Add the use_nnpack parameter in ExpandConvLayer, so that the convolution...

Add the use_nnpack parameter in ExpandConvLayer, so that the convolution calculation can be switched to the NNPACK function.

paddle/function/nnpack/NNPACKConvOp.cpp

@@ -70,6 +70,9 @@ public:
     if (threadpool_) {
       pthreadpool_destroy(threadpool_);
     }
+    if (workspaceBuffer_) {
+      free(workspaceBuffer_);
+    }
   }
 
   virtual void check(const BufferArgs& inputs,
@@ -160,7 +163,7 @@ public:
         CHECK_EQ(status, nnp_status_success);
       }
 
-      LOG(INFO) << "workspace size is " << needSize;
+      VLOG(3) << "workspace size is " << needSize;
       if (needSize > workspaceSize_) {
         workspaceSize_ = needSize;
         if (workspaceBuffer_) {

paddle/gserver/layers/ExpandConvLayer.cpp

@@ -16,6 +16,10 @@ limitations under the License. */
 #include "paddle/utils/Logging.h"
 #include "paddle/utils/Stat.h"
 
+DEFINE_bool(use_nnpack,
+            false,
+            "Whether to use nnpack for convolution calculation.");
+
 namespace paddle {
 
 /*
@@ -37,26 +41,38 @@ bool ExpandConvLayer::init(const LayerMap &layerMap,
   for (int i = 0; i < config_.inputs_size(); i++) {
     std::vector<size_t> paddings = {(size_t)paddingY_[i], (size_t)padding_[i]};
     std::vector<size_t> strides = {(size_t)strideY_[i], (size_t)stride_[i]};
-    createFunction(forward_,
-                   !isDeconv_ ? "GemmConv" : "GemmConvGradInput",
-                   FuncConfig()
-                       .set("paddings", paddings)
-                       .set("strides", strides)
-                       .set("groups", (size_t)groups_[i]));
-
-    createFunction(backward_,
-                   !isDeconv_ ? "GemmConvGradInput" : "GemmConv",
-                   FuncConfig()
-                       .set("paddings", paddings)
-                       .set("strides", strides)
-                       .set("groups", (size_t)groups_[i]));
-
-    createFunction(backward_,
-                   "GemmConvGradFilter",
-                   FuncConfig()
-                       .set("paddings", paddings)
-                       .set("strides", strides)
-                       .set("groups", (size_t)groups_[i]));
+
+    if (FLAGS_use_nnpack) {
+      CHECK_EQ(isDeconv_, false);
+      createFunction(forward_,
+                     "NNPACKConv",
+                     FuncConfig()
+                         .set("paddings", paddings)
+                         .set("strides", strides)
+                         .set("groups", (size_t)groups_[i])
+                         .set("algo", "auto"));
+    } else {
+      createFunction(forward_,
+                     !isDeconv_ ? "GemmConv" : "GemmConvGradInput",
+                     FuncConfig()
+                         .set("paddings", paddings)
+                         .set("strides", strides)
+                         .set("groups", (size_t)groups_[i]));
+
+      createFunction(backward_,
+                     !isDeconv_ ? "GemmConvGradInput" : "GemmConv",
+                     FuncConfig()
+                         .set("paddings", paddings)
+                         .set("strides", strides)
+                         .set("groups", (size_t)groups_[i]));
+
+      createFunction(backward_,
+                     "GemmConvGradFilter",
+                     FuncConfig()
+                         .set("paddings", paddings)
+                         .set("strides", strides)
+                         .set("groups", (size_t)groups_[i]));
+    }
   }
   return true;
 }