reste

paddle/pybind/pybind.cc

@@ -19,7 +19,6 @@ limitations under the License. */
 #include "paddle/framework/backward.h"
 #include "paddle/framework/lod_tensor.h"
 #include "paddle/framework/op_registry.h"
-#include "paddle/operators/cond_op.h"
 #include "paddle/operators/net_op.h"
 #include "paddle/operators/recurrent_op.h"
 #include "paddle/platform/enforce.h"
@@ -289,28 +288,6 @@ All parameter, weight, gradient are variables in Paddle.
            [](operators::RecurrentOp &self, const operators::NetOp &net)
                -> void { self.set_stepnet(net.Clone()); });
 
-  // cond_op
-  py::class_<operators::CondOp, OperatorBase>(m, "CondOp")
-      .def_static("create",
-                  [](py::bytes protobin) -> operators::CondOp * {
-                    OpDesc desc;
-                    PADDLE_ENFORCE(desc.ParsePartialFromString(protobin),
-                                   "Cannot parse user input to OpDesc");
-                    PADDLE_ENFORCE(desc.IsInitialized(),
-                                   "User OpDesc is not initialized, reason %s",
-                                   desc.InitializationErrorString());
-                    auto cond_op = OpRegistry::CreateOp(desc);
-                    return static_cast<operators::CondOp *>(cond_op.release());
-                  })
-      .def("set_truenet",
-           [](operators::CondOp &self, const operators::NetOp &net) -> void {
-             self.set_truenet(net.Clone());
-           })
-      .def("set_falsenet",
-           [](operators::CondOp &self, const operators::NetOp &net) -> void {
-             self.set_falsenet(net.Clone());
-           });
-
   m.def("unique_integer", UniqueIntegerGenerator);
 
   m.def("is_compile_gpu", IsCompileGPU);

python/paddle/v2/framework/tests/op_test.py

@@ -64,6 +64,7 @@ def set_input(scope, op, inputs, place):
                 tensor.set_dims(in_array.shape)
                 tensor.set(in_array, place)
                 if isinstance(in_val, tuple):
+                    print "set lod"
                     tensor.set_lod(in_val[1])