old_contents: # Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
  #
  # Licensed under the Apache License, Version 2.0 (the "License");
  # you may not use this file except in compliance with the License.
  # You may obtain a copy of the License at
  #
  #     http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  
  import unittest
  import numpy as np
  from inference_pass_test import InferencePassTest
  import paddle.fluid as fluid
  import paddle.fluid.core as core
  
  
  class TransposeFlattenConcatFusePassTest(InferencePassTest):
      def setUp(self):
          with fluid.program_guard(self.main_program, self.startup_program):
              data1 = fluid.data(
                  name="data1", shape=[8, 32, 128], dtype="float32")
              data2 = fluid.data(
                  name="data2", shape=[8, 32, 128], dtype="float32")
              trans1 = fluid.layers.transpose(data1, perm=[2, 1, 0])
              trans2 = fluid.layers.transpose(data2, perm=[2, 1, 0])
              flatt1 = fluid.layers.flatten(trans1)
              flatt2 = fluid.layers.flatten(trans2)
              concat_out = fluid.layers.concat([flatt1, flatt2])
              # There is no parameters for above structure. 
              # Hence, append a batch_norm to avoid failure caused by load_combined. 
              out = fluid.layers.batch_norm(concat_out, is_test=True)
  
          self.feeds = {
              "data1": np.random.random([8, 32, 128]).astype("float32"),
              "data2": np.random.random([8, 32, 128]).astype("float32")
          }
          self.fetch_list = [out]
  
      def test_check_output(self):
          # There is no cpu pass for transpose_flatten_concat_fuse
          if core.is_compiled_with_cuda():
              self.check_output_with_option([True])
  
  
  if __name__ == "__main__":
      unittest.main()
  
new_contents: # Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
  #
  # Licensed under the Apache License, Version 2.0 (the "License");
  # you may not use this file except in compliance with the License.
  # You may obtain a copy of the License at
  #
  #     http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  
  import unittest
  import numpy as np
  from inference_pass_test import InferencePassTest
  import paddle.fluid as fluid
  import paddle.fluid.core as core
  
  
  class TransposeFlattenConcatFusePassTest(InferencePassTest):
      def setUp(self):
          with fluid.program_guard(self.main_program, self.startup_program):
              data1 = fluid.data(name="data1", shape=[5, 5, 5], dtype="float32")
              data2 = fluid.data(name="data2", shape=[5, 5, 5], dtype="float32")
              trans1 = fluid.layers.transpose(data1, perm=[2, 1, 0])
              trans2 = fluid.layers.transpose(data2, perm=[2, 1, 0])
              flatt1 = fluid.layers.flatten(trans1)
              flatt2 = fluid.layers.flatten(trans2)
              concat_out = fluid.layers.concat([flatt1, flatt2])
              # There is no parameters for above structure. 
              # Hence, append a batch_norm to avoid failure caused by load_combined. 
              out = fluid.layers.batch_norm(concat_out, is_test=True)
  
          self.feeds = {
              "data1": np.random.random([5, 5, 5]).astype("float32"),
              "data2": np.random.random([5, 5, 5]).astype("float32")
          }
          self.fetch_list = [out]
  
      def test_check_output(self):
          # There is no cpu pass for transpose_flatten_concat_fuse
          if core.is_compiled_with_cuda():
              self.check_output_with_option([True])
  
  
  if __name__ == "__main__":
      unittest.main()
  
subject: decrease the input size for test_transpose_flatten_concat_fuse_pass, test=develop (#24992)