Change *(smart_ptr.get()) -> *smart_ptr

reason: dereferencing smart pointer is the same as the underlying pointer
test=develop

paddle/fluid/operators/beam_search_decode_op.h

@@ -122,7 +122,7 @@ void BeamSearchDecoder<T>::ConvertSentenceVectorToLodTensor(
 
   auto cpu_place = std::unique_ptr<paddle::platform::CPUPlace>(
       new paddle::platform::CPUPlace());
-  paddle::platform::CPUDeviceContext cpu_ctx(*cpu_place.get());
+  paddle::platform::CPUDeviceContext cpu_ctx(*cpu_place);
 
   framework::LoD lod;
   lod.push_back(source_level_lod);

paddle/fluid/operators/mkldnn/activation_mkldnn_op.cc

@@ -225,7 +225,7 @@ void eltwise_grad(const framework::ExecutionContext &ctx,
       std::static_pointer_cast<mkldnn::memory>(dev_ctx.GetBlob(key_src_mem));
   PADDLE_ENFORCE(src_memory != nullptr,
                  "Fail to find src_memory in device context");
-  src_memory->set_data_handle(*p_src_data.get());
+  src_memory->set_data_handle(*p_src_data);
 
   std::shared_ptr<memory> diff_src_memory;
 

paddle/fluid/operators/mkldnn/pool_mkldnn_op.cc

@@ -198,7 +198,7 @@ class PoolMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
     }
 
     // push primitive to stream and wait until it's executed
-    std::vector<mkldnn::primitive> pipeline{*(pool_p.get())};
+    std::vector<mkldnn::primitive> pipeline{*pool_p};
     stream(stream::kind::eager).submit(pipeline).wait();
 
     output->set_layout(DataLayout::kMKLDNN);
@@ -367,8 +367,7 @@ class PoolMKLDNNGradOpKernel : public paddle::framework::OpKernel<T> {
       dev_ctx.SetBlob(key_pool_diff_dst_mem_p, diff_dst_memory);
 
       pool_bwd_p = std::make_shared<pooling_backward>(
-          pool_bwd_pd, *(diff_dst_memory.get()), *workspace_memory,
-          *(diff_src_memory));
+          pool_bwd_pd, *diff_dst_memory, *workspace_memory, *diff_src_memory);
       dev_ctx.SetBlob(key_pool_bwd_p, pool_bwd_p);
 
     } else {
@@ -404,7 +403,7 @@ class PoolMKLDNNGradOpKernel : public paddle::framework::OpKernel<T> {
     if (is_diff_dst_reordered) {
       pipeline.push_back(reorder_diff_dst);
     }
-    pipeline.push_back(*(pool_bwd_p.get()));
+    pipeline.push_back(*pool_bwd_p);
     mkldnn::stream(mkldnn::stream::kind::eager).submit(pipeline).wait();
 
     in_x_grad->set_layout(DataLayout::kMKLDNN);

paddle/fluid/operators/mkldnn/softmax_mkldnn_op.cc

@@ -66,8 +66,7 @@ class SoftmaxMKLDNNHandler : public platform::MKLDNNHandler {
                    "Fail to find softmax primitive in device context");
     if (softmax_p == nullptr) {
       softmax_p = std::make_shared<mkldnn::softmax_forward>(
-          *(softmax_pd_.get()),
-          *(static_cast<mkldnn::memory*>(src_memory_p.get())),
+          *softmax_pd_, *(static_cast<mkldnn::memory*>(src_memory_p.get())),
           *(static_cast<mkldnn::memory*>(dst_memory_p.get())));
       dev_ctx_.SetBlob(prim_key, softmax_p);
     } else {
@@ -88,8 +87,8 @@ class SoftmaxMKLDNNHandler : public platform::MKLDNNHandler {
                    "Fail to find softmax backward primitive in device context");
     if (softmax_bwd_p == nullptr) {
       softmax_bwd_p = std::make_shared<mkldnn::softmax_backward>(
-          *softmax_bwd_pd_, *(dst_memory_p.get()), *(diff_dst_memory_p.get()),
-          *(diff_src_memory_p.get()));
+          *softmax_bwd_pd_, *dst_memory_p, *diff_dst_memory_p,
+          *diff_src_memory_p);
       dev_ctx_.SetBlob(prim_key, softmax_bwd_p);
     } else {
       is_reusing_ = true;

