forked from mindspore-Ecosystem/mindspore
161 lines
4.8 KiB
Python
161 lines
4.8 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 import context
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from mindspore.ops import operations as P
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from mindspore import dtype as mstype
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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_graph_conj():
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"""
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Feature: ALL TO ALL
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Description: test cases for conj in graph mode cpu backend.
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Expectation: the result match numpy conj
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"""
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context.set_context(mode=context.GRAPH_MODE)
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x = np.asarray(np.complex(1.3 + 0.4j), dtype=np.complex64)
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ms_x = Tensor(x, mstype.complex64)
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output = P.Conj()(ms_x)
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expect = np.conj(x)
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assert np.allclose(output.asnumpy(), expect)
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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_pynative_conj():
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"""
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Feature: ALL TO ALL
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Description: test cases for conj in pynative mode cpu backend.
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Expectation: the result match numpy conj
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"""
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context.set_context(mode=context.PYNATIVE_MODE)
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x = np.asarray(np.complex(1.3 + 0.4j), dtype=np.complex64)
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ms_x = Tensor(x, mstype.complex64)
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output = P.Conj()(ms_x)
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expect = np.conj(x)
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assert np.allclose(output.asnumpy(), expect)
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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_graph_real():
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"""
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Feature: ALL TO ALL
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Description: test cases for real in graph mode cpu backend.
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Expectation: the result match numpy real
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"""
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context.set_context(mode=context.GRAPH_MODE)
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x = np.asarray(np.complex(1.3 + 0.4j), dtype=np.complex64)
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ms_x = Tensor(x, mstype.complex64)
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output = P.Real()(ms_x)
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expect = np.real(x)
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assert np.allclose(output.asnumpy(), expect)
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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_pynative_real():
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"""
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Feature: ALL TO ALL
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Description: test cases for real in pynative mode cpu backend.
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Expectation: the result match numpy real
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"""
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context.set_context(mode=context.GRAPH_MODE)
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x = np.asarray(np.complex(1.3 + 0.4j), dtype=np.complex64)
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ms_x = Tensor(x, mstype.complex64)
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output = P.Real()(ms_x)
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expect = np.real(x)
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assert np.allclose(output.asnumpy(), expect)
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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_graph_imag():
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"""
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Feature: ALL TO ALL
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Description: test cases for image in graph mode cpu backend.
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Expectation: the result match numpy conj
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"""
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context.set_context(mode=context.GRAPH_MODE)
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x = np.asarray(np.complex(1.3 + 0.4j), dtype=np.complex64)
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ms_x = Tensor(x, mstype.complex64)
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output = P.Imag()(ms_x)
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expect = np.imag(x)
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assert np.allclose(output.asnumpy(), expect)
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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_pynative_imag():
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"""
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Feature: ALL TO ALL
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Description: test cases for image in pynative mode cpu backend.
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Expectation: the result match numpy image
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"""
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context.set_context(mode=context.GRAPH_MODE)
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x = np.asarray(np.complex(1.3 + 0.4j), dtype=np.complex64)
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ms_x = Tensor(x, mstype.complex64)
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output = P.Imag()(ms_x)
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expect = np.imag(x)
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assert np.allclose(output.asnumpy(), expect)
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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_graph_ceil():
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"""
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Feature: ALL TO ALL
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Description: test cases for ceil in graph mode cpu backend.
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Expectation: the result match numpy ceil
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"""
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context.set_context(mode=context.GRAPH_MODE)
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x = Tensor(np.array([1.1, -2.1]).astype(np.float32))
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np_x = np.array([1.1, -2.1]).astype(np.float32)
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output = P.Ceil()(x)
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expect = np.ceil(np_x)
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assert np.allclose(output.asnumpy(), expect)
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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_pynative_ceil():
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"""
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Feature: ALL TO ALL
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Description: test cases for ceil in pynative mode cpu backend.
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Expectation: the result match numpy ceil
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"""
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context.set_context(mode=context.PYNATIVE_MODE)
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x = Tensor(np.array([1.1, -2.1]).astype(np.float32))
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np_x = np.array([1.1, -2.1]).astype(np.float32)
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output = P.Ceil()(x)
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expect = np.ceil(np_x)
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assert np.allclose(output.asnumpy(), expect)
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