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test_embedding_lookup_op.py 2.4 kB

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  1. # Copyright 2021 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. from mindspore import Tensor
  18. from mindspore.ops import operations as P
  19. import mindspore.nn as nn
  20. import mindspore.context as context
  21. class Net(nn.Cell):
  22. def __init__(self):
  23. super(Net, self).__init__()
  24. self.embeddinglookup = P.EmbeddingLookup()
  25. def construct(self, input_params, input_indices, offset):
  26. return self.embeddinglookup(input_params, input_indices, offset)
  27. def embeddinglookup_testcase(nptype):
  28. context.set_context(mode=context.GRAPH_MODE, device_target="GPU")
  29. input_params = Tensor(np.array([[8, 9], [10, 11], [12, 13], [14, 15]]).astype(nptype))
  30. input_indices = Tensor(np.array([[5, 2], [8, 5]]).astype(np.int32))
  31. offset = 4
  32. output = Net()(input_params, input_indices, offset)
  33. expect = np.array([[[10, 11], [0, 0]], [[0, 0], [10, 11]]]).astype(nptype)
  34. np.testing.assert_almost_equal(expect, output.asnumpy())
  35. context.set_context(mode=context.PYNATIVE_MODE, device_target="GPU")
  36. input_params = Tensor(np.array([[8, 9], [10, 11], [12, 13], [14, 15]]).astype(nptype))
  37. input_indices = Tensor(np.array([[5, 2], [8, 5]]).astype(np.int32))
  38. offset = 4
  39. output = Net()(input_params, input_indices, offset)
  40. expect = np.array([[[10, 11], [0, 0]], [[0, 0], [10, 11]]]).astype(nptype)
  41. np.testing.assert_almost_equal(expect, output.asnumpy())
  42. @pytest.mark.level0
  43. @pytest.mark.platform_x86_gpu_training
  44. @pytest.mark.env_onecard
  45. def test_embeddinglookup_float32():
  46. embeddinglookup_testcase(np.float32)
  47. @pytest.mark.level0
  48. @pytest.mark.platform_x86_gpu_training
  49. @pytest.mark.env_onecard
  50. def test_embeddinglookup_float16():
  51. embeddinglookup_testcase(np.float16)