code: def _convert_tflite_enum_type_to_tf_type(tflite_enum_type):
      """Converts tflite enum type (eg: 0) to tf type (eg: tf.float32).
  
      Args:
        tflite_enum_type: tflite enum type (eg: 0, that corresponds to float32)
  
      Raises:
        ValueError: If an invalid tflite enum type is provided.
  
      Returns:
        tf type (eg: tf.float32)
      """
      tf_type = _MAP_TFLITE_ENUM_TO_TF_TYPES.get(tflite_enum_type)
      if tf_type is None:
          raise ValueError(
              "Unsupported enum {}. The valid map of enum to tf types is : {}".format(
                  tflite_enum_type, _MAP_TFLITE_ENUM_TO_TF_TYPES
              )
          )
      return tf_type
  
imports: import copy
  import datetime
  import sys
  from absl import logging
  import flatbuffers
  from tensorflow.core.protobuf import config_pb2
  from tensorflow.core.protobuf import meta_graph_pb2
  from tensorflow.lite.python import conversion_metadata_schema_py_generated
  from tensorflow.lite.python import schema_py_generated
  from tensorflow.lite.python import schema_util
  from tensorflow.lite.python import tflite_keras_util
  from tensorflow.lite.python.op_hint import convert_op_hints_to_stubs
  from tensorflow.lite.python.op_hint import find_all_hinted_output_nodes
  from tensorflow.lite.tools import flatbuffer_utils
  from tensorflow.python.eager import function
  from tensorflow.python.framework import convert_to_constants
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import error_interpolation
  from tensorflow.python.grappler import tf_optimizer
  from tensorflow.python.training.saver import export_meta_graph
label_desc: Use image node_id 1 for calling a global function with example usage: _convert_tflite_enum_type_to_tf_type(tflite_enum_type) and returns: tf_type