Datasets:
ArXiv:
License:
error fix
Browse files- snow-mountain.py +12 -12
snow-mountain.py
CHANGED
@@ -102,35 +102,35 @@ class Test(datasets.GeneratorBasedBuilder):
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name="train_500",
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gen_kwargs={
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"filepath": downloaded_files["train_500"],
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-
"
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},
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),
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datasets.SplitGenerator(
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name="train_1000",
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gen_kwargs={
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"filepath": downloaded_files["train_1000"],
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-
"
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},
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),
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datasets.SplitGenerator(
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name="train_2500",
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gen_kwargs={
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"filepath": downloaded_files["train_2500"],
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-
"
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},
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),
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datasets.SplitGenerator(
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name="train_short",
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gen_kwargs={
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"filepath": downloaded_files["train_short"],
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-
"
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},
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),
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datasets.SplitGenerator(
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name="train_full",
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gen_kwargs={
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"filepath": downloaded_files["train_full"],
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-
"
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},
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),
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]
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@@ -140,35 +140,35 @@ class Test(datasets.GeneratorBasedBuilder):
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name="val_500",
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gen_kwargs={
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"filepath": downloaded_files["val_500"],
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-
"
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},
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),
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datasets.SplitGenerator(
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name="val_1000",
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gen_kwargs={
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"filepath": downloaded_files["val_1000"],
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-
"
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},
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),
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datasets.SplitGenerator(
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name="val_2500",
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gen_kwargs={
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"filepath": downloaded_files["val_2500"],
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-
"
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},
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),
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datasets.SplitGenerator(
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name="val_short",
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gen_kwargs={
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"filepath": downloaded_files["val_short"],
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-
"
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},
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),
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datasets.SplitGenerator(
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name="val_full",
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gen_kwargs={
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"filepath": downloaded_files["val_full"],
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-
"
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},
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),
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]
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@@ -178,14 +178,14 @@ class Test(datasets.GeneratorBasedBuilder):
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name="test_common",
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gen_kwargs={
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"filepath": downloaded_files["test_common"],
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-
"
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},
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),
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]
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return train_splits + dev_splits + test_splits
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-
def _generate_examples(self, filepath,
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key = 0
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with open(filepath) as f:
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data_df = pd.read_csv(f,sep=',')
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name="train_500",
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gen_kwargs={
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"filepath": downloaded_files["train_500"],
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+
"dl_manager": dl_manager,
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},
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),
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datasets.SplitGenerator(
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name="train_1000",
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gen_kwargs={
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"filepath": downloaded_files["train_1000"],
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+
"dl_manager": dl_manager,
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},
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),
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datasets.SplitGenerator(
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name="train_2500",
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gen_kwargs={
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"filepath": downloaded_files["train_2500"],
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+
"dl_manager": dl_manager,
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},
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),
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datasets.SplitGenerator(
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name="train_short",
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gen_kwargs={
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"filepath": downloaded_files["train_short"],
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+
"dl_manager": dl_manager,
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},
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),
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datasets.SplitGenerator(
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name="train_full",
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gen_kwargs={
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"filepath": downloaded_files["train_full"],
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+
"dl_manager": dl_manager,
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},
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),
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]
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name="val_500",
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gen_kwargs={
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"filepath": downloaded_files["val_500"],
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+
"dl_manager": dl_manager,
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},
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),
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datasets.SplitGenerator(
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name="val_1000",
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gen_kwargs={
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"filepath": downloaded_files["val_1000"],
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+
"dl_manager": dl_manager,
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},
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),
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datasets.SplitGenerator(
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name="val_2500",
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gen_kwargs={
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"filepath": downloaded_files["val_2500"],
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+
"dl_manager": dl_manager,
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},
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),
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datasets.SplitGenerator(
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name="val_short",
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gen_kwargs={
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"filepath": downloaded_files["val_short"],
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+
"dl_manager": dl_manager,
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},
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),
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datasets.SplitGenerator(
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name="val_full",
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gen_kwargs={
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"filepath": downloaded_files["val_full"],
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+
"dl_manager": dl_manager,
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},
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),
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]
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name="test_common",
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gen_kwargs={
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"filepath": downloaded_files["test_common"],
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+
"dl_manager": dl_manager,
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},
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),
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]
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return train_splits + dev_splits + test_splits
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+
def _generate_examples(self, filepath, dl_manager):
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key = 0
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with open(filepath) as f:
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data_df = pd.read_csv(f,sep=',')
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