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} | Signed-off-by: smajumdar <[email protected]>
# What does this PR do ?
Adds Squeezeformer CTC checkpoints
**Collection**: [ASR]
```python
import nemo.collections.asr as nemo_asr
asr_model = nemo_asr.models.EncDecCTCModelBPE.from_pretrained(model_name="stt_en_squeezeformer_ctc_large_ls")
```
# Before your PR is "Ready for review"
**Pre checks**:
- [x] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [x] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [x] New Feature
- [ ] Bugfix
- [ ] Documentation
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} | Signed-off-by: MaximumEntropy <[email protected]>
# What does this PR do ?
Fixes hanging with T5 prompt learning for PP > 1
**Collection**: NLP
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
# Additional Information
* Related to # (issue)
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} | null | null | null | **Describe the bug**
The wrapper for HF tokenizers misses some key functionality.
**Steps/Code to reproduce bug**
```python
from nemo.collections.nlp.modules.common.tokenizer_utils import get_tokenizer
tokenizer = get_tokenizer(
tokenizer_name="bert-base-multilingual-cased",
tokenizer_model="huggingface"
)
# The problem
print(f"{tokenizer.tokenizer.do_basic_tokenize=}")
text = "Knock, knock. Who's there? Interrupting cow. Interrupting cow wMOOOOOOOOOOOOOOO"
print(tokenizer.ids_to_text(tokenizer.text_to_ids(text)))
```
Output:
```
Knock , knock . Who ' s there ? Interrupting cow . Interrupting cow wMOOOOOOOOOOOOOOO
```
**Expected behavior**
Expected that for some tokenizer, `ids_to_text(text_to_ids) == text`.
We can accomplish this if we reach under NeMo's wrapper:
```python
print(tokenizer.tokenizer.decode(tokenizer.text_to_ids(text)))
```
Output:
```
Knock, knock. Who's there? Interrupting cow. Interrupting cow wMOOOOOOOOOOOOOOO
```
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} | # What does this PR do ?
Fixes for docs/typos + remove max_utts parameter from tarred datasets as it causes hang in training
**Collection**: asr mainly
# Changelog
The changes should be straightforward in most cases. The only thing to double check is that I fully removed `max_utts` parameter from tarred datasets (confirmed that it's not usable for ASR). But I'm not sure if there are some additional use-cases of this parameter besides ASR (e.g., TTS?) that might still be valid and working - but at least it does not seem to be present in any of the checked-in configs.
Another thing to mention is about changes in tutorials/00_NeMo_Primer.ipynb - I've only removed ";" at the end of some lines, since it seems like it was there by mistake (e.g., in cases of `model.summarize()` - we'd want to display the output, right?). But please let me know if it's there on purpose and I can put it back.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# Before your PR is "Ready for review"
**Pre checks**:
- [x] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [x] Did you write any new necessary tests?
- [x] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [x] Bugfix
- [x] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
# Additional Information
* Related to # (issue)
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} | null | null | null | **Describe the bug**
`ConcatMapDataset` doesn't check it's `worker_id` and all workers are seeded with the same RNG, then return the same data.
```python
import torch
from pytorch_lightning import seed_everything
from nemo.collections.common.data import ConcatMapDataset
seed_everything(42)
class IntegerDataset(torch.utils.data.Dataset):
def __init__(self, n: int, dataset_id: int):
self._ints = list(range(n))
self._id = torch.tensor(dataset_id)
def __len__(self):
return len(self._ints)
def __getitem__(self, idx):
worker_info = torch.utils.data.get_worker_info()
worker_id = worker_info.id
return self._id, worker_id, self._ints[idx]
concat_dataset = ConcatMapDataset(
datasets=[
IntegerDataset(5, 1),
IntegerDataset(10, 2)
]
)
dataloader = torch.utils.data.DataLoader(
dataset=concat_dataset,
batch_size=1,
num_workers=3
)
for batch in dataloader:
batch_dataset_id, batch_worker_id, batch_value = batch
print(
f"Dataset {batch_dataset_id.item()} worker {batch_worker_id.item()} fetched {batch_value.item()}"
)
```
Output:
```
Global seed set to 42
Dataset 2 worker 0 fetched 6
Dataset 2 worker 1 fetched 6
Dataset 2 worker 2 fetched 6
Dataset 1 worker 0 fetched 2
Dataset 1 worker 1 fetched 2
Dataset 1 worker 2 fetched 2
Dataset 2 worker 0 fetched 5
Dataset 2 worker 1 fetched 5
Dataset 2 worker 2 fetched 5
Dataset 2 worker 0 fetched 4
Dataset 2 worker 1 fetched 4
Dataset 2 worker 2 fetched 4
Dataset 2 worker 0 fetched 0
Dataset 2 worker 1 fetched 0
Dataset 2 worker 2 fetched 0
```
**Expected behavior**
`worker_id` should be utilized. See what happens with `ConcatDataset`:
```python
import torch
from pytorch_lightning import seed_everything
from nemo.collections.common.data import ConcatDataset
seed_everything(42)
class IntegerDataset(torch.utils.data.Dataset):
def __init__(self, n: int, dataset_id: int):
self._ints = list(range(n))
self._id = torch.tensor(dataset_id)
def __len__(self):
return len(self._ints)
def __getitem__(self, idx):
worker_info = torch.utils.data.get_worker_info()
worker_id = worker_info.id
return self._id, worker_id, self._ints[idx]
concat_dataset = ConcatDataset(
datasets=[
IntegerDataset(5, 1),
IntegerDataset(10, 2)
]
)
dataloader = torch.utils.data.DataLoader(
dataset=concat_dataset,
batch_size=1,
num_workers=3
)
for batch in dataloader:
batch_dataset_id, batch_worker_id, batch_value = batch
print(
f"Dataset {batch_dataset_id.item()} worker {batch_worker_id.item()} fetched {batch_value.item()}"
)
```
Output:
```
Global seed set to 42
Dataset 1 worker 0 fetched 0
Dataset 1 worker 1 fetched 4
Dataset 1 worker 2 fetched 2
Dataset 2 worker 0 fetched 6
Dataset 1 worker 1 fetched 1
Dataset 2 worker 2 fetched 8
Dataset 2 worker 0 fetched 0
Dataset 2 worker 1 fetched 7
Dataset 2 worker 2 fetched 5
Dataset 2 worker 0 fetched 9
Dataset 2 worker 1 fetched 4
Dataset 1 worker 2 fetched 2
Dataset 2 worker 0 fetched 3
Dataset 2 worker 1 fetched 1
Dataset 2 worker 2 fetched 2
```
Also, shuffling seems hard-coded. | {
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} | Signed-off-by: arendu <[email protected]>
