joelniklaus commited on
Commit
4f61c9c
1 Parent(s): 7a2647a

Fixed Bug in loading script

Browse files
Files changed (1) hide show
  1. lextreme.py +7 -5
lextreme.py CHANGED
@@ -68,7 +68,7 @@ class LextremeConfig(datasets.BuilderConfig):
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  hf_hub_name: `string`, huggingface dataset identifier
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  hf_hub_name: `string`, the language of the dataset (either multilingual or a single language ISO code)
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  config_name: `string`, huggingface dataset config name
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- label_level: `string`, the label level (only necessary for multieurlex)
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  label_classes: `list[string]`, the list of classes if the label is
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  categorical. If not provided, then the label will be of type
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  `datasets.Value('float32')`.
@@ -4070,10 +4070,12 @@ class LEXTREME(datasets.GeneratorBasedBuilder):
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  def _generate_examples(self, split):
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  """This function returns the examples in the raw (text) form."""
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  # we can just do this, since all our datasets are available on the huggingface hub
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- dataset = datasets.load_dataset(self.config.hf_hub_name,
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- self.config.config_name,
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- label_level=self.config.label_level,
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- split=split)
 
 
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  for id, item in enumerate(dataset):
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  # In case we have a class label and not just a string: convert it back to the string
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  label_col = self.config.label_col
 
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  hf_hub_name: `string`, huggingface dataset identifier
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  hf_hub_name: `string`, the language of the dataset (either multilingual or a single language ISO code)
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  config_name: `string`, huggingface dataset config name
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+ label_level: `string`, the label level (only necessary for multi_eurlex)
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  label_classes: `list[string]`, the list of classes if the label is
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  categorical. If not provided, then the label will be of type
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  `datasets.Value('float32')`.
 
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  def _generate_examples(self, split):
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  """This function returns the examples in the raw (text) form."""
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  # we can just do this, since all our datasets are available on the huggingface hub
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+ if "multi_eurlex" in self.config.config_name:
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+ dataset = datasets.load_dataset(self.config.hf_hub_name, self.config.config_name, split=split,
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+ label_level=self.config.label_level)
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+ else:
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+ dataset = datasets.load_dataset(self.config.hf_hub_name, self.config.config_name, split=split)
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+
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  for id, item in enumerate(dataset):
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  # In case we have a class label and not just a string: convert it back to the string
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  label_col = self.config.label_col