text: """
  Copyright 2020 The OneFlow 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
  
  from oneflow.test_utils.automated_test_util import *
  
  import oneflow as flow
  import oneflow.unittest
  
  
  @flow.unittest.skip_unless_1n1d()
  class TestGluModule(flow.unittest.TestCase):
      @autotest(n=5, check_graph=True)
      def test_glu_module_with_random_data(test_case):
          device = random_device()
          dim = random(-3, 3).to(int)
          m = torch.nn.functional.glu
          x = random_tensor(ndim=3, dim0=2, dim1=4, dim2=6).to(device)
          y = m(x, dim)
          return y
  
      @autotest(n=5, check_graph=True)
      def test_glu_module_with_random_data(test_case):
          device = random_device()
          m = torch.nn.GLU()
          m.train(random())
          m.to(device)
          x = random_tensor(ndim=3, dim0=2, dim1=4, dim2=6).to(device)
          y = m(x)
          return y
  
  
  if __name__ == "__main__":
      unittest.main()
  