# What does this PR do ?
Adds pipeline parallel support for T5 based IA3 and Adapter learning and inference.
**Collection**: [NLP]
# Changelog
- all changes are in the `megatron_t5_adapters_model.py` file.
- added CI tests
# Usage
* You can potentially add a usage example below
```python
python examples/nlp/language_modeling/tuning/megatron_t5_adapter_tuning.py
python examples/nlp/language_modeling/tuning/megatron_t5_adapter_eval.py
python examples/nlp/language_modeling/tuning/megatron_t5_ia3_tuning.py
python examples/nlp/language_modeling/tuning/megatron_t5_ia3_eval.py
```
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [x] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [x] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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* Related to # (issue)
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] | closed | false | null | [] | null | null | 2022-10-07T18:15:22 | 2022-10-08T03:37:55 | 2022-10-08T03:37:49 | CONTRIBUTOR | {
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"merged_at": "2022-10-08T03:37:49"
} | …field.
Signed-off-by: Xuesong Yang <[email protected]>
# What does this PR do ?
Add a one line overview of what this PR aims to accomplish.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# Before your PR is "Ready for review"
**Pre checks**:
- [x] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [x] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
# Additional Information
* Related to # (issue)
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"merged_at": "2022-10-20T13:26:18"
} | # What does this PR do ?
Fixed the self-attention export bug for cache-aware streaming Conformer
# Changelog
- There was an issue with ONNX conversion of cache-aware streaming Conformer in the self-attention module which raised error for empty caches. Fixed it with wrapping the code by torch script.
**PR Type**:
- [ ] New Feature
- [x] Bugfix
- [ ] Documentation | {
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} | …field.
Signed-off-by: Xuesong Yang <[email protected]>
# What does this PR do ?
Add a one line overview of what this PR aims to accomplish.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# Before your PR is "Ready for review"
**Pre checks**:
- [x] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [x] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
# Additional Information
* Related to # (issue)
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} | null | null | null | **The bug**
Megatron GPT training requires NVIDIA Apex to be installed. Token_Classification-BioMegatron.ipynb does not import module and provided solution found through (Error(s): Apex was not found. Please see the NeMo README for installation instructions: https://github.com/NVIDIA/NeMo#megatron-gpt.) does not solve import error.
**To reproduce bug**
Run script through google colab as presented on Nvidia nemo tutorials or through provided github. Notebook will error out at line 25 when model is initialized. Follow steps listed in error messaging to attempt to correct error.
**Expected behavior**
Notebook will error out at line 25 when model is initialized and return "Error(s): Apex was not found. Please see the NeMo README for installation instructions: https://github.com/NVIDIA/NeMo#megatron-gpt."
**Environment overview (please complete the following information)**
- Environment location: Colab
- Method of NeMo install:
!python -m pip install git+https://github.com/NVIDIA/NeMo.git@$BRANCH#egg=nemo_toolkit[nlp]
from nemo.collections import nlp as nemo_nlp
from nemo.utils.exp_manager import exp_manager
import os
import wget
import torch
import pytorch_lightning as pl
from omegaconf import OmegaConf
**Environment details**
- OS version: posix
- PyTorch version: 1.12.1+cu113
- Python version: Python 3.7.14
**Additional context**
Standard GPU selection on Colab
**Screen capture after implementing official solution**
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} | # What does this PR do ?
Add a one line overview of what this PR aims to accomplish.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [x] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
# Additional Information
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Add a one line overview of what this PR aims to accomplish.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [x] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
# Additional Information
* Related to # (issue)
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} | # What does this PR do ?
Adds support for concat dataloader into ASR models
**Collection**: ASR
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
Set the following dataset variables:
train_ds["is_concat"] = True
train_ds["concat_sampling"] = "random"
train_ds["concat_probabilities"] = [0.3, 0.6, 0.1]
train_ds["manifest_filepath"] = ["path1", "path2", "path3"]
In this case, there are three manfests and they will be sampled from with the probabilities provided.
```python
# Add a code snippet demonstrating how to use this
```
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ X] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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} | Signed-off-by: Matvei Novikov <[email protected]>
# What does this PR do ?
Add a one line overview of what this PR aims to accomplish.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
# Additional Information
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} | Signed-off-by: Matvei Novikov <[email protected]>
# What does this PR do ?
Add a one line overview of what this PR aims to accomplish.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
# Additional Information
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} | # What does this PR do ?
Add a one line overview of what this PR aims to accomplish.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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} | # What does this PR do ?
This PR integrates NeMo Megatron with Transformer Engine: https://github.com/NVIDIA/TransformerEngine
Transformer Engine enables FP8 training. Currently this will only be enabled for GPT but is planned for all NeMo Megatron models.
