class_docstr: BuilderConfig for AbstractReasoning.
class_docstr_tok: ["BuilderConfig","for","AbstractReasoning","."]
docstr: BuilderConfig for AbstractReasoning.
  
  Args:
    split_type: String with split_type to use. Should be one of ["neutral",
      "interpolation", "extrapolation", "attr.rel.pairs", "attr.rels",
      "attrs.pairs", "attrs.shape.color", "attrs.line.type",].
    **kwargs: keyword arguments forwarded to super.
docstr_tok: ["BuilderConfig","for","AbstractReasoning",".","Args",":","split_type",":","String","with","split_type","to","use",".","Should","be","one","of","[","``","neutral","''",",","``","interpolation","''",",","``","extrapolation","''",",","``","attr.rel.pairs","''",",","``","attr.rels","''",",","``","attrs.pairs","''",",","``","attrs.shape.color","''",",","``","attrs.line.type","''",",","]",".","*","*","kwargs",":","keyword","arguments","forwarded","to","super","."]
code: def __init__(self, *, split_type="neutral", **kwargs):
      """BuilderConfig for AbstractReasoning.
  
      Args:
        split_type: String with split_type to use. Should be one of ["neutral",
          "interpolation", "extrapolation", "attr.rel.pairs", "attr.rels",
          "attrs.pairs", "attrs.shape.color", "attrs.line.type",].
        **kwargs: keyword arguments forwarded to super.
      """
      super(AbstractReasoningConfig, self).__init__(
          version=tfds.core.Version("1.0.0"),
          **kwargs,
      )
      self.split_type = split_type
  
file_path: datasets/tensorflow_datasets/datasets/abstract_reasoning/abstract_reasoning_dataset_builder.py
imports: import os
  import random
  import numpy
  import six
  import tensorflow_datasets.public_api
label_desc: Use image node_id 1 to create a new AbstractReasoningConfig object from inherited base classes: tfds.core with example: obj = AbstractReasoningConfig()