forked from mindspore-Ecosystem/mindspore
70 lines
2.6 KiB
Python
70 lines
2.6 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 numpy as np
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import pytest
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from mindspore import Tensor
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from mindspore.ops.operations import math_ops as P
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import mindspore.common.dtype as ms
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@pytest.mark.level1
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.env_onecard
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def test_complex_abs_complex64_3x3():
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"""
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Feature: ComplexAbs 1 input and 1 output.
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Description: Compatible with Tensorflow's ComplexAbs.
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Expectation: The result matches numpy implementation.
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"""
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m = 3
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input_c = np.arange(m)[:, None] + np.complex('j') * np.arange(m)
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input_c = Tensor(input_c, ms.complex64)
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expected_out = np.array([[0, 1, 2], [1, 2. ** 0.5, 5. ** 0.5], [2, 5. ** 0.5, 8. ** 0.5]], np.float32)
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complex_abs_net = P.ComplexAbs()
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complex_abs_ms_out = complex_abs_net(input_c)
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np.testing.assert_almost_equal(complex_abs_ms_out, expected_out)
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def test_complex_abs_complex128_3x3():
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"""
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Feature: ComplexAbs 1 input and 1 output.
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Description: Compatible with Tensorflow's ComplexAbs.
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Expectation: The result matches numpy implementation.
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"""
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m = 3
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input_c = np.arange(m)[:, None] + np.complex('j') * np.arange(m)
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input_c = Tensor(input_c, ms.complex128)
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expected_out = np.array([[0, 1, 2], [1, 2. ** 0.5, 5. ** 0.5], [2, 5. ** 0.5, 8. ** 0.5]], np.float64)
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complex_abs_net = P.ComplexAbs()
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complex_abs_ms_out = complex_abs_net(input_c)
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np.testing.assert_almost_equal(complex_abs_ms_out, expected_out)
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def test_complex_abs_complex128_1x1():
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"""
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Feature: ComplexAbs 1 input and 1 output.
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Description: Compatible with Tensorflow's ComplexAbs.
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Expectation: The result matches numpy implementation.
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"""
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input_c = np.array([3]) + np.complex('j') * np.array([4])
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input_c = Tensor(input_c, ms.complex64)
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expected_out = np.array([5], np.float32)
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complex_abs_net = P.ComplexAbs()
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complex_abs_ms_out = complex_abs_net(input_c)
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np.testing.assert_almost_equal(complex_abs_ms_out, expected_out)
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