**Collection**: NLP
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
# Additional Information
* Related to # (issue)
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https://api.github.com/repos/NVIDIA/NeMo/issues/5103 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/5103/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/5103/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/5103/events | https://github.com/NVIDIA/NeMo/pull/5103 | 1,400,036,521 | PR_kwDOC_bI7s5AVcIA | 5,103 | T5 Decoding with PP > 2 fix | {
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} | # What does this PR do ?
Fixes a bug that would cause decoding with an enc-dec model with PP > 2 to hang.
**Collection**: NLP
# Changelog
- Set sequence lengths for the pipeline properly while decoding.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
# Additional Information
* Related to # (issue)
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https://api.github.com/repos/NVIDIA/NeMo/issues/5102 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/5102/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/5102/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/5102/events | https://github.com/NVIDIA/NeMo/pull/5102 | 1,400,024,832 | PR_kwDOC_bI7s5AVZnZ | 5,102 | [TTS] fixed wrong val loss for epoch 0 and inconsistent metrics names | {
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} | Signed-off-by: Xuesong Yang <[email protected]>
# What does this PR do ?
This PR fixed two issues below,
1. initial checkpoint got wrong `val_loss` so the name was not correct. The root-cause is that `trainer.max_epochs=1` is less than `train.check_val_every_n_epoch=5`. So specify `train.check_val_every_n_epoch=1` would fix the issue for FastPitch. Similar fix for HiFiGAN. See results comparison below,
```
# before fix:
$ ls resultGermanTTS/FastPitch/2022-10-05_12-35-50/checkpoints/
FastPitch.nemo 'FastPitch--val_loss=0.0000-epoch=1-last.ckpt
$ ls resultGermanTTS/HifiGan/2022-10-05_19-29-39/checkpoints/
HifiGan.nemo 'HifiGan--val_loss=0.0000-epoch=1-last.ckpt'
# after fix:
$ ls resultGermanTTS/FastPitch/2022-10-05_14-18-25/checkpoints/
FastPitch.nemo 'FastPitch--val_loss=4.0512-epoch=0.ckpt' 'FastPitch--val_loss=4.0512-epoch=1-last.ckpt'
$ ls resultGermanTTS/HifiGan/2022-10-05_20-10-50/checkpoints/
HifiGan.nemo 'HifiGan--val_loss=0.5253-epoch=0.ckpt' 'HifiGan--val_loss=0.5253-epoch=0-last.ckpt'
```
2. TTS loss metrics used `v_loss` rather than `val_loss` as the keyword for validation loss. So this check (https://github.com/NVIDIA/NeMo/blob/r1.12.0/nemo/utils/exp_manager.py#L906) was never succeeded. Rename to `val_loss` helps to make the check valid.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# Before your PR is "Ready for review"
**Pre checks**:
- [x] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [x] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
# Additional Information
* Related to # (issue)
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} | # What does this PR do ?
Adds fixes that were missing from r1.11.0 merge to main.
**Collection**: NLP
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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} | # What does this PR do ?
Explicitly specify `batch_size` for the `global_step` log.
Apparently, the call to `log` for the `global_step` metric in `ctc_models.py` sometimes fails with the following stack trace.
<details>
<summary>Stacktrace</summary>
```
Traceback (most recent call last):
File "/home/msis/tdreeb/train.py", line 67, in main
trainer.fit(asr_model)
File "/opt/conda/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py", line 696, in fit
self._call_and_handle_interrupt(
File "/opt/conda/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py", line 650, in _call_and_handle_interrupt
return trainer_fn(*args, **kwargs)
File "/opt/conda/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py", line 735, in _fit_impl
results = self._run(model, ckpt_path=self.ckpt_path)
File "/opt/conda/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py", line 1166, in _run
results = self._run_stage()
File "/opt/conda/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py", line 1252, in _run_stage
return self._run_train()
File "/opt/conda/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py", line 1283, in _run_train
self.fit_loop.run()
File "/opt/conda/lib/python3.8/site-packages/pytorch_lightning/loops/loop.py", line 200, in run
self.advance(*args, **kwargs)
File "/opt/conda/lib/python3.8/site-packages/pytorch_lightning/loops/fit_loop.py", line 271, in advance
self._outputs = self.epoch_loop.run(self._data_fetcher)
File "/opt/conda/lib/python3.8/site-packages/pytorch_lightning/loops/loop.py", line 201, in run
self.on_advance_end()
File "/opt/conda/lib/python3.8/site-packages/pytorch_lightning/loops/epoch/training_epoch_loop.py", line 241, in on_advance_end
self._run_validation()
File "/opt/conda/lib/python3.8/site-packages/pytorch_lightning/loops/epoch/training_epoch_loop.py", line 299, in _run_validation
self.val_loop.run()
File "/opt/conda/lib/python3.8/site-packages/pytorch_lightning/loops/loop.py", line 200, in run
self.advance(*args, **kwargs)
File "/opt/conda/lib/python3.8/site-packages/pytorch_lightning/loops/dataloader/evaluation_loop.py", line 155, in advance
dl_outputs = self.epoch_loop.run(self._data_fetcher, dl_max_batches, kwargs)
File "/opt/conda/lib/python3.8/site-packages/pytorch_lightning/loops/loop.py", line 200, in run
self.advance(*args, **kwargs)
File "/opt/conda/lib/python3.8/site-packages/pytorch_lightning/loops/epoch/evaluation_epoch_loop.py", line 143, in advance
output = self._evaluation_step(**kwargs)
File "/opt/conda/lib/python3.8/site-packages/pytorch_lightning/loops/epoch/evaluation_epoch_loop.py", line 240, in _evaluation_step
output = self.trainer._call_strategy_hook(hook_name, *kwargs.values())
File "/opt/conda/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py", line 1704, in _call_strategy_hook
output = fn(*args, **kwargs)
File "/opt/conda/lib/python3.8/site-packages/pytorch_lightning/strategies/ddp.py", line 358, in validation_step
return self.model(*args, **kwargs)
File "/opt/conda/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1129, in _call_impl
return forward_call(*input, **kwargs)
File "/opt/conda/lib/python3.8/site-packages/torch/nn/parallel/distributed.py", line 987, in forward
output = self.module(*inputs[0], **kwargs[0])
File "/opt/conda/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1129, in _call_impl
return forward_call(*input, **kwargs)
File "/opt/conda/lib/python3.8/site-packages/pytorch_lightning/overrides/base.py", line 90, in forward
return self.module.validation_step(*inputs, **kwargs)
File "/opt/conda/lib/python3.8/site-packages/nemo/collections/asr/models/ctc_models.py", line 641, in validation_step
self.log('global_step', torch.tensor(self.trainer.global_step, dtype=torch.float32))
File "/opt/conda/lib/python3.8/site-packages/pytorch_lightning/core/module.py", line 487, in log
results.log(
File "/opt/conda/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/logger_connector/result.py", line 493, in log
batch_size = self._extract_batch_size(self[key], batch_size, meta)
File "/opt/conda/lib/python3.8/site-packages/pytorch_lightning/trainer/connectors/logger_connector/result.py", line 428, in _extract_batch_size
batch_size = extract_batch_size(self.batch)
File "/opt/conda/lib/python3.8/site-packages/pytorch_lightning/utilities/data.py", line 107, in extract_batch_size
raise MisconfigurationException(error_msg)
pytorch_lightning.utilities.exceptions.MisconfigurationException: We could not infer the batch_size from the batch. Either simplify its structure or provide the batch_size as `self.log(..., batch_size=batch_size)`.
