未验证 提交 13451615 编写于 作者: X xiongkun 提交者: GitHub

add unittest for PR43688 (#43747)

* add unittest for PR43688
上级 4ef704eb
# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from __future__ import print_function
import paddle
import paddle.fluid as fluid
import unittest
class MyLayer(paddle.nn.Layer):
def __init__(self):
super().__init__()
self.linear = paddle.nn.Linear(1, 1)
@paddle.jit.to_static(input_spec=[
paddle.static.InputSpec(shape=[None, None], dtype=paddle.float32)
])
def forward(self, x):
return self.linear(x)
class TestBackward(unittest.TestCase):
def test_order_0(self):
"""
loss = 1 * w * 1 + 2 * w * 2
delta_w = 5
"""
model = MyLayer()
model.clear_gradients()
inp = paddle.ones([1, 1])
out1 = model(inp * 1)
out2 = model(inp * 2)
loss = out2 * 2 + out1 * 1
loss.backward()
self.assertEqual(model.linear.weight.grad, 5)
def test_order_1(self):
"""
loss = 2 * w * 2 + 1 * w * 1
delta_w = 5
"""
model = MyLayer()
model.clear_gradients()
inp = paddle.ones([1, 1])
out1 = model(inp * 1)
out2 = model(inp * 2)
loss = out1 * 1 + out2 * 2
loss.backward()
self.assertEqual(model.linear.weight.grad, 5)
if __name__ == '__main__':
with fluid.framework._test_eager_guard():
unittest.main()
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