forked from mindspore-Ecosystem/mindspore
52 lines
1.6 KiB
Python
52 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 as ms
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import mindspore.nn as nn
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from mindspore import Tensor
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class Net(nn.Cell):
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def construct(self, x, other):
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return x.ldexp(other)
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@pytest.mark.level0
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@pytest.mark.platform_x86_cpu
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@pytest.mark.platform_arm_cpu
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.platform_arm_ascend_training
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@pytest.mark.platform_x86_ascend_training
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@pytest.mark.env_onecard
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@pytest.mark.parametrize('mode', [ms.GRAPH_MODE, ms.PYNATIVE_MODE])
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def test_ldexp(mode):
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"""
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Feature: test Tensor.ldexp
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Description: Verify the result of Tensor.ldexp
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Expectation: expect correct forward result
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"""
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ms.set_context(mode=mode)
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x1_np = np.array([1.0])
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x2_np = np.array([1, 2, 3, 4])
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input_x1 = Tensor(x1_np)
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input_x2 = Tensor(x2_np)
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net = Net()
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output_ms = net(input_x1, input_x2)
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expect_output = np.ldexp(x1_np, x2_np)
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assert np.allclose(output_ms.asnumpy(), expect_output)
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