forked from mindspore-Ecosystem/mindspore
118 lines
3.9 KiB
Python
118 lines
3.9 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 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 mindspore.context as context
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context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
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class CdistTEST(nn.Cell):
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def __init__(self, p):
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super(CdistTEST, self).__init__()
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self.cdist = P.Cdist(p)
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def construct(self, x1, x2):
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return self.cdist(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_CdistP2_float32():
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"""
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Feature: Cdist cpu kernel
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Description: test the cdist p = 2.0.
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Expectation: the output[0] is same as numpy
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"""
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cdist = CdistTEST(2.)
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x1 = Tensor(np.array([[[1.0, 1.0], [2.0, 2.0]]]).astype(np.float32))
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x2 = Tensor(np.array([[[3.0, 3.0], [3.0, 3.0]]]).astype(np.float32))
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output = cdist(x1, x2)
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expect = np.array([[[2.828427, 2.828427], [1.4142135, 1.4142135]]]).astype(np.float32)
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print(output)
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assert (output.asnumpy() == expect).all()
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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_CdistP0_float32():
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"""
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Feature: Cdist cpu kernel
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Description: test the cdist p = 0.0.
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Expectation: the output[0] is same as numpy
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"""
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cdist = CdistTEST(0.)
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x1 = Tensor(np.array([[[1.0, 1.0], [2.0, 2.0]]]).astype(np.float32))
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x2 = Tensor(np.array([[[3.0, 3.0], [3.0, 3.0]]]).astype(np.float32))
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output = cdist(x1, x2)
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expect = np.array([[[2.0, 2.0], [2.0, 2.0]]]).astype(np.float32)
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print(output)
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assert (output.asnumpy() == expect).all()
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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_CdistP1_float32():
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"""
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Feature: Cdist cpu kernel
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Description: test the cdist p = 1.0.
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Expectation: the output[0] is same as numpy
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"""
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cdist = CdistTEST(1.)
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x1 = Tensor(np.array([[[1.0, 1.0], [2.0, 2.0]]]).astype(np.float32))
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x2 = Tensor(np.array([[[3.0, 3.0], [3.0, 3.0]]]).astype(np.float32))
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output = cdist(x1, x2)
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expect = np.array([[[4.0, 4.0], [2.0, 2.0]]]).astype(np.float32)
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print(output)
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assert (output.asnumpy() == expect).all()
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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_CdistP8_float32():
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"""
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Feature: Cdist cpu kernel
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Description: test the cdist p = 8.0.
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Expectation: the output[0] is same as numpy
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"""
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cdist = CdistTEST(8.)
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x1 = Tensor(np.array([[[1.0, 1.0], [2.0, 2.0]]]).astype(np.float32))
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x2 = Tensor(np.array([[[3.0, 3.0], [3.0, 3.0]]]).astype(np.float32))
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output = cdist(x1, x2)
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expect = np.array([[[2.1810155, 2.1810155], [1.0905077, 1.0905077]]]).astype(np.float32)
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print(output)
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assert (output.asnumpy() == expect).all()
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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_CdistPinf_float32():
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"""
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Feature: Cdist cpu kernel
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Description: test the cdist p = inf.
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Expectation: the output[0] is same as numpy
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"""
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cdist = CdistTEST(float('inf'))
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x1 = Tensor(np.array([[[1.0, 1.0], [2.0, 2.0]]]).astype(np.float32))
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x2 = Tensor(np.array([[[3.0, 3.0], [3.0, 3.0]]]).astype(np.float32))
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output = cdist(x1, x2)
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expect = np.array([[[2., 2.], [1., 1.]]]).astype(np.float32)
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print(output)
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assert (output.asnumpy() == expect).all()
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