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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 pytest
  16. from mindspore import Tensor
  17. from mindspore.ops import operations as P
  18. import mindspore.nn as nn
  19. import numpy as np
  20. import mindspore.context as context
  21. from mindspore.common.initializer import initializer
  22. from mindspore.common.parameter import Parameter
  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()