merge develop

test=develop

paddle/fluid/framework/CMakeLists.txt

@@ -131,11 +131,13 @@ cc_test(version_test SRCS version_test.cc DEPS version)
 
 cc_library(proto_desc SRCS var_desc.cc op_desc.cc block_desc.cc program_desc.cc DEPS shape_inference op_info operator glog version)
 
-if(NOT WIN32)
-cc_library(ngraph_bridge SRCS ngraph_bridge.cc DEPS operator framework_proto ngraph)
-cc_library(ngraph_operator SRCS ngraph_operator.cc DEPS ngraph_bridge operator op_info device_context tensor scope glog
-  shape_inference data_transform lod_tensor profiler)
-endif(NOT WIN32)
+if(WITH_NGRAPH)
+  if(NOT WIN32)
+    cc_library(ngraph_bridge SRCS ngraph_bridge.cc DEPS operator framework_proto ngraph)
+    cc_library(ngraph_operator SRCS ngraph_operator.cc DEPS ngraph_bridge operator op_info device_context tensor scope glog
+      shape_inference data_transform lod_tensor profiler ngraph)
+  endif(NOT WIN32)
+endif(WITH_NGRAPH)
 
 cc_library(op_registry SRCS op_registry.cc DEPS op_proto_maker op_info operator glog proto_desc)
 nv_test(op_registry_test SRCS op_registry_test.cc DEPS op_registry)
@@ -171,14 +173,20 @@ if(WITH_DISTRIBUTE)
   set(DISTRIBUTE_COMPILE_FLAGS "-Wno-non-virtual-dtor -Wno-error=non-virtual-dtor -Wno-error=delete-non-virtual-dtor")
   set_source_files_properties(executor.cc PROPERTIES COMPILE_FLAGS ${DISTRIBUTE_COMPILE_FLAGS})
 else()
-  if(NOT WIN32)
-    cc_library(executor SRCS executor.cc DEPS op_registry device_context scope framework_proto glog lod_rank_table feed_fetch_method graph_to_program_pass ngraph_operator variable_helper garbage_collector)
-  else(NOT WIN32)
-    cc_library(executor SRCS executor.cc DEPS op_registry device_context scope framework_proto glog lod_rank_table feed_fetch_method graph_to_program_pass variable_helper garbage_collector)
-  endif(NOT WIN32)
+  if(WITH_NGRAPH)
+    if(NOT WIN32)
+      cc_library(executor SRCS executor.cc DEPS op_registry device_context scope framework_proto glog lod_rank_table feed_fetch_method graph_to_program_pass ngraph ngraph_operator variable_helper)
+    else(NOT WIN32)
+      cc_library(executor SRCS executor.cc DEPS op_registry device_context scope framework_proto glog lod_rank_table feed_fetch_method graph_to_program_pass variable_helper)
+    endif(NOT WIN32)
+  else(WITH_NGRAPH)
+    cc_library(executor SRCS executor.cc DEPS op_registry device_context scope framework_proto glog lod_rank_table feed_fetch_method graph_to_program_pass variable_helper)
+  endif(WITH_NGRAPH)
   cc_test(test_naive_executor SRCS naive_executor_test.cc DEPS naive_executor elementwise_add_op)
 endif()
 
+target_link_libraries(executor garbage_collector)
+
 cc_library(parallel_executor SRCS parallel_executor.cc DEPS
         threaded_ssa_graph_executor scope_buffered_ssa_graph_executor
         graph build_strategy

paddle/fluid/framework/executor.cc

@@ -18,7 +18,6 @@ limitations under the License. */
 #include "paddle/fluid/framework/feed_fetch_method.h"
 #include "paddle/fluid/framework/lod_rank_table.h"
 #include "paddle/fluid/framework/lod_tensor_array.h"
-#include "paddle/fluid/framework/ngraph_operator.h"
 #include "paddle/fluid/framework/op_registry.h"
 #include "paddle/fluid/framework/reader.h"
 #include "paddle/fluid/framework/transfer_scope_cache.h"
@@ -27,6 +26,10 @@ limitations under the License. */
 #include "paddle/fluid/platform/place.h"
 #include "paddle/fluid/platform/profiler.h"
 
