SavedModelBundle saved_model_bundle;
  SignatureDef signature_def_0 = BuildSignatureDef({"input0:0"}, {"output0:0"});
  SignatureDef signature_def_1 = BuildSignatureDef({"input1:0"}, {"output1:0"});
  AddSignatureDefToSavedModelBundle(signature_def_0, "signature_def_0",
                                    &saved_model_bundle);
  AddSignatureDefToSavedModelBundle(signature_def_1, "signature_def_1",
                                    &saved_model_bundle);

// CHECK-NEXT:  } ],
// CHECK-NEXT:  description: "MLIR Converted.",

// CHECK:  metadata: [ {
// CHECK-NEXT:    name: "min_runtime_version",
// CHECK-NEXT:    buffer: 8
// CHECK-NEXT:  } ],
// CHECK-NEXT:  signature_defs: [ {
// CHECK-NEXT:    inputs: [ {
// CHECK-NEXT:      name: "input1",
// CHECK-NEXT:      tensor_index: 1
// CHECK-NEXT:    }, {
// CHECK-NEXT:      name: "input2"
// CHECK-NEXT:    } ],

  tensor_info_s = tf.compat.v1.saved_model.utils.build_tensor_info(s)
  tensor_info_t = tf.compat.v1.saved_model.utils.build_tensor_info(t)

  signature_def = tf.saved_model.signature_def_utils.build_signature_def(
      inputs=None, outputs={'s': tensor_info_s}, method_name='some_function')
  signature_def2 = tf.saved_model.signature_def_utils.build_signature_def(
      inputs=None, outputs={'t': tensor_info_t}, method_name='some_function')

  tensor_info_x = tf.saved_model.utils.build_tensor_info(x)
  tensor_info_r = tf.saved_model.utils.build_tensor_info(r)

  signature_def = tf.saved_model.signature_def_utils.build_signature_def(
      inputs={'x': tensor_info_x},
      outputs={'r': tensor_info_r},
      method_name='some_function')
  signature_def2 = tf.saved_model.signature_def_utils.build_signature_def(
      inputs={'x': tensor_info_x},
      outputs={'r': tensor_info_r},

  tensor_info_result = tf.compat.v1.saved_model.utils.build_tensor_info(result)

  signature_def = tf.saved_model.signature_def_utils.build_signature_def(
      inputs=None,
      outputs={'result': tensor_info_result},
      method_name='some_function')

  return {'key_1': signature_def, 'key_2': signature_def}, None, None


if __name__ == '__main__':
  common_v1.set_tf_options()

        }
      }
    }
  }
  signature_def: {
    key: "predict0"
    value: {
      inputs: {
        key: "inputs"
        value: {
          name: "input0"
          dtype: DT_STRING
        }
      }
      outputs: {
        key: "outputs"
        value: {
          name: "batch_func:0"
        }
      }
    }
  }
  signature_def: {
    key: "predict1"
    value: {

  result = tf.transpose(merge_op)

  tensor_info_result = tf.compat.v1.saved_model.utils.build_tensor_info(result)

  signature_def = tf.saved_model.signature_def_utils.build_signature_def(
      inputs=None,
      outputs={'result': tensor_info_result},
      method_name='some_function')

  return {'key': signature_def}, None, None


if __name__ == '__main__':
  common_v1.set_tf_options()

  meta_graphdef = loader.get_meta_graph_def_from_tags(tags)
  signatures = {}
  for key, signature_def in meta_graphdef.signature_def.items():
    if key == saved_model_constants.INIT_OP_SIGNATURE_KEY:
      continue
    if signature_keys is not None and key not in signature_keys:
      continue
    signatures[key] = signature_def

  return signatures


def _restore_output_tensor_names(
    graph_def: graph_pb2.GraphDef,

    feed_dict = repr_dataset.create_feed_dict_from_input_data(
        sample, signature_def
    )

    self.assertLen(feed_dict, 1)
    self.assertIn('input:0', feed_dict)
    self.assertAllEqual(feed_dict['input:0'], input_tensor_value)

  @test_util.deprecated_graph_mode_only
  def test_create_feed_dict_from_input_data_core_tensors(self):
    signature_def = meta_graph_pb2.SignatureDef(

  Returns:
    Signature def map where the values (`SignatureDef`) are serialized.
  """
  signature_def_map_serialized = {}
  for key, signature_def in signature_def_map.items():
    signature_def_map_serialized[key] = signature_def.SerializeToString()

  return signature_def_map_serialized


def _has_quantization_method(
    quantization_specs: qc.QuantizationSpecs, method: str
) -> bool: