class_docstr: A wrapper around the output of the tf.Transform.
docstr: Init method for TFTransformOutput.
  
  Args:
    transform_output_dir: The directory containig tf.Transform output.
docstr_tok: ["Init","method","for","TFTransformOutput",".","Args",":","transform_output_dir",":","The","directory","containig","tf.Transform","output","."]
code: def __init__(self, transform_output_dir: str):
      """Init method for TFTransformOutput.
  
      Args:
        transform_output_dir: The directory containig tf.Transform output.
      """
      self._transform_output_dir = transform_output_dir
  
      # Lazily constructed properties.
      self._transformed_metadata = None
      self._raw_metadata = None
      self._transform_features_layer = None
      self._exported_as_v1_value = None
      self._transformed_domains = None
  
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 1 to create a new TFTransformOutput object  with example: obj = TFTransformOutput(transform_output_dir)