class_docstr: Representative dataset loader.
  
  Exposes the `load` method that loads the representative dataset from files.
class_docstr_tok: ["Representative","dataset","loader",".","Exposes","the","`","load","`","method","that","loads","the","representative","dataset","from","files","."]
docstr: Initializes TFRecord represenatative dataset loader.
  
  Args:
    dataset_file_map: Signature key -> `RepresentativeDatasetFile` mapping.
  
  Raises:
    DecodeError: If the sample is not RepresentativeDataSample.
docstr_tok: ["Initializes","TFRecord","represenatative","dataset","loader",".","Args",":","dataset_file_map",":","Signature","key","-",">","`","RepresentativeDatasetFile","`","mapping",".","Raises",":","DecodeError",":","If","the","sample","is","not","RepresentativeDataSample","."]
code: def __init__(
      self,
      dataset_file_map: Mapping[str, _RepresentativeDatasetFile],
  ) -> None:
      """Initializes TFRecord represenatative dataset loader.
  
      Args:
        dataset_file_map: Signature key -> `RepresentativeDatasetFile` mapping.
  
      Raises:
        DecodeError: If the sample is not RepresentativeDataSample.
      """
      self.dataset_file_map = dataset_file_map
  
imports: import collections.abc
  import os
  from typing import Iterable, Mapping, Optional, Union
  import numpy
  from tensorflow.compiler.mlir.quantization.tensorflow import quantization_options_pb2
  from tensorflow.core.protobuf import meta_graph_pb2
  from tensorflow.python.client import session
  from tensorflow.python.data.ops import readers
  from tensorflow.python.eager import context
  from tensorflow.python.framework import tensor_util
  from tensorflow.python.lib.io import python_io
  from tensorflow.python.platform import tf_logging
  from tensorflow.python.types import core
  from tensorflow.python.util import tf_export
label_desc: Use image node_id 1 to create a new RepresentativeDatasetLoader object  with example: obj = RepresentativeDatasetLoader(dataset_file_map)