Stern5497 commited on
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086de5d
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1 Parent(s): c22f1de

Delete querie.py

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  1. querie.py +0 -119
querie.py DELETED
@@ -1,119 +0,0 @@
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- import csv
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- import json
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- import lzma
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- import os
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-
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- import datasets
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- try:
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- import lzma as xz
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- except ImportError:
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- import pylzma as xz
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-
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-
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- # TODO: Add BibTeX citation
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- # Find for instance the citation on arxiv or on the dataset repo/website
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- _CITATION = """\
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- @InProceedings{huggingface:dataset,
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- title = {A great new dataset},
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- author={huggingface, Inc.
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- },
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- year={2020}
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- }
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- """
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-
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- # You can copy an official description
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- _DESCRIPTION = """TODO"""
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-
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- # TODO: Add a link to an official homepage for the dataset here
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- _HOMEPAGE = ""
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-
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- # TODO: Add the licence for the dataset here if you can find it
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- _LICENSE = ""
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-
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- # The HuggingFace Datasets library doesn't host the datasets but only points to the original files.
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- # This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
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- _URLS = {
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- "german": "https://huggingface.co/datasets/Stern5497/querie/resolve/main/queries_de.jsonl",
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- "italian": "https://huggingface.co/datasets/Stern5497/querie/resolve/main/queries_it.jsonl",
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- "french": "https://huggingface.co/datasets/Stern5497/querie/resolve/main/queries_fr.jsonl",
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-
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- }
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-
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- def get_url(config_name):
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- return _URLS[config_name]
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-
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-
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- class querie(datasets.GeneratorBasedBuilder):
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- """This dataset contains court decision for law area prediction task."""
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-
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- VERSION = datasets.Version("1.1.0")
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-
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- BUILDER_CONFIGS = [
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- datasets.BuilderConfig(name="german", version=VERSION, description="This part of my dataset covers the whole dataset"),
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- datasets.BuilderConfig(name="italian", version=VERSION, description="This dataset is for predicting the sub law areas of the public law"),
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- datasets.BuilderConfig(name="french", version=VERSION, description="This dataset is for predicting the sub law areas of the civil law"),
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- ]
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-
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- DEFAULT_CONFIG_NAME = "german" # It's not mandatory to have a default configuration. Just use one if it make sense.
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-
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- def _info(self):
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- features = datasets.Features(
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- {
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- "id": datasets.Value("string")
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- # These are the features of your dataset like images, labels ...
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- }
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- )
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- return datasets.DatasetInfo(
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- # This is the description that will appear on the datasets page.
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- description=_DESCRIPTION,
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- # This defines the different columns of the dataset and their types
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- features=features, # Here we define them above because they are different between the two configurations
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- # If there's a common (input, target) tuple from the features, uncomment supervised_keys line below and
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- # specify them. They'll be used if as_supervised=True in builder.as_dataset.
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- # supervised_keys=("sentence", "label"),
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- # Homepage of the dataset for documentation
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- # homepage=_HOMEPAGE,
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- # License for the dataset if available
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- # license=_LICENSE,
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- # Citation for the dataset
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- # citation=_CITATION,
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- )
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-
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- def _split_generators(self, dl_manager):
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- # If several configurations are possible (listed in BUILDER_CONFIGS), the configuration selected by the user is in self.config.name
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-
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- # dl_manager is a datasets.download.DownloadManager that can be used to download and extract URLS
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- # It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files.
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- # By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive
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- urls = get_url(self.config.name)
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- filepath = dl_manager.download(urls)
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-
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- return [
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- datasets.SplitGenerator(
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- name=datasets.Split.TRAIN,
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- # These kwargs will be passed to _generate_examples
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- gen_kwargs={
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- "filepath": filepath,
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- "split": "train",
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- },
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- )
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- ]
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-
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- # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
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- def _generate_examples(self, filepath, split):
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- # The `key` is for legacy reasons (tfds) and is not important in itself, but must be unique for each example.
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- line_counter = 0
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- try:
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- with xz.open(open(filepath, "rb"), "rt", encoding="utf-8") as f:
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- for id, line in enumerate(f):
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- line_counter += 1
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- if line:
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- data = json.loads(line)
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- if self.config.name == "german" or self.config.name == "italian" or self.config.name == "french":
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- yield id, {
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- "id": data["id"]
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- }
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- except lzma.LZMAError as e:
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- print(split, e)
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- if line_counter == 0:
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- raise e