fix bug of ParamAttr (#126)

* fix bug of ParamAttr

* refine imports of unittest

parl/algorithms/fluid/impala/tests/vtrace_test.py

@@ -20,7 +20,7 @@ https://github.com/deepmind/scalable_agent/blob/master/vtrace_test.py
 import copy
 import numpy as np
 import unittest
-from parl.core.fluid import layers
+from parl import layers
 from paddle import fluid
 from parameterized import parameterized
 from parl.algorithms.fluid.impala import vtrace

parl/core/fluid/layers/layer_wrappers.py

@@ -16,7 +16,7 @@ Wrappers for fluid.layers. It helps to easily share parameters between layers.
 
 Here is an example:
     ```python
-    import parl.layers as layers
+    from parl import layers
 
     class MLPModel(Model):
         def __init__(self):
@@ -67,6 +67,7 @@ def update_attr_name(name, default_name, attr, is_bias):
             attr.name = name
         return attr
 
+    attr = ParamAttr._to_attr(attr)
     name = (default_name if name is None else name)
     suffix = "b" if is_bias else "w"
     new_name = unique_name.generate(name + "." + suffix)

parl/core/fluid/layers/tests/param_name_test.py

@@ -12,18 +12,20 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import parl.core.fluid.layers as layers
+import parl
+from paddle import fluid
+from parl import layers
 import unittest
-from parl.core.fluid.model import Model
 
 
-class MyNetWork(Model):
+class MyNetWork(parl.Model):
     def __init__(self):
         self.fc1 = layers.fc(100)
         self.fc2 = layers.fc(100)
         self.fc3 = layers.fc(100, bias_attr=False)
         self.fc4 = layers.fc(100, param_attr=False)
         self.fc5 = layers.fc(100, name="fc", bias_attr=False)
+        self.fc6 = layers.fc(100, param_attr=fluid.initializer.Xavier())
         self.embedding = layers.embedding((100, 128))
         self.embedding_custom = layers.embedding((100, 128),
                                                  name="embedding_custom")
@@ -55,6 +57,8 @@ class TestParamName(unittest.TestCase):
         self.assertEqual(net.fc5.param_name, "fc.w_4")
         self.assertEqual(net.fc5.bias_name, None)
 
+        self.assertEqual(net.fc6.param_name, "fc.w_5")
+
         ## embedding layer has no bias
         self.assertEqual(net.embedding.param_name, "embedding.w_0")
         self.assertEqual(net.embedding.bias_name, None)

parl/core/fluid/layers/tests/param_sharing_test.py

@@ -14,12 +14,12 @@
 
 import numpy as np
 import paddle.fluid as fluid
+import parl
 import unittest
 from parl import layers
-from parl.core.fluid.model import Model
 
 
-class MyNetWork(Model):
+class MyNetWork(parl.Model):
     def __init__(self):
         self.fc1 = layers.fc(64, bias_attr=False)
         self.fc2 = layers.fc(64, bias_attr=False)

parl/core/fluid/tests/model_base_test.py

@@ -14,16 +14,16 @@
 
 import numpy as np
 import paddle.fluid as fluid
-import parl.core.fluid.layers as layers
+import parl
 import unittest
 from copy import deepcopy
 from paddle.fluid import ParamAttr
-from parl.core.fluid.model import Model
+from parl import layers
 from parl.utils import get_gpu_count
 from parl.core.fluid.plutils import fetch_value
 
 
-class TestModel(Model):
+class TestModel(parl.Model):
     def __init__(self):
         self.fc1 = layers.fc(
             size=256,
@@ -48,7 +48,7 @@ class TestModel(Model):
         return out
 
 
-class TestModel2(Model):
+class TestModel2(parl.Model):
     def __init__(self):
         self.created_param = layers.create_parameter(
             shape=[100],
@@ -60,7 +60,7 @@ class TestModel2(Model):
         return out
 
 
-class TestModel3(Model):
+class TestModel3(parl.Model):
     def __init__(self):
         self.fc1 = layers.fc(64, bias_attr=False)
         self.batch_norm = layers.batch_norm()
@@ -71,7 +71,7 @@ class TestModel3(Model):
         return out
 
 
-class TestModel4(Model):
+class TestModel4(parl.Model):
     def __init__(self):
         self.fc1 = layers.fc(size=256)
         self.fc2 = layers.fc(size=128)