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test_embedding_lookup.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 mindspore.context as context
  17. import mindspore.nn as nn
  18. import mindspore.common.dtype as mstype
  19. from mindspore import Tensor
  20. from mindspore.ops import operations as P
  21. context.set_context(mode=context.GRAPH_MODE,
  22. device_target="Ascend")
  23. class Net(nn.Cell):
  24. def __init__(self, offset):
  25. super(Net, self).__init__()
  26. self.embedding = P.EmbeddingLookup()
  27. self.offset = offset
  28. def construct(self, param, index):
  29. return self.embedding(param, index, self.offset)
  30. def test_embedding_lookup_sparse():
  31. params = Tensor(np.array([[8, 9], [10, 11], [12, 13], [14, 15]]), mstype.int32)
  32. indices = Tensor(np.array([[5, 2], [8, 5]]), mstype.int32)
  33. offset = 4
  34. embedding = Net(offset)
  35. out = embedding(params, indices)
  36. assert(out.asnumpy() == [[[10, 11], [0, 0]], [[0, 0], [10, 11]]]).all()