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50 lines
1.7 KiB
50 lines
1.7 KiB
# Copyright 2020 Huawei Technologies Co., Ltd
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ============================================================================
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import numpy as np
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import pytest
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import mindspore.context as context
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import mindspore.nn as nn
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from mindspore import Tensor, Parameter
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import mindspore.common.dtype as mstype
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from mindspore.ops import operations as P
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context.set_context(mode=context.GRAPH_MODE, device_target="CPU")
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class Net(nn.Cell):
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def __init__(self):
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super(Net, self).__init__()
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self.unique = P.Unique()
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self.dynamic_assign = P.DynamicAssign()
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self.param = Parameter(
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Tensor(np.zeros((5,), np.int32)), name="assign_x")
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def construct(self, y):
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y, _ = self.unique(y)
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return self.dynamic_assign(self.param, y)
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@pytest.mark.level0
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@pytest.mark.platform_arm_ascend_training
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@pytest.mark.platform_x86_ascend_training
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@pytest.mark.env_onecard
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def test_dynamic_assign():
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y = Tensor(np.array([2, 2, 3, 3, 4]), mstype.int32)
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dynamic_assign = Net()
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_ = dynamic_assign(y)
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expect1 = np.array([2, 3, 4])
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param_np = dynamic_assign.param.data.asnumpy()
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assert (param_np == expect1).all()
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