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103 lines
3.3 KiB
103 lines
3.3 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 pytest
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from mindspore import Tensor
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from mindspore.ops import operations as P
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import mindspore.nn as nn
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import numpy as np
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import mindspore.context as context
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from mindspore.common import dtype as mstype
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context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
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class Concat_Axis0(nn.Cell):
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def __init__(self):
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super(Concat_Axis0, self).__init__()
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self.cat = P.Concat(axis=0)
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def construct(self, x1, x2):
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return self.cat((x1, x2))
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@pytest.mark.level0
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@pytest.mark.platform_x86_cpu
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@pytest.mark.env_onecard
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def test_in2_axis0():
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x1 = Tensor(np.arange(2 * 2 * 2).reshape(2, 2, 2), mstype.float32)
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x2 = Tensor(np.arange(3 * 2 * 2).reshape(3, 2, 2), mstype.float32)
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cat = Concat_Axis0()
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output_ms = cat(x1, x2)
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print("output:\n", output_ms)
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output_np = np.concatenate((x1.asnumpy(), x2.asnumpy()), axis=0)
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error = np.ones(shape=output_np.shape) * 10e-6
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diff = output_ms.asnumpy() - output_np
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assert np.all(diff < error)
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assert np.all(-diff < error)
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class Concat_Axis1(nn.Cell):
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def __init__(self):
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super(Concat_Axis1, self).__init__()
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self.cat = P.Concat(axis=1)
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def construct(self, x1, x2):
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return self.cat((x1, x2))
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@pytest.mark.level0
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@pytest.mark.platform_x86_cpu
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@pytest.mark.env_onecard
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def test_in2_axis1():
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x1 = Tensor(np.arange(2 * 2 * 2).reshape(2, 2, 2), mstype.float32)
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x2 = Tensor(np.arange(2 * 3 * 2).reshape(2, 3, 2), mstype.float32)
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cat = Concat_Axis1()
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output_ms = cat(x1, x2)
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print("output:\n", output_ms)
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output_np = np.concatenate((x1.asnumpy(), x2.asnumpy()), axis=1)
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error = np.ones(shape=output_np.shape) * 10e-6
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diff = output_ms.asnumpy() - output_np
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assert np.all(diff < error)
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assert np.all(-diff < error)
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class Concat_Axis2(nn.Cell):
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def __init__(self):
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super(Concat_Axis2, self).__init__()
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self.cat = P.Concat(axis=-1)
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def construct(self, x1, x2):
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return self.cat((x1, x2))
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@pytest.mark.level0
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@pytest.mark.platform_x86_cpu
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@pytest.mark.env_onecard
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def test_in3_axis2():
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x1 = Tensor(np.arange(2 * 2 * 1).reshape(2, 2, 1), mstype.float32)
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x2 = Tensor(np.arange(2 * 2 * 2).reshape(2, 2, 2), mstype.float32)
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x3 = Tensor(np.arange(2 * 2 * 3).reshape(2, 2, 3), mstype.float32)
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cat = Concat_Axis2()
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output_ms = cat(x1, x2)
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print("output:\n", output_ms)
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output_np = np.concatenate((x1.asnumpy(), x2.asnumpy()), axis=-1)
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error = np.ones(shape=output_np.shape) * 10e-6
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diff = output_ms.asnumpy() - output_np
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assert np.all(diff < error)
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assert np.all(-diff < error)
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if __name__ == '__main__':
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test_in2_axis0()
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test_in2_axis1()
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test_in3_axis2()
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