Merge remote-tracking branch 'upstream/develop' into backward_on_parallel_do

cmake/external/mkldnn.cmake

@@ -56,6 +56,7 @@ ExternalProject_Add(
     PREFIX              ${MKLDNN_SOURCES_DIR}
     UPDATE_COMMAND      ""
     CMAKE_ARGS          -DCMAKE_INSTALL_PREFIX=${MKLDNN_INSTALL_DIR}
+    CMAKE_ARGS          -DCMAKE_BUILD_TYPE=${CMAKE_BUILD_TYPE} 
     CMAKE_ARGS          -DMKLROOT=${MKLML_ROOT}
     CMAKE_ARGS          -DCMAKE_C_FLAGS=${MKLDNN_CFLAG}
     CMAKE_ARGS          -DCMAKE_CXX_FLAGS=${MKLDNN_CXXFLAG}

paddle/fluid/framework/tensor.h

@@ -130,8 +130,6 @@ class Tensor {
   inline void set_layout(const DataLayout layout) { layout_ = layout; }
 
  private:
-  friend class LoDTensor;
-
   /**
    * @note    Placeholder hides type T, so it doesn't appear as a template
    *          parameter of Variable.

paddle/fluid/operators/detection_map_op.h

@@ -151,7 +151,7 @@ class DetectionMAPOpKernel : public framework::OpKernel<T> {
 
     for (int n = 0; n < batch_size; ++n) {
       std::map<int, std::vector<Box>> boxes;
-      for (int i = label_index[n]; i < label_index[n + 1]; ++i) {
+      for (size_t i = label_index[n]; i < label_index[n + 1]; ++i) {
         Box box(labels(i, 2), labels(i, 3), labels(i, 4), labels(i, 5));
         int label = labels(i, 0);
         auto is_difficult = labels(i, 1);
@@ -167,7 +167,7 @@ class DetectionMAPOpKernel : public framework::OpKernel<T> {
     auto detect_index = detect_lod[0];
     for (int n = 0; n < batch_size; ++n) {
       std::map<int, std::vector<std::pair<T, Box>>> boxes;
-      for (int i = detect_index[n]; i < detect_index[n + 1]; ++i) {
+      for (size_t i = detect_index[n]; i < detect_index[n + 1]; ++i) {
         Box box(detect(i, 2), detect(i, 3), detect(i, 4), detect(i, 5));
         int label = detect(i, 0);
         auto score = detect(i, 1);
@@ -269,8 +269,8 @@ class DetectionMAPOpKernel : public framework::OpKernel<T> {
                       std::map<int, std::vector<std::pair<T, int>>>& pos) {
       const T* pos_data = pos_tensor.data<T>();
       auto pos_data_lod = pos_tensor.lod();
-      for (int i = 0; i < pos_data_lod.size(); ++i) {
-        for (int j = pos_data_lod[0][i]; j < pos_data_lod[0][i + 1]; ++j) {
+      for (size_t i = 0; i < pos_data_lod.size(); ++i) {
+        for (size_t j = pos_data_lod[0][i]; j < pos_data_lod[0][i + 1]; ++j) {
           T score = pos_data[j * 2];
           int flag = 1;
           if (pos_data[j * 2 + 1] < kEPS) flag = 0;

python/paddle/v2/fluid/data_feeder.py

@@ -107,6 +107,9 @@ class DataFeeder(object):
                     dtype=dtype))
 
         for each_sample in iterable:
+            assert len(each_sample) == len(converter), (
+                "The number of fields in data (%s) does not match " +
+                "len(feed_list) (%s)") % (len(each_sample), len(converter))
             for each_converter, each_slot in six.zip(converter, each_sample):
                 each_converter.feed(each_slot)
         ret_dict = {}