103 lines
3.4 KiB
Python
103 lines
3.4 KiB
Python
# Copyright (c) 2019 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.
|
|
|
|
import unittest
|
|
|
|
import numpy as np
|
|
|
|
import paddle
|
|
from paddle import base
|
|
|
|
|
|
class MyLayer(paddle.nn.Layer):
|
|
def __init__(self, layerlist):
|
|
super().__init__()
|
|
self.layerlist = layerlist
|
|
|
|
def forward(self, x):
|
|
for l in self.layerlist:
|
|
x = l(x)
|
|
return x
|
|
|
|
|
|
class TestImperativeContainer(unittest.TestCase):
|
|
def paddle_imperative_list(self):
|
|
return paddle.nn.LayerList(
|
|
[paddle.nn.Linear(2**i, 2 ** (i + 1)) for i in range(6)]
|
|
)
|
|
|
|
def layer_list(self, use_base_api):
|
|
data_np = np.random.uniform(-1, 1, [5, 1]).astype('float32')
|
|
with base.dygraph.guard():
|
|
x = paddle.to_tensor(data_np)
|
|
layerlist = self.paddle_imperative_list()
|
|
size = len(layerlist)
|
|
|
|
model = MyLayer(layerlist)
|
|
res1 = model(x)
|
|
self.assertListEqual(res1.shape, [5, 2**size])
|
|
model.layerlist[size - 1] = paddle.nn.Linear(2 ** (size - 1), 5)
|
|
res2 = model(x)
|
|
self.assertListEqual(res2.shape, [5, 5])
|
|
del model.layerlist[size - 1]
|
|
res3 = model(x)
|
|
self.assertListEqual(res3.shape, [5, 2 ** (size - 1)])
|
|
model.layerlist.append(paddle.nn.Linear(2 ** (size - 1), 3))
|
|
res4 = model(x)
|
|
self.assertListEqual(res4.shape, [5, 3])
|
|
res4.backward()
|
|
|
|
model2 = MyLayer(layerlist[:-1])
|
|
res5 = model2(x)
|
|
self.assertListEqual(res5.shape, [5, 2 ** (size - 1)])
|
|
del model2.layerlist[1:]
|
|
res6 = model2(x)
|
|
self.assertListEqual(res6.shape, [5, 2 ** (0 + 1)])
|
|
res6.backward()
|
|
|
|
model3 = MyLayer(layerlist[:-2])
|
|
model3.layerlist.append(paddle.nn.Linear(3, 1))
|
|
model3.layerlist.insert(
|
|
size - 2, paddle.nn.Linear(2 ** (size - 2), 3)
|
|
)
|
|
res7 = model3(x)
|
|
self.assertListEqual(res7.shape, [5, 1])
|
|
to_be_extended = [
|
|
paddle.nn.Linear(3**i, 3 ** (i + 1)) for i in range(3)
|
|
]
|
|
model3.layerlist.extend(to_be_extended)
|
|
res8 = model3(x)
|
|
self.assertListEqual(res8.shape, [5, 3**3])
|
|
res8.backward()
|
|
|
|
model4 = MyLayer(layerlist[:3])
|
|
model4.layerlist[-1] = paddle.nn.Linear(4, 5)
|
|
res9 = model4(x)
|
|
self.assertListEqual(res9.shape, [5, 5])
|
|
del model4.layerlist[-1]
|
|
res10 = model4(x)
|
|
self.assertListEqual(res10.shape, [5, 4])
|
|
model4.layerlist.insert(-1, paddle.nn.Linear(2, 2))
|
|
res11 = model4(x)
|
|
self.assertListEqual(res11.shape, [5, 4])
|
|
res11.backward()
|
|
|
|
def test_test_layer_list(self):
|
|
self.layer_list(True)
|
|
self.layer_list(False)
|
|
|
|
|
|
if __name__ == '__main__':
|
|
unittest.main()
|