Update inspec.py
Browse files
inspec.py
CHANGED
@@ -51,7 +51,7 @@ class TestLDKP(datasets.GeneratorBasedBuilder):
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if self.config.name == "extraction" or self.config.name == "ldkp_extraction": # This is the name of the configuration selected in BUILDER_CONFIGS above
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features = datasets.Features(
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{
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"id": datasets.Value("int64")
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"document": datasets.features.Sequence(datasets.Value("string")),
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"BIO_tags": datasets.features.Sequence(datasets.Value("string"))
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@@ -60,7 +60,7 @@ class TestLDKP(datasets.GeneratorBasedBuilder):
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elif self.config.name == "generation" or self.config.name == "ldkp_generation":
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features = datasets.Features(
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{
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"id": datasets.Value("int64")
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"document": datasets.features.Sequence(datasets.Value("string")),
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"extractive_keyphrases": datasets.features.Sequence(datasets.Value("string")),
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"abstractive_keyphrases": datasets.features.Sequence(datasets.Value("string"))
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@@ -70,7 +70,7 @@ class TestLDKP(datasets.GeneratorBasedBuilder):
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else:
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features = datasets.Features(
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{
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"id": datasets.Value("int64")
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"document": datasets.features.Sequence(datasets.Value("string")),
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"document_tags": datasets.features.Sequence(datasets.Value("string")),
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"extractive_keyphrases": datasets.features.Sequence(datasets.Value("string")),
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@@ -101,14 +101,14 @@ class TestLDKP(datasets.GeneratorBasedBuilder):
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data_dir = dl_manager.download_and_extract(_URLS)
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return [
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datasets.SplitGenerator(
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),
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datasets.SplitGenerator(
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name=datasets.Split.TEST,
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# These kwargs will be passed to _generate_examples
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if self.config.name == "extraction" or self.config.name == "ldkp_extraction": # This is the name of the configuration selected in BUILDER_CONFIGS above
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features = datasets.Features(
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{
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"id": datasets.Value("int64"),
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"document": datasets.features.Sequence(datasets.Value("string")),
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"BIO_tags": datasets.features.Sequence(datasets.Value("string"))
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elif self.config.name == "generation" or self.config.name == "ldkp_generation":
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features = datasets.Features(
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{
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"id": datasets.Value("int64"),
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"document": datasets.features.Sequence(datasets.Value("string")),
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"extractive_keyphrases": datasets.features.Sequence(datasets.Value("string")),
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"abstractive_keyphrases": datasets.features.Sequence(datasets.Value("string"))
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else:
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features = datasets.Features(
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{
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"id": datasets.Value("int64"),
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"document": datasets.features.Sequence(datasets.Value("string")),
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"document_tags": datasets.features.Sequence(datasets.Value("string")),
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"extractive_keyphrases": datasets.features.Sequence(datasets.Value("string")),
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data_dir = dl_manager.download_and_extract(_URLS)
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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": data_dir['train'],
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# "split": "train",
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# },
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# ),
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datasets.SplitGenerator(
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name=datasets.Split.TEST,
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# These kwargs will be passed to _generate_examples
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