wehub-resource-sync
100 lines
2.6 KiB
Python
100 lines
2.6 KiB
Python
# Copyright (c) 2022 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 os
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import tempfile
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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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def forward_post_hook1(layer, input, output):
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return output + output
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def forward_pre_hook1(layer, input):
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input_return = (input[0] * 2,)
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return input_return
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class SimpleNet(paddle.nn.Layer):
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def __init__(
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self,
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):
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super().__init__()
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self.fc1 = paddle.nn.Linear(10, 10)
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# sublayer1 register post hook
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self.fc1.register_forward_post_hook(forward_post_hook1)
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self.fc2 = paddle.nn.Linear(10, 10)
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# sublayer2 register pre hook
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self.fc2.register_forward_pre_hook(forward_pre_hook1)
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# register pre/post hook
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self.register_forward_pre_hook(forward_pre_hook1)
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self.register_forward_post_hook(forward_post_hook1)
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def forward(self, x):
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x = self.fc1(x)
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x = self.fc2(x)
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out = paddle.mean(x)
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return out
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class TestNestLayerHook(Dy2StTestBase):
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def setUp(self):
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paddle.seed(2022)
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self.x = paddle.randn([4, 10])
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self.temp_dir = tempfile.TemporaryDirectory()
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self.path = os.path.join(self.temp_dir.name, 'net_hook')
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def tearDown(self):
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self.temp_dir.cleanup()
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def train_net(self, to_static=False):
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paddle.seed(2022)
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net = SimpleNet()
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if to_static:
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net = paddle.jit.to_static(net)
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out = net(self.x)
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paddle.jit.save(net, self.path, input_spec=[self.x])
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return float(out)
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def load_train(self):
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net = paddle.jit.load(self.path)
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out = net(self.x)
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return float(out)
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def test_hook(self):
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dy_out = self.train_net(to_static=False)
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st_out = self.train_net(to_static=True)
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np.testing.assert_allclose(
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st_out,
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dy_out,
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rtol=1e-05,
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err_msg=f'dygraph_res is {dy_out}\nstatic_res is {st_out}',
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)
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if __name__ == "__main__":
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unittest.main()
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