forked from mindspore-Ecosystem/mindspore
46 lines
1.6 KiB
Python
46 lines
1.6 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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import mindspore.context as context
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from mindspore import Tensor
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from mindspore.ops import operations as P
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from scipy import special
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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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@pytest.mark.level0
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@pytest.mark.parametrize('mode', [context.GRAPH_MODE, context.PYNATIVE_MODE])
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@pytest.mark.parametrize('shape', [(2,), (4, 5), (3, 4, 5, 6)])
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@pytest.mark.parametrize('dtype, tol', [(np.float16, 1.0e-3), (np.float32, 1.0e-4)])
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def test_erfc(mode, shape, dtype, tol):
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"""
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Feature: ALL To ALL
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Description: test cases for erf
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Expectation: the result match to scipy
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"""
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context.set_context(mode=mode, device_target="CPU")
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erfc = P.Erfc()
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input_x = np.random.randn(*shape).astype(dtype)
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output = erfc(Tensor(input_x))
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expect_output = special.erfc(input_x)
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diff = output.asnumpy() - expect_output
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error = np.ones(shape=expect_output.shape) * tol
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assert np.all(np.abs(diff) < error)
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