requesting 'https://storage.googleapis.com/huggingface-nlp/cache/datasets/trec/default/1.1.0/dataset_info.json' returns <Response [404]> before, but it doesn't raise any errors. Not sure if that's relevant.
* datasets.__version__ == '1.1.2'
* requests.__version__ == '2.24.0'
## Error trace
```
>>> import datasets
>>> datasets.__version__
'1.1.2'
>>> dataset = load_dataset("trec", split="train")
Using custom data configuration default
Downloading and preparing dataset trec/default (download: 350.79 KiB, generated: 403.39 KiB, post-processed: Unknown size, total: 754.18 KiB) to /home/przemyslaw/.cache/huggingface/datasets/trec/default/1.1.0/ca4248481ad244f235f4cf277186cad2ee8769f975119a2bbfc41b8932b88bd7...
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/load.py", line 611, in load_dataset
ignore_verifications=ignore_verifications,
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/builder.py", line 476, in download_and_prepare
dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/builder.py", line 531, in _download_and_prepare
split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
File "/home/przemyslaw/.cache/huggingface/modules/datasets_modules/datasets/trec/ca4248481ad244f235f4cf277186cad2ee8769f975119a2bbfc41b8932b88bd7/trec.py", line 140, in _split_generators
dl_files = dl_manager.download_and_extract(_URLs)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/download_manager.py", line 254, in download_and_extract
return self.extract(self.download(url_or_urls))
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/download_manager.py", line 179, in download
num_proc=download_config.num_proc,
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 225, in map_nested
_single_map_nested((function, obj, types, None, True)) for obj in tqdm(iterable, disable=disable_tqdm)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 225, in <listcomp>
_single_map_nested((function, obj, types, None, True)) for obj in tqdm(iterable, disable=disable_tqdm)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 163, in _single_map_nested
return function(data_struct)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/file_utils.py", line 308, in cached_path
use_etag=download_config.use_etag,
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/file_utils.py", line 475, in get_from_cache
raise ConnectionError("Couldn't reach {}".format(url))
ConnectionError: Couldn't reach http://cogcomp.org/Data/QA/QC/train_5500.label
```
I would appreciate some suggestions here. | 16 | Cannot load TREC dataset: ConnectionError
## Problem
I cannot load "trec" dataset, it results with ConnectionError as shown below. I've tried on both Google Colab and locally.
* `requests.head('http://cogcomp.org/Data/QA/QC/train_5500.label')` returns <Response [302]>.
* `requests.head('http://cogcomp.org/Data/QA/QC/train_5500.label', allow_redirects=True)` raises `requests.exceptions.TooManyRedirects: Exceeded 30 redirects.`
* Opening `http://cogcomp.org/Data/QA/QC/train_5500.label' in a browser works, but opens a different address
* Increasing max_redirects to 100 doesn't help
Also, while debugging I've seen that requesting 'https://storage.googleapis.com/huggingface-nlp/cache/datasets/trec/default/1.1.0/dataset_info.json' returns <Response [404]> before, but it doesn't raise any errors. Not sure if that's relevant.
* datasets.__version__ == '1.1.2'
* requests.__version__ == '2.24.0'
## Error trace
```
>>> import datasets
>>> datasets.__version__
'1.1.2'
>>> dataset = load_dataset("trec", split="train")
Using custom data configuration default
Downloading and preparing dataset trec/default (download: 350.79 KiB, generated: 403.39 KiB, post-processed: Unknown size, total: 754.18 KiB) to /home/przemyslaw/.cache/huggingface/datasets/trec/default/1.1.0/ca4248481ad244f235f4cf277186cad2ee8769f975119a2bbfc41b8932b88bd7...
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/load.py", line 611, in load_dataset
ignore_verifications=ignore_verifications,
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/builder.py", line 476, in download_and_prepare
dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/builder.py", line 531, in _download_and_prepare
split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
File "/home/przemyslaw/.cache/huggingface/modules/datasets_modules/datasets/trec/ca4248481ad244f235f4cf277186cad2ee8769f975119a2bbfc41b8932b88bd7/trec.py", line 140, in _split_generators
dl_files = dl_manager.download_and_extract(_URLs)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/download_manager.py", line 254, in download_and_extract
return self.extract(self.download(url_or_urls))
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/download_manager.py", line 179, in download
num_proc=download_config.num_proc,
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 225, in map_nested
_single_map_nested((function, obj, types, None, True)) for obj in tqdm(iterable, disable=disable_tqdm)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 225, in <listcomp>
_single_map_nested((function, obj, types, None, True)) for obj in tqdm(iterable, disable=disable_tqdm)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 163, in _single_map_nested
return function(data_struct)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/file_utils.py", line 308, in cached_path
use_etag=download_config.use_etag,
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/file_utils.py", line 475, in get_from_cache
raise ConnectionError("Couldn't reach {}".format(url))
ConnectionError: Couldn't reach http://cogcomp.org/Data/QA/QC/train_5500.label
```
I would appreciate some suggestions here.
Hi, the same issue here, could you tell me how to download it through datasets? thanks |
https://github.com/huggingface/datasets/issues/798 | Cannot load TREC dataset: ConnectionError | Actually it's already fixed on the master branch since #740
I'll do the 1.1.3 release soon | ## Problem
I cannot load "trec" dataset, it results with ConnectionError as shown below. I've tried on both Google Colab and locally.
* `requests.head('http://cogcomp.org/Data/QA/QC/train_5500.label')` returns <Response [302]>.
* `requests.head('http://cogcomp.org/Data/QA/QC/train_5500.label', allow_redirects=True)` raises `requests.exceptions.TooManyRedirects: Exceeded 30 redirects.`
* Opening `http://cogcomp.org/Data/QA/QC/train_5500.label' in a browser works, but opens a different address
* Increasing max_redirects to 100 doesn't help
Also, while debugging I've seen that requesting 'https://storage.googleapis.com/huggingface-nlp/cache/datasets/trec/default/1.1.0/dataset_info.json' returns <Response [404]> before, but it doesn't raise any errors. Not sure if that's relevant.
* datasets.__version__ == '1.1.2'
* requests.__version__ == '2.24.0'
## Error trace
```
>>> import datasets
>>> datasets.__version__
'1.1.2'
>>> dataset = load_dataset("trec", split="train")
Using custom data configuration default
Downloading and preparing dataset trec/default (download: 350.79 KiB, generated: 403.39 KiB, post-processed: Unknown size, total: 754.18 KiB) to /home/przemyslaw/.cache/huggingface/datasets/trec/default/1.1.0/ca4248481ad244f235f4cf277186cad2ee8769f975119a2bbfc41b8932b88bd7...
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/load.py", line 611, in load_dataset
ignore_verifications=ignore_verifications,
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/builder.py", line 476, in download_and_prepare
dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/builder.py", line 531, in _download_and_prepare
split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
File "/home/przemyslaw/.cache/huggingface/modules/datasets_modules/datasets/trec/ca4248481ad244f235f4cf277186cad2ee8769f975119a2bbfc41b8932b88bd7/trec.py", line 140, in _split_generators
dl_files = dl_manager.download_and_extract(_URLs)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/download_manager.py", line 254, in download_and_extract
return self.extract(self.download(url_or_urls))
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/download_manager.py", line 179, in download
num_proc=download_config.num_proc,
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 225, in map_nested
_single_map_nested((function, obj, types, None, True)) for obj in tqdm(iterable, disable=disable_tqdm)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 225, in <listcomp>
_single_map_nested((function, obj, types, None, True)) for obj in tqdm(iterable, disable=disable_tqdm)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 163, in _single_map_nested
return function(data_struct)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/file_utils.py", line 308, in cached_path
use_etag=download_config.use_etag,
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/file_utils.py", line 475, in get_from_cache
raise ConnectionError("Couldn't reach {}".format(url))
ConnectionError: Couldn't reach http://cogcomp.org/Data/QA/QC/train_5500.label
```
I would appreciate some suggestions here. | 16 | Cannot load TREC dataset: ConnectionError
## Problem
I cannot load "trec" dataset, it results with ConnectionError as shown below. I've tried on both Google Colab and locally.
* `requests.head('http://cogcomp.org/Data/QA/QC/train_5500.label')` returns <Response [302]>.
* `requests.head('http://cogcomp.org/Data/QA/QC/train_5500.label', allow_redirects=True)` raises `requests.exceptions.TooManyRedirects: Exceeded 30 redirects.`
* Opening `http://cogcomp.org/Data/QA/QC/train_5500.label' in a browser works, but opens a different address
* Increasing max_redirects to 100 doesn't help
Also, while debugging I've seen that requesting 'https://storage.googleapis.com/huggingface-nlp/cache/datasets/trec/default/1.1.0/dataset_info.json' returns <Response [404]> before, but it doesn't raise any errors. Not sure if that's relevant.
* datasets.__version__ == '1.1.2'
* requests.__version__ == '2.24.0'
## Error trace
```
>>> import datasets
>>> datasets.__version__
'1.1.2'
>>> dataset = load_dataset("trec", split="train")
Using custom data configuration default
Downloading and preparing dataset trec/default (download: 350.79 KiB, generated: 403.39 KiB, post-processed: Unknown size, total: 754.18 KiB) to /home/przemyslaw/.cache/huggingface/datasets/trec/default/1.1.0/ca4248481ad244f235f4cf277186cad2ee8769f975119a2bbfc41b8932b88bd7...
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/load.py", line 611, in load_dataset
ignore_verifications=ignore_verifications,
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/builder.py", line 476, in download_and_prepare
dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/builder.py", line 531, in _download_and_prepare
split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
File "/home/przemyslaw/.cache/huggingface/modules/datasets_modules/datasets/trec/ca4248481ad244f235f4cf277186cad2ee8769f975119a2bbfc41b8932b88bd7/trec.py", line 140, in _split_generators
dl_files = dl_manager.download_and_extract(_URLs)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/download_manager.py", line 254, in download_and_extract
return self.extract(self.download(url_or_urls))
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/download_manager.py", line 179, in download
num_proc=download_config.num_proc,
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 225, in map_nested
_single_map_nested((function, obj, types, None, True)) for obj in tqdm(iterable, disable=disable_tqdm)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 225, in <listcomp>
_single_map_nested((function, obj, types, None, True)) for obj in tqdm(iterable, disable=disable_tqdm)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 163, in _single_map_nested
return function(data_struct)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/file_utils.py", line 308, in cached_path
use_etag=download_config.use_etag,
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/file_utils.py", line 475, in get_from_cache
raise ConnectionError("Couldn't reach {}".format(url))
ConnectionError: Couldn't reach http://cogcomp.org/Data/QA/QC/train_5500.label
```
I would appreciate some suggestions here.
Actually it's already fixed on the master branch since #740
I'll do the 1.1.3 release soon |
https://github.com/huggingface/datasets/issues/798 | Cannot load TREC dataset: ConnectionError | Hi
thanks, but I did tried to install from the pip install git+... and it does
not work for me,. thanks for the help. I have the same issue with wmt16,
"ro-en"
thanks.
Best
Rabeeh
On Mon, Nov 16, 2020 at 10:29 AM Quentin Lhoest <[email protected]>
wrote:
> Actually it's already fixed on the master branch since #740
> <https://github.com/huggingface/datasets/pull/740>
> I'll do the 1.1.3 release soon
>
> —
> You are receiving this because you commented.
> Reply to this email directly, view it on GitHub
> <https://github.com/huggingface/datasets/issues/798#issuecomment-727854736>,
> or unsubscribe
> <https://github.com/notifications/unsubscribe-auth/ABP4ZCEUBJKPOCLABXCKMPDSQDWH3ANCNFSM4TJBUKSA>
> .
