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test_select_op.py 1.7 kB

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  1. # Copyright 2020 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.ops import operations as P
  21. class Net(nn.Cell):
  22. def __init__(self):
  23. super(Net, self).__init__()
  24. self.select = P.Select()
  25. def construct(self, cond_op, input_x, input_y):
  26. return self.select(cond_op, input_x, input_y)
  27. cond = np.array([[True, False], [True, False]]).astype(np.bool)
  28. x = np.array([[1.2, 1], [1, 0]]).astype(np.float32)
  29. y = np.array([[1, 2], [3, 4.0]]).astype(np.float32)
  30. @pytest.mark.level0
  31. @pytest.mark.platform_x86_gpu_training
  32. @pytest.mark.env_onecard
  33. def test_select():
  34. context.set_context(mode=context.GRAPH_MODE, device_target="GPU")
  35. select = Net()
  36. output = select(Tensor(cond), Tensor(x), Tensor(y))
  37. expect = [[1.2, 2], [1, 4.0]]
  38. error = np.ones(shape=[2, 2]) * 1.0e-6
  39. diff = output.asnumpy() - expect
  40. assert np.all(diff < error)
  41. assert np.all(-diff < error)