wehub-resource-sync
75 lines
2.0 KiB
Python
75 lines
2.0 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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import numpy as np
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from dygraph_to_static_utils import (
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Dy2StTestBase,
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test_ast_only,
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)
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import paddle
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class TestInplaceAssign(Dy2StTestBase):
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@test_ast_only
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def test_case0(self):
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a = paddle.ones((1024, 2)) * 1
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b = paddle.ones((1024, 3)) * 2
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c = paddle.ones((1024, 4)) * 3
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a._inplace_assign(b)
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np.testing.assert_array_equal(a.numpy(), b.numpy())
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b._inplace_assign(c)
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np.testing.assert_array_equal(b.numpy(), c.numpy())
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@test_ast_only
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def test_case1(self):
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def func(x):
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a = 1 * x
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b = 2 * x
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a._inplace_assign(b)
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return a
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x = paddle.ones((1,))
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a = paddle.randn((1,))
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x.stop_gradient = False
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a.stop_gradient = False
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y = func(x)
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y.mean().backward()
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np.testing.assert_array_equal(x.grad.numpy(), np.array([2.0]))
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def test_case2(self):
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def func(a, x):
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x = 2 * x
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x[:] = a * 2.0
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return x
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def forward(a, x):
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output = paddle.jit.to_static(func)(a, x)
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x._inplace_assign(output)
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return x
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x = paddle.ones((1,))
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a = paddle.randn((1,))
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x.stop_gradient = False
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a.stop_gradient = False
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y = forward(a, x)
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y.mean().backward()
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np.testing.assert_array_equal(a.grad.numpy(), np.array([2.0]))
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if __name__ == "__main__":
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unittest.main()
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