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test_cse.py 1.6 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. from mindspore import Tensor
  19. from mindspore.nn import Cell
  20. import mindspore.ops.operations as P
  21. context.set_context(mode=context.GRAPH_MODE, enable_graph_kernel=True, device_target="GPU")
  22. class Net(Cell):
  23. def __init__(self):
  24. super(Net, self).__init__()
  25. self.add = P.TensorAdd()
  26. self.mul = P.Mul()
  27. def construct(self, x):
  28. mul_res = self.mul(x, x)
  29. square_res = P.Square()(x)
  30. return self.add(mul_res, square_res)
  31. @pytest.mark.level0
  32. @pytest.mark.platform_x86_gpu_training
  33. @pytest.mark.env_onecard
  34. def test_basic():
  35. input_x = np.random.normal(0, 1, [2, 3, 4, 3]).astype(np.float32)
  36. mul_res = input_x * input_x
  37. square_res = np.square(input_x)
  38. expect = mul_res + square_res
  39. net = Net()
  40. result = net(Tensor(input_x))
  41. res = np.allclose(expect, result.asnumpy(), rtol=1.e-4, atol=1.e-7, equal_nan=True)
  42. assert res