>
| ## Problem
I cannot load "trec" dataset, it results with ConnectionError as shown below. I've tried on both Google Colab and locally.
* `requests.head('http://cogcomp.org/Data/QA/QC/train_5500.label')` returns <Response [302]>.
* `requests.head('http://cogcomp.org/Data/QA/QC/train_5500.label', allow_redirects=True)` raises `requests.exceptions.TooManyRedirects: Exceeded 30 redirects.`
* Opening `http://cogcomp.org/Data/QA/QC/train_5500.label' in a browser works, but opens a different address
* Increasing max_redirects to 100 doesn't help
Also, while debugging I've seen that requesting 'https://storage.googleapis.com/huggingface-nlp/cache/datasets/trec/default/1.1.0/dataset_info.json' returns <Response [404]> before, but it doesn't raise any errors. Not sure if that's relevant.
* datasets.__version__ == '1.1.2'
* requests.__version__ == '2.24.0'
## Error trace
```
>>> import datasets
>>> datasets.__version__
'1.1.2'
>>> dataset = load_dataset("trec", split="train")
Using custom data configuration default
Downloading and preparing dataset trec/default (download: 350.79 KiB, generated: 403.39 KiB, post-processed: Unknown size, total: 754.18 KiB) to /home/przemyslaw/.cache/huggingface/datasets/trec/default/1.1.0/ca4248481ad244f235f4cf277186cad2ee8769f975119a2bbfc41b8932b88bd7...
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/load.py", line 611, in load_dataset
ignore_verifications=ignore_verifications,
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/builder.py", line 476, in download_and_prepare
dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/builder.py", line 531, in _download_and_prepare
split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
File "/home/przemyslaw/.cache/huggingface/modules/datasets_modules/datasets/trec/ca4248481ad244f235f4cf277186cad2ee8769f975119a2bbfc41b8932b88bd7/trec.py", line 140, in _split_generators
dl_files = dl_manager.download_and_extract(_URLs)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/download_manager.py", line 254, in download_and_extract
return self.extract(self.download(url_or_urls))
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/download_manager.py", line 179, in download
num_proc=download_config.num_proc,
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 225, in map_nested
_single_map_nested((function, obj, types, None, True)) for obj in tqdm(iterable, disable=disable_tqdm)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 225, in <listcomp>
_single_map_nested((function, obj, types, None, True)) for obj in tqdm(iterable, disable=disable_tqdm)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 163, in _single_map_nested
return function(data_struct)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/file_utils.py", line 308, in cached_path
use_etag=download_config.use_etag,
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/file_utils.py", line 475, in get_from_cache
raise ConnectionError("Couldn't reach {}".format(url))
ConnectionError: Couldn't reach http://cogcomp.org/Data/QA/QC/train_5500.label
```
I would appreciate some suggestions here. | 98 | Cannot load TREC dataset: ConnectionError
## Problem
I cannot load "trec" dataset, it results with ConnectionError as shown below. I've tried on both Google Colab and locally.
* `requests.head('http://cogcomp.org/Data/QA/QC/train_5500.label')` returns <Response [302]>.
* `requests.head('http://cogcomp.org/Data/QA/QC/train_5500.label', allow_redirects=True)` raises `requests.exceptions.TooManyRedirects: Exceeded 30 redirects.`
* Opening `http://cogcomp.org/Data/QA/QC/train_5500.label' in a browser works, but opens a different address
* Increasing max_redirects to 100 doesn't help
Also, while debugging I've seen that requesting 'https://storage.googleapis.com/huggingface-nlp/cache/datasets/trec/default/1.1.0/dataset_info.json' returns <Response [404]> before, but it doesn't raise any errors. Not sure if that's relevant.
* datasets.__version__ == '1.1.2'
* requests.__version__ == '2.24.0'
## Error trace
```
>>> import datasets
>>> datasets.__version__
'1.1.2'
>>> dataset = load_dataset("trec", split="train")
Using custom data configuration default
Downloading and preparing dataset trec/default (download: 350.79 KiB, generated: 403.39 KiB, post-processed: Unknown size, total: 754.18 KiB) to /home/przemyslaw/.cache/huggingface/datasets/trec/default/1.1.0/ca4248481ad244f235f4cf277186cad2ee8769f975119a2bbfc41b8932b88bd7...
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/load.py", line 611, in load_dataset
ignore_verifications=ignore_verifications,
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/builder.py", line 476, in download_and_prepare
dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/builder.py", line 531, in _download_and_prepare
split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
File "/home/przemyslaw/.cache/huggingface/modules/datasets_modules/datasets/trec/ca4248481ad244f235f4cf277186cad2ee8769f975119a2bbfc41b8932b88bd7/trec.py", line 140, in _split_generators
dl_files = dl_manager.download_and_extract(_URLs)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/download_manager.py", line 254, in download_and_extract
return self.extract(self.download(url_or_urls))
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/download_manager.py", line 179, in download
num_proc=download_config.num_proc,
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 225, in map_nested
_single_map_nested((function, obj, types, None, True)) for obj in tqdm(iterable, disable=disable_tqdm)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 225, in <listcomp>
_single_map_nested((function, obj, types, None, True)) for obj in tqdm(iterable, disable=disable_tqdm)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 163, in _single_map_nested
return function(data_struct)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/file_utils.py", line 308, in cached_path
use_etag=download_config.use_etag,
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/file_utils.py", line 475, in get_from_cache
raise ConnectionError("Couldn't reach {}".format(url))
ConnectionError: Couldn't reach http://cogcomp.org/Data/QA/QC/train_5500.label
```
I would appreciate some suggestions here.
Hi
thanks, but I did tried to install from the pip install git+... and it does
not work for me,. thanks for the help. I have the same issue with wmt16,
"ro-en"
thanks.
Best
Rabeeh
On Mon, Nov 16, 2020 at 10:29 AM Quentin Lhoest <[email protected]>
wrote:
> Actually it's already fixed on the master branch since #740
> <https://github.com/huggingface/datasets/pull/740>
> I'll do the 1.1.3 release soon
>
> —
> You are receiving this because you commented.
> Reply to this email directly, view it on GitHub
> <https://github.com/huggingface/datasets/issues/798#issuecomment-727854736>,
> or unsubscribe
> <https://github.com/notifications/unsubscribe-auth/ABP4ZCEUBJKPOCLABXCKMPDSQDWH3ANCNFSM4TJBUKSA>
> .
>
|
https://github.com/huggingface/datasets/issues/798 | Cannot load TREC dataset: ConnectionError | I just tested on google colab using
```python
!pip install git+https://github.com/huggingface/datasets.git
from datasets import load_dataset
load_dataset("trec")
```
and it works.
Can you detail how you got the issue even when using the latest version on master ?
Also about wmt we'll look into it, thanks for reporting ! | ## Problem
I cannot load "trec" dataset, it results with ConnectionError as shown below. I've tried on both Google Colab and locally.
* `requests.head('http://cogcomp.org/Data/QA/QC/train_5500.label')` returns <Response [302]>.
* `requests.head('http://cogcomp.org/Data/QA/QC/train_5500.label', allow_redirects=True)` raises `requests.exceptions.TooManyRedirects: Exceeded 30 redirects.`
* Opening `http://cogcomp.org/Data/QA/QC/train_5500.label' in a browser works, but opens a different address
* Increasing max_redirects to 100 doesn't help
Also, while debugging I've seen that requesting 'https://storage.googleapis.com/huggingface-nlp/cache/datasets/trec/default/1.1.0/dataset_info.json' returns <Response [404]> before, but it doesn't raise any errors. Not sure if that's relevant.
* datasets.__version__ == '1.1.2'
* requests.__version__ == '2.24.0'
## Error trace
```
>>> import datasets
>>> datasets.__version__
'1.1.2'
>>> dataset = load_dataset("trec", split="train")
Using custom data configuration default
Downloading and preparing dataset trec/default (download: 350.79 KiB, generated: 403.39 KiB, post-processed: Unknown size, total: 754.18 KiB) to /home/przemyslaw/.cache/huggingface/datasets/trec/default/1.1.0/ca4248481ad244f235f4cf277186cad2ee8769f975119a2bbfc41b8932b88bd7...
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/load.py", line 611, in load_dataset
ignore_verifications=ignore_verifications,
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/builder.py", line 476, in download_and_prepare
dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/builder.py", line 531, in _download_and_prepare
split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
File "/home/przemyslaw/.cache/huggingface/modules/datasets_modules/datasets/trec/ca4248481ad244f235f4cf277186cad2ee8769f975119a2bbfc41b8932b88bd7/trec.py", line 140, in _split_generators
dl_files = dl_manager.download_and_extract(_URLs)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/download_manager.py", line 254, in download_and_extract
return self.extract(self.download(url_or_urls))
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/download_manager.py", line 179, in download
num_proc=download_config.num_proc,
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 225, in map_nested
_single_map_nested((function, obj, types, None, True)) for obj in tqdm(iterable, disable=disable_tqdm)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 225, in <listcomp>
_single_map_nested((function, obj, types, None, True)) for obj in tqdm(iterable, disable=disable_tqdm)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 163, in _single_map_nested
return function(data_struct)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/file_utils.py", line 308, in cached_path
use_etag=download_config.use_etag,
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/file_utils.py", line 475, in get_from_cache
raise ConnectionError("Couldn't reach {}".format(url))
ConnectionError: Couldn't reach http://cogcomp.org/Data/QA/QC/train_5500.label
```
I would appreciate some suggestions here. | 48 | Cannot load TREC dataset: ConnectionError
## Problem
I cannot load "trec" dataset, it results with ConnectionError as shown below. I've tried on both Google Colab and locally.
* `requests.head('http://cogcomp.org/Data/QA/QC/train_5500.label')` returns <Response [302]>.
* `requests.head('http://cogcomp.org/Data/QA/QC/train_5500.label', allow_redirects=True)` raises `requests.exceptions.TooManyRedirects: Exceeded 30 redirects.`
* Opening `http://cogcomp.org/Data/QA/QC/train_5500.label' in a browser works, but opens a different address
* Increasing max_redirects to 100 doesn't help
Also, while debugging I've seen that requesting 'https://storage.googleapis.com/huggingface-nlp/cache/datasets/trec/default/1.1.0/dataset_info.json' returns <Response [404]> before, but it doesn't raise any errors. Not sure if that's relevant.
* datasets.__version__ == '1.1.2'
* requests.__version__ == '2.24.0'
## Error trace
```
>>> import datasets
>>> datasets.__version__
'1.1.2'
>>> dataset = load_dataset("trec", split="train")
Using custom data configuration default
Downloading and preparing dataset trec/default (download: 350.79 KiB, generated: 403.39 KiB, post-processed: Unknown size, total: 754.18 KiB) to /home/przemyslaw/.cache/huggingface/datasets/trec/default/1.1.0/ca4248481ad244f235f4cf277186cad2ee8769f975119a2bbfc41b8932b88bd7...
