class_docstr: A wrapper around the output of the tf.Transform.
docstr: Returns the number of buckets for an integerized transformed feature.
docstr_tok: ["Returns","the","number","of","buckets","for","an","integerized","transformed","feature","."]
code: def num_buckets_for_transformed_feature(self, name: str) -> int:
      """Returns the number of buckets for an integerized transformed feature."""
      # Do checks that this tensor can be wrapped in
      # sparse_column_with_integerized_feature
      try:
          domain = self.transformed_domains()[name]
      except KeyError:
          raise ValueError(
              "Column {} did not have a domain provided.".format(name)
          )
      if not isinstance(domain, schema_pb2.IntDomain):
          raise ValueError(
              "Column {} has domain {}, expected an IntDomain".format(
                  name, domain
              )
          )
      if domain.min != 0:
          raise ValueError(
              "Column {} has min value {}, should be 0".format(
                  name, domain.min
              )
          )
      return domain.max + 1
  
imports: import json
  import os
  from typing import Any, Dict, List, Mapping, Optional
  import numpy
  import tensorflow
  from tensorflow_transform import common
  from tensorflow_transform import common_types
  from tensorflow_transform import graph_tools
  from tensorflow_transform.analyzers import sanitized_vocab_filename
  from tensorflow_transform.keras_lib import tf_keras
  from tensorflow_transform.saved import saved_transform_io
  from tensorflow_transform.saved import saved_transform_io_v2
  from tensorflow_transform.tf_metadata import dataset_metadata
  from tensorflow_transform.tf_metadata import metadata_io
  from tensorflow_transform.tf_metadata import schema_utils
  from tensorflow.python.framework import ops
  from tensorflow.tools.docs import doc_controls
  from tensorflow_metadata.proto.v0 import schema_pb2
label_desc: Use image node_id 12 for calling the TFTransformOutput obj's underlying member method code with example usage: obj.num_buckets_for_transformed_feature(name) and returns: unknown