Update files from the datasets library (from 1.1.3)
Browse filesRelease notes: https://github.com/huggingface/datasets/releases/tag/1.1.3
- clue.py +31 -3
- dataset_infos.json +1 -1
- dummy/ocnli/1.0.0/dummy_data.zip +3 -0
clue.py
CHANGED
@@ -288,6 +288,34 @@ class Clue(datasets.GeneratorBasedBuilder):
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}"""
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ClueConfig(
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name="diagnostics",
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description=textwrap.dedent(
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@@ -306,7 +334,7 @@ class Clue(datasets.GeneratorBasedBuilder):
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]
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def _info(self):
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-
if self.config.name in ["afqmc", "tnews", "iflytek", "cmnli", "diagnostics"]:
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features = {
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text_feature: datasets.Value("string") for text_feature in six.iterkeys(self.config.text_features)
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}
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@@ -506,8 +534,8 @@ class Clue(datasets.GeneratorBasedBuilder):
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elif self.config.label_column in row:
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label = row[self.config.label_column]
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# Notice: some labels in CMNLI are
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if self.config.name
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continue
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# For some tasks, the label is represented as 0 and 1 in the tsv
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# files and needs to be cast to integer to work with the feature.
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}"""
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),
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ClueConfig(
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name="ocnli",
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description=textwrap.dedent(
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"""\
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OCNLI stands for Original Chinese Natural Language Inference. It is a corpus for
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Chinese Natural Language Inference, collected following closely the procedures of MNLI,
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but with enhanced strategies aiming for more challenging inference pairs. We want to
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emphasize we did not use human/machine translation in creating the dataset, and thus
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our Chinese texts are original and not translated.
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"""
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),
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text_features={"sentence1": "sentence1", "sentence2": "sentence2"},
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label_classes=["neutral", "entailment", "contradiction"],
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label_column="label",
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data_url="https://github.com/CLUEbenchmark/OCNLI/archive/02d55cb3c7dc984682677b8dd81db6a1e4710720.zip",
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data_dir="OCNLI-02d55cb3c7dc984682677b8dd81db6a1e4710720/data/ocnli",
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url="https://arxiv.org/abs/2010.05444",
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citation=textwrap.dedent(
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"""\
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@inproceedings{ocnli,
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title={OCNLI: Original Chinese Natural Language Inference},
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author={Hai Hu and Kyle Richardson and Liang Xu and Lu Li and Sandra Kuebler and Larry Moss},
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booktitle={Findings of EMNLP},
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year={2020},
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url={https://arxiv.org/abs/2010.05444}
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}"""
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),
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),
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ClueConfig(
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name="diagnostics",
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description=textwrap.dedent(
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]
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def _info(self):
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if self.config.name in ["afqmc", "tnews", "iflytek", "cmnli", "diagnostics", "ocnli"]:
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features = {
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text_feature: datasets.Value("string") for text_feature in six.iterkeys(self.config.text_features)
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}
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elif self.config.label_column in row:
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label = row[self.config.label_column]
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# Notice: some labels in CMNLI and OCNLI are invalid. We drop these data.
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if self.config.name in ["cmnli", "ocnli"] and label == "-":
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continue
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# For some tasks, the label is represented as 0 and 1 in the tsv
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# files and needs to be cast to integer to work with the feature.
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dataset_infos.json
CHANGED
@@ -1 +1 @@
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-
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