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/load.py", line 611, in load_dataset
ignore_verifications=ignore_verifications,
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/builder.py", line 476, in download_and_prepare
dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/builder.py", line 531, in _download_and_prepare
split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
File "/home/przemyslaw/.cache/huggingface/modules/datasets_modules/datasets/trec/ca4248481ad244f235f4cf277186cad2ee8769f975119a2bbfc41b8932b88bd7/trec.py", line 140, in _split_generators
dl_files = dl_manager.download_and_extract(_URLs)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/download_manager.py", line 254, in download_and_extract
return self.extract(self.download(url_or_urls))
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/download_manager.py", line 179, in download
num_proc=download_config.num_proc,
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 225, in map_nested
_single_map_nested((function, obj, types, None, True)) for obj in tqdm(iterable, disable=disable_tqdm)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 225, in <listcomp>
_single_map_nested((function, obj, types, None, True)) for obj in tqdm(iterable, disable=disable_tqdm)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 163, in _single_map_nested
return function(data_struct)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/file_utils.py", line 308, in cached_path
use_etag=download_config.use_etag,
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/file_utils.py", line 475, in get_from_cache
raise ConnectionError("Couldn't reach {}".format(url))
ConnectionError: Couldn't reach http://cogcomp.org/Data/QA/QC/train_5500.label
```
I would appreciate some suggestions here.
I just tested on google colab using
```python
!pip install git+https://github.com/huggingface/datasets.git
from datasets import load_dataset
load_dataset("trec")
```
and it works.
Can you detail how you got the issue even when using the latest version on master ?
Also about wmt we'll look into it, thanks for reporting ! |
https://github.com/huggingface/datasets/issues/798 | Cannot load TREC dataset: ConnectionError | I think the new url with .edu is also broken:
```
ConnectionError: Couldn't reach https://cogcomp.seas.upenn.edu/Data/QA/QC/train_5500.label
```
Cant download the dataset anymore. | ## Problem
I cannot load "trec" dataset, it results with ConnectionError as shown below. I've tried on both Google Colab and locally.
* `requests.head('http://cogcomp.org/Data/QA/QC/train_5500.label')` returns <Response [302]>.
* `requests.head('http://cogcomp.org/Data/QA/QC/train_5500.label', allow_redirects=True)` raises `requests.exceptions.TooManyRedirects: Exceeded 30 redirects.`
* Opening `http://cogcomp.org/Data/QA/QC/train_5500.label' in a browser works, but opens a different address
* Increasing max_redirects to 100 doesn't help
Also, while debugging I've seen that requesting 'https://storage.googleapis.com/huggingface-nlp/cache/datasets/trec/default/1.1.0/dataset_info.json' returns <Response [404]> before, but it doesn't raise any errors. Not sure if that's relevant.
* datasets.__version__ == '1.1.2'
* requests.__version__ == '2.24.0'
## Error trace
```
>>> import datasets
>>> datasets.__version__
'1.1.2'
>>> dataset = load_dataset("trec", split="train")
Using custom data configuration default
Downloading and preparing dataset trec/default (download: 350.79 KiB, generated: 403.39 KiB, post-processed: Unknown size, total: 754.18 KiB) to /home/przemyslaw/.cache/huggingface/datasets/trec/default/1.1.0/ca4248481ad244f235f4cf277186cad2ee8769f975119a2bbfc41b8932b88bd7...
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/load.py", line 611, in load_dataset
ignore_verifications=ignore_verifications,
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/builder.py", line 476, in download_and_prepare
dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/builder.py", line 531, in _download_and_prepare
split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
File "/home/przemyslaw/.cache/huggingface/modules/datasets_modules/datasets/trec/ca4248481ad244f235f4cf277186cad2ee8769f975119a2bbfc41b8932b88bd7/trec.py", line 140, in _split_generators
dl_files = dl_manager.download_and_extract(_URLs)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/download_manager.py", line 254, in download_and_extract
return self.extract(self.download(url_or_urls))
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/download_manager.py", line 179, in download
num_proc=download_config.num_proc,
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 225, in map_nested
_single_map_nested((function, obj, types, None, True)) for obj in tqdm(iterable, disable=disable_tqdm)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 225, in <listcomp>
_single_map_nested((function, obj, types, None, True)) for obj in tqdm(iterable, disable=disable_tqdm)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 163, in _single_map_nested
return function(data_struct)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/file_utils.py", line 308, in cached_path
use_etag=download_config.use_etag,
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/file_utils.py", line 475, in get_from_cache
raise ConnectionError("Couldn't reach {}".format(url))
ConnectionError: Couldn't reach http://cogcomp.org/Data/QA/QC/train_5500.label
```
I would appreciate some suggestions here. | 21 | Cannot load TREC dataset: ConnectionError
## Problem
I cannot load "trec" dataset, it results with ConnectionError as shown below. I've tried on both Google Colab and locally.
* `requests.head('http://cogcomp.org/Data/QA/QC/train_5500.label')` returns <Response [302]>.
* `requests.head('http://cogcomp.org/Data/QA/QC/train_5500.label', allow_redirects=True)` raises `requests.exceptions.TooManyRedirects: Exceeded 30 redirects.`
* Opening `http://cogcomp.org/Data/QA/QC/train_5500.label' in a browser works, but opens a different address
* Increasing max_redirects to 100 doesn't help
Also, while debugging I've seen that requesting 'https://storage.googleapis.com/huggingface-nlp/cache/datasets/trec/default/1.1.0/dataset_info.json' returns <Response [404]> before, but it doesn't raise any errors. Not sure if that's relevant.
* datasets.__version__ == '1.1.2'
* requests.__version__ == '2.24.0'
## Error trace
```
>>> import datasets
>>> datasets.__version__
'1.1.2'
>>> dataset = load_dataset("trec", split="train")
Using custom data configuration default
Downloading and preparing dataset trec/default (download: 350.79 KiB, generated: 403.39 KiB, post-processed: Unknown size, total: 754.18 KiB) to /home/przemyslaw/.cache/huggingface/datasets/trec/default/1.1.0/ca4248481ad244f235f4cf277186cad2ee8769f975119a2bbfc41b8932b88bd7...
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/load.py", line 611, in load_dataset
ignore_verifications=ignore_verifications,
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/builder.py", line 476, in download_and_prepare
dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/builder.py", line 531, in _download_and_prepare
split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
File "/home/przemyslaw/.cache/huggingface/modules/datasets_modules/datasets/trec/ca4248481ad244f235f4cf277186cad2ee8769f975119a2bbfc41b8932b88bd7/trec.py", line 140, in _split_generators
dl_files = dl_manager.download_and_extract(_URLs)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/download_manager.py", line 254, in download_and_extract
return self.extract(self.download(url_or_urls))
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/download_manager.py", line 179, in download
num_proc=download_config.num_proc,
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 225, in map_nested
_single_map_nested((function, obj, types, None, True)) for obj in tqdm(iterable, disable=disable_tqdm)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 225, in <listcomp>
_single_map_nested((function, obj, types, None, True)) for obj in tqdm(iterable, disable=disable_tqdm)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 163, in _single_map_nested
return function(data_struct)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/file_utils.py", line 308, in cached_path
use_etag=download_config.use_etag,
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/file_utils.py", line 475, in get_from_cache
raise ConnectionError("Couldn't reach {}".format(url))
ConnectionError: Couldn't reach http://cogcomp.org/Data/QA/QC/train_5500.label
```
I would appreciate some suggestions here.
I think the new url with .edu is also broken:
```
ConnectionError: Couldn't reach https://cogcomp.seas.upenn.edu/Data/QA/QC/train_5500.label
```
Cant download the dataset anymore. |
https://github.com/huggingface/datasets/issues/798 | Cannot load TREC dataset: ConnectionError | Hi ! The URL seems to work fine on my side, can you try again ? | ## Problem
I cannot load "trec" dataset, it results with ConnectionError as shown below. I've tried on both Google Colab and locally.
* `requests.head('http://cogcomp.org/Data/QA/QC/train_5500.label')` returns <Response [302]>.
* `requests.head('http://cogcomp.org/Data/QA/QC/train_5500.label', allow_redirects=True)` raises `requests.exceptions.TooManyRedirects: Exceeded 30 redirects.`
* Opening `http://cogcomp.org/Data/QA/QC/train_5500.label' in a browser works, but opens a different address
* Increasing max_redirects to 100 doesn't help
Also, while debugging I've seen that requesting 'https://storage.googleapis.com/huggingface-nlp/cache/datasets/trec/default/1.1.0/dataset_info.json' returns <Response [404]> before, but it doesn't raise any errors. Not sure if that's relevant.
* datasets.__version__ == '1.1.2'
* requests.__version__ == '2.24.0'
## Error trace
```
>>> import datasets
>>> datasets.__version__
'1.1.2'
>>> dataset = load_dataset("trec", split="train")
Using custom data configuration default
Downloading and preparing dataset trec/default (download: 350.79 KiB, generated: 403.39 KiB, post-processed: Unknown size, total: 754.18 KiB) to /home/przemyslaw/.cache/huggingface/datasets/trec/default/1.1.0/ca4248481ad244f235f4cf277186cad2ee8769f975119a2bbfc41b8932b88bd7...
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/load.py", line 611, in load_dataset
ignore_verifications=ignore_verifications,
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/builder.py", line 476, in download_and_prepare
dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/builder.py", line 531, in _download_and_prepare
split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
File "/home/przemyslaw/.cache/huggingface/modules/datasets_modules/datasets/trec/ca4248481ad244f235f4cf277186cad2ee8769f975119a2bbfc41b8932b88bd7/trec.py", line 140, in _split_generators
dl_files = dl_manager.download_and_extract(_URLs)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/download_manager.py", line 254, in download_and_extract
return self.extract(self.download(url_or_urls))
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/download_manager.py", line 179, in download
num_proc=download_config.num_proc,
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 225, in map_nested
_single_map_nested((function, obj, types, None, True)) for obj in tqdm(iterable, disable=disable_tqdm)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 225, in <listcomp>
_single_map_nested((function, obj, types, None, True)) for obj in tqdm(iterable, disable=disable_tqdm)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 163, in _single_map_nested
return function(data_struct)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/file_utils.py", line 308, in cached_path
use_etag=download_config.use_etag,
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/file_utils.py", line 475, in get_from_cache
raise ConnectionError("Couldn't reach {}".format(url))
ConnectionError: Couldn't reach http://cogcomp.org/Data/QA/QC/train_5500.label
```
I would appreciate some suggestions here. | 16 | Cannot load TREC dataset: ConnectionError
## Problem
I cannot load "trec" dataset, it results with ConnectionError as shown below. I've tried on both Google Colab and locally.
* `requests.head('http://cogcomp.org/Data/QA/QC/train_5500.label')` returns <Response [302]>.
* `requests.head('http://cogcomp.org/Data/QA/QC/train_5500.label', allow_redirects=True)` raises `requests.exceptions.TooManyRedirects: Exceeded 30 redirects.`
* Opening `http://cogcomp.org/Data/QA/QC/train_5500.label' in a browser works, but opens a different address
* Increasing max_redirects to 100 doesn't help
Also, while debugging I've seen that requesting 'https://storage.googleapis.com/huggingface-nlp/cache/datasets/trec/default/1.1.0/dataset_info.json' returns <Response [404]> before, but it doesn't raise any errors. Not sure if that's relevant.
* datasets.__version__ == '1.1.2'
* requests.__version__ == '2.24.0'
## Error trace
```
>>> import datasets
>>> datasets.__version__
'1.1.2'
>>> dataset = load_dataset("trec", split="train")
Using custom data configuration default
Downloading and preparing dataset trec/default (download: 350.79 KiB, generated: 403.39 KiB, post-processed: Unknown size, total: 754.18 KiB) to /home/przemyslaw/.cache/huggingface/datasets/trec/default/1.1.0/ca4248481ad244f235f4cf277186cad2ee8769f975119a2bbfc41b8932b88bd7...
