import tensorflow as tf

      dict(
          testcase_name='fixed_len_float',
          make_tensors_fn=lambda:
          {'x': tf.compat.v1.placeholder(tf.float32, (None,))},
          feature_spec={'x': tf.io.FixedLenFeature([], tf.float32)}),
      dict(
          testcase_name='override',
          make_tensors_fn=_make_tensors_with_override,
          feature_spec={'x': tf.io.FixedLenFeature([], tf.int64)},
          domains={'x': schema_pb2.IntDomain(is_categorical=True)}),
      dict(
          testcase_name='override_with_session',
          make_tensors_fn=_make_tensors_with_override,
          feature_spec={'x': tf.io.FixedLenFeature([], tf.int64)},
          domains={
              'x': schema_pb2.IntDomain(min=5, max=6, is_categorical=True)
          },
          create_session=True))
  # pylint: enable=g-long-lambda
  def test_infer_feature_schema(self,
                                make_tensors_fn,
                                feature_spec,
                                domains=None,
                                create_session=False):
    with tf.compat.v1.Graph().as_default() as graph:
      tensors = make_tensors_fn()
