You can not select more than 25 topics Topics must start with a chinese character,a letter or number, can include dashes ('-') and can be up to 35 characters long.

test_cast_op.py 2.2 kB

5 years ago
5 years ago
5 years ago
12345678910111213141516171819202122232425262728293031323334353637383940414243444546474849505152535455565758596061626364656667686970
  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.common.dtype as mstype
  18. import mindspore.context as context
  19. from mindspore.common.tensor import Tensor
  20. from mindspore.nn import Cell
  21. from mindspore.ops import operations as P
  22. class Net(Cell):
  23. def __init__(self):
  24. super(Net, self).__init__()
  25. self.Cast = P.Cast()
  26. def construct(self, x0, type0, x1, type1):
  27. output = (self.Cast(x0, type0),
  28. self.Cast(x1, type1))
  29. return output
  30. @pytest.mark.level0
  31. @pytest.mark.platform_x86_gpu_training
  32. @pytest.mark.env_onecard
  33. def test_cast():
  34. x0 = Tensor(np.arange(24).reshape((4, 3, 2)).astype(np.float32))
  35. t0 = mstype.float16
  36. x1 = Tensor(np.arange(24).reshape((4, 3, 2)).astype(np.float16))
  37. t1 = mstype.float32
  38. context.set_context(mode=context.GRAPH_MODE, device_target='GPU')
  39. net = Net()
  40. output = net(x0, t0, x1, t1)
  41. type0 = output[0].asnumpy().dtype
  42. assert type0 == 'float16'
  43. type1 = output[1].asnumpy().dtype
  44. assert type1 == 'float32'
  45. @pytest.mark.level0
  46. @pytest.mark.platform_x86_gpu_training
  47. @pytest.mark.env_onecard
  48. def test_cast1():
  49. x0 = Tensor(np.arange(24).reshape((4, 3, 2)).astype(np.int32))
  50. t0 = mstype.float32
  51. x1 = Tensor(np.arange(24).reshape((4, 3, 2)).astype(np.bool))
  52. t1 = mstype.float32
  53. context.set_context(mode=context.GRAPH_MODE, device_target='GPU')
  54. net = Net()
  55. output = net(x0, t0, x1, t1)
  56. type0 = output[0].asnumpy().dtype
  57. assert type0 == 'float32'
  58. type1 = output[1].asnumpy().dtype
  59. assert type1 == 'float32'