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/load.py", line 611, in load_dataset
ignore_verifications=ignore_verifications,
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/builder.py", line 476, in download_and_prepare
dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/builder.py", line 531, in _download_and_prepare
split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
File "/home/przemyslaw/.cache/huggingface/modules/datasets_modules/datasets/trec/ca4248481ad244f235f4cf277186cad2ee8769f975119a2bbfc41b8932b88bd7/trec.py", line 140, in _split_generators
dl_files = dl_manager.download_and_extract(_URLs)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/download_manager.py", line 254, in download_and_extract
return self.extract(self.download(url_or_urls))
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/download_manager.py", line 179, in download
num_proc=download_config.num_proc,
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 225, in map_nested
_single_map_nested((function, obj, types, None, True)) for obj in tqdm(iterable, disable=disable_tqdm)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 225, in <listcomp>
_single_map_nested((function, obj, types, None, True)) for obj in tqdm(iterable, disable=disable_tqdm)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 163, in _single_map_nested
return function(data_struct)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/file_utils.py", line 308, in cached_path
use_etag=download_config.use_etag,
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/file_utils.py", line 475, in get_from_cache
raise ConnectionError("Couldn't reach {}".format(url))
ConnectionError: Couldn't reach http://cogcomp.org/Data/QA/QC/train_5500.label
```
I would appreciate some suggestions here.
Hi ! The URL seems to work fine on my side, can you try again ? |
https://github.com/huggingface/datasets/issues/798 | Cannot load TREC dataset: ConnectionError | Forgot to update, i wrote an email to the webmaster of seas.upenn.edu because i couldnt reach the url on any machine. This was the answer:
```
Thank you for your report. The server was offline for maintenance and is now available again.
```
Guess all back to normal now 🙂 | ## Problem
I cannot load "trec" dataset, it results with ConnectionError as shown below. I've tried on both Google Colab and locally.
* `requests.head('http://cogcomp.org/Data/QA/QC/train_5500.label')` returns <Response [302]>.
* `requests.head('http://cogcomp.org/Data/QA/QC/train_5500.label', allow_redirects=True)` raises `requests.exceptions.TooManyRedirects: Exceeded 30 redirects.`
* Opening `http://cogcomp.org/Data/QA/QC/train_5500.label' in a browser works, but opens a different address
* Increasing max_redirects to 100 doesn't help
Also, while debugging I've seen that requesting 'https://storage.googleapis.com/huggingface-nlp/cache/datasets/trec/default/1.1.0/dataset_info.json' returns <Response [404]> before, but it doesn't raise any errors. Not sure if that's relevant.
* datasets.__version__ == '1.1.2'
* requests.__version__ == '2.24.0'
## Error trace
```
>>> import datasets
>>> datasets.__version__
'1.1.2'
>>> dataset = load_dataset("trec", split="train")
Using custom data configuration default
Downloading and preparing dataset trec/default (download: 350.79 KiB, generated: 403.39 KiB, post-processed: Unknown size, total: 754.18 KiB) to /home/przemyslaw/.cache/huggingface/datasets/trec/default/1.1.0/ca4248481ad244f235f4cf277186cad2ee8769f975119a2bbfc41b8932b88bd7...
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/load.py", line 611, in load_dataset
ignore_verifications=ignore_verifications,
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/builder.py", line 476, in download_and_prepare
dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/builder.py", line 531, in _download_and_prepare
split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
File "/home/przemyslaw/.cache/huggingface/modules/datasets_modules/datasets/trec/ca4248481ad244f235f4cf277186cad2ee8769f975119a2bbfc41b8932b88bd7/trec.py", line 140, in _split_generators
dl_files = dl_manager.download_and_extract(_URLs)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/download_manager.py", line 254, in download_and_extract
return self.extract(self.download(url_or_urls))
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/download_manager.py", line 179, in download
num_proc=download_config.num_proc,
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 225, in map_nested
_single_map_nested((function, obj, types, None, True)) for obj in tqdm(iterable, disable=disable_tqdm)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 225, in <listcomp>
_single_map_nested((function, obj, types, None, True)) for obj in tqdm(iterable, disable=disable_tqdm)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 163, in _single_map_nested
return function(data_struct)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/file_utils.py", line 308, in cached_path
use_etag=download_config.use_etag,
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/file_utils.py", line 475, in get_from_cache
raise ConnectionError("Couldn't reach {}".format(url))
ConnectionError: Couldn't reach http://cogcomp.org/Data/QA/QC/train_5500.label
```
I would appreciate some suggestions here. | 50 | Cannot load TREC dataset: ConnectionError
## Problem
I cannot load "trec" dataset, it results with ConnectionError as shown below. I've tried on both Google Colab and locally.
* `requests.head('http://cogcomp.org/Data/QA/QC/train_5500.label')` returns <Response [302]>.
* `requests.head('http://cogcomp.org/Data/QA/QC/train_5500.label', allow_redirects=True)` raises `requests.exceptions.TooManyRedirects: Exceeded 30 redirects.`
* Opening `http://cogcomp.org/Data/QA/QC/train_5500.label' in a browser works, but opens a different address
* Increasing max_redirects to 100 doesn't help
Also, while debugging I've seen that requesting 'https://storage.googleapis.com/huggingface-nlp/cache/datasets/trec/default/1.1.0/dataset_info.json' returns <Response [404]> before, but it doesn't raise any errors. Not sure if that's relevant.
* datasets.__version__ == '1.1.2'
* requests.__version__ == '2.24.0'
## Error trace
```
>>> import datasets
>>> datasets.__version__
'1.1.2'
>>> dataset = load_dataset("trec", split="train")
Using custom data configuration default
Downloading and preparing dataset trec/default (download: 350.79 KiB, generated: 403.39 KiB, post-processed: Unknown size, total: 754.18 KiB) to /home/przemyslaw/.cache/huggingface/datasets/trec/default/1.1.0/ca4248481ad244f235f4cf277186cad2ee8769f975119a2bbfc41b8932b88bd7...
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/load.py", line 611, in load_dataset
ignore_verifications=ignore_verifications,
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/builder.py", line 476, in download_and_prepare
dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/builder.py", line 531, in _download_and_prepare
split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
File "/home/przemyslaw/.cache/huggingface/modules/datasets_modules/datasets/trec/ca4248481ad244f235f4cf277186cad2ee8769f975119a2bbfc41b8932b88bd7/trec.py", line 140, in _split_generators
dl_files = dl_manager.download_and_extract(_URLs)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/download_manager.py", line 254, in download_and_extract
return self.extract(self.download(url_or_urls))
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/download_manager.py", line 179, in download
num_proc=download_config.num_proc,
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 225, in map_nested
_single_map_nested((function, obj, types, None, True)) for obj in tqdm(iterable, disable=disable_tqdm)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 225, in <listcomp>
_single_map_nested((function, obj, types, None, True)) for obj in tqdm(iterable, disable=disable_tqdm)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/py_utils.py", line 163, in _single_map_nested
return function(data_struct)
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/file_utils.py", line 308, in cached_path
use_etag=download_config.use_etag,
File "/home/przemyslaw/.local/lib/python3.6/site-packages/datasets/utils/file_utils.py", line 475, in get_from_cache
raise ConnectionError("Couldn't reach {}".format(url))
ConnectionError: Couldn't reach http://cogcomp.org/Data/QA/QC/train_5500.label
```
I would appreciate some suggestions here.
Forgot to update, i wrote an email to the webmaster of seas.upenn.edu because i couldnt reach the url on any machine. This was the answer:
```
Thank you for your report. The server was offline for maintenance and is now available again.
```
Guess all back to normal now 🙂 |
https://github.com/huggingface/datasets/issues/792 | KILT dataset: empty string in triviaqa input field | Just found out about https://github.com/huggingface/datasets/blob/master/datasets/kilt_tasks/README.md
(Not very clear in https://huggingface.co/datasets/kilt_tasks links to http://github.com/huggingface/datasets/datasets/kilt_tasks/README.md which is dead, closing the issue though :)) | # What happened
Both train and test splits of the triviaqa dataset (part of the KILT benchmark) seem to have empty string in their input field (unlike the natural questions dataset, part of the same benchmark)
# Versions
KILT version is `1.0.0`
`datasets` version is `1.1.2`
[more here](https://gist.github.com/PaulLerner/3768c8d25f723edbac20d99b6a4056c1)
# How to reproduce
```py
In [1]: from datasets import load_dataset
In [4]: dataset = load_dataset("kilt_tasks")
# everything works fine, removed output for a better readibility
Dataset kilt_tasks downloaded and prepared to /people/lerner/.cache/huggingface/datasets/kilt_tasks/all_tasks/1.0.0/821c4295a2c35db2847585918d9c47d7f028f1a26b78825d8e77cd3aeb2621a1. Subsequent calls will reuse this data.
# empty string in triviaqa input field
In [36]: dataset['train_triviaqa'][0]
Out[36]:
{'id': 'dpql_5197',
'input': '',
'meta': {'left_context': '',
'mention': '',
'obj_surface': {'text': []},
'partial_evidence': {'end_paragraph_id': [],
'meta': [],
'section': [],
'start_paragraph_id': [],
'title': [],
'wikipedia_id': []},
'right_context': '',
'sub_surface': {'text': []},
'subj_aliases': {'text': []},
'template_questions': {'text': []}},
'output': {'answer': ['five £', '5 £', '£5', 'five £'],
'meta': [],
'provenance': [{'bleu_score': [1.0],
'end_character': [248],
'end_paragraph_id': [30],
'meta': [],
'section': ['Section::::Question of legal tender.\n'],
'start_character': [246],
'start_paragraph_id': [30],
'title': ['Banknotes of the pound sterling'],
'wikipedia_id': ['270680']}]}}
In [35]: dataset['train_triviaqa']['input'][:10]
Out[35]: ['', '', '', '', '', '', '', '', '', '']
# same with test set
In [37]: dataset['test_triviaqa']['input'][:10]
Out[37]: ['', '', '', '', '', '', '', '', '', '']
# works fine with natural questions
In [34]: dataset['train_nq']['input'][:10]
Out[34]:
['how i.met your mother who is the mother',
'who had the most wins in the nfl',
'who played mantis guardians of the galaxy 2',
'what channel is the premier league on in france',
"god's not dead a light in the darkness release date",
'who is the current president of un general assembly',
'when do the eclipse supposed to take place',
'what is the name of the sea surrounding dubai',
'who holds the nba record for most points in a career',
'when did the new maze runner movie come out']
```
Stay safe :) | 21 | KILT dataset: empty string in triviaqa input field
# What happened
Both train and test splits of the triviaqa dataset (part of the KILT benchmark) seem to have empty string in their input field (unlike the natural questions dataset, part of the same benchmark)
# Versions
KILT version is `1.0.0`
`datasets` version is `1.1.2`
[more here](https://gist.github.com/PaulLerner/3768c8d25f723edbac20d99b6a4056c1)
# How to reproduce
```py
In [1]: from datasets import load_dataset
In [4]: dataset = load_dataset("kilt_tasks")
# everything works fine, removed output for a better readibility
Dataset kilt_tasks downloaded and prepared to /people/lerner/.cache/huggingface/datasets/kilt_tasks/all_tasks/1.0.0/821c4295a2c35db2847585918d9c47d7f028f1a26b78825d8e77cd3aeb2621a1. Subsequent calls will reuse this data.