paddle/fluid/operators/mkldnn/sum_mkldnn_op.cc

@@ -160,7 +160,7 @@ class SumMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
 
       auto get_selected_row = [&](size_t i) -> const SelectedRows& {
         if (i == 0 && in0) {
-          return *in0.get();
+          return *in0;
         } else {
           return in_vars[i]->Get<SelectedRows>();
         }

paddle/fluid/platform/device_context.cc

@@ -394,7 +394,7 @@ void MKLDNNDeviceContext::SetBlob(const std::string& name,
 
   int tid = platform::get_cur_thread_id();
 
-  std::lock_guard<std::mutex> lock(*p_mutex_.get());
+  std::lock_guard<std::mutex> lock(*p_mutex_);
 
   // Find KeyBlob for current thread
   auto map_it = pMap->find(tid);
@@ -427,7 +427,7 @@ std::shared_ptr<void> MKLDNNDeviceContext::GetBlob(
 
   int tid = platform::get_cur_thread_id();
 
-  std::lock_guard<std::mutex> lock(*p_mutex_.get());
+  std::lock_guard<std::mutex> lock(*p_mutex_);
 
   // Find KeyBlob for current thread firstly
   auto map_it = pMap->find(tid);

paddle/fluid/platform/mkldnn_reuse.h

@@ -548,9 +548,8 @@ class ConvMKLDNNTemplateHandler : public MKLDNNHandler {
     PADDLE_ENFORCE((conv_p != nullptr) || (is_reusing_ == false),
                    "Fail to find convolution primitive in device context");
     if (conv_p == nullptr) {
-      conv_p = std::make_shared<forward_t>(*conv_pd_, *(src_memory_p),
-                                           *(weights_memory_p.get()),
-                                           *(dst_memory_p.get()));
+      conv_p = std::make_shared<forward_t>(*conv_pd_, *src_memory_p,
+                                           *weights_memory_p, *dst_memory_p);
 
       dev_ctx_.SetBlob(prim_key, conv_p);
     } else {
@@ -570,9 +569,9 @@ class ConvMKLDNNTemplateHandler : public MKLDNNHandler {
     PADDLE_ENFORCE((conv_p != nullptr) || (is_reusing_ == false),
                    "Fail to find convolution primitive in device context");
     if (conv_p == nullptr) {
-      conv_p = std::make_shared<forward_t>(
-          *conv_pd_, *(src_memory_p), *(weights_memory_p.get()),
-          *(bias_memory_p.get()), *(dst_memory_p.get()));
+      conv_p = std::make_shared<forward_t>(*conv_pd_, *src_memory_p,
+                                           *weights_memory_p, *bias_memory_p,
+                                           *dst_memory_p);
 
       dev_ctx_.SetBlob(prim_key, conv_p);
     } else {

paddle/fluid/train/demo/demo_trainer.cc

@@ -73,7 +73,7 @@ int main() {
   PADDLE_ENFORCE_NE(loss_name, "", "loss not found");
 
   // init all parameters
-  executor.Run(*startup_program.get(), &scope, 0);
+  executor.Run(*startup_program, &scope, 0);
 
   // prepare data
   auto x_var = scope.Var("x");
@@ -101,7 +101,7 @@ int main() {
   clock_t t1 = clock();
 
   for (int i = 0; i < 10; ++i) {
-    executor.Run(*train_program.get(), &scope, 0, false, true);
+    executor.Run(*train_program, &scope, 0, false, true);
     std::cout << "step: " << i << " loss: "
               << loss_var->Get<paddle::framework::LoDTensor>().data<float>()[0]
               << std::endl;

paddle/fluid/train/test_train_recognize_digits.cc

@@ -74,7 +74,7 @@ void Train() {
   float first_loss = 0.0;
   float last_loss = 0.0;
   for (int i = 0; i < 100; ++i) {
-    executor.Run(*train_program.get(), &scope, 0, false, true);
+    executor.Run(*train_program, &scope, 0, false, true);
     if (i == 0) {
       first_loss = loss_var->Get<framework::LoDTensor>().data<float>()[0];
     } else if (i == 99) {