+#ifdef PADDLE_WITH_NGRAPH
+#include "paddle/fluid/framework/ngraph_operator.h"
+#endif
+
 DECLARE_bool(benchmark);
 DEFINE_bool(use_mkldnn, false, "Use MKLDNN to run");
 DEFINE_bool(use_ngraph, false, "Use NGRAPH to run");
@@ -131,11 +134,11 @@ static void DeleteUnusedTensors(
 static void EnableFusedOp(ExecutorPrepareContext* ctx) {
 #ifdef PADDLE_WITH_NGRAPH
   VLOG(3) << "use_ngraph=True";
-  auto intervals = FusedOperator::FusedOpIntervals(&ctx->ops_);
+  auto intervals = NgraphOperator::NgraphOpIntervals(&ctx->ops_);
   for (auto& interval : intervals) {
-    auto* fused_op = new FusedOperator(ctx->prog_, ctx->block_id_,
-                                       interval.at(0), interval.at(1));
-    *interval[0] = std::unique_ptr<OperatorBase>(fused_op);
+    auto* ng_op = new NgraphOperator(ctx->prog_, ctx->block_id_, interval.at(0),
+                                     interval.at(1));
+    *interval[0] = std::unique_ptr<OperatorBase>(ng_op);
   }
   for (auto it = intervals.rbegin(); it != intervals.rend(); ++it) {
     ctx->ops_.erase(it->at(0) + 1, it->at(1));

paddle/fluid/framework/ngraph_bridge.cc

@@ -12,7 +12,6 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 See the License for the specific language governing permissions and
 limitations under the License. */
 
-#ifdef PADDLE_WITH_NGRAPH
 #include <algorithm>
 #include <functional>
 #include <vector>
@@ -27,14 +26,15 @@ namespace paddle {
 namespace framework {
 
 static std::shared_ptr<ngraph::Node> GetNode(
-    const std::shared_ptr<OperatorBase>& op, const std::string prm,
+    const std::shared_ptr<OperatorBase>& op, const std::string name,
     const VariableNameMap& var_map,
     std::shared_ptr<
         std::unordered_map<std::string, std::shared_ptr<ngraph::Node>>>
         ngb_node_map) {
-  auto& var_names = var_map.at(prm);
+  auto& var_names = var_map.at(name);
   PADDLE_ENFORCE_EQ(var_names.size(), 1,
-                    "op %s prm %s expects one associated var", op->Type(), prm);
+                    "op %s name %s expects one associated var", op->Type(),
+                    name);
   if (ngb_node_map->find(var_names[0]) != ngb_node_map->end()) {
     return (*ngb_node_map)[var_names[0]];
   } else {
@@ -43,42 +43,42 @@ static std::shared_ptr<ngraph::Node> GetNode(
 }
 
 static std::shared_ptr<ngraph::Node> GetInputNode(
-    const std::shared_ptr<OperatorBase>& op, const std::string prm,
+    const std::shared_ptr<OperatorBase>& op, const std::string name,
     std::shared_ptr<
         std::unordered_map<std::string, std::shared_ptr<ngraph::Node>>>
         ngb_node_map) {
-  return GetNode(op, prm, op->Inputs(), ngb_node_map);
+  return GetNode(op, name, op->Inputs(), ngb_node_map);
 }
 
 static std::shared_ptr<ngraph::Node> GetOutputNode(
-    const std::shared_ptr<OperatorBase>& op, const std::string prm,
+    const std::shared_ptr<OperatorBase>& op, const std::string name,
     std::shared_ptr<
         std::unordered_map<std::string, std::shared_ptr<ngraph::Node>>>
         ngb_node_map) {
-  return GetNode(op, prm, op->Outputs(), ngb_node_map);
+  return GetNode(op, name, op->Outputs(), ngb_node_map);
 }
 