# empty string in triviaqa input field
In [36]: dataset['train_triviaqa'][0]
Out[36]:
{'id': 'dpql_5197',
'input': '',
'meta': {'left_context': '',
'mention': '',
'obj_surface': {'text': []},
'partial_evidence': {'end_paragraph_id': [],
'meta': [],
'section': [],
'start_paragraph_id': [],
'title': [],
'wikipedia_id': []},
'right_context': '',
'sub_surface': {'text': []},
'subj_aliases': {'text': []},
'template_questions': {'text': []}},
'output': {'answer': ['five £', '5 £', '£5', 'five £'],
'meta': [],
'provenance': [{'bleu_score': [1.0],
'end_character': [248],
'end_paragraph_id': [30],
'meta': [],
'section': ['Section::::Question of legal tender.\n'],
'start_character': [246],
'start_paragraph_id': [30],
'title': ['Banknotes of the pound sterling'],
'wikipedia_id': ['270680']}]}}
In [35]: dataset['train_triviaqa']['input'][:10]
Out[35]: ['', '', '', '', '', '', '', '', '', '']
# same with test set
In [37]: dataset['test_triviaqa']['input'][:10]
Out[37]: ['', '', '', '', '', '', '', '', '', '']
# works fine with natural questions
In [34]: dataset['train_nq']['input'][:10]
Out[34]:
['how i.met your mother who is the mother',
'who had the most wins in the nfl',
'who played mantis guardians of the galaxy 2',
'what channel is the premier league on in france',
"god's not dead a light in the darkness release date",
'who is the current president of un general assembly',
'when do the eclipse supposed to take place',
'what is the name of the sea surrounding dubai',
'who holds the nba record for most points in a career',
'when did the new maze runner movie come out']
```
Stay safe :)
Just found out about https://github.com/huggingface/datasets/blob/master/datasets/kilt_tasks/README.md
(Not very clear in https://huggingface.co/datasets/kilt_tasks links to http://github.com/huggingface/datasets/datasets/kilt_tasks/README.md which is dead, closing the issue though :)) |
https://github.com/huggingface/datasets/issues/790 | Error running pip install -e ".[dev]" on MacOS 10.13.6: faiss/python does not exist | I saw that `faiss-cpu` 1.6.4.post2 was released recently to fix the installation on macos. It should work now | I was following along with https://huggingface.co/docs/datasets/share_dataset.html#adding-tests-and-metadata-to-the-dataset when I ran into this error.
```sh
git clone https://github.com/huggingface/datasets
cd datasets
virtualenv venv -p python3 --system-site-packages
source venv/bin/activate
pip install -e ".[dev]"
```
Python 3.7.7
| 18 | Error running pip install -e ".[dev]" on MacOS 10.13.6: faiss/python does not exist
I was following along with https://huggingface.co/docs/datasets/share_dataset.html#adding-tests-and-metadata-to-the-dataset when I ran into this error.
```sh
git clone https://github.com/huggingface/datasets
cd datasets
virtualenv venv -p python3 --system-site-packages
source venv/bin/activate
pip install -e ".[dev]"
```
Python 3.7.7
I saw that `faiss-cpu` 1.6.4.post2 was released recently to fix the installation on macos. It should work now |
https://github.com/huggingface/datasets/issues/786 | feat(dataset): multiprocessing _generate_examples | I agree that would be cool :)
Right now the only distributed dataset builder is based on Apache Beam so you can use distributed processing frameworks like Dataflow, Spark, Flink etc. to build your dataset but it's not really well suited for single-worker parallel processing afaik | forking this out of #741, this issue is only regarding multiprocessing
I'd love if there was a dataset configuration parameter `workers`, where when it is `1` it behaves as it does right now, and when its `>1` maybe `_generate_examples` can also get the `pool` and return an iterable using the pool.
In my use case, I would instead of:
```python
for datum in data:
yield self.load_datum(datum)
```
do:
```python
return pool.map(self.load_datum, data)
```
As the dataset in question, as an example, has **only** 7000 rows, and takes 10 seconds to load each row on average, it takes almost 20 hours to load the entire dataset.
If this was a larger dataset (and many such datasets exist), it would take multiple days to complete.
Using multiprocessing, for example, 40 cores, could speed it up dramatically. For this dataset, hopefully to fully load in under an hour. | 46 | feat(dataset): multiprocessing _generate_examples
forking this out of #741, this issue is only regarding multiprocessing
I'd love if there was a dataset configuration parameter `workers`, where when it is `1` it behaves as it does right now, and when its `>1` maybe `_generate_examples` can also get the `pool` and return an iterable using the pool.
In my use case, I would instead of:
```python
for datum in data:
yield self.load_datum(datum)
```
do:
```python
return pool.map(self.load_datum, data)
```
As the dataset in question, as an example, has **only** 7000 rows, and takes 10 seconds to load each row on average, it takes almost 20 hours to load the entire dataset.
If this was a larger dataset (and many such datasets exist), it would take multiple days to complete.
Using multiprocessing, for example, 40 cores, could speed it up dramatically. For this dataset, hopefully to fully load in under an hour.
I agree that would be cool :)
Right now the only distributed dataset builder is based on Apache Beam so you can use distributed processing frameworks like Dataflow, Spark, Flink etc. to build your dataset but it's not really well suited for single-worker parallel processing afaik |
https://github.com/huggingface/datasets/issues/786 | feat(dataset): multiprocessing _generate_examples | `_generate_examples` can now be run in parallel thanks to https://github.com/huggingface/datasets/pull/5107. You can find more info [here](https://huggingface.co/docs/datasets/dataset_script#sharding). | forking this out of #741, this issue is only regarding multiprocessing
I'd love if there was a dataset configuration parameter `workers`, where when it is `1` it behaves as it does right now, and when its `>1` maybe `_generate_examples` can also get the `pool` and return an iterable using the pool.
In my use case, I would instead of:
```python
for datum in data:
yield self.load_datum(datum)
```
do:
```python
return pool.map(self.load_datum, data)
```
As the dataset in question, as an example, has **only** 7000 rows, and takes 10 seconds to load each row on average, it takes almost 20 hours to load the entire dataset.
If this was a larger dataset (and many such datasets exist), it would take multiple days to complete.
Using multiprocessing, for example, 40 cores, could speed it up dramatically. For this dataset, hopefully to fully load in under an hour. | 16 | feat(dataset): multiprocessing _generate_examples
forking this out of #741, this issue is only regarding multiprocessing
I'd love if there was a dataset configuration parameter `workers`, where when it is `1` it behaves as it does right now, and when its `>1` maybe `_generate_examples` can also get the `pool` and return an iterable using the pool.
In my use case, I would instead of:
```python
for datum in data:
yield self.load_datum(datum)
```
do:
```python
return pool.map(self.load_datum, data)
```
As the dataset in question, as an example, has **only** 7000 rows, and takes 10 seconds to load each row on average, it takes almost 20 hours to load the entire dataset.
If this was a larger dataset (and many such datasets exist), it would take multiple days to complete.
Using multiprocessing, for example, 40 cores, could speed it up dramatically. For this dataset, hopefully to fully load in under an hour.
`_generate_examples` can now be run in parallel thanks to https://github.com/huggingface/datasets/pull/5107. You can find more info [here](https://huggingface.co/docs/datasets/dataset_script#sharding). |
https://github.com/huggingface/datasets/issues/784 | Issue with downloading Wikipedia data for low resource language | Hello, maybe you could ty to use another date for the wikipedia dump (see the available [dates](https://dumps.wikimedia.org/jvwiki) here for `jv`) ? | Hi, I tried to download Sundanese and Javanese wikipedia data with the following snippet
```
jv_wiki = datasets.load_dataset('wikipedia', '20200501.jv', beam_runner='DirectRunner')
su_wiki = datasets.load_dataset('wikipedia', '20200501.su', beam_runner='DirectRunner')
```
And I get the following error for these two languages:
Javanese
```
FileNotFoundError: Couldn't find file at https://dumps.wikimedia.org/jvwiki/20200501/dumpstatus.json
```
Sundanese
```
FileNotFoundError: Couldn't find file at https://dumps.wikimedia.org/suwiki/20200501/dumpstatus.json
```
I found from https://github.com/huggingface/datasets/issues/577#issuecomment-688435085 that for small languages, they are directly downloaded and parsed from the Wikipedia dump site, but both of `https://dumps.wikimedia.org/jvwiki/20200501/dumpstatus.json` and `https://dumps.wikimedia.org/suwiki/20200501/dumpstatus.json` are no longer valid.
Any suggestions on how to handle this issue? Thanks! | 21 | Issue with downloading Wikipedia data for low resource language
Hi, I tried to download Sundanese and Javanese wikipedia data with the following snippet
```
jv_wiki = datasets.load_dataset('wikipedia', '20200501.jv', beam_runner='DirectRunner')
su_wiki = datasets.load_dataset('wikipedia', '20200501.su', beam_runner='DirectRunner')
```
And I get the following error for these two languages:
Javanese
```
FileNotFoundError: Couldn't find file at https://dumps.wikimedia.org/jvwiki/20200501/dumpstatus.json
```
Sundanese
```
FileNotFoundError: Couldn't find file at https://dumps.wikimedia.org/suwiki/20200501/dumpstatus.json
```
I found from https://github.com/huggingface/datasets/issues/577#issuecomment-688435085 that for small languages, they are directly downloaded and parsed from the Wikipedia dump site, but both of `https://dumps.wikimedia.org/jvwiki/20200501/dumpstatus.json` and `https://dumps.wikimedia.org/suwiki/20200501/dumpstatus.json` are no longer valid.
Any suggestions on how to handle this issue? Thanks!
Hello, maybe you could ty to use another date for the wikipedia dump (see the available [dates](https://dumps.wikimedia.org/jvwiki) here for `jv`) ? |
https://github.com/huggingface/datasets/issues/784 | Issue with downloading Wikipedia data for low resource language | @lhoestq
I've tried `load_dataset('wikipedia', '20200501.zh', beam_runner='DirectRunner')` and got the same `FileNotFoundError` as @SamuelCahyawijaya.
Also, using another date (e.g. `load_dataset('wikipedia', '20201120.zh', beam_runner='DirectRunner')`) will give the following error message.
