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test_relu_op.py 1.8 kB

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  1. # Copyright 2019 Huawei Technologies Co., Ltd
  2. #
  3. # Licensed under the Apache License, Version 2.0 (the "License");
  4. # you may not use this file except in compliance with the License.
  5. # You may obtain a copy of the License at
  6. #
  7. # http://www.apache.org/licenses/LICENSE-2.0
  8. #
  9. # Unless required by applicable law or agreed to in writing, software
  10. # distributed under the License is distributed on an "AS IS" BASIS,
  11. # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  12. # See the License for the specific language governing permissions and
  13. # limitations under the License.
  14. # ============================================================================
  15. import numpy as np
  16. import pytest
  17. import mindspore.context as context
  18. import mindspore.nn as nn
  19. from mindspore import Tensor
  20. from mindspore.common.initializer import initializer
  21. from mindspore.common.parameter import Parameter
  22. from mindspore.ops import operations as P
  23. context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
  24. class NetRelu(nn.Cell):
  25. def __init__(self):
  26. super(NetRelu, self).__init__()
  27. self.relu = P.ReLU()
  28. self.x = Parameter(initializer(Tensor(np.array([[[[-1, 1, 10],
  29. [1, -1, 1],
  30. [10, 1, -1]]]]).astype(np.float32)), [1, 1, 3, 3]), name='x')
  31. def construct(self):
  32. return self.relu(self.x)
  33. @pytest.mark.level0
  34. @pytest.mark.platform_x86_cpu
  35. @pytest.mark.env_onecard
  36. def test_relu():
  37. relu = NetRelu()
  38. output = relu()
  39. expect = np.array([[[[0, 1, 10,],
  40. [1, 0, 1,],
  41. [10, 1, 0.]]]]).astype(np.float32)
  42. print(output)
  43. assert (output.asnumpy() == expect).all()