```
</details>
I'm unsure if this points to an underlying issue w/ PTL or the `global_step` param, but this change resolves the issue.
**Collection**: ASR
# Changelog
- Explicitly specify `batch_size` for the `global_step` log.
# Before your PR is "Ready for review"
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**PR Type**:
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} | Signed-off-by: Xuesong Yang <[email protected]>
# What does this PR do ?
This hook does following process. I also manually add `# noqa` to avoid changes for some lines of codes for safety purpose. Domain experts please help to review.
```
# after process, we fixed,
22 for Unused import
1 for 'import *' may pollute namespace
```
```
--expand-star-imports
expand wildcard star imports with undefined names; this only triggers if there is only one star import in the file; this is skipped if there are any uses of `__all__` or `del` in the file
--remove-all-unused-imports
remove all unused imports (not just those from the standard library)
--ignore-init-module-imports
exclude __init__.py when removing unused imports
--ignore-pass-after-docstring
keep `pass` statements after a new line ending on """
```
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
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- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
# Additional Information
* Related to # (issue)
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# What does this PR do ?
Manually apply patches for numba checks.
**Collection**: [ASR]
# Before your PR is "Ready for review"
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- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
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- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [x] Bugfix
- [ ] Documentation
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# What does this PR do ?
Add a one line overview of what this PR aims to accomplish.
**Collection**: [ASR]
**PR Type**:
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- [ ] Documentation | {
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} | Signed-off-by: smajumdar <[email protected]>
# What does this PR do ?
Fixes an issue where Numba Spec Augment kernel can no longer execute due to passing a list of values for `blocks_per_grid` on Numba > 0.56.0
**Collection**: [ASR]
# Changelog
- Convert the list to tuple before passing to numba kernel launch
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [x] Bugfix
- [ ] Documentation
Closes #4863
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# What does this PR do ?
Fixes an issue where Numba Spec Augment kernel can no longer execute due to passing a list of values for `blocks_per_grid` on Numba > 0.56.0
**Collection**: [ASR]
# Changelog
- Convert the list to tuple before passing to numba kernel launch
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [x] Bugfix
- [ ] Documentation
Closes #4863
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} | Signed-off-by: Elena Rastorgueva <[email protected]>
# What does this PR do ?
Makes it possible to specify output_filename in normalize_with_audio.py
**Collection**: [Note which collection this PR will affect]
nemo_text_processing
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
python <nemo>/nemo_text_processing/text_normalization/normalize_with_audio.py \
--audio_data <audio_data> \
--language <lang> \
--output_filename "outputs.json"
```
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
# Additional Information
* Related to # (issue)
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} | # What does this PR do ?
Fixes a bug that would cause decoding with an enc-dec model with PP > 2 to hang.
**Collection**: NLP
# Changelog
- Set sequence lengths for the pipeline properly while decoding.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
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} | Signed-off-by: Xuesong Yang [[email protected]](mailto:[email protected])
# What does this PR do ?
Manually cherry pick https://github.com/NVIDIA/NeMo/pull/5071 to main because automatically cherry-pick was ignored.
we decided to remove phonemizer python script. We decided to add an instruction about how to transliterate graphemes into phonemes using phonemizer + espeak in the tutorial.
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} | # What does this PR do ?
Fix qa notebook bug when device has >1 gpu
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} | # What does this PR do ?
