class_docstr: Base class for testing TFRecord-based features.
code: def make_batch_feature(
      self,
      filenames,
      num_epochs,
      batch_size,
      label_key=None,
      reader_num_threads=1,
      parser_num_threads=1,
      shuffle=False,
      shuffle_seed=None,
      drop_final_batch=False,
  ):
      self.filenames = filenames
      self.num_epochs = num_epochs
      self.batch_size = batch_size
  
      return readers.make_batched_features_dataset(
          file_pattern=self.filenames,
          batch_size=self.batch_size,
          features={
              "file": parsing_ops.FixedLenFeature([], dtypes.int64),
              "record": parsing_ops.FixedLenFeature([], dtypes.int64),
              "keywords": parsing_ops.VarLenFeature(dtypes.string),
              "label": parsing_ops.FixedLenFeature([], dtypes.string),
          },
          label_key=label_key,
          reader=core_readers.TFRecordDataset,
          num_epochs=self.num_epochs,
          shuffle=shuffle,
          shuffle_seed=shuffle_seed,
          reader_num_threads=reader_num_threads,
          parser_num_threads=parser_num_threads,
          drop_final_batch=drop_final_batch,
      )
  
imports: import os
  from tensorflow.core.example import example_pb2
  from tensorflow.core.example import feature_pb2
  from tensorflow.python.data.experimental.ops import readers
  from tensorflow.python.data.kernel_tests import test_base
  from tensorflow.python.data.ops import readers
  from tensorflow.python.framework import dtypes
  from tensorflow.python.lib.io import python_io
  from tensorflow.python.ops import parsing_ops
  from tensorflow.python.util import compat
label_desc: Use image node_id 2 for calling the FeaturesTestBase obj's underlying member method code with example usage: obj.make_batch_feature(filenames, num_epochs, batch_size, label_key, reader_num_threads, parser_num_threads, shuffle, shuffle_seed, drop_final_batch) and returns: readers