```
ValueError: BuilderConfig 20201120.zh not found. Available: ['20200501.aa', '20200501.ab', '20200501.ace', '20200501.ady', '20200501.af', '20200501.ak', '20200501.als', '20200501.am', '20200501.an', '20200501.ang', '20200501.ar', '20200501.arc', '20200501.arz', '20200501.as', '20200501.ast', '20200501.atj', '20200501.av', '20200501.ay', '20200501.az', '20200501.azb', '20200501.ba', '20200501.bar', '20200501.bat-smg', '20200501.bcl', '20200501.be', '20200501.be-x-old', '20200501.bg', '20200501.bh', '20200501.bi', '20200501.bjn', '20200501.bm', '20200501.bn', '20200501.bo', '20200501.bpy', '20200501.br', '20200501.bs', '20200501.bug', '20200501.bxr', '20200501.ca', '20200501.cbk-zam', '20200501.cdo', '20200501.ce', '20200501.ceb', '20200501.ch', '20200501.cho', '20200501.chr', '20200501.chy', '20200501.ckb', '20200501.co', '20200501.cr', '20200501.crh', '20200501.cs', '20200501.csb', '20200501.cu', '20200501.cv', '20200501.cy', '20200501.da', '20200501.de', '20200501.din', '20200501.diq', '20200501.dsb', '20200501.dty', '20200501.dv', '20200501.dz', '20200501.ee', '20200501.el', '20200501.eml', '20200501.en', '20200501.eo', '20200501.es', '20200501.et', '20200501.eu', '20200501.ext', '20200501.fa', '20200501.ff', '20200501.fi', '20200501.fiu-vro', '20200501.fj', '20200501.fo', '20200501.fr', '20200501.frp', '20200501.frr', '20200501.fur', '20200501.fy', '20200501.ga', '20200501.gag', '20200501.gan', '20200501.gd', '20200501.gl', '20200501.glk', '20200501.gn', '20200501.gom', '20200501.gor', '20200501.got', '20200501.gu', '20200501.gv', '20200501.ha', '20200501.hak', '20200501.haw', '20200501.he', '20200501.hi', '20200501.hif', '20200501.ho', '20200501.hr', '20200501.hsb', '20200501.ht', '20200501.hu', '20200501.hy', '20200501.ia', '20200501.id', '20200501.ie', '20200501.ig', '20200501.ii', '20200501.ik', '20200501.ilo', '20200501.inh', '20200501.io', '20200501.is', '20200501.it', '20200501.iu', '20200501.ja', '20200501.jam', '20200501.jbo', '20200501.jv', '20200501.ka', '20200501.kaa', '20200501.kab', '20200501.kbd', '20200501.kbp', '20200501.kg', '20200501.ki', '20200501.kj', '20200501.kk', '20200501.kl', '20200501.km', '20200501.kn', '20200501.ko', '20200501.koi', '20200501.krc', '20200501.ks', '20200501.ksh', '20200501.ku', '20200501.kv', '20200501.kw', '20200501.ky', '20200501.la', '20200501.lad', '20200501.lb', '20200501.lbe', '20200501.lez', '20200501.lfn', '20200501.lg', '20200501.li', '20200501.lij', '20200501.lmo', '20200501.ln', '20200501.lo', '20200501.lrc', '20200501.lt', '20200501.ltg', '20200501.lv', '20200501.mai', '20200501.map-bms', '20200501.mdf', '20200501.mg', '20200501.mh', '20200501.mhr', '20200501.mi', '20200501.min', '20200501.mk', '20200501.ml', '20200501.mn', '20200501.mr', '20200501.mrj', '20200501.ms', '20200501.mt', '20200501.mus', '20200501.mwl', '20200501.my', '20200501.myv', '20200501.mzn', '20200501.na', '20200501.nah', '20200501.nap', '20200501.nds', '20200501.nds-nl', '20200501.ne', '20200501.new', '20200501.ng', '20200501.nl', '20200501.nn', '20200501.no', '20200501.nov', '20200501.nrm', '20200501.nso', '20200501.nv', '20200501.ny', '20200501.oc', '20200501.olo', '20200501.om', '20200501.or', '20200501.os', '20200501.pa', '20200501.pag', '20200501.pam', '20200501.pap', '20200501.pcd', '20200501.pdc', '20200501.pfl', '20200501.pi', '20200501.pih', '20200501.pl', '20200501.pms', '20200501.pnb', '20200501.pnt', '20200501.ps', '20200501.pt', '20200501.qu', '20200501.rm', '20200501.rmy', '20200501.rn', '20200501.ro', '20200501.roa-rup', '20200501.roa-tara', '20200501.ru', '20200501.rue', '20200501.rw', '20200501.sa', '20200501.sah', '20200501.sat', '20200501.sc', '20200501.scn', '20200501.sco', '20200501.sd', '20200501.se', '20200501.sg', '20200501.sh', '20200501.si', '20200501.simple', '20200501.sk', '20200501.sl', '20200501.sm', '20200501.sn', '20200501.so', '20200501.sq', '20200501.sr', '20200501.srn', '20200501.ss', '20200501.st', '20200501.stq', '20200501.su', '20200501.sv', '20200501.sw', '20200501.szl', '20200501.ta', '20200501.tcy', '20200501.te', '20200501.tet', '20200501.tg', '20200501.th', '20200501.ti', '20200501.tk', '20200501.tl', '20200501.tn', '20200501.to', '20200501.tpi', '20200501.tr', '20200501.ts', '20200501.tt', '20200501.tum', '20200501.tw', '20200501.ty', '20200501.tyv', '20200501.udm', '20200501.ug', '20200501.uk', '20200501.ur', '20200501.uz', '20200501.ve', '20200501.vec', '20200501.vep', '20200501.vi', '20200501.vls', '20200501.vo', '20200501.wa', '20200501.war', '20200501.wo', '20200501.wuu', '20200501.xal', '20200501.xh', '20200501.xmf', '20200501.yi', '20200501.yo', '20200501.za', '20200501.zea', '20200501.zh', '20200501.zh-classical', '20200501.zh-min-nan', '20200501.zh-yue', '20200501.zu']
```
I am pretty sure that `https://dumps.wikimedia.org/enwiki/20201120/dumpstatus.json` exists. | Hi, I tried to download Sundanese and Javanese wikipedia data with the following snippet
```
jv_wiki = datasets.load_dataset('wikipedia', '20200501.jv', beam_runner='DirectRunner')
su_wiki = datasets.load_dataset('wikipedia', '20200501.su', beam_runner='DirectRunner')
```
And I get the following error for these two languages:
Javanese
```
FileNotFoundError: Couldn't find file at https://dumps.wikimedia.org/jvwiki/20200501/dumpstatus.json
```
Sundanese
```
FileNotFoundError: Couldn't find file at https://dumps.wikimedia.org/suwiki/20200501/dumpstatus.json
```
I found from https://github.com/huggingface/datasets/issues/577#issuecomment-688435085 that for small languages, they are directly downloaded and parsed from the Wikipedia dump site, but both of `https://dumps.wikimedia.org/jvwiki/20200501/dumpstatus.json` and `https://dumps.wikimedia.org/suwiki/20200501/dumpstatus.json` are no longer valid.
Any suggestions on how to handle this issue? Thanks! | 342 | Issue with downloading Wikipedia data for low resource language
Hi, I tried to download Sundanese and Javanese wikipedia data with the following snippet
```
jv_wiki = datasets.load_dataset('wikipedia', '20200501.jv', beam_runner='DirectRunner')
su_wiki = datasets.load_dataset('wikipedia', '20200501.su', beam_runner='DirectRunner')
```
And I get the following error for these two languages:
Javanese
```
FileNotFoundError: Couldn't find file at https://dumps.wikimedia.org/jvwiki/20200501/dumpstatus.json
```
Sundanese
```
FileNotFoundError: Couldn't find file at https://dumps.wikimedia.org/suwiki/20200501/dumpstatus.json
```
I found from https://github.com/huggingface/datasets/issues/577#issuecomment-688435085 that for small languages, they are directly downloaded and parsed from the Wikipedia dump site, but both of `https://dumps.wikimedia.org/jvwiki/20200501/dumpstatus.json` and `https://dumps.wikimedia.org/suwiki/20200501/dumpstatus.json` are no longer valid.
Any suggestions on how to handle this issue? Thanks!
@lhoestq
I've tried `load_dataset('wikipedia', '20200501.zh', beam_runner='DirectRunner')` and got the same `FileNotFoundError` as @SamuelCahyawijaya.
Also, using another date (e.g. `load_dataset('wikipedia', '20201120.zh', beam_runner='DirectRunner')`) will give the following error message.
```
ValueError: BuilderConfig 20201120.zh not found. Available: ['20200501.aa', '20200501.ab', '20200501.ace', '20200501.ady', '20200501.af', '20200501.ak', '20200501.als', '20200501.am', '20200501.an', '20200501.ang', '20200501.ar', '20200501.arc', '20200501.arz', '20200501.as', '20200501.ast', '20200501.atj', '20200501.av', '20200501.ay', '20200501.az', '20200501.azb', '20200501.ba', '20200501.bar', '20200501.bat-smg', '20200501.bcl', '20200501.be', '20200501.be-x-old', '20200501.bg', '20200501.bh', '20200501.bi', '20200501.bjn', '20200501.bm', '20200501.bn', '20200501.bo', '20200501.bpy', '20200501.br', '20200501.bs', '20200501.bug', '20200501.bxr', '20200501.ca', '20200501.cbk-zam', '20200501.cdo', '20200501.ce', '20200501.ceb', '20200501.ch', '20200501.cho', '20200501.chr', '20200501.chy', '20200501.ckb', '20200501.co', '20200501.cr', '20200501.crh', '20200501.cs', '20200501.csb', '20200501.cu', '20200501.cv', '20200501.cy', '20200501.da', '20200501.de', '20200501.din', '20200501.diq', '20200501.dsb', '20200501.dty', '20200501.dv', '20200501.dz', '20200501.ee', '20200501.el', '20200501.eml', '20200501.en', '20200501.eo', '20200501.es', '20200501.et', '20200501.eu', '20200501.ext', '20200501.fa', '20200501.ff', '20200501.fi', '20200501.fiu-vro', '20200501.fj', '20200501.fo', '20200501.fr', '20200501.frp', '20200501.frr', '20200501.fur', '20200501.fy', '20200501.ga', '20200501.gag', '20200501.gan', '20200501.gd', '20200501.gl', '20200501.glk', '20200501.gn', '20200501.gom', '20200501.gor', '20200501.got', '20200501.gu', '20200501.gv', '20200501.ha', '20200501.hak', '20200501.haw', '20200501.he', '20200501.hi', '20200501.hif', '20200501.ho', '20200501.hr', '20200501.hsb', '20200501.ht', '20200501.hu', '20200501.hy', '20200501.ia', '20200501.id', '20200501.ie', '20200501.ig', '20200501.ii', '20200501.ik', '20200501.ilo', '20200501.inh', '20200501.io', '20200501.is', '20200501.it', '20200501.iu', '20200501.ja', '20200501.jam', '20200501.jbo', '20200501.jv', '20200501.ka', '20200501.kaa', '20200501.kab', '20200501.kbd', '20200501.kbp', '20200501.kg', '20200501.ki', '20200501.kj', '20200501.kk', '20200501.kl', '20200501.km', '20200501.kn', '20200501.ko', '20200501.koi', '20200501.krc', '20200501.ks', '20200501.ksh', '20200501.ku', '20200501.kv', '20200501.kw', '20200501.ky', '20200501.la', '20200501.lad', '20200501.lb', '20200501.lbe', '20200501.lez', '20200501.lfn', '20200501.lg', '20200501.li', '20200501.lij', '20200501.lmo', '20200501.ln', '20200501.lo', '20200501.lrc', '20200501.lt', '20200501.ltg', '20200501.lv', '20200501.mai', '20200501.map-bms', '20200501.mdf', '20200501.mg', '20200501.mh', '20200501.mhr', '20200501.mi', '20200501.min', '20200501.mk', '20200501.ml', '20200501.mn', '20200501.mr', '20200501.mrj', '20200501.ms', '20200501.mt', '20200501.mus', '20200501.mwl', '20200501.my', '20200501.myv', '20200501.mzn', '20200501.na', '20200501.nah', '20200501.nap', '20200501.nds', '20200501.nds-nl', '20200501.ne', '20200501.new', '20200501.ng', '20200501.nl', '20200501.nn', '20200501.no', '20200501.nov', '20200501.nrm', '20200501.nso', '20200501.nv', '20200501.ny', '20200501.oc', '20200501.olo', '20200501.om', '20200501.or', '20200501.os', '20200501.pa', '20200501.pag', '20200501.pam', '20200501.pap', '20200501.pcd', '20200501.pdc', '20200501.pfl', '20200501.pi', '20200501.pih', '20200501.pl', '20200501.pms', '20200501.pnb', '20200501.pnt', '20200501.ps', '20200501.pt', '20200501.qu', '20200501.rm', '20200501.rmy', '20200501.rn', '20200501.ro', '20200501.roa-rup', '20200501.roa-tara', '20200501.ru', '20200501.rue', '20200501.rw', '20200501.sa', '20200501.sah', '20200501.sat', '20200501.sc', '20200501.scn', '20200501.sco', '20200501.sd', '20200501.se', '20200501.sg', '20200501.sh', '20200501.si', '20200501.simple', '20200501.sk', '20200501.sl', '20200501.sm', '20200501.sn', '20200501.so', '20200501.sq', '20200501.sr', '20200501.srn', '20200501.ss', '20200501.st', '20200501.stq', '20200501.su', '20200501.sv', '20200501.sw', '20200501.szl', '20200501.ta', '20200501.tcy', '20200501.te', '20200501.tet', '20200501.tg', '20200501.th', '20200501.ti', '20200501.tk', '20200501.tl', '20200501.tn', '20200501.to', '20200501.tpi', '20200501.tr', '20200501.ts', '20200501.tt', '20200501.tum', '20200501.tw', '20200501.ty', '20200501.tyv', '20200501.udm', '20200501.ug', '20200501.uk', '20200501.ur', '20200501.uz', '20200501.ve', '20200501.vec', '20200501.vep', '20200501.vi', '20200501.vls', '20200501.vo', '20200501.wa', '20200501.war', '20200501.wo', '20200501.wuu', '20200501.xal', '20200501.xh', '20200501.xmf', '20200501.yi', '20200501.yo', '20200501.za', '20200501.zea', '20200501.zh', '20200501.zh-classical', '20200501.zh-min-nan', '20200501.zh-yue', '20200501.zu']
```
I am pretty sure that `https://dumps.wikimedia.org/enwiki/20201120/dumpstatus.json` exists. |
https://github.com/huggingface/datasets/issues/784 | Issue with downloading Wikipedia data for low resource language | For posterity, here's how I got the data I needed: I needed Bengali, so I had to check which dumps are available here: https://dumps.wikimedia.org/bnwiki/ , then I ran:
```
load_dataset("wikipedia", language="bn", date="20211101",
beam_runner="DirectRunner")
``` | Hi, I tried to download Sundanese and Javanese wikipedia data with the following snippet
```
jv_wiki = datasets.load_dataset('wikipedia', '20200501.jv', beam_runner='DirectRunner')
su_wiki = datasets.load_dataset('wikipedia', '20200501.su', beam_runner='DirectRunner')
```
And I get the following error for these two languages:
Javanese
```
FileNotFoundError: Couldn't find file at https://dumps.wikimedia.org/jvwiki/20200501/dumpstatus.json
```
Sundanese
```
FileNotFoundError: Couldn't find file at https://dumps.wikimedia.org/suwiki/20200501/dumpstatus.json
```
I found from https://github.com/huggingface/datasets/issues/577#issuecomment-688435085 that for small languages, they are directly downloaded and parsed from the Wikipedia dump site, but both of `https://dumps.wikimedia.org/jvwiki/20200501/dumpstatus.json` and `https://dumps.wikimedia.org/suwiki/20200501/dumpstatus.json` are no longer valid.
