Merge pull request #15531 from jczaja/prv-googlenet-fix

Performance and functional fixes to LRN

Author: luotao1

paddle/fluid/inference/tests/api/CMakeLists.txt

@@ -54,6 +54,7 @@ else()
     message(WARNING "These tests has been disabled in OSX or WITH_MKL=OFF before being fixed: \n test_analyzer_seq_pool1")
 endif()
 
+
 # RNN2
 set(RNN2_INSTALL_DIR "${INFERENCE_DEMO_INSTALL_DIR}/rnn2")
 download_model_and_data(${RNN2_INSTALL_DIR} "rnn2_model.tar.gz" "rnn2_data.txt.tar.gz")
@@ -115,6 +116,10 @@ if (NOT EXISTS ${MOBILENET_INSTALL_DIR})
 endif()
 inference_analysis_api_test_with_refer_result(test_analyzer_mobilenet_transpose ${MOBILENET_INSTALL_DIR} analyzer_vis_tester.cc SERIAL)
 
+# googlenet
+inference_analysis_api_test_with_fake_data(test_analyzer_googlenet
+  "${INFERENCE_DEMO_INSTALL_DIR}/googlenet" analyzer_resnet50_tester.cc "googlenet.tar.gz" SERIAL)
+
 # resnet50
 inference_analysis_api_test_with_fake_data(test_analyzer_resnet50
   "${INFERENCE_DEMO_INSTALL_DIR}/resnet50" analyzer_resnet50_tester.cc "resnet50_model.tar.gz" SERIAL)

paddle/fluid/operators/lrn_mkldnn_op.cc

@@ -67,7 +67,13 @@ class LRNMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
     mid->mutable_data<T>(ctx.GetPlace());
 
     const int n = ctx.Attr<int>("n");
-    const float alpha = ctx.Attr<float>("alpha");
+    // MKL-DNN implements LRN in a caffe way:
+    // http://caffe.berkeleyvision.org/tutorial/layers/lrn.html
+    // Where sum of squares is divided by size of normalization window
+    // this is not the case for PaddlePaddle LRN.
+    // Hence we need to compensate for this diffrence by
+    // multipliing alpha by size of window(n)
+    const float alpha = ctx.Attr<float>("alpha") * static_cast<float>(n);
     const float beta = ctx.Attr<float>("beta");
     const float k = ctx.Attr<float>("k");
     const bool is_test = ctx.Attr<bool>("is_test");
@@ -78,10 +84,7 @@ class LRNMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
     auto dims = paddle::framework::vectorize2int(x->dims());
 
     auto src_md = paddle::platform::MKLDNNMemDesc(
-        dims, mkldnn::memory::data_type::f32, mkldnn::memory::format::nchw);
-
-    auto dst_md = paddle::platform::MKLDNNMemDesc(
-        dims, mkldnn::memory::data_type::f32, mkldnn::memory::format::nchw);
+        dims, mkldnn::memory::data_type::f32, x->format());
 
     auto forward_desc = mkldnn::lrn_forward::desc{mkldnn::prop_kind::forward,
                                                   mkldnn::lrn_across_channels,
@@ -92,8 +95,6 @@ class LRNMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
                                                   k};
 
     auto src_memory_pd = mkldnn::memory::primitive_desc{src_md, mkldnn_engine};
-    auto dst_memory = mkldnn::memory{{dst_md, mkldnn_engine},
-                                     static_cast<void*>(output_data)};
 
     if (!is_test) {
       const std::string key = ctx.op().Output("Out");
@@ -110,20 +111,30 @@ class LRNMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
       src_memory->set_data_handle(
           static_cast<void*>(const_cast<T*>(input_data)));
 
+      auto dst_memory = mkldnn::memory(forward_pd->dst_primitive_desc(),
+                                       static_cast<void*>(output_data));
       auto workspace_memory = insert_to_context<mkldnn::memory>(
           key_workspace_memory, dev_ctx,
           forward_pd->workspace_primitive_desc());
 
       run_primitive(*forward_pd, *src_memory, *workspace_memory, dst_memory);
+
+      out->set_layout(framework::DataLayout::kMKLDNN);
+      out->set_format(platform::GetMKLDNNFormat(dst_memory));
     } else {
       auto forward_pd =
           mkldnn::lrn_forward::primitive_desc{forward_desc, mkldnn_engine};
       auto src_memory = mkldnn::memory{
           src_memory_pd, static_cast<void*>(const_cast<T*>(input_data))};
       auto workspace_memory =
           mkldnn::memory{forward_pd.workspace_primitive_desc()};
+      auto dst_memory = mkldnn::memory(forward_pd.dst_primitive_desc(),
+                                       static_cast<void*>(output_data));
 
       run_primitive(forward_pd, src_memory, workspace_memory, dst_memory);
+
+      out->set_layout(framework::DataLayout::kMKLDNN);
+      out->set_format(platform::GetMKLDNNFormat(dst_memory));
     }
   }
 };
@@ -151,7 +162,7 @@ class LRNMKLDNNGradOpKernel : public paddle::framework::OpKernel<T> {
     const std::string key_workspace_memory = key + "@lrn_workspace_memory";
 
     const int n = ctx.Attr<int>("n");
-    const float alpha = ctx.Attr<float>("alpha");
+    const float alpha = ctx.Attr<float>("alpha") * static_cast<float>(n);
     const float beta = ctx.Attr<float>("beta");
     const float k = ctx.Attr<float>("k");