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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 pytest
-
- import mindspore.context as context
- import mindspore.nn as nn
- from mindspore import Tensor
- from mindspore import Parameter
- from mindspore.ops import operations as P
-
- context.set_context(mode=context.GRAPH_MODE,
- device_target='CPU', save_graphs=True)
-
-
- class UpdateCacheNet(nn.Cell):
- def __init__(self, x):
- super().__init__()
- self.ops = P.UpdateCache()
- self.max_num = 9999
- self.x = Parameter(Tensor(x), name='x')
-
- def construct(self, indices, update):
- return self.ops(self.x, indices, update, self.max_num)
-
-
- @pytest.mark.level0
- @pytest.mark.platform_x86_cpu
- @pytest.mark.env_onecard
- def test_update_cache():
- x_np = np.array([[2, 3, 4, 5],
- [6, 7, 8, 9],
- [11, 12, 13, 14],
- [1, 2, 3, 4],
- [5, 6, 7, 8]], np.int32)
-
- indices_np = np.array([[-1, 3, 4]], np.int32)
- update_np = np.array([[0, 0, 0, 0],
- [23, 34, 56, 78],
- [44, 55, 66, 77]], np.int32)
-
- indices = Tensor(indices_np)
- update = Tensor(update_np)
-
- expect = np.array([[2, 3, 4, 5],
- [6, 7, 8, 9],
- [11, 12, 13, 14],
- [23, 34, 56, 78],
- [44, 55, 66, 77]], np.int32)
- net = UpdateCacheNet(x_np)
- out = net(indices, update)
- assert np.allclose(net.x.data.asnumpy(), expect)
- assert np.allclose(out.asnumpy(), np.array([0], np.int32))
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