Merge pull request #6744 from jacquesqiao/expose-const-value

Expose const value

paddle/pybind/CMakeLists.txt

 if(WITH_PYTHON)
   cc_library(paddle_pybind SHARED
-    SRCS pybind.cc exception.cc protobuf.cc
+    SRCS pybind.cc exception.cc protobuf.cc const_value.cc
     DEPS pybind python backward proto_desc paddle_memory executor prune init
     ${GLOB_OP_LIB})
 endif(WITH_PYTHON)

paddle/pybind/const_value.cc

+/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
+
+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. */
+
+#include "const_value.h"
+#include "paddle/framework/operator.h"
+
+namespace paddle {
+namespace pybind {
+
+void BindConstValue(pybind11::module& m) {
+  m.def("kEmptyVarName", [] { return framework::kEmptyVarName; });
+  m.def("kTempVarName", [] { return framework::kTempVarName; });
+  m.def("kGradVarSuffix", [] { return framework::kGradVarSuffix; });
+  m.def("kZeroVarSuffix", [] { return framework::kZeroVarSuffix; });
+}
+
+}  // namespace pybind
+}  // namespace paddle

paddle/pybind/const_value.h

+/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
+
+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. */
+
+#pragma once
+#include <Python.h>
+#include "paddle/platform/enforce.h"
+#include "pybind11/pybind11.h"
+
+namespace py = pybind11;
+
+namespace paddle {
+namespace pybind {
+extern void BindConstValue(pybind11::module& m);
+}  // namespace pybind
+}  // namespace paddle

paddle/pybind/pybind.cc

@@ -30,6 +30,7 @@ limitations under the License. */
 #include "paddle/operators/net_op.h"
 #include "paddle/platform/enforce.h"
 #include "paddle/platform/place.h"
+#include "paddle/pybind/const_value.h"
 #include "paddle/pybind/exception.h"
 #include "paddle/pybind/pybind.h"
 #include "paddle/pybind/tensor_py.h"
@@ -431,6 +432,7 @@ All parameter, weight, gradient are variables in Paddle.
   BindBlockDesc(m);
   BindVarDsec(m);
   BindOpDesc(m);
+  BindConstValue(m);
 
   py::class_<framework::LoDRankTable>(m, "LodRankTable")
       .def("items", [](framework::LoDRankTable &table) {

python/paddle/v2/fluid/framework.py

 import collections
+import contextlib
 
 import numpy as np
-from . import core
+
 import proto.framework_pb2 as framework_pb2
-import google.protobuf.message
-import contextlib
+from . import core
 
 __all__ = [
     'Block', 'Variable', 'Program', 'Operator', 'default_startup_program',
@@ -12,6 +12,18 @@ __all__ = [
     'switch_main_program'
 ]
 
+EMPTY_VAR_NAME = core.kEmptyVarName()
+TEMP_VAR_NAME = core.kTempVarName()
+GRAD_VAR_SUFFIX = core.kGradVarSuffix()
+ZERO_VAR_SUFFIX = core.kZeroVarSuffix()
+
+
+def grad_var_name(var_name):
+    """
+    return gradient name for a certain var name
+    """
+    return var_name + GRAD_VAR_SUFFIX
+
 
 def unique_name(prefix):
     """

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

@@ -3,10 +3,7 @@ import numpy as np
 from op_test import OpTest
 import paddle.v2.fluid.core as core
 from paddle.v2.fluid.op import Operator
-
-
-def grad_var_name(var_name):
-    return var_name + "@GRAD"
+from paddle.v2.fluid.framework import grad_var_name
 
 
 def get_backward_op(scope, op, no_grad_set):

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

+import unittest
+import paddle.v2.fluid.framework as framework
+
+
+class ConditionalBlock(unittest.TestCase):
+    def test_const_value(self):
+        self.assertEqual(framework.GRAD_VAR_SUFFIX, "@GRAD")
+        self.assertEqual(framework.TEMP_VAR_NAME, "@TEMP@")
+        self.assertEqual(framework.GRAD_VAR_SUFFIX, "@GRAD")
+        self.assertEqual(framework.ZERO_VAR_SUFFIX, "@ZERO")
+
+
+if __name__ == '__main__':
+    unittest.main()

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

 import unittest
+
 import paddle.v2.fluid.op as op
-import paddle.v2.fluid.core as core
 import paddle.v2.fluid.proto.framework_pb2 as framework_pb2
 
 

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

 from __future__ import print_function
 import unittest
 
-from paddle.v2.fluid.framework import Program, default_main_program, program_guard
+from paddle.v2.fluid.framework import Program, default_main_program, program_guard, grad_var_name
 import paddle.v2.fluid.layers as layers
 
 main_program = default_main_program()
@@ -109,12 +109,10 @@ class TestProgram(unittest.TestCase):
         self.assertEqual(add_op.idx, 1)
         param_to_grad = prog.append_backward(mean_out, set())
 
-        def grad_name(name):
-            return name + "@GRAD"
-
         for var_name in ("mul.x", "mul.y", "mul.out", "add.y", "add.out",
                          "mean.out"):
-            self.assertEqual(param_to_grad[var_name][0], grad_name(var_name))
+            self.assertEqual(param_to_grad[var_name][0],
+                             grad_var_name(var_name))
             self.assertEqual(param_to_grad[var_name][1], 0)
 
         expect_ops = [

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

 import unittest
 
 import paddle.v2.fluid.layers as layers
-from paddle.v2.fluid.framework import Program
+from paddle.v2.fluid.framework import Program, grad_var_name
 from paddle.v2.fluid.executor import Executor
 from paddle.v2.fluid.backward import append_backward_ops
 import numpy as np
@@ -164,7 +164,7 @@ class RecurrentOpTest1(unittest.TestCase):
             for x in self.data_field
         }
         fetch_list = [
-            self.main_program.global_block().var(x + "@GRAD")
+            self.main_program.global_block().var(grad_var_name(x))
             for x in self.data_field
         ]