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- # Copyright 2020 Huawei Technologies Co., Ltd
- #
- # Licensed under the Apache License, Version 2.0 (the "License");
- # you may not use this file except in compliance with the License.
- # You may obtain a copy of the License at
- #
- # http://www.apache.org/licenses/LICENSE-2.0
- #
- # Unless required by applicable law or agreed to in writing, software
- # distributed under the License is distributed on an "AS IS" BASIS,
- # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- # See the License for the specific language governing permissions and
- # limitations under the License.
- # ============================================================================
- import numpy as np
-
- import mindspore.context as context
- import mindspore.common.dtype as mstype
- from mindspore import Tensor
- from mindspore.ops import operations as P
-
- context.set_context(mode=context.GRAPH_MODE,
- device_target="Ascend")
-
-
- class Net(nn.Cell):
- def __init__(self, offset):
- super(Net, self).__init__()
- self.embedding = P.EmbeddingLookup()
- self.offset = offset
-
- def construct(self, param, index):
- return self.embedding(param, index, self.offset)
-
-
- def test_embedding_lookup_sparse():
- params = Tensor(np.array([[8, 9], [10, 11], [12, 13], [14, 15]]), mstype.int32)
- indices = Tensor(np.array([[5, 2], [8, 5]]), mstype.int32)
- offset = 4
- embedding = Net(offset)
- out = embedding(params, indices)
- assert(out.asnumpy() == [[[10, 11], [0, 0]], [[0, 0], [10, 11]]]).all()
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