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107 lines
2.7 KiB
107 lines
2.7 KiB
4 years ago
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# Copyright 2020 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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context.set_context(mode=context.GRAPH_MODE, device_target="GPU")
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class SoftplusNet(nn.Cell):
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def __init__(self):
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super(SoftplusNet, self).__init__()
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self.softplus = P.Softplus()
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def construct(self, x):
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return self.softplus(x)
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def SoftplusCompute(x):
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return np.log(1 + np.exp(x))
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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_softplus_1d():
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x_np = np.random.random((50,)).astype(np.float32)
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y_np = SoftplusCompute(x_np)
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x_ms = Tensor(x_np)
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net = SoftplusNet()
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y_ms = net(x_ms)
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assert np.allclose(y_np, y_ms.asnumpy())
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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_softplus_2d():
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x_np = np.random.random((50, 40)).astype(np.float32)
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y_np = SoftplusCompute(x_np)
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x_ms = Tensor(x_np)
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net = SoftplusNet()
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y_ms = net(x_ms)
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assert np.allclose(y_np, y_ms.asnumpy())
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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_softplus_4d():
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x_np = np.random.random((32, 3, 224, 224)).astype(np.float32)
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y_np = SoftplusCompute(x_np)
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x_ms = Tensor(x_np)
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net = SoftplusNet()
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y_ms = net(x_ms)
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assert np.allclose(y_np, y_ms.asnumpy())
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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_softplus_neg():
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x_np = np.random.random((32, 3, 224, 224)).astype(np.float32) * -1
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y_np = SoftplusCompute(x_np)
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x_ms = Tensor(x_np)
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net = SoftplusNet()
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y_ms = net(x_ms)
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assert np.allclose(y_np, y_ms.asnumpy())
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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_softplus_4d_fp16():
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x_np = np.random.random((32, 3, 224, 224)).astype(np.float16)
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y_np = SoftplusCompute(x_np)
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x_ms = Tensor(x_np)
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net = SoftplusNet()
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y_ms = net(x_ms)
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assert np.allclose(y_np, y_ms.asnumpy(), rtol=5e-3)
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