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test_bias_add.py 2.0 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. context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
  22. class Net(nn.Cell):
  23. def __init__(self):
  24. super(Net, self).__init__()
  25. self.bias_add = P.BiasAdd()
  26. def construct(self, x, b):
  27. return self.bias_add(x, b)
  28. @pytest.mark.level0
  29. @pytest.mark.platform_x86_cpu
  30. @pytest.mark.env_onecard
  31. def test_bias_add1():
  32. x = np.ones([2, 3, 4, 4]).astype(np.float32)
  33. b = np.array([1, 1, 1]).astype(np.float32)
  34. bias_add = Net()
  35. output = bias_add(Tensor(x), Tensor(b))
  36. expect_output = np.ones([2, 3, 4, 4]).astype(np.float32) * 2
  37. print(output)
  38. assert np.all(output.asnumpy() == expect_output), "bias_add execute failed, please check current code commit"
  39. @pytest.mark.level0
  40. @pytest.mark.platform_x86_cpu
  41. @pytest.mark.env_onecard
  42. def test_bias_add2():
  43. x = np.ones([2, 3]).astype(np.float32)
  44. b = np.array([1, 1, 1]).astype(np.float32)
  45. bias_add = Net()
  46. output = bias_add(Tensor(x), Tensor(b))
  47. expect_output = np.ones([2, 3]).astype(np.float32) * 2
  48. print(output)
  49. assert np.all(output.asnumpy() == expect_output), "bias_add execute failed, please check current code commit"