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test_softmax_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 NetSoftmax(nn.Cell):
  25. def __init__(self):
  26. super(NetSoftmax, self).__init__()
  27. self.softmax = P.Softmax()
  28. x = Tensor(np.array([[0.1, 0.3, 0.6],
  29. [0.2, -0.6, 0.8],
  30. [0.6, 1, 0.4]]).astype(np.float32))
  31. self.x = Parameter(initializer(x, x.shape()), name='x')
  32. def construct(self):
  33. return self.softmax(self.x)
  34. @pytest.mark.level0
  35. @pytest.mark.platform_x86_cpu
  36. @pytest.mark.env_onecard
  37. def test_softmax():
  38. Softmax = NetSoftmax()
  39. output = Softmax()
  40. output = output.asnumpy()
  41. outputSum = output.sum(axis=1)
  42. expect = np.ones(3)
  43. error = expect * 1.0e-6
  44. diff = np.abs(outputSum - expect)
  45. print(diff)
  46. assert np.all(diff < error)