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Kosuke-Yamada commited on
Commit
707ae5a
1 Parent(s): e01c16e

modify the difinition of features

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Files changed (1) hide show
  1. ner-wikipedia-dataset.py +13 -9
ner-wikipedia-dataset.py CHANGED
@@ -96,17 +96,17 @@ class NerWikipediaDataset(datasets.GeneratorBasedBuilder):
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  # This defines the different columns of the dataset and their types
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  features=datasets.Features(
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  {
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- "curid": datasets.Value("int32"),
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  "text": datasets.Value("string"),
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  "entities": datasets.Sequence(
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- feature={
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  "name": datasets.Value(dtype="string"),
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  "span": datasets.Sequence(
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- feature=datasets.Value(dtype="int32"), length=2
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  ),
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  "type": datasets.Value(dtype="string"),
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- },
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- )
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  # These are the features of your dataset like images, labels ...
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  }
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  ), # Here we define them above because they are different between the two configurations
@@ -149,22 +149,26 @@ class NerWikipediaDataset(datasets.GeneratorBasedBuilder):
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  test_data = data[validation_split:]
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  return [
 
 
 
 
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  datasets.SplitGenerator(
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  name=datasets.Split.TRAIN,
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- gen_kwargs={"data": train_data, "split": "train"},
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  ),
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  datasets.SplitGenerator(
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  name=datasets.Split.VALIDATION,
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- gen_kwargs={"data": validation_data, "split": "validation"},
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  ),
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  datasets.SplitGenerator(
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  name=datasets.Split.TEST,
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- gen_kwargs={"data": test_data, "split": "test"},
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  ),
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  ]
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  # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
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- def _generate_examples(self, data, split):
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  # TODO: This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.
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  # The `key` is for legacy reasons (tfds) and is not important in itself, but must be unique for each example.
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  for key, data in enumerate(data):
 
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  # This defines the different columns of the dataset and their types
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  features=datasets.Features(
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  {
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+ "curid": datasets.Value("string"),
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  "text": datasets.Value("string"),
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  "entities": datasets.Sequence(
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+ {
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  "name": datasets.Value(dtype="string"),
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  "span": datasets.Sequence(
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+ datasets.Value(dtype="int64"), length=2
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  ),
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  "type": datasets.Value(dtype="string"),
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+ }
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+ ),
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  # These are the features of your dataset like images, labels ...
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  }
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  ), # Here we define them above because they are different between the two configurations
 
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  test_data = data[validation_split:]
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  return [
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+ datasets.SplitGenerator(
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+ name=datasets.Split.ALL,
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+ gen_kwargs={"data": data},
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+ ),
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  datasets.SplitGenerator(
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  name=datasets.Split.TRAIN,
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+ gen_kwargs={"data": train_data},
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  ),
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  datasets.SplitGenerator(
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  name=datasets.Split.VALIDATION,
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+ gen_kwargs={"data": validation_data},
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  ),
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  datasets.SplitGenerator(
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  name=datasets.Split.TEST,
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+ gen_kwargs={"data": test_data},
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  ),
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  ]
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  # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
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+ def _generate_examples(self, data):
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  # TODO: This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.
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  # The `key` is for legacy reasons (tfds) and is not important in itself, but must be unique for each example.
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  for key, data in enumerate(data):