forked from mindspore-Ecosystem/mindspore
61 lines
1.9 KiB
Python
61 lines
1.9 KiB
Python
# Copyright 2021 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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import mindspore.nn as nn
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from mindspore import Tensor, ops
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class Net(nn.Cell):
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def __init__(self):
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super(Net, self).__init__()
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self.round = ops.Round()
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def construct(self, x):
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return self.round(x)
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def generate_testcases(nptype):
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context.set_context(mode=context.GRAPH_MODE, device_target="GPU")
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x = np.array([0.9920, -0.4077, 0.9734, -1.0362, 1.5, -2.5, 4.5]).astype(nptype)
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net = Net()
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output = net(Tensor(x))
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expect = np.round(x).astype(nptype)
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np.testing.assert_almost_equal(output.asnumpy(), expect)
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context.set_context(mode=context.PYNATIVE_MODE, device_target="GPU")
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x = np.array([0.9920, -0.4077, 0.9734, -1.0362, 1.5, -2.5, 4.5]).astype(nptype)
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net = Net()
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output = net(Tensor(x))
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expect = np.round(x).astype(nptype)
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np.testing.assert_almost_equal(output.asnumpy(), expect)
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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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def test_round_float32():
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generate_testcases(np.float32)
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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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def test_round_float16():
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generate_testcases(np.float16)
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