forked from huawei/mindspore2022
68 lines
1.9 KiB
Python
68 lines
1.9 KiB
Python
# Copyright 2021 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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from mindspore import Tensor
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from mindspore.nn import Cell
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import mindspore.ops.operations as P
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class Net(Cell):
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def __init__(self):
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super(Net, self).__init__()
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self.addn = P.AddN()
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def construct(self, *args):
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return self.addn(*args)
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def get_output(*tensors):
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net = Net()
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output = net(tensors)
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return output
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def test_basic():
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np.random.seed(0)
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tensors = []
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expect = np.array([0], np.float32)
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for _ in range(10):
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t = np.random.normal(0, 1, [2, 3, 4, 3]).astype(np.float32)
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expect = t + expect
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tensors.append(Tensor(t))
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output = get_output(*tensors).asnumpy()
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assert np.allclose(expect, output, 1.e-4, 1.e-7)
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@pytest.mark.level0
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.env_onecard
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def test_basic_gpu():
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context.set_context(mode=context.GRAPH_MODE, device_target="GPU", enable_graph_kernel=True)
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test_basic()
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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_basic_ascend():
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context.set_context(mode=context.GRAPH_MODE, device_target="Ascend", enable_graph_kernel=True)
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test_basic()
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