forked from huawei/mindspore2022
65 lines
2.0 KiB
Python
65 lines
2.0 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
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from mindspore.ops import operations as P
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class Net(nn.Cell):
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def __init__(self, axis=-1):
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super(Net, self).__init__()
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self.Softmax = P.Softmax(axis)
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def construct(self, x):
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return self.Softmax(x)
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def get_output(x, enable_graph_kernel=False):
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context.set_context(enable_graph_kernel=enable_graph_kernel)
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opt = Net()
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output = opt(Tensor(x))
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return output
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def test_softmax(shape, dtype):
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np.random.seed(0)
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x = np.random.normal(0, 1, shape).astype(dtype)
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expect = get_output(x, False)
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output = get_output(x, True)
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rtol = 1.e-4
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atol = 1.e-4
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if dtype == "float16":
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rtol = 1.e-3
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atol = 1.e-3
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assert np.allclose(expect.asnumpy(), output.asnumpy(), rtol, atol, equal_nan=True)
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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_softmax_gpu():
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context.set_context(mode=context.GRAPH_MODE, device_target="GPU")
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test_softmax([4, 32, 48], np.float32)
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@pytest.mark.level1
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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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def test_softmax_ascend():
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context.set_context(mode=context.GRAPH_MODE, device_target="Ascend")
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test_softmax([2, 32, 48, 64], np.float32)
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