Any suggestions on how to handle this issue? Thanks! | 34 | Issue with downloading Wikipedia data for low resource language
Hi, I tried to download Sundanese and Javanese wikipedia data with the following snippet
```
jv_wiki = datasets.load_dataset('wikipedia', '20200501.jv', beam_runner='DirectRunner')
su_wiki = datasets.load_dataset('wikipedia', '20200501.su', beam_runner='DirectRunner')
```
And I get the following error for these two languages:
Javanese
```
FileNotFoundError: Couldn't find file at https://dumps.wikimedia.org/jvwiki/20200501/dumpstatus.json
```
Sundanese
```
FileNotFoundError: Couldn't find file at https://dumps.wikimedia.org/suwiki/20200501/dumpstatus.json
```
I found from https://github.com/huggingface/datasets/issues/577#issuecomment-688435085 that for small languages, they are directly downloaded and parsed from the Wikipedia dump site, but both of `https://dumps.wikimedia.org/jvwiki/20200501/dumpstatus.json` and `https://dumps.wikimedia.org/suwiki/20200501/dumpstatus.json` are no longer valid.
Any suggestions on how to handle this issue? Thanks!
For posterity, here's how I got the data I needed: I needed Bengali, so I had to check which dumps are available here: https://dumps.wikimedia.org/bnwiki/ , then I ran:
```
load_dataset("wikipedia", language="bn", date="20211101",
beam_runner="DirectRunner")
``` |
https://github.com/huggingface/datasets/issues/778 | Unexpected behavior when loading cached csv file? | Hi ! Thanks for reporting.
The same issue was reported in #730 (but with the encodings instead of the delimiter). It was fixed by #770 .
The fix will be available in the next release :) | I read a csv file from disk and forgot so specify the right delimiter. When i read the csv file again specifying the right delimiter it had no effect since it was using the cached dataset. I am not sure if this is unwanted behavior since i can always specify `download_mode="force_redownload"`. But i think it would be nice if the information what `delimiter` or what `column_names` were used would influence the identifier of the cached dataset.
Small snippet to reproduce the behavior:
```python
import datasets
with open("dummy_data.csv", "w") as file:
file.write("test,this;text\n")
print(datasets.load_dataset("csv", data_files="dummy_data.csv", split="train").column_names)
# ["test", "this;text"]
print(datasets.load_dataset("csv", data_files="dummy_data.csv", split="train", delimiter=";").column_names)
# still ["test", "this;text"]
```
By the way, thanks a lot for this amazing library! :) | 36 | Unexpected behavior when loading cached csv file?
I read a csv file from disk and forgot so specify the right delimiter. When i read the csv file again specifying the right delimiter it had no effect since it was using the cached dataset. I am not sure if this is unwanted behavior since i can always specify `download_mode="force_redownload"`. But i think it would be nice if the information what `delimiter` or what `column_names` were used would influence the identifier of the cached dataset.
Small snippet to reproduce the behavior:
```python
import datasets
with open("dummy_data.csv", "w") as file:
file.write("test,this;text\n")
print(datasets.load_dataset("csv", data_files="dummy_data.csv", split="train").column_names)
# ["test", "this;text"]
print(datasets.load_dataset("csv", data_files="dummy_data.csv", split="train", delimiter=";").column_names)
# still ["test", "this;text"]
```
By the way, thanks a lot for this amazing library! :)
Hi ! Thanks for reporting.
The same issue was reported in #730 (but with the encodings instead of the delimiter). It was fixed by #770 .
The fix will be available in the next release :) |
https://github.com/huggingface/datasets/issues/778 | Unexpected behavior when loading cached csv file? | Thanks for the prompt reply and terribly sorry for the spam!
Looking forward to the new release! | I read a csv file from disk and forgot so specify the right delimiter. When i read the csv file again specifying the right delimiter it had no effect since it was using the cached dataset. I am not sure if this is unwanted behavior since i can always specify `download_mode="force_redownload"`. But i think it would be nice if the information what `delimiter` or what `column_names` were used would influence the identifier of the cached dataset.
Small snippet to reproduce the behavior:
```python
import datasets
with open("dummy_data.csv", "w") as file:
file.write("test,this;text\n")
print(datasets.load_dataset("csv", data_files="dummy_data.csv", split="train").column_names)
# ["test", "this;text"]
print(datasets.load_dataset("csv", data_files="dummy_data.csv", split="train", delimiter=";").column_names)
# still ["test", "this;text"]
```
By the way, thanks a lot for this amazing library! :) | 17 | Unexpected behavior when loading cached csv file?
I read a csv file from disk and forgot so specify the right delimiter. When i read the csv file again specifying the right delimiter it had no effect since it was using the cached dataset. I am not sure if this is unwanted behavior since i can always specify `download_mode="force_redownload"`. But i think it would be nice if the information what `delimiter` or what `column_names` were used would influence the identifier of the cached dataset.
Small snippet to reproduce the behavior:
```python
import datasets
with open("dummy_data.csv", "w") as file:
file.write("test,this;text\n")
print(datasets.load_dataset("csv", data_files="dummy_data.csv", split="train").column_names)
# ["test", "this;text"]
print(datasets.load_dataset("csv", data_files="dummy_data.csv", split="train", delimiter=";").column_names)
# still ["test", "this;text"]
```
By the way, thanks a lot for this amazing library! :)
Thanks for the prompt reply and terribly sorry for the spam!
Looking forward to the new release! |
https://github.com/huggingface/datasets/issues/773 | Adding CC-100: Monolingual Datasets from Web Crawl Data | These dataset files are no longer available. https://data.statmt.org/cc-100/ files provided in this link are no longer available. Can anybody fix that issue?
@abhishekkrthakur @yjernite | ## Adding a Dataset
- **Name:** CC-100: Monolingual Datasets from Web Crawl Data
- **Description:** https://twitter.com/alex_conneau/status/1321507120848625665
- **Paper:** https://arxiv.org/abs/1911.02116
- **Data:** http://data.statmt.org/cc-100/
- **Motivation:** A large scale multi-lingual language modeling dataset. Text is de-duplicated and filtered by how "Wikipedia-like" it is, hopefully helping avoid some of the worst parts of the common crawl.
Instructions to add a new dataset can be found [here](https://huggingface.co/docs/datasets/share_dataset.html).
| 24 | Adding CC-100: Monolingual Datasets from Web Crawl Data
## Adding a Dataset
- **Name:** CC-100: Monolingual Datasets from Web Crawl Data
- **Description:** https://twitter.com/alex_conneau/status/1321507120848625665
- **Paper:** https://arxiv.org/abs/1911.02116
- **Data:** http://data.statmt.org/cc-100/
- **Motivation:** A large scale multi-lingual language modeling dataset. Text is de-duplicated and filtered by how "Wikipedia-like" it is, hopefully helping avoid some of the worst parts of the common crawl.
Instructions to add a new dataset can be found [here](https://huggingface.co/docs/datasets/share_dataset.html).
These dataset files are no longer available. https://data.statmt.org/cc-100/ files provided in this link are no longer available. Can anybody fix that issue?
@abhishekkrthakur @yjernite |
https://github.com/huggingface/datasets/issues/773 | Adding CC-100: Monolingual Datasets from Web Crawl Data | Hi ! Can you open an issue to report this problem ? This will help keep track of the fix :) | ## Adding a Dataset
- **Name:** CC-100: Monolingual Datasets from Web Crawl Data
- **Description:** https://twitter.com/alex_conneau/status/1321507120848625665
- **Paper:** https://arxiv.org/abs/1911.02116
- **Data:** http://data.statmt.org/cc-100/
- **Motivation:** A large scale multi-lingual language modeling dataset. Text is de-duplicated and filtered by how "Wikipedia-like" it is, hopefully helping avoid some of the worst parts of the common crawl.
Instructions to add a new dataset can be found [here](https://huggingface.co/docs/datasets/share_dataset.html).
| 21 | Adding CC-100: Monolingual Datasets from Web Crawl Data
## Adding a Dataset
- **Name:** CC-100: Monolingual Datasets from Web Crawl Data
- **Description:** https://twitter.com/alex_conneau/status/1321507120848625665
- **Paper:** https://arxiv.org/abs/1911.02116
- **Data:** http://data.statmt.org/cc-100/
- **Motivation:** A large scale multi-lingual language modeling dataset. Text is de-duplicated and filtered by how "Wikipedia-like" it is, hopefully helping avoid some of the worst parts of the common crawl.
Instructions to add a new dataset can be found [here](https://huggingface.co/docs/datasets/share_dataset.html).
Hi ! Can you open an issue to report this problem ? This will help keep track of the fix :) |
https://github.com/huggingface/datasets/issues/771 | Using `Dataset.map` with `n_proc>1` print multiple progress bars | Yes it allows to monitor the speed of each process. Currently each process takes care of one shard of the dataset.
