class_docstr: DatasetBuilder initialized from a Croissant config file.
class_docstr_tok: ["DatasetBuilder","initialized","from","a","Croissant","config","file","."]
docstr: Initializes a CroissantBuilder.
  
  Args:
    file: The Croissant config file for the given dataset.
    record_set_names: The names of the record sets to generate. Each record
      set will correspond to a separate config.
    disable_shuffling: Specify whether to shuffle the examples.
    int_dtype: The dtype to use for TFDS integer features. Defaults to
      np.int64.
    float_dtype: The dtype to use for TFDS float features. Defaults to
      np.float32.
    **kwargs: kwargs to pass to GeneratorBasedBuilder directly.
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code: def __init__(
      self,
      *,
      file: epath.PathLike,
      record_set_names: Sequence[str],
      disable_shuffling: Optional[bool] = False,
      int_dtype: Optional[type_utils.TfdsDType] = np.int64,
      float_dtype: Optional[type_utils.TfdsDType] = np.float32,
      **kwargs: Any,
  ):
      """Initializes a CroissantBuilder.
  
      Args:
        file: The Croissant config file for the given dataset.
        record_set_names: The names of the record sets to generate. Each record
          set will correspond to a separate config.
        disable_shuffling: Specify whether to shuffle the examples.
        int_dtype: The dtype to use for TFDS integer features. Defaults to
          np.int64.
        float_dtype: The dtype to use for TFDS float features. Defaults to
          np.float32.
        **kwargs: kwargs to pass to GeneratorBasedBuilder directly.
      """
      self.dataset = mlc.Dataset(file)
      self.name = self.dataset.metadata.name
      self.metadata = self.dataset.metadata
  
      # In TFDS, version is a mandatory attribute, while in Croissant it is only a
      # recommended attribute. If the version is unspecified in Croissant, we set
      # it to `1.0.0` in TFDS.
      self.VERSION = (
          self.dataset.metadata.version or "1.0.0"
      )  # pylint: disable=invalid-name
      self.RELEASE_NOTES = {}  # pylint: disable=invalid-name
  
      self.BUILDER_CONFIGS: Sequence[
          dataset_builder.BuilderConfig
      ] = [  # pylint: disable=invalid-name
          dataset_builder.BuilderConfig(name=record_set_name)
          for record_set_name in record_set_names
      ]
  
      self._disable_shuffling = disable_shuffling
  
      self._int_dtype = int_dtype
      self._float_dtype = float_dtype
  
      super().__init__(
          **kwargs,
      )
  
imports: from typing import Any, Dict, Optional, Sequence
  from etils import epath
  import numpy
  from tensorflow_datasets.core import dataset_builder
  from tensorflow_datasets.core import dataset_info
  from tensorflow_datasets.core import download
  from tensorflow_datasets.core import split_builder
  from tensorflow_datasets.core import splits
  from tensorflow_datasets.core.features import feature
  from tensorflow_datasets.core.features import features_dict
  from tensorflow_datasets.core.features import image_feature
  from tensorflow_datasets.core.features import sequence_feature
  from tensorflow_datasets.core.features import text_feature
  from tensorflow_datasets.core.utils import type_utils
  from tensorflow_datasets.core.utils.lazy_imports_utils import mlcroissant
  from tensorflow_datasets.core.utils.lazy_imports_utils import pandas
label_desc: Use image node_id 1 to create a new CroissantBuilder object from inherited base classes: dataset_builder with example: obj = CroissantBuilder()