Merge pull request #7721 from reyoung/feature/rename_fluid

Move registery.py to layers module

python/paddle/v2/fluid/layers/control_flow.py

@@ -11,13 +11,13 @@
 # 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
 
-from ..layer_helper import LayerHelper, unique_name
-from ..framework import Program, Variable, Operator
-from .. import core
+from layer_function_generator import autodoc
 from tensor import assign, fill_constant
-import contextlib
-from ..registry import autodoc
+from .. import core
+from ..framework import Program, Variable, Operator
+from ..layer_helper import LayerHelper, unique_name
 
 __all__ = [
     'split_lod_tensor',
@@ -1477,7 +1477,7 @@ class DynamicRNN(object):
                 method))
 
 
-@autodoc
+@autodoc()
 def reorder_lod_tensor_by_rank(x, rank_table):
     helper = LayerHelper('reorder_lod_tensor_by_rank', **locals())
     helper.is_instance('x', Variable)

python/paddle/v2/fluid/layers/device.py

@@ -15,14 +15,14 @@
 All util layers.
 """
 
-from ..layer_helper import LayerHelper
+from layer_function_generator import autodoc
 from ..framework import unique_name
-from ..registry import autodoc
+from ..layer_helper import LayerHelper
 
 __all__ = ['get_places']
 
 
-@autodoc
+@autodoc()
 def get_places(device_count=None, device_type=None):
     helper = LayerHelper('get_places', **locals())
     out_places = helper.create_variable(name=unique_name(helper.name + ".out"))

python/paddle/v2/fluid/layers/layer_function_generator.py

@@ -13,17 +13,19 @@
 # limitations under the License.
 import re
 import cStringIO
-import warnings
 import functools
-import inspect
+import warnings
+
+from .. import proto
 
-import proto.framework_pb2 as framework_pb2
-from framework import OpProtoHolder, Variable, Program, Operator
-from paddle.v2.fluid.layer_helper import LayerHelper, unique_name
+framework_pb2 = proto.framework_pb2
+
+from ..framework import OpProtoHolder, Variable
+from ..layer_helper import LayerHelper
 
 __all__ = [
     'deprecated',
-    'register_layer',
+    'generate_layer_fn',
     'autodoc',
 ]
 
@@ -96,7 +98,7 @@ def _generate_doc_string_(op_proto):
     return buf.getvalue()
 
 
-def register_layer(op_type):
+def generate_layer_fn(op_type):
     """Register the Python layer for an Operator.
 
     Args:
@@ -207,7 +209,10 @@ def deprecated(func_or_class):
     return func_wrapper
 
 
-def autodoc(func):
-    func.__doc__ = _generate_doc_string_(OpProtoHolder.instance().get_op_proto(
-        func.__name__))
-    return func
+def autodoc(comment=""):
+    def __impl__(func):
+        func.__doc__ = _generate_doc_string_(OpProtoHolder.instance(
+        ).get_op_proto(func.__name__)) + comment
+        return func
+
+    return __impl__

python/paddle/v2/fluid/layers/ops.py

@@ -11,8 +11,7 @@
 # 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 ..registry import register_layer
+from layer_function_generator import generate_layer_fn
 
 __activations__ = [
     'sigmoid',
@@ -53,4 +52,4 @@ __all__ = [
 ] + __activations__
 
 for _OP in set(__all__):
-    globals()[_OP] = register_layer(_OP)
+    globals()[_OP] = generate_layer_fn(_OP)

python/paddle/v2/fluid/tests/test_registry.py

@@ -11,26 +11,21 @@
 # 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 warnings
 
 import paddle.v2.fluid as fluid
-import paddle.v2.fluid.framework as framework
-import paddle.v2.fluid.layers as layers
-import paddle.v2.fluid.registry as registry
+import numpy as np
+import decorators
 
 
 class TestRegistry(unittest.TestCase):
+    @decorators.prog_scope()
     def test_registry_layer(self):
-        self.layer_type = "mean"
-        program = framework.Program()
-
         x = fluid.layers.data(name='X', shape=[10, 10], dtype='float32')
-        output = layers.mean(x)
+        output = fluid.layers.mean(x=x)
+
         place = fluid.CPUPlace()
         exe = fluid.Executor(place)
-
         X = np.random.random((10, 10)).astype("float32")
-        mean_out = exe.run(program, feed={"X": X}, fetch_list=[output])
-        self.assertAlmostEqual(np.mean(X), mean_out)
+        mean_out = exe.run(feed={"X": X}, fetch_list=[output])
+        self.assertAlmostEqual(np.mean(X), mean_out[0])