wehub-resource-sync
114 lines
3.7 KiB
Python
114 lines
3.7 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 unittest
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from copy import deepcopy
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from types import MethodType
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import numpy as np
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from dygraph_to_static_utils import Dy2StTestBase, test_ast_only
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from test_rollback import Net, foo
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import paddle
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from paddle.jit.dy2static.program_translator import StaticFunction
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class InnerLayer(paddle.nn.Layer):
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def __init__(self):
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super().__init__()
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self.linear = paddle.nn.Linear(32, 32)
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def forward(self, x):
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return self.linear(x)
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class NestedLayerForDeepcopy(paddle.nn.Layer):
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def __init__(self):
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super().__init__()
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self.inner = InnerLayer()
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def forward(self, x):
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return self.inner(x)
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class TestDeepCopy(Dy2StTestBase):
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def test_net(self):
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net = Net()
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net = paddle.jit.to_static(net)
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x = paddle.randn([3, 4])
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src_out = net(x)
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self.assertTrue(isinstance(net.forward, StaticFunction))
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copy_net = deepcopy(net)
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copy_out = copy_net(x)
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self.assertIsInstance(copy_net.forward, StaticFunction)
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self.assertIsNot(net.forward, copy_net.forward)
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self.assertIsNot(
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net.forward.class_instance, copy_net.forward.class_instance
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)
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self.assertIs(net, net.forward.class_instance)
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self.assertIs(copy_net, copy_net.forward.class_instance)
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np.testing.assert_array_equal(src_out.numpy(), copy_out.numpy())
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copy_net.forward.rollback()
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self.assertFalse(isinstance(copy_net.forward, StaticFunction))
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copy_rollback_out = copy_net(x)
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np.testing.assert_array_equal(
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src_out.numpy(), copy_rollback_out.numpy()
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)
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def test_func(self):
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st_foo = paddle.jit.to_static(foo)
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x = paddle.randn([3, 4])
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st_out = st_foo(x)
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self.assertTrue(isinstance(st_foo, StaticFunction))
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new_foo = deepcopy(st_foo)
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self.assertFalse(isinstance(new_foo, StaticFunction))
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new_out = new_foo(x)
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np.testing.assert_array_equal(st_out.numpy(), new_out.numpy())
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@test_ast_only
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def test_nested_net(self):
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model = NestedLayerForDeepcopy()
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static_model = paddle.jit.to_static(model)
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x = paddle.randn([1, 256, 32])
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out = model(x)
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copied_model = deepcopy(static_model)
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self.assertIsInstance(copied_model.inner.forward, MethodType)
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self.assertIsNot(static_model.inner.forward, copied_model.inner.forward)
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self.assertIsNot(
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static_model.inner.forward.__self__,
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copied_model.inner.forward.__self__,
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)
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self.assertIs(static_model.inner, static_model.inner.forward.__self__)
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self.assertIs(copied_model.inner, copied_model.inner.forward.__self__)
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copied_out = copied_model(x)
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copied_model.forward.rollback()
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self.assertIsInstance(copied_model.inner.forward, MethodType)
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copied_model(x)
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copied_rollback_out = copied_model(x)
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np.testing.assert_array_equal(out.numpy(), copied_out.numpy())
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np.testing.assert_array_equal(out.numpy(), copied_rollback_out.numpy())
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if __name__ == "__main__":
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unittest.main()
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