class_docstr: ImageDecoderInterface implementation based on tensorflow library.
  
  This image decoder only supports image formats supported by:
  tf.image.decode_image, ['bmp', 'gif', 'jpeg', 'png'].
  
  Image sizes are computed using tf.image.decode_image, which requires tf.
  Initializating and pickling tf objects can be non-trivial, so:
  - Initialization is done lazily when get_sizes computation is needed.
  - __reduce__() is overridden so that tf state is ignored. It is lazily
    initialized as needed, after deserialization.
code: def __reduce__(self):
      return TfImageDecoder, tuple()
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import abc
  import collections
  from typing import Iterable, List, Optional, Text
  import numpy
  import pandas
  import pyarrow
  import six
  import tensorflow
  from tensorflow_data_validation import types
  from tensorflow_data_validation.statistics.generators import stats_generator
  from tensorflow_data_validation.utils import stats_util
  from tfx_bsl.arrow import array_util
  from tensorflow_metadata.proto.v0 import statistics_pb2
label_desc: Use image node_id 2 for calling the TfImageDecoder obj's underlying member method code with example usage: obj.__reduce__() and returns: TfImageDecoder,  tuple