Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into check_out_lod

cmake/external/nccl.cmake

@@ -2,7 +2,7 @@ INCLUDE(ExternalProject)
 
 SET(NCCL_SOURCE_DIR ${THIRD_PARTY_PATH}/nccl)
 
-INCLUDE_DIRECTORIES(${NCCL_SOURCE_DIR}/src/extern_nccl)
+INCLUDE_DIRECTORIES(${NCCL_SOURCE_DIR}/src/extern_nccl/src)
 
 
 if(WITH_DSO)

paddle/operators/conv2dtranspose_op.h

@@ -120,7 +120,7 @@ class GemmConv2DTransposeKernel : public framework::OpKernel<T> {
       math::matmul<Place, T>(context.device_context(), filter, true,
                              input_batch, false, T(1.0), &col_matrix, T(0.0));
       col2im(context.device_context(), output_batch, col, strides[0],
-             strides[1], 0, 0);
+             strides[1], 0, 0, 0, 0);
     }
   }
 };
@@ -206,7 +206,7 @@ class GemmConv2DTransposeGradKernel : public framework::OpKernel<T> {
 
         // im2col: dy from (c, o_h, o_w) -> (c * k_h * k_w, h * w)
         im2col(context.device_context(), output_grad_batch, col, strides[0],
-               strides[1], paddings[0], paddings[1]);
+               strides[1], paddings[0], paddings[0], paddings[1], paddings[1]);
 
         // gemm: dx = filter * dy
         // (m, c * k_h * k_w) * (c * k_h * k_w, h * w) -> (m, c, h)
@@ -238,7 +238,7 @@ class GemmConv2DTransposeGradKernel : public framework::OpKernel<T> {
 
         // im2col: (c * h * w, k_h * k_w)
         im2col(context.device_context(), output_grad_batch, col, strides[0],
-               strides[1], paddings[0], paddings[1]);
+               strides[1], paddings[0], paddings[0], paddings[1], paddings[1]);
 
         // gemm: d_filter = x * y_grad^T
         // (m, c * h * w) * (k_h * k_w, c * h * w) -> (m, c, h)

python/paddle/v2/parameters.py

@@ -326,6 +326,17 @@ class Parameters(object):
         self.set(name, arr.reshape(self.get_shape(name)))
 
     def to_tar(self, f):
+        """
+        Save parameters to a tar file.
+
+        WARNING: You should use `paddle.v2.trainer.SGD.save_parameter_to_tar(f)`
+            to save parameters most of the time. Otherwise, some settings such
+            as model average will not take effect.
+
+        :param f:
+        :type f: file
+        :return:
+        """
         tar = tarfile.TarFile(fileobj=f, mode='w')
         for nm in self.names():
             buf = cStringIO.StringIO()