提交 2058bab1 编写于 作者: Y Youwei Song 提交者: hong

Add Sequential api (#20789)

* add Sequential api
test=develop

* fix unittest
test=develop

* refine code sample

* test=develop
上级 6802539a
...@@ -20,6 +20,9 @@ from .base import * ...@@ -20,6 +20,9 @@ from .base import *
from . import layers from . import layers
from .layers import * from .layers import *
from . import container
from .container import *
from . import nn from . import nn
from .nn import * from .nn import *
...@@ -41,6 +44,7 @@ from .backward_strategy import * ...@@ -41,6 +44,7 @@ from .backward_strategy import *
__all__ = [] __all__ = []
__all__ += layers.__all__ __all__ += layers.__all__
__all__ += base.__all__ __all__ += base.__all__
__all__ += container.__all__
__all__ += nn.__all__ __all__ += nn.__all__
__all__ += tracer.__all__ __all__ += tracer.__all__
__all__ += parallel.__all__ __all__ += parallel.__all__
......
# 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.
from .layers import Layer
__all__ = ['Sequential']
class Sequential(Layer):
"""Sequential container.
Sub layers will be added to this container in the order of argument in the constructor.
The argument passed to the constructor can be iterable Layers or iterable name Layer pairs.
Parameters:
name_scope(str): The name of this class.
layers(iterable): Iterable Layers or iterable name Layer pairs.
Examples:
.. code-block:: python
import paddle.fluid as fluid
import numpy as np
data = np.random.uniform(-1, 1, [30, 10]).astype('float32')
with fluid.dygraph.guard():
data = fluid.dygraph.to_variable(data)
# create Sequential with iterable Layers
model1 = fluid.dygraph.Sequential('model1',
fluid.FC('fc1', 2),
fluid.FC('fc2', 3)
)
model1[0] # access fc1 layer
res1 = model1(data) # sequential execution
# create Sequential with name Layer pairs
model2 = fluid.dygraph.Sequential('model2',
('l1', fluid.FC('l1', 2)),
('l2', fluid.FC('l2', 3))
)
model2['l1'] # access l1 layer
model2.add_sublayer('l3', fluid.FC('l3', 3)) # add sublayer
print([l.full_name() for l in model2.sublayers()]) # ['l1/FC_0', 'l2/FC_0', 'l3/FC_0']
res2 = model2(data) # sequential execution
"""
def __init__(self, name_scope, *layers):
super(Sequential, self).__init__(name_scope)
if len(layers) > 0 and isinstance(layers[0], tuple):
for name, layer in layers:
self.add_sublayer(name, layer)
else:
for idx, layer in enumerate(layers):
self.add_sublayer(str(idx), layer)
def __getitem__(self, name):
return self._sub_layers[str(name)]
def __setitem__(self, name, layer):
assert isinstance(layer, Layer)
setattr(self, str(name), layer)
def __delitem__(self, name):
name = str(name)
assert name in self._sub_layers
del self._sub_layers[name]
def __len__(self):
return len(self._sub_layers)
def forward(self, input):
for layer in self._sub_layers.values():
input = layer(input)
return input
# 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.
from __future__ import print_function
import unittest
import paddle.fluid as fluid
import numpy as np
class TestImperativeContainerSequential(unittest.TestCase):
def test_sequential(self):
data = np.random.uniform(-1, 1, [5, 10]).astype('float32')
with fluid.dygraph.guard():
data = fluid.dygraph.to_variable(data)
model1 = fluid.dygraph.Sequential('model1',
fluid.FC('fc1', 1),
fluid.FC('fc2', 2))
res1 = model1(data)
self.assertListEqual(res1.shape, [5, 2])
self.assertTrue('fc1' in model1[0]._full_name)
model1[1] = fluid.FC('fc2_new', 3)
res1 = model1(data)
self.assertListEqual(res1.shape, [5, 3])
self.assertTrue('fc2_new' in name
for name in [p.name for p in model1.parameters()])
loss1 = fluid.layers.reduce_mean(res1)
loss1.backward()
model2 = fluid.dygraph.Sequential(
'model2', ('l1', fluid.FC('l1', 1)), ('l2', fluid.FC('l2', 3)))
self.assertEqual(len(model2), 2)
res2 = model2(data)
self.assertTrue('l1' in model2.l1.full_name())
self.assertListEqual(res2.shape, res1.shape)
self.assertEqual(len(model1.parameters()), len(model2.parameters()))
del model2['l2']
self.assertEqual(len(model2), 1)
res2 = model2(data)
self.assertListEqual(res2.shape, [5, 1])
model2.add_sublayer('l3', fluid.FC('l3', 3))
model2.add_sublayer('l4', fluid.FC('l4', 4))
self.assertEqual(len(model2), 3)
res2 = model2(data)
self.assertListEqual(res2.shape, [5, 4])
loss2 = fluid.layers.reduce_mean(res2)
loss2.backward()
if __name__ == '__main__':
unittest.main()
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