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 2.3 kB

5 years ago
5 years ago
5 years ago
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172
  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, type0, type1):
  24. super(Net, self).__init__()
  25. self.Cast = P.Cast()
  26. self.type0 = type0
  27. self.type1 = type1
  28. def construct(self, x0, x1):
  29. output = (self.Cast(x0, self.type0),
  30. self.Cast(x1, self.type1))
  31. return output
  32. @pytest.mark.level0
  33. @pytest.mark.platform_x86_gpu_training
  34. @pytest.mark.env_onecard
  35. def test_cast():
  36. x0 = Tensor(np.arange(24).reshape((4, 3, 2)).astype(np.float32))
  37. t0 = mstype.float16
  38. x1 = Tensor(np.arange(24).reshape((4, 3, 2)).astype(np.float16))
  39. t1 = mstype.float32
  40. context.set_context(mode=context.GRAPH_MODE, device_target='GPU')
  41. net = Net(t0, t1)
  42. output = net(x0, x1)
  43. type0 = output[0].asnumpy().dtype
  44. assert type0 == 'float16'
  45. type1 = output[1].asnumpy().dtype
  46. assert type1 == 'float32'
  47. @pytest.mark.level0
  48. @pytest.mark.platform_x86_gpu_training
  49. @pytest.mark.env_onecard
  50. def test_cast1():
  51. x0 = Tensor(np.arange(24).reshape((4, 3, 2)).astype(np.int32))
  52. t0 = mstype.float32
  53. x1 = Tensor(np.arange(24).reshape((4, 3, 2)).astype(np.bool))
  54. t1 = mstype.float32
  55. context.set_context(mode=context.GRAPH_MODE, device_target='GPU')
  56. net = Net(t0, t1)
  57. output = net(x0, x1)
  58. type0 = output[0].asnumpy().dtype
  59. assert type0 == 'float32'
  60. type1 = output[1].asnumpy().dtype
  61. assert type1 == 'float32'