Fix qa notebook bug when device has >1 gpu
**Collection**: nlp
# Changelog
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} | Signed-off-by: Xuesong Yang <[email protected]>
# What does this PR do ?
This PR fixed two issues below,
1. initial checkpoint got wrong `val_loss` so the name was not correct. The root-cause is that `trainer.max_epochs=1` is less than `train.check_val_every_n_epoch=5`. So specify `train.check_val_every_n_epoch=1` would fix the issue for FastPitch. Similar fix for HiFiGAN. See results comparison below,
```
# before fix:
$ ls resultGermanTTS/FastPitch/2022-10-05_12-35-50/checkpoints/
FastPitch.nemo 'FastPitch--val_loss=0.0000-epoch=1-last.ckpt
$ ls resultGermanTTS/HifiGan/2022-10-05_19-29-39/checkpoints/
HifiGan.nemo 'HifiGan--val_loss=0.0000-epoch=1-last.ckpt'
# after fix:
$ ls resultGermanTTS/FastPitch/2022-10-05_14-18-25/checkpoints/
FastPitch.nemo 'FastPitch--val_loss=4.0512-epoch=0.ckpt' 'FastPitch--val_loss=4.0512-epoch=1-last.ckpt'
$ ls resultGermanTTS/HifiGan/2022-10-05_20-10-50/checkpoints/
HifiGan.nemo 'HifiGan--val_loss=0.5253-epoch=0.ckpt' 'HifiGan--val_loss=0.5253-epoch=0-last.ckpt'
```
2. TTS loss metrics used `v_loss` rather than `val_loss` as the keyword for validation loss. So this check (https://github.com/NVIDIA/NeMo/blob/r1.12.0/nemo/utils/exp_manager.py#L906) was never succeeded. Rename to `val_loss` helps to make the check valid.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# Before your PR is "Ready for review"
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- [ ] Did you write any new necessary tests?
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- [x] Bugfix
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## Who can review?
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[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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} | Signed-off-by: arendu <[email protected]>
# What does this PR do ?
- GPT and T5 adapter/ia3 training depends on requires_grad=False to be obeyed by all Apex modules, because all the params of the frozen model are supplied into the optimizer_param_groups.
- This PR only supplies the optimizer_param_groups the parameters that only belong to the adapters/ia3 and does not supply params from the base model.
Add a one line overview of what this PR aims to accomplish.
**Collection**: [NLP]
# Changelog
- Modified the `setup_optimizer_param_groups` method in GPTBaseAdapter and T5BaseAdapter classes.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [x] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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} | # What does this PR do ?
Release SOTA lang id model AmberNet which achieves 5.22% error rate on the official evaluation set of [voxlingua107](http://bark.phon.ioc.ee/voxlingua107/) and update doc.
**Collection**: ASR
# Changelog
# Usage
```python
langidmodel = nemo_asr.models.EncDecSpeakerLabelModel.from_pretrained(model_name="langid_ambernet")
```
# Before your PR is "Ready for review"
**Pre checks**:
- [x] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [x] Did you write any new necessary tests?
- [x] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
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**PR Type**:
- [x] New Feature
- [ ] Bugfix
- [x] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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} | Signed-off-by: Virginia Adams <[email protected]>
Fixes Entity Linking and Prompt Learning Notebook Bugs:
https://nvbugs/3802936 [ML-NeMo][A40] Entity_Linking_Medical.ipynb failed with TypeError: __init__() got an unexpected keyword argument 'checkpoint_callback'
https://nvbugs/3801562 [ML-NeMo][A40] Multitask_Prompt_and_PTuning.ipynb contains broken links
https://nvbugs/3803232 [ML-NeMo][A40] Multitask_Prompt_and_PTuning.ipynb failed with FileNotFoundError: [Errno 2] No such file or directory: 'data/SQuAD/train-v1.1.json'
**Collection**: NLP
# Changelog
- Updates entity linking and prompt learning notebooks
# Usage
N/A
# Before your PR is "Ready for review"
**Pre checks**:
- [x] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [x] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
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Add a one line overview of what this PR aims to accomplish.
NeMo Megatron will and Megatron-lm will use a shared core so that more model parallelism code can be shared between the two repositories.
Apex dependency will become optional and only used for performance improvements.
**Collection**: NLP
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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I am working on developing pipelines for Laughing, Crying etc. I want to achieve them, like VAD in pyannote/Nemo/silero pipeline. How can I use Nemofor training purposes? Moreover, I want to use the pipeline on device: Android/IoS, so kindly also guide me in that direction as well..
Thanks | {
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I'm working on crafting a model that can identify music within an audio that contains speech and came across this option.
Is it feasible to use the process for creating a VAD model to create a music-detection model? Would there it be any difference from using the same method beyond the source? | null | {
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} | # What does this PR do ?
Release SOTA lang id model AmberNet which achieves 5.22% error rate on the official evaluation set of [voxlingua107](http://bark.phon.ioc.ee/voxlingua107/) and update doc.
**Collection**: ASR
# Changelog
# Usage
```python
langidmodel = nemo_asr.models.EncDecSpeakerLabelModel.from_pretrained(model_name="langid_ambernet")
```
# Before your PR is "Ready for review"
**Pre checks**:
- [x] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [x] Did you write any new necessary tests?
- [x] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [x] New Feature
- [ ] Bugfix
- [x] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
# Additional Information
* Related to # (issue)
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} | Signed-off-by: nithinraok <[email protected]>
# What does this PR do ?
typo fix
**Collection**: ASR
# Changelog
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**PR Type**:
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- [x] Documentation
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# What does this PR do ?
typo fix
**Collection**: ASR
# Changelog
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} | Signed-off-by: MaximumEntropy <[email protected]>
# What does this PR do ?
Fixes and refactors things related to loading of consumed samples.
**Collection**: NLP
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
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# Before your PR is "Ready for review"
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- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
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**PR Type**:
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- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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} | Signed-off-by: arendu <[email protected]>
# What does this PR do ?
renames the `output_file` for adapter and ia3 training to `pred_file_path`
**Collection**: [nlp]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
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# Before your PR is "Ready for review"
**Pre checks**:
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- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
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**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
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[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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} | # What does this PR do ?
Adds fixes that were missing from r1.11.0 merge to main.
