system HF staff commited on
Commit
9203151
1 Parent(s): 6323813

Update files from the datasets library (from 1.2.0)

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Release notes: https://github.com/huggingface/datasets/releases/tag/1.2.0

Files changed (1) hide show
  1. cosmos_qa.py +7 -9
cosmos_qa.py CHANGED
@@ -4,7 +4,6 @@ from __future__ import absolute_import, division, print_function
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  import csv
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  import json
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- import os
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  import datasets
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@@ -24,10 +23,13 @@ _CITATION = """\
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  _DESCRIPTION = """\
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  Cosmos QA is a large-scale dataset of 35.6K problems that require commonsense-based reading comprehension, formulated as multiple-choice questions. It focuses on reading between the lines over a diverse collection of people's everyday narratives, asking questions concerning on the likely causes or effects of events that require reasoning beyond the exact text spans in the context
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  """
 
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  _URL = "https://github.com/wilburOne/cosmosqa/raw/master/data/"
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- _TEST_FILE = "test.jsonl"
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- _TRAIN_FILE = "train.csv"
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- _DEV_FILE = "valid.csv"
 
 
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  class CosmosQa(datasets.GeneratorBasedBuilder):
@@ -69,11 +71,7 @@ class CosmosQa(datasets.GeneratorBasedBuilder):
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  # TODO(cosmos_qa): Downloads the data and defines the splits
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  # dl_manager is a datasets.download.DownloadManager that can be used to
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  # download and extract URLs
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- urls_to_download = {
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- "train": os.path.join(_URL, _TRAIN_FILE),
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- "test": os.path.join(_URL, _TEST_FILE),
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- "dev": os.path.join(_URL, _DEV_FILE),
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- }
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  dl_dir = dl_manager.download_and_extract(urls_to_download)
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  return [
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  datasets.SplitGenerator(
 
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  import csv
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  import json
 
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  import datasets
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  _DESCRIPTION = """\
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  Cosmos QA is a large-scale dataset of 35.6K problems that require commonsense-based reading comprehension, formulated as multiple-choice questions. It focuses on reading between the lines over a diverse collection of people's everyday narratives, asking questions concerning on the likely causes or effects of events that require reasoning beyond the exact text spans in the context
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  """
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+
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  _URL = "https://github.com/wilburOne/cosmosqa/raw/master/data/"
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+ _URLS = {
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+ "train": _URL + "train.csv",
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+ "test": _URL + "test.jsonl",
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+ "dev": _URL + "valid.csv",
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+ }
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  class CosmosQa(datasets.GeneratorBasedBuilder):
 
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  # TODO(cosmos_qa): Downloads the data and defines the splits
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  # dl_manager is a datasets.download.DownloadManager that can be used to
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  # download and extract URLs
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+ urls_to_download = _URLS
 
 
 
 
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  dl_dir = dl_manager.download_and_extract(urls_to_download)
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  return [
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  datasets.SplitGenerator(