wehub-resource-sync
70 lines
1.8 KiB
Python
70 lines
1.8 KiB
Python
# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
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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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import unittest
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import numpy as np
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from dygraph_to_static_utils import (
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Dy2StTestBase,
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)
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import paddle
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class Net(paddle.nn.Layer):
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def __init__(self):
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super().__init__()
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def forward(self, x):
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out = x + 1
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return out
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class TestBackwardWithoutParams(Dy2StTestBase):
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def test_run(self):
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net = paddle.jit.to_static(Net())
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x = paddle.ones([2, 2])
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x.stop_gradient = False
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out = net(x)
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loss = paddle.mean(out)
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loss.backward()
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np.testing.assert_equal(x.grad.numpy(), np.full(x.shape, 0.25))
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class ZeroSizeNet(paddle.nn.Layer):
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def __init__(self):
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super().__init__()
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def forward(self, x):
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y = paddle.randn((0,))
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out = paddle.nn.functional.relu(x)
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y.stop_gradient = True
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return y, out
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class TestZeroSizeNet(Dy2StTestBase):
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def test_run(self):
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net = paddle.jit.to_static(ZeroSizeNet())
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x = paddle.ones([2, 2])
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x.stop_gradient = False
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_, out = net(x)
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loss = paddle.mean(out)
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loss.backward()
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np.testing.assert_equal(x.grad.numpy(), np.full(x.shape, 0.25))
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if __name__ == '__main__':
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unittest.main()
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