**Collection**: NLP
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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} | Signed-off-by: Xuesong Yang <[email protected]>
# What does this PR do ?
This was added in r1.11.0, but not sure why it disappears for r1.12.0. See previous PR:https://github.com/NVIDIA/NeMo/pull/4756
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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"merged_at": "2022-10-05T15:41:58"
} | Signed-off-by: Xuesong Yang <[email protected]>
# What does this PR do ?
* refine the workflow name, and close stale messages;
* increase sweep quantity for PR and Issues at each cycle;
* activate close for inactive PRs in 30 days.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
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# Before your PR is "Ready for review"
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If you haven't finished some of the above items you can still open "Draft" PR.
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} | # What does this PR do ?
Expose the `spe_split_by_unicode_script` SentencePiece cmd line flag to the tokenizer generation script.
Arabic text contains diacritics that can influence the meaning of a word, therefore, they must be considered part of a character when generating a tokenizer vocabulary.
The `sentencepiece` library however does not consider diacritics as part of the word and generally considers it as a separate token altogether.
As a result, the diacritics are generally stripped as separate tokens from the word and the generated vocabulary does not properly represent the words in the dataset.
By adding this flag, we allow the SPE library to consider multiple unicode scripts as a single "piece".
See the comments on the flag [here](https://github.com/google/sentencepiece/blob/9f3ed99f5c68609fc94ac83a5c0aea9eb163f6d9/src/sentencepiece_model.proto#L135).
**Collection**: ASR
# Changelog
- Expose the `spe_split_by_unicode_script` SentencePiece command line flag to the tokenizer generation script.
# Usage
```sh
python process_asr_text_tokenizer.py --manifest=/path/to/dataset_manifest.json \
--data_root=tokenizers/datatset \
--vocab_size=1024 \
--tokenizer=spe \
--spe_no_spe_split_by_unicode_script \
--log
```
# Before your PR is "Ready for review"
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} | Signed-off-by: Xuesong Yang <[email protected]>
# What does this PR do ?
we decided to remove phonemizer python script. We decided to add an instruction about how to transliterate graphemes into phonemes using phonemizer + espeak in the tutorial.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# Before your PR is "Ready for review"
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**PR Type**:
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- [ ] Bugfix
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If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
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[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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} | Signed-off-by: Xuesong Yang <[email protected]>
# What does this PR do ?
This was added in r1.11.0, but not sure why it disappears for r1.12.0. See previous PR:https://github.com/NVIDIA/NeMo/pull/4756
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# Before your PR is "Ready for review"
**Pre checks**:
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- [ ] Did you write any new necessary tests?
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- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
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- [ ] Bugfix
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If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
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[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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} | Signed-off-by: Matvei Novikov <[email protected]>
# What does this PR do ?
Documentation for P&C model update
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# Before your PR is "Ready for review"
**Pre checks**:
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**PR Type**:
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If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
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} | Signed-off-by: Matvei Novikov <[email protected]>
# What does this PR do ?
Documentation for P&C model update
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} | Signed-off-by: Shanmugam Ramasamy <[email protected]>
# What does this PR do ?
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} | Signed-off-by: arendu <[email protected]>
# What does this PR do ?
IA3 logic should look at `kv_channels * num_attention_heads` to get the true `hidden_size` for k,v,q in `ParallelAttention`.
**Collection**: [nlp]
# Changelog
- checks if `kv_channels` is available in the config of a T5 model, if available it will use it and ignore `hidden_size`.
# Usage
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```python
# Add a code snippet demonstrating how to use this
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**PR Type**:
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## Who can review?
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} | Signed-off-by: MaximumEntropy <[email protected]>
# What does this PR do ?
Removes unsupported args from MegatronNMT.
Specifically removes
1. MTDataPreproc (needed for tarred datasets)
2. Tarred and text datasets as options for train_ds.
3. Removes distributed sampler option. Only possible to use megatron batch samplers.
4. Removes associated code in the model like GlobalBatchDataFetcher, train step reconfiguring of MBS etc.
**Collection**: NLP
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
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[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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} | Signed-off-by: MaximumEntropy <[email protected]>
# What does this PR do ?
Adds fixes that were initially a part of the BigNLP cherry-pick but were not merged back to main.
**Collection**: NLP
# Changelog
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https://api.github.com/repos/NVIDIA/NeMo/issues/5060 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/5060/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/5060/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/5060/events | https://github.com/NVIDIA/NeMo/issues/5060 | 1,394,421,069 | I_kwDOC_bI7s5THS1N | 5,060 | Question about Diarization inference | {
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} | null | null | null | Hi guys
I have couple of questions about Diarization inference script
1. https://github.com/NVIDIA/NeMo/blob/f964e1c17c3922d6f35b5e453aa712f2be153e6d/nemo/collections/asr/parts/utils/nmesc_clustering.py#L723
Here, we are trying to marge clustering outputs together using ```torch.mode```. But it seems wrong, because at each trial the output class indices are different. So majority voting will not produce any benefits. Can you explain how it works?
https://github.com/NVIDIA/NeMo/blob/f964e1c17c3922d6f35b5e453aa712f2be153e6d/nemo/collections/asr/parts/utils/nmesc_clustering.py#L895
2. Why are you making graph fully connected after binarization? Are there any corner cases in which fully connected graph is necessary?
Thanks | null | {
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} | null | null | null | Hello, I'm trying to use the ASR chunk Inference script as the video I want too process is too big (2 hours). But getting an error while running the script.
command I'm using `python .\speech_to_text_buffered_infer_ctc.py --asr_model="stt_en_conformer_ctc_xlarge" --test_manifest="video_2.wav" --model_stride=4`
Issue
`Traceback (most recent call last):
File ".\chunk_inference.py", line 169, in <module>
main() # noqa pylint: disable=no-value-for-parameter
File ".\chunk_inference.py", line 132, in main
hyps, refs, wer = get_wer_feat(
File ".\chunk_inference.py", line 62, in get_wer_feat
row = json.loads(l.strip())
File "C:\Users\dhruv\AppData\Local\Programs\Python\Python38\lib\json\__init__.py", line 343, in loads
s = s.decode(detect_encoding(s), 'surrogatepass')
UnicodeDecodeError: 'utf-8' codec can't decode byte 0x98 in position 5: invalid start byte` | {
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} | null | null | null | **Is your feature request related to a problem? Please describe.**
Whenever I'm training, I cannot conclude the exact performance of a TTS model when training, having to manually stop and resume training.
