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# ============================================================================ 15import numpy as np 16 17import mindspore.context as context 18import mindspore.nn as nn 19import mindspore.common.dtype as mstype 20from mindspore import Tensor 21from mindspore.ops import operations as P 22 23context.set_context(mode=context.GRAPH_MODE, 24 device_target="Ascend") 25 26 27class Net(nn.Cell): 28 def __init__(self, offset): 29 super(Net, self).__init__() 30 self.embedding = P.EmbeddingLookup() 31 self.offset = offset 32 33 def construct(self, param, index): 34 return self.embedding(param, index, self.offset) 35 36 37def test_embedding_lookup_sparse(): 38 params = Tensor(np.array([[8, 9], [10, 11], [12, 13], [14, 15]]), mstype.int32) 39 indices = Tensor(np.array([[5, 2], [8, 5]]), mstype.int32) 40 offset = 4 41 embedding = Net(offset) 42 out = embedding(params, indices) 43 assert(out.asnumpy() == [[[10, 11], [0, 0]], [[0, 0], [10, 11]]]).all() 44