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test_zeroslike_op.py 2.5 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.ops import operations as P
  21. context.set_context(mode=context.PYNATIVE_MODE, device_target="GPU")
  22. class NetZerosLike(nn.Cell):
  23. def __init__(self):
  24. super(NetZerosLike, self).__init__()
  25. self.zeros_like = P.ZerosLike()
  26. def construct(self, x):
  27. return self.zeros_like(x)
  28. @pytest.mark.level0
  29. @pytest.mark.platform_x86_gpu_training
  30. @pytest.mark.env_onecard
  31. def test_ZerosLike():
  32. x0_np = np.random.uniform(-2, 2, (2, 3, 4, 4)).astype(np.float32)
  33. x1_np = np.random.uniform(-2, 2, 1).astype(np.float32)
  34. x0 = Tensor(x0_np)
  35. x1 = Tensor(x1_np)
  36. context.set_context(mode=context.PYNATIVE_MODE, device_target="GPU")
  37. zeros_like = NetZerosLike()
  38. output0 = zeros_like(x0)
  39. expect0 = np.zeros_like(x0_np)
  40. diff0 = output0.asnumpy() - expect0
  41. error0 = np.ones(shape=expect0.shape) * 1.0e-5
  42. assert np.all(diff0 < error0)
  43. assert output0.shape == expect0.shape
  44. output1 = zeros_like(x1)
  45. expect1 = np.zeros_like(x1_np)
  46. diff1 = output1.asnumpy() - expect1
  47. error1 = np.ones(shape=expect1.shape) * 1.0e-5
  48. assert np.all(diff1 < error1)
  49. assert output1.shape == expect1.shape
  50. context.set_context(mode=context.GRAPH_MODE, device_target="GPU")
  51. zeros_like = NetZerosLike()
  52. output0 = zeros_like(x0)
  53. expect0 = np.zeros_like(x0_np)
  54. diff0 = output0.asnumpy() - expect0
  55. error0 = np.ones(shape=expect0.shape) * 1.0e-5
  56. assert np.all(diff0 < error0)
  57. assert output0.shape == expect0.shape
  58. output1 = zeros_like(x1)
  59. expect1 = np.zeros_like(x1_np)
  60. diff1 = output1.asnumpy() - expect1
  61. error1 = np.ones(shape=expect1.shape) * 1.0e-5
  62. assert np.all(diff1 < error1)
  63. assert output1.shape == expect1.shape