class_docstr: BuilderConfig for GLUE.
class_docstr_tok: ["BuilderConfig","for","GLUE","."]
docstr: BuilderConfig for GLUE.
  
  Args:
    text_features: `dict[string, string]`, map from the name of the feature
      dict for each text field to the name of the column in the tsv file
    label_column: `string`, name of the column in the tsv file corresponding
      to the label
    data_url: `string`, url to download the zip file from
    data_dir: `string`, the path to the folder containing the tsv files in the
      downloaded zip
    citation: `string`, citation for the data set
    url: `string`, url for information about the data set
    label_classes: `list[string]`, the list of classes if the label is
      categorical. If not provided, then the label will be of type
      `np.float32`.
    process_label: `Function[string, any]`, function taking in the raw value
      of the label and processing it to the form required by the label feature
    **kwargs: keyword arguments forwarded to super.
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code: def __init__(
      self,
      *,
      text_features,
      label_column,
      data_url,
      data_dir,
      citation,
      url,
      label_classes=None,
      process_label=lambda x: x,
      **kwargs,
  ):
      """BuilderConfig for GLUE.
  
      Args:
        text_features: `dict[string, string]`, map from the name of the feature
          dict for each text field to the name of the column in the tsv file
        label_column: `string`, name of the column in the tsv file corresponding
          to the label
        data_url: `string`, url to download the zip file from
        data_dir: `string`, the path to the folder containing the tsv files in the
          downloaded zip
        citation: `string`, citation for the data set
        url: `string`, url for information about the data set
        label_classes: `list[string]`, the list of classes if the label is
          categorical. If not provided, then the label will be of type
          `np.float32`.
        process_label: `Function[string, any]`, function taking in the raw value
          of the label and processing it to the form required by the label feature
        **kwargs: keyword arguments forwarded to super.
      """
      super(GlueConfig, self).__init__(
          version=tfds.core.Version("2.0.0"),
          supported_versions=[
              tfds.core.Version("1.0.0"),
              tfds.core.Version("1.0.1"),
          ],
          release_notes={
              "1.0.0": "New split API (https://tensorflow.org/datasets/splits)",
              "1.0.1": "Update dead URL links.",
              "2.0.0": "Update data source for glue/qqp.",
          },
          **kwargs,
      )  # pytype: disable=wrong-arg-types  # gen-stub-imports
      self.text_features = text_features
      self.label_column = label_column
      self.label_classes = label_classes
      self.data_url = data_url
      self.data_dir = data_dir
      self.citation = citation
      self.url = url
      self.process_label = process_label
  
file_path: datasets/tensorflow_datasets/text/glue.py
imports: import csv
  import os
  import textwrap
  from etils import epath
  import numpy
  import six
  import tensorflow_datasets.public_api
label_desc: Use image node_id 1 to create a new GlueConfig object from inherited base classes: tfds.core with example: obj = GlueConfig()