**Describe the solution you'd like**
A simple parameter in the training config to add audio samples & alignment (if possible) into the tensorboard.
**Describe alternatives you've considered**
N/A
**Additional context**
N/A
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https://api.github.com/repos/NVIDIA/NeMo/issues/5057 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/5057/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/5057/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/5057/events | https://github.com/NVIDIA/NeMo/issues/5057 | 1,393,128,883 | I_kwDOC_bI7s5TCXWz | 5,057 | Unable to instantiate HuggingFace AUTOTOKENIZER for gpt2 and facebook/bart-base | {
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} | null | null | null | **Describe the bug**
Get errors
`Unable to instantiate HuggingFace AUTOTOKENIZER `
for both gpt2 and facebook/bart-base
**Steps/Code to reproduce bug**
Trying to run NeMO tutorial from https://github.com/NVIDIA/NeMo/blob/stable/tutorials/nlp/Question_Answering.ipynb
The notebook fails when trying to create trainer and initialize models gpt2 and facebook/bart-base
**Expected behavior**
I expected to bee able to create a trainer properly just like it happened for "bert-base-uncased" which worked well earlier in the same notebook.
**Environment overview (please complete the following information)**
- Environment location: VMware vSphere VM
- Method of NeMo install:
```
conda create --name nemo python==3.8
conda activate nemo
conda install pytorch torchvision torchaudio cudatoolkit=11.3 -c pytorch
apt-get update && apt-get install -y libsndfile1 ffmpeg
pip install Cython
pip install nemo_toolkit['all']
```
**Environment details**
If NVIDIA docker image is used you don't need to specify these.
Otherwise, please provide:
- OS version Ubuntu 20.04.5 LTS
- PyTorch version 1.12.1
- Python version 3.8.0
- nemo-toolkit 1.11.0
**Additional context**
Add any other context about the problem here.
**GPU model V100**
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} | # What does this PR do ?
1. Loading index file into memmap object.
2. Deallocates indexed dataset memory after samples mapping has been computed.
3. Blendable dataset supports index computation
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
# Additional Information
* Related to # (issue)
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} | Signed-off-by: Virginia Adams <[email protected]>
# What does this PR do ?
Saves inference ready .nemo checkpoint every time a training checkpoint is saved.
**Collection**: NLP
# Changelog
- Updates Base Prompt Learning Model Class
- Updates GPT Prompt Learning Model Class
- Updates T5 Prompt Learning Model Class
# Usage
Now, when a .ckpt file is saved at the end of validation, an inference ready .nemo file is also saved at the path given in `models.nemo_path`
# Before your PR is "Ready for review"
**Pre checks**:
- [x] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [x] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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} | Signed-off-by: MaximumEntropy <[email protected]>
# What does this PR do ?
Adds fixes that were initially a part of the BigNLP cherry-pick but were not merged back to main.
**Collection**: NLP
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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Add a one line overview of what this PR aims to accomplish.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [X ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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} | # What does this PR do ?
[`torch.onnx.export`](https://pytorch.org/docs/stable/onnx.html#torch.onnx.export) has the parameter `keep_initializers_as_inputs` which allows to conveniently override parameters when running a graph.
**Collection**: Every collection that is exportable.
# Changelog
- Allow to use `keep_initializers_as_inputs` parameter when exporting a model to ONNX
# Usage
* You can potentially add a usage example below
```python
model.export(..., keep_initializers_as_inputs=True)
```
# Before your PR is "Ready for review"
**Pre checks**:
- [x] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [x] New Feature
- [ ] Bugfix
- [ ] Documentation
## Who can review?
@ericharper, @titu1994, @blisc, or @okuchaiev
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} | Signed-off-by: Dima Rekesh <[email protected]>
# What does this PR do ?
Prevents the use of bfloat16 autocast when jit() is used
Add a one line overview of what this PR aims to accomplish.
Prevents the use of bfloat16 autocast when jit() is used
**Collection**: [Note which collection this PR will affect]
general
# Changelog
- Add specific line by line info of high level changes in this PR.
- [training_utils.py](https://github.com/NVIDIA/NeMo/compare/main...no_bfloat16_in_jit#diff-09d6a5be8cc6d798800c50fa7cb0d7bd34e89ad5a71c872c87f6e07c4f4ea38f)
# Usage
* You can potentially add a usage example below
* No change
```python
# Add a code snippet demonstrating how to use this
```
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
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## Who can review?
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[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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Fix bug in question answering tutorial
**Collection**: nlp
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# Before your PR is "Ready for review"
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- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [x] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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Fix bug in question answering tutorial
**Collection**: nlp
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [x] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
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- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [X ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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} | Signed-off-by: Alexandra Antonova <[email protected]>
# What does this PR do ?
Fix undefined constant in code example.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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Signed-off-by: SeanNaren <[email protected]>
(cherry picked from commit 986a76612593863a8fa3a8529fb60c620c91bd7b)
# What does this PR do ?
Add a one line overview of what this PR aims to accomplish.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
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If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
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[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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} | # What does this PR do ?
The output directory was assumed as apposed to using the variable to track. This ensures we use the variable as apposed to `outputs/`.
# Before your PR is "Ready for review"
**Pre checks**:
- [x] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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} | Signed-off-by: George Zelenfroynd <[email protected]>
# What does this PR do ?
Add a one line overview of what this PR aims to accomplish.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [x] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [x] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
# Additional Information
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} | # What does this PR do ?
