Add Sequential api (#20789)

* add Sequential api
test=develop

* fix unittest
test=develop

* refine code sample

* test=develop

python/paddle/fluid/dygraph/__init__.py

@@ -20,6 +20,9 @@ from .base import *
 from . import layers
 from .layers import *
 
+from . import container
+from .container import *
+
 from . import nn
 from .nn import *
 
@@ -41,6 +44,7 @@ from .backward_strategy import *
 __all__ = []
 __all__ += layers.__all__
 __all__ += base.__all__
+__all__ += container.__all__
 __all__ += nn.__all__
 __all__ += tracer.__all__
 __all__ += parallel.__all__

python/paddle/fluid/dygraph/container.py

+# 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

python/paddle/fluid/tests/unittests/test_imperative_container_sequential.py

+# 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()