Datasets:
Tasks:
Question Answering
Modalities:
Text
Sub-tasks:
extractive-qa
Languages:
code
Size:
100K - 1M
License:
Merge branch 'main' of https://huggingface.co/datasets/thepurpleowl/codequeries into main
Browse files- codequeries.py +40 -41
codequeries.py
CHANGED
@@ -41,9 +41,6 @@ CodeQueries Ideal setup.
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_PREFIX_DESCRIPTION = """\
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CodeQueries Prefix setup."""
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_SLIDING_WINDOW_DESCRIPTION = """\
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CodeQueries Sliding window setup."""
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_FILE_IDEAL_DESCRIPTION = """\
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CodeQueries File level Ideal setup."""
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@@ -82,28 +79,25 @@ class Codequeries(datasets.GeneratorBasedBuilder):
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"supporting_fact_spans", "code_file_path", "example_type",
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"subtokenized_input_sequence", "label_sequence"],
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citation=_CODEQUERIES_CITATION,
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-
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url="",
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),
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# CodequeriesConfig(
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# name="prefix",
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# description=_PREFIX_DESCRIPTION,
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# features=["query_name", "context_blocks", "answer_spans",
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# "supporting_fact_spans", "code_file_path", "example_type",
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# "subtokenized_input_sequence", "label_sequence"],
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# citation=_CODEQUERIES_CITATION,
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# url="",
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# ),
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# CodequeriesConfig(
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# name="sliding_window",
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# description=_SLIDING_WINDOW_DESCRIPTION,
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# features=["query_name", "context_blocks", "answer_spans",
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# "supporting_fact_spans", "code_file_path", "example_type",
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# "subtokenized_input_sequence", "label_sequence"],
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# citation=_CODEQUERIES_CITATION,
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# url="",
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# ),
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CodequeriesConfig(
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name="file_ideal",
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description=_FILE_IDEAL_DESCRIPTION,
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@@ -111,23 +105,28 @@ class Codequeries(datasets.GeneratorBasedBuilder):
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"supporting_fact_spans", "code_file_path", "example_type",
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"subtokenized_input_sequence", "label_sequence"],
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citation=_CODEQUERIES_CITATION,
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url="",
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),
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# CodequeriesConfig(
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# name="twostep",
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# description=_TWOSTEP_DESCRIPTION,
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# features=["query_name", "context_blocks", "answer_spans",
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# "supporting_fact_spans", "code_file_path", "example_type",
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# "subtokenized_input_sequence", "label_sequence"],
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# citation=_CODEQUERIES_CITATION,
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# url="",
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# ),
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]
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def _info(self):
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# features = {feature: datasets.Value("string") for feature in self.config.features}
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features = {}
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features["query_name"] = datasets.Value("string")
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features["context_blocks"] = [
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@@ -168,13 +167,13 @@ class Codequeries(datasets.GeneratorBasedBuilder):
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)
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def _split_generators(self, dl_manager):
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dl_dir =
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if self.config.name in ["prefix", "
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return [
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datasets.SplitGenerator(
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name=datasets.Split.TEST,
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gen_kwargs={
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"filepath": os.path.join(dl_dir
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"split": datasets.Split.TEST,
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},
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),
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@@ -184,28 +183,28 @@ class Codequeries(datasets.GeneratorBasedBuilder):
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datasets.SplitGenerator(
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name=datasets.Split.TRAIN,
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gen_kwargs={
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"filepath": os.path.join(dl_dir
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"split": datasets.Split.TRAIN,
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},
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),
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datasets.SplitGenerator(
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name=datasets.Split.VALIDATION,
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gen_kwargs={
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"filepath": os.path.join(dl_dir
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"split": datasets.Split.VALIDATION,
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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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gen_kwargs={
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"filepath": os.path.join(dl_dir
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"split": datasets.Split.TEST,
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},
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),
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]
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def _generate_examples(self, filepath, split):
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if self.config.name in ["prefix", "
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assert split == datasets.Split.TEST
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logger.info("generating examples from = %s", filepath)
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_PREFIX_DESCRIPTION = """\
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CodeQueries Prefix setup."""
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_FILE_IDEAL_DESCRIPTION = """\
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CodeQueries File level Ideal setup."""
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"supporting_fact_spans", "code_file_path", "example_type",
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"subtokenized_input_sequence", "label_sequence"],
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citation=_CODEQUERIES_CITATION,
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data_url={
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"train": "ideal_train.json",
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"dev": "ideal_val.json",
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"test": "ideal_test.json"
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},
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url="",
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),
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CodequeriesConfig(
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name="prefix",
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description=_PREFIX_DESCRIPTION,
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features=["query_name", "answer_spans",
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"supporting_fact_spans", "code_file_path", "example_type",
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"subtokenized_input_sequence", "label_sequence"],
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citation=_CODEQUERIES_CITATION,
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data_url={
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"test": "prefix_test.json"
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},
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url="",
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),
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CodequeriesConfig(
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name="file_ideal",
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description=_FILE_IDEAL_DESCRIPTION,
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"supporting_fact_spans", "code_file_path", "example_type",
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"subtokenized_input_sequence", "label_sequence"],
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citation=_CODEQUERIES_CITATION,
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data_url={
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"test": "file_ideal_test.json"
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},
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url="",
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),
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CodequeriesConfig(
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name="twostep",
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description=_TWOSTEP_DESCRIPTION,
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features=["query_name", "context_blocks", "answer_spans",
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"supporting_fact_spans", "code_file_path", "example_type",
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"subtokenized_input_sequence", "label_sequence"],
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citation=_CODEQUERIES_CITATION,
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data_url={
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"test": "twostep_relevance"
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},
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url="",
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),
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]
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DEFAULT_CONFIG_NAME = "ideal"
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def _info(self):
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features = {}
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features["query_name"] = datasets.Value("string")
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features["context_blocks"] = [
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)
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def _split_generators(self, dl_manager):
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dl_dir = dl_manager.download_and_extract(self.config.data_url)
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if self.config.name in ["prefix", "file_ideal", "twostep"]:
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return [
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datasets.SplitGenerator(
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name=datasets.Split.TEST,
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gen_kwargs={
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"filepath": os.path.join(dl_dir["test"]),
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"split": datasets.Split.TEST,
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},
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),
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datasets.SplitGenerator(
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name=datasets.Split.TRAIN,
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gen_kwargs={
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"filepath": os.path.join(dl_dir["train"]),
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"split": datasets.Split.TRAIN,
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},
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),
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datasets.SplitGenerator(
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name=datasets.Split.VALIDATION,
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gen_kwargs={
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"filepath": os.path.join(dl_dir["dev"]),
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"split": datasets.Split.VALIDATION,
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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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gen_kwargs={
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"filepath": os.path.join(dl_dir["test"]),
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"split": datasets.Split.TEST,
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},
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),
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]
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def _generate_examples(self, filepath, split):
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if self.config.name in ["prefix", "file_ideal", "twostep"]:
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assert split == datasets.Split.TEST
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logger.info("generating examples from = %s", filepath)
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