class_docstr: Base class for testing TFRecord-based features.
code: def _run_actual_batch(self, outputs, label_key_provided=False):
      if label_key_provided:
          # outputs would be a tuple of (feature dict, label)
          features, label = self.evaluate(outputs())
      else:
          features = self.evaluate(outputs())
          label = features["label"]
      file_out = features["file"]
      keywords_indices = features["keywords"].indices
      keywords_values = features["keywords"].values
      keywords_dense_shape = features["keywords"].dense_shape
      record = features["record"]
      return [
          file_out,
          keywords_indices,
          keywords_values,
          keywords_dense_shape,
          record,
          label,
      ]
  
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 7 for calling the FeaturesTestBase obj's underlying member method code with example usage: obj._run_actual_batch(outputs, label_key_provided) and returns: list