Adds a folder to store the `speaker_tasks` datasets. Few things to consider:
* I could create a nested `diarization` folder to be more specific, but I thought just one folder would be fine
* I might've missed some scripts that would be better suited to exist in this new folder
# Changelog
- Add `speaker_tasks` datasets folder, add diarization datasets voxconverse/aishell.
# Before your PR is "Ready for review"
**Pre checks**:
- [x] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [x] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [x] New Feature
- [ ] Bugfix
- [ ] Documentation
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} | Signed-off-by: SeanNaren <[email protected]>
# What does this PR do ?
Add a one line overview of what this PR aims to accomplish.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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} | # What does this PR do ?
fixing chinese tn and adding nemo core to text_processing package | {
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} | # What does this PR do ?
Fix bugs relating to dialogue and question answering due to pytorch lightning and transformers version upgrade
**Collection**: nlp
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [x] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
# Additional Information
* Related to # (issue)
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} | # What does this PR do ?
Updating Megatron LM conversion according to PTL 1.7
**Collection**: [Note which collection this PR will affect]
# Changelog
- Updated megatron_lm_ckpt_to_nemo.py
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# Before your PR is "Ready for review"
**Pre checks**:
- [X] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [X] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
# Additional Information
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} | # What does this PR do ?
Fix bugs relating to dialogue and question answering due to pytorch lightning and transformers version upgrade
**Collection**: nlp
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [x] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
# Additional Information
* Related to # (issue)
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} | # What does this PR do ?
fixing chinese tn and adding nemo core to text_processing package | {
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} | # What does this PR do ?
1. Improved range testing of text-memmap dataset when __len__ method is overriden.
Add a one line overview of what this PR aims to accomplish.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
# Additional Information
* Related to # (issue)
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} | # What does this PR do ?
Fixes the bugs in cache-aware streaming.
**PR Type**:
- [ ] New Feature
- [x] Bugfix
- [ ] Documentation
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} | Signed-off-by: MaximumEntropy <[email protected]>
# What does this PR do ?
Fixes a bug that causes decoding for enc-dec models with O2 to crash
**Collection**: [Note which collection this PR will affect]
# Changelog
- Change the module being inspected with O2 to determine forward args.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
# Additional Information
* Related to # (issue)
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} | # What does this PR do ?
Adds docs for p&c lexical audio model
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [X] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
# Additional Information
* Related to # (issue)
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It adds docs for p&c lexical audio model.
**Collection**: nlp
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [X] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
# Additional Information
* Related to # (issue)
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} | # What does this PR do ?
Added patch for tao realted bug 3809486. Included functionality to restore the value of is_model_being_restore to true if user has sent restore_attr_is_model_being_restore=True
**Collection**: [Note which collection this PR will affect]
# Changelog
- modified nlp_model.py to restore is_model_being_restore=True as at line 81( bert_model = get_lm_model(..) ) while intializing the model , the states is_model_being_restore is set to false . This needs to be true to initialize the model (at line super().__init__(cfg, trainer) ).
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# Before your PR is "Ready for review"
**Pre checks**:
- [x] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [x] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
# Additional Information
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Figured out how to do this with keeping click the correct version to allow this older black to run.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
# Additional Information
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} | # What does this PR do ?
Adds the following
1. XLM + UL2-based datasets for BERT and SeqSeq
2. Multilingual support for MegatronNMT (x -> En, En -> x and x <-> y).
**Collection**: NLP
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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* Related to # (issue)
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} | # What does this PR do ?
Adds interleaved pipeline schedule to GPT.
The interleaved pipeline schedule helps to improve the efficiency of training pipeline parallel models. With the interleaved schedule, we split our model into chunks where the number of chunks is equal to the virtual pipeline model parallel size. By chunking our model and using the interleaved pipeline schedule we can reduce the "pipeline bubble" and increase throughput. See https://arxiv.org/pdf/2104.04473.pdf for more details.
Note: in order to run interleaved, Apex needs to have the virtual pipeline parallel setter
**Collection**: [NLP]
# Changelog
- Make virtual pipeline size configurable
- Add interleaved pipeline functions
- Properly sync embeddings when using interleaved
- Properly skip loading inputs when using interleaved
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [x] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
# Additional Information
* Related to # (issue)
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} | Signed-off-by: smajumdar <[email protected]>
# What does this PR do ?
Fixes a bug in squeezeformer preventing loading of checkpoints.
**Collection**: [ASR]
# Changelog
- Fix a calculation of groups that prevents loading of checkpoints
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [x] Bugfix
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} | Signed-off-by: shanmugamr1992 <[email protected]>
# What does this PR do ?
* Limit val batches 1.0 does not work as expected when num validation iterations * global batch size > num samples
**Collection**: [Note which collection this PR will affect]
Large language model
# Changelog
- Add specific line by line info of high level changes in this PR.
* If limit val batches is set to 1.0 it automatically uses only one epoch of validation data for every validation iteration
* Bug fix when adding blendable dataset as values for train / test / validation keys .
# Usage
* You can potentially add a usage example below
limit_val_batches: 1.0
```python
# Add a code snippet demonstrating how to use this
```
# Before your PR is "Ready for review"
**Pre checks**:
- [x] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [x] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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* Related to # (issue)
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} | # What does this PR do ?
The transformers library should be fixed for offline, however we'll try to allow HF API calls based on the latest release to see if this is feasible.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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* Related to # (issue)
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} | # What does this PR do ?
Fixes invalid link in notebook.
**Collection**: ASR
# Changelog
- Fix invalid ASR inference link.
# Before your PR is "Ready for review"
**Pre checks**:
- [x] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
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- [ ] New Feature
- [x] Bugfix
- [ ] Documentation
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