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test_biasAddGrad.py 1.7 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. from mindspore import Tensor
  16. from mindspore.ops import operations as P
  17. from mindspore.ops.operations import _grad_ops as G
  18. import mindspore.nn as nn
  19. from mindspore.common.api import ms_function
  20. import numpy as np
  21. import mindspore.context as context
  22. from mindspore.common.initializer import initializer
  23. from mindspore.common.parameter import Parameter
  24. context.set_context(device_target="Ascend")
  25. class Net(nn.Cell):
  26. def __init__(self):
  27. super(Net, self).__init__()
  28. self.bias_add_grad = G.BiasAddGrad()
  29. # self.dout = Parameter(initializer(
  30. # 'normal', [2, 3, 3, 4]), name='dout')
  31. @ms_function
  32. def construct(self, dout):
  33. return self.bias_add_grad(dout)
  34. dout = np.ones([2, 3, 4, 4]).astype(np.float32)
  35. bias_add_grad = Net()
  36. output = bias_add_grad(Tensor(dout))
  37. expect_output = np.array([32., 32., 32.]).astype(np.float32)
  38. assert np.all(output.asnumpy() == expect_output), "bias_add_grad execute failed, please check current code commit"
  39. print(output.asnumpy())