polish

test=develop

python/paddle/fluid/imperative/layers.py

@@ -34,16 +34,21 @@ class Layer(core.Layer):
         self._parameters = collections.OrderedDict()
         self._sub_layers = collections.OrderedDict()
 
-    def parameters(self):
-        """Returns an OrderedDict with parameters from current and sub-layers.
+    def parameters(self, include_sublayers=True):
+        """Returns a list of Parameters from current and sub-layers.
         """
-        return self._parameters
+        ret = [p for p in self._parameters.values()]
+        if include_sublayers:
+            for l in self._sub_layers.values():
+                for p in l.parameters(include_sublayers):
+                    ret.append(p)
+        return ret
 
     def clear_gradients(self):
         for p in self.parameters():
             p._clear_gradient()
 
-    def _build_once(self, inputs):
+    def _build_once(self, *args):
         pass
 
     def __call__(self, *inputs):

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

+# Copyright (c) 2018 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 contextlib
+import unittest
+import numpy as np
+import six
+import sys
+
+import paddle
+import paddle.fluid as fluid
+from paddle.fluid.layer_helper import LayerHelper
+
+
+class L1(fluid.imperative.Layer):
+    def __init__(self):
+        super(L1, self).__init__()
+        self._helper = LayerHelper(
+            'MyLayer',
+            param_attr=fluid.ParamAttr(
+                initializer=fluid.initializer.Constant(value=0.1)))
+
+        self.w1 = self._helper.create_parameter(
+            attr=self._helper.param_attr,
+            shape=[2, 2],
+            dtype='float32',
+            is_bias=False)
+        self.w2 = self._helper.create_parameter(
+            attr=self._helper.param_attr,
+            shape=[2, 2],
+            dtype='float32',
+            is_bias=False)
+
+    def forward(self):
+        return self.w1 + self.w2
+
+
+class L2(fluid.imperative.Layer):
+    def __init__(self):
+        super(L2, self).__init__()
+        self.layer1 = L1()
+        self.layer2 = L1()
+
+    def forward(self):
+        return self.layer1() + self.layer2()
+
+
+class L3(fluid.imperative.Layer):
+    def __init__(self):
+        super(L3, self).__init__()
+        self.layer1 = L2()
+        self.layer2 = L2()
+
+    def forward(self):
+        return self.layer1() + self.layer2()
+
+
+class TestBaseLayer(unittest.TestCase):
+    def test_one_level(self):
+        with fluid.imperative.guard():
+            l = L1()
+            ret = l()
+            self.assertEqual(l.w1.name, "MyLayer_0.w_0")
+            self.assertEqual(l.w2.name, "MyLayer_0.w_1")
+            self.assertTrue(np.allclose(ret._numpy(), 0.2 * np.ones([2, 2])))
+            sys.stderr.write(
+                '%s %s %s %s\n' %
+                (ret._numpy(), l.w1.name, l.w2.name, l._sub_layers))
+
+    def test_three_level(self):
+        with fluid.imperative.guard():
+            l = L3()
+            ret = l()
+            sys.stderr.write('%s\n' % ret._numpy())
+
+            for p in l.parameters():
+                sys.stderr.write('%s\n' % p.name)
+
+
+if __name__ == '__main__':
+    unittest.main()