At one point we can consider using streaming batches to a pool of processes instead of sharding the dataset in `num_proc` parts. At that point it will be easy to use only one progress bar | When using `Dataset.map` with `n_proc > 1`, only one of the processes should print a progress bar (to make the output readable). Right now, `n_proc` progress bars are printed. | 56 | Using `Dataset.map` with `n_proc>1` print multiple progress bars
When using `Dataset.map` with `n_proc > 1`, only one of the processes should print a progress bar (to make the output readable). Right now, `n_proc` progress bars are printed.
Yes it allows to monitor the speed of each process. Currently each process takes care of one shard of the dataset.
At one point we can consider using streaming batches to a pool of processes instead of sharding the dataset in `num_proc` parts. At that point it will be easy to use only one progress bar |
https://github.com/huggingface/datasets/issues/771 | Using `Dataset.map` with `n_proc>1` print multiple progress bars | Hi @lhoestq, I am facing a similar issue, it is annoying when lots of progress bars are printed. Is there a way to turn off this behavior? | When using `Dataset.map` with `n_proc > 1`, only one of the processes should print a progress bar (to make the output readable). Right now, `n_proc` progress bars are printed. | 27 | Using `Dataset.map` with `n_proc>1` print multiple progress bars
When using `Dataset.map` with `n_proc > 1`, only one of the processes should print a progress bar (to make the output readable). Right now, `n_proc` progress bars are printed.
Hi @lhoestq, I am facing a similar issue, it is annoying when lots of progress bars are printed. Is there a way to turn off this behavior? |
https://github.com/huggingface/datasets/issues/769 | How to choose proper download_mode in function load_dataset? | `download_mode=datasets.GenerateMode.FORCE_REDOWNLOAD` should work.
This makes me think we we should rename this to DownloadMode.FORCE_REDOWNLOAD. Currently that's confusing | Hi, I am a beginner to datasets and I try to use datasets to load my csv file.
my csv file looks like this
```
text,label
"Effective but too-tepid biopic",3
"If you sometimes like to go to the movies to have fun , Wasabi is a good place to start .",4
"Emerges as something rare , an issue movie that 's so honest and keenly observed that it does n't feel like one .",5
```
First I try to use this command to load my csv file .
``` python
dataset=load_dataset('csv', data_files=['sst_test.csv'])
```
It seems good, but when i try to overwrite the convert_options to convert 'label' columns from int64 to float32 like this.
``` python
import pyarrow as pa
from pyarrow import csv
read_options = csv.ReadOptions(block_size=1024*1024)
parse_options = csv.ParseOptions()
convert_options = csv.ConvertOptions(column_types={'text': pa.string(), 'label': pa.float32()})
dataset = load_dataset('csv', data_files=['sst_test.csv'], read_options=read_options,
parse_options=parse_options, convert_options=convert_options)
```
It keeps the same:
```shell
Dataset(features: {'text': Value(dtype='string', id=None), 'label': Value(dtype='int64', id=None)}, num_rows: 2210)
```
I think this issue is caused by the parameter "download_mode" Default to REUSE_DATASET_IF_EXISTS because after I delete the cache_dir, it seems right.
Is it a bug? How to choose proper download_mode to avoid this issue?
| 17 | How to choose proper download_mode in function load_dataset?
Hi, I am a beginner to datasets and I try to use datasets to load my csv file.
my csv file looks like this
```
text,label
"Effective but too-tepid biopic",3
"If you sometimes like to go to the movies to have fun , Wasabi is a good place to start .",4
"Emerges as something rare , an issue movie that 's so honest and keenly observed that it does n't feel like one .",5
```
First I try to use this command to load my csv file .
``` python
dataset=load_dataset('csv', data_files=['sst_test.csv'])
```
It seems good, but when i try to overwrite the convert_options to convert 'label' columns from int64 to float32 like this.
``` python
import pyarrow as pa
from pyarrow import csv
read_options = csv.ReadOptions(block_size=1024*1024)
parse_options = csv.ParseOptions()
convert_options = csv.ConvertOptions(column_types={'text': pa.string(), 'label': pa.float32()})
dataset = load_dataset('csv', data_files=['sst_test.csv'], read_options=read_options,
parse_options=parse_options, convert_options=convert_options)
```
It keeps the same:
```shell
Dataset(features: {'text': Value(dtype='string', id=None), 'label': Value(dtype='int64', id=None)}, num_rows: 2210)
```
I think this issue is caused by the parameter "download_mode" Default to REUSE_DATASET_IF_EXISTS because after I delete the cache_dir, it seems right.
Is it a bug? How to choose proper download_mode to avoid this issue?
`download_mode=datasets.GenerateMode.FORCE_REDOWNLOAD` should work.
This makes me think we we should rename this to DownloadMode.FORCE_REDOWNLOAD. Currently that's confusing |
https://github.com/huggingface/datasets/issues/769 | How to choose proper download_mode in function load_dataset? | Indeed you should use `features` in this case.
```python
features = Features({'text': Value('string'), 'label': Value('float32')})
dataset = load_dataset('csv', data_files=['sst_test.csv'], features=features)
```
Note that because of an issue with the caching when you change the features (see #750 ) you still need to specify the `FORCE_REDOWNLOAD ` flag. I'm working on a fix for this one | Hi, I am a beginner to datasets and I try to use datasets to load my csv file.
my csv file looks like this
```
text,label
"Effective but too-tepid biopic",3
"If you sometimes like to go to the movies to have fun , Wasabi is a good place to start .",4
"Emerges as something rare , an issue movie that 's so honest and keenly observed that it does n't feel like one .",5
```
First I try to use this command to load my csv file .
``` python
dataset=load_dataset('csv', data_files=['sst_test.csv'])
```
It seems good, but when i try to overwrite the convert_options to convert 'label' columns from int64 to float32 like this.
``` python
import pyarrow as pa
from pyarrow import csv
read_options = csv.ReadOptions(block_size=1024*1024)
parse_options = csv.ParseOptions()
convert_options = csv.ConvertOptions(column_types={'text': pa.string(), 'label': pa.float32()})
dataset = load_dataset('csv', data_files=['sst_test.csv'], read_options=read_options,
parse_options=parse_options, convert_options=convert_options)
```
It keeps the same:
```shell
Dataset(features: {'text': Value(dtype='string', id=None), 'label': Value(dtype='int64', id=None)}, num_rows: 2210)
```
I think this issue is caused by the parameter "download_mode" Default to REUSE_DATASET_IF_EXISTS because after I delete the cache_dir, it seems right.
Is it a bug? How to choose proper download_mode to avoid this issue?
| 55 | How to choose proper download_mode in function load_dataset?
Hi, I am a beginner to datasets and I try to use datasets to load my csv file.
my csv file looks like this
```
text,label
"Effective but too-tepid biopic",3
"If you sometimes like to go to the movies to have fun , Wasabi is a good place to start .",4
"Emerges as something rare , an issue movie that 's so honest and keenly observed that it does n't feel like one .",5
```
First I try to use this command to load my csv file .
``` python
dataset=load_dataset('csv', data_files=['sst_test.csv'])
```
It seems good, but when i try to overwrite the convert_options to convert 'label' columns from int64 to float32 like this.
``` python
import pyarrow as pa
from pyarrow import csv
read_options = csv.ReadOptions(block_size=1024*1024)
parse_options = csv.ParseOptions()
convert_options = csv.ConvertOptions(column_types={'text': pa.string(), 'label': pa.float32()})
dataset = load_dataset('csv', data_files=['sst_test.csv'], read_options=read_options,
parse_options=parse_options, convert_options=convert_options)
```
It keeps the same:
```shell
Dataset(features: {'text': Value(dtype='string', id=None), 'label': Value(dtype='int64', id=None)}, num_rows: 2210)
```
I think this issue is caused by the parameter "download_mode" Default to REUSE_DATASET_IF_EXISTS because after I delete the cache_dir, it seems right.
Is it a bug? How to choose proper download_mode to avoid this issue?
Indeed you should use `features` in this case.
```python
features = Features({'text': Value('string'), 'label': Value('float32')})
dataset = load_dataset('csv', data_files=['sst_test.csv'], features=features)
```
Note that because of an issue with the caching when you change the features (see #750 ) you still need to specify the `FORCE_REDOWNLOAD ` flag. I'm working on a fix for this one |
https://github.com/huggingface/datasets/issues/769 | How to choose proper download_mode in function load_dataset? | https://github.com/huggingface/datasets/issues/769#issuecomment-717837832
> This makes me think we we should rename this to DownloadMode.FORCE_REDOWNLOAD. Currently that's confusing
@lhoestq do you still think we should rename it?
| Hi, I am a beginner to datasets and I try to use datasets to load my csv file.
my csv file looks like this
```
text,label
"Effective but too-tepid biopic",3
"If you sometimes like to go to the movies to have fun , Wasabi is a good place to start .",4
"Emerges as something rare , an issue movie that 's so honest and keenly observed that it does n't feel like one .",5
```
First I try to use this command to load my csv file .
``` python
dataset=load_dataset('csv', data_files=['sst_test.csv'])
```
It seems good, but when i try to overwrite the convert_options to convert 'label' columns from int64 to float32 like this.
``` python
import pyarrow as pa
from pyarrow import csv
read_options = csv.ReadOptions(block_size=1024*1024)
parse_options = csv.ParseOptions()
convert_options = csv.ConvertOptions(column_types={'text': pa.string(), 'label': pa.float32()})
dataset = load_dataset('csv', data_files=['sst_test.csv'], read_options=read_options,
parse_options=parse_options, convert_options=convert_options)
```
It keeps the same:
```shell
Dataset(features: {'text': Value(dtype='string', id=None), 'label': Value(dtype='int64', id=None)}, num_rows: 2210)
```
I think this issue is caused by the parameter "download_mode" Default to REUSE_DATASET_IF_EXISTS because after I delete the cache_dir, it seems right.
Is it a bug? How to choose proper download_mode to avoid this issue?
| 25 | How to choose proper download_mode in function load_dataset?
Hi, I am a beginner to datasets and I try to use datasets to load my csv file.
my csv file looks like this
```
text,label
"Effective but too-tepid biopic",3
"If you sometimes like to go to the movies to have fun , Wasabi is a good place to start .",4
"Emerges as something rare , an issue movie that 's so honest and keenly observed that it does n't feel like one .",5
```
First I try to use this command to load my csv file .
``` python
dataset=load_dataset('csv', data_files=['sst_test.csv'])
```
It seems good, but when i try to overwrite the convert_options to convert 'label' columns from int64 to float32 like this.
``` python
import pyarrow as pa
from pyarrow import csv
read_options = csv.ReadOptions(block_size=1024*1024)
parse_options = csv.ParseOptions()
convert_options = csv.ConvertOptions(column_types={'text': pa.string(), 'label': pa.float32()})
dataset = load_dataset('csv', data_files=['sst_test.csv'], read_options=read_options,
parse_options=parse_options, convert_options=convert_options)
```
It keeps the same:
```shell
Dataset(features: {'text': Value(dtype='string', id=None), 'label': Value(dtype='int64', id=None)}, num_rows: 2210)
```
I think this issue is caused by the parameter "download_mode" Default to REUSE_DATASET_IF_EXISTS because after I delete the cache_dir, it seems right.
Is it a bug? How to choose proper download_mode to avoid this issue?
https://github.com/huggingface/datasets/issues/769#issuecomment-717837832
> This makes me think we we should rename this to DownloadMode.FORCE_REDOWNLOAD. Currently that's confusing
@lhoestq do you still think we should rename it?
|