code: def testSerializedContainingDenseWithConcat(self):
      aname = "a"
      bname = "b*has+a:tricky_name"
      # TODO(lew): Feature appearing twice should be an error in future.
      original = [
          (
              example(
                  features=features(
                      {
                          aname: float_feature([10, 10]),
                      }
                  )
              ),
              example(
                  features=features(
                      {
                          aname: float_feature([1, 1]),
                          bname: bytes_feature([b"b0_str"]),
                      }
                  )
              ),
          ),
          (
              example(
                  features=features(
                      {
                          bname: bytes_feature([b"b100"]),
                      }
                  )
              ),
              example(
                  features=features(
                      {
                          aname: float_feature([-1, -1]),
                          bname: bytes_feature([b"b1"]),
                      }
                  )
              ),
          ),
      ]
  
      # pylint: disable=too-many-function-args
      expected_outputs = [
          {
              aname: np.array([1, 1], dtype=np.float32).reshape(
                  1, 2, 1
              ),
              bname: np.array(["b0_str"], dtype=bytes).reshape(
                  1, 1, 1, 1
              ),
          },
          {
              aname: np.array([-1, -1], dtype=np.float32).reshape(
                  1, 2, 1
              ),
              bname: np.array(["b1"], dtype=bytes).reshape(1, 1, 1, 1),
          },
      ]
      # pylint: enable=too-many-function-args
  
      for (m, n), expected_output in zip(original, expected_outputs):
          # No defaults, values required
          self._test(
              {
                  "serialized": ops.convert_to_tensor(
                      m.SerializeToString() + n.SerializeToString()
                  ),
                  "features": {
                      aname: parsing_ops.FixedLenFeature(
                          (1, 2, 1), dtype=dtypes.float32
                      ),
                      bname: parsing_ops.FixedLenFeature(
                          (1, 1, 1, 1), dtype=dtypes.string
                      ),
                  },
              },
              expected_output,
          )
  
imports: import itertools
  import numpy
  from tensorflow.core.example import example_pb2
  from tensorflow.core.example import feature_pb2
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors_impl
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import sparse_tensor
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import parsing_ops
  from tensorflow.python.platform import test
  from tensorflow.python.platform import tf_logging
label_desc: Use image node_id 11 for calling the ParseExampleTest obj's underlying member method code with example usage: obj.testSerializedContainingDenseWithConcat() without return types