forked from mindspore-Ecosystem/mindspore
54 lines
1.8 KiB
Python
54 lines
1.8 KiB
Python
# Copyright 2022 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 pytest
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import numpy as np
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from mindspore import ops, Tensor, context
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from mindspore.common.parameter import Parameter
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from mindspore.nn import Cell
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class AssignNet(Cell):
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def __init__(self, input_variable):
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super(AssignNet, self).__init__()
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self.op = ops.Assign()
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self.input_data = input_variable
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def construct(self, input_x):
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self.op(self.input_data, input_x)
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return self.input_data
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@pytest.mark.level0
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@pytest.mark.platform_x86_cpu
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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.platform_x86_gpu_training
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@pytest.mark.env_onecard
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def test_assign_as_output():
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"""
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Feature: PyNative MindRT
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Description: Test PyNative MindRT RefNode.
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Expectation: No exception.
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"""
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np.random.seed(0)
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input_np = np.random.randn(5, 5).astype(dtype=np.int32)
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context.set_context(mode=context.PYNATIVE_MODE)
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input_variable = Parameter(Tensor(np.random.randn(5, 5).astype(dtype=np.float32)))
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input_x = Tensor(input_np)
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net = AssignNet(input_variable)
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out = net(input_x)
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assert input_np.all() == out.asnumpy().astype(dtype=np.int32).all()
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