class_docstr: InputCreator with feature specs.
  
  Example usage:
  
  ```python
  input_creator=FeatureSpecInputCreator(
      {},
      {"example_feature_1": tf.io.FixedLenFeature(
          shape=(1,), dtype=tf.float32, default_value=0.0)})
  ```
docstr: See `InputCreator`.
docstr_tok: ["See","`","InputCreator","`","."]
code: def __call__(self) -> Tuple[TensorDict, TensorDict]:
      """See `InputCreator`."""
  
      def get_keras_input(feature_spec, name, is_example=False):
          if isinstance(feature_spec, tf.io.FixedLenFeature):
              return tf.keras.Input(
                  shape=(None,) + tuple(feature_spec.shape)
                  if is_example
                  else tuple(feature_spec.shape),
                  dtype=feature_spec.dtype,
                  name=name,
              )
          elif isinstance(feature_spec, tf.io.VarLenFeature):
              return tf.keras.Input(
                  shape=(None, 1) if is_example else (1),
                  dtype=feature_spec.dtype,
                  name=name,
                  sparse=True,
              )
          elif isinstance(feature_spec, tf.io.RaggedFeature):
              return tf.keras.Input(
                  shape=(None,) * (len(feature_spec.partitions) + 2)
                  if is_example
                  else (None,) * (len(feature_spec.partitions) + 1),
                  dtype=feature_spec.dtype,
                  name=name,
                  ragged=True,
              )
          else:
              raise ValueError(
                  "{} is not supported.".format(feature_spec)
              )
  
      context_inputs = {
          name: get_keras_input(spec, name)
          for name, spec in self._context_feature_spec.items()
      }
      example_inputs = {
          name: get_keras_input(spec, name, is_example=True)
          for name, spec in self._example_feature_spec.items()
      }
      return context_inputs, example_inputs
  
imports: import abc
  from typing import Any, Callable, Dict, List, Optional, Tuple, Union
  from absl import logging
  import tensorflow
  from tensorflow_ranking.python.keras import feature
  from tensorflow_ranking.python.keras import layers
label_desc: Use image node_id 2 for calling the FeatureSpecInputCreator obj's underlying member method code with example usage: obj.__call__() and returns: context_inputs,  example_inputs, tf, tf, tf