 static void SetOutputNode(
-    const std::shared_ptr<OperatorBase>& op, const std::string prm,
+    const std::shared_ptr<OperatorBase>& op, const std::string name,
     std::shared_ptr<ngraph::Node> node,
     std::shared_ptr<
         std::unordered_map<std::string, std::shared_ptr<ngraph::Node>>>
         ngb_node_map) {
-  auto& var_names = op->Outputs().at(prm);
+  auto& var_names = op->Outputs().at(name);
   if (var_names.size() == 1) {
     (*ngb_node_map)[var_names[0]] = node;
   } else if (var_names.size() == 0) {
     (*ngb_node_map)[""] = node;
   } else {
-    PADDLE_THROW("prm %s has more than 1 var_names.", prm);
+    PADDLE_THROW("name %s has more than 1 var_names.", name);
   }
 }
 
 static bool HasOutput(const std::shared_ptr<OperatorBase>& op,
-                      const std::string prm) {
+                      const std::string name) {
   auto& outputs = op->Outputs();
-  if (outputs.find(prm) == outputs.end()) return false;
-  return outputs.at(prm).size() > 0;
+  if (outputs.find(name) == outputs.end()) return false;
+  return outputs.at(name).size() > 0;
 }
 
 template <typename T>
@@ -118,4 +118,3 @@ void NgraphBridge::BuildNgNode(const std::shared_ptr<OperatorBase>& op) {
 
 }  // namespace framework
 }  // namespace paddle
-#endif

paddle/fluid/framework/ngraph_bridge.h

@@ -14,8 +14,6 @@ limitations under the License. */
 
 #pragma once
 
-#ifdef PADDLE_WITH_NGRAPH
-
 #include <algorithm>
 #include <map>
 #include <string>
@@ -53,4 +51,3 @@ class NgraphBridge {
 
 }  // namespace framework
 }  // namespace paddle
-#endif

paddle/fluid/framework/ngraph_operator.cc

@@ -12,7 +12,6 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 See the License for the specific language governing permissions and
 limitations under the License. */
 
-#ifdef PADDLE_WITH_NGRAPH
 #include <glog/logging.h>
 
 #include <algorithm>
@@ -58,16 +57,16 @@ typedef enum {                /* nGraph support state on ops          */
 } op_state;
 
 // perform graph build through bridge and execute computation
-class NgraphOperator {
+class NgraphEngine {
  public:
-  explicit NgraphOperator(const Scope& scope, const platform::Place& place,
-                          const std::vector<std::shared_ptr<OperatorBase>>& ops,
-                          const std::unordered_map<
-                              std::string, ngraph::element::Type>& var_type_map,
-                          const std::unordered_set<std::string>& persist,
-                          const std::unordered_set<std::string>& fetches,
-                          const std::unordered_set<std::string>& post_op_inputs,
-                          op_state ng_op_state)
+  explicit NgraphEngine(const Scope& scope, const platform::Place& place,
+                        const std::vector<std::shared_ptr<OperatorBase>>& ops,
+                        const std::unordered_map<
+                            std::string, ngraph::element::Type>& var_type_map,
+                        const std::unordered_set<std::string>& persist,
+                        const std::unordered_set<std::string>& fetches,
+                        const std::unordered_set<std::string>& post_op_inputs,
+                        op_state ng_op_state)
       : scope_(scope),
         place_(place),
         fused_ops_(ops),
@@ -132,7 +131,7 @@ class NgraphOperator {
 };
 
 std::vector<std::vector<std::vector<std::unique_ptr<OperatorBase>>::iterator>>
-FusedOperator::FusedOpIntervals(
+NgraphOperator::NgraphOpIntervals(
     std::vector<std::unique_ptr<paddle::framework::OperatorBase>>* ops) {
   std::vector<std::vector<std::vector<std::unique_ptr<OperatorBase>>::iterator>>
       intervals;
@@ -185,7 +184,7 @@ FusedOperator::FusedOpIntervals(
   return intervals;
 }
 
-FusedOperator::FusedOperator(
+NgraphOperator::NgraphOperator(
     const ProgramDesc& prog, size_t block_id,
     std::vector<std::unique_ptr<OperatorBase>>::iterator start,
     std::vector<std::unique_ptr<OperatorBase>>::iterator end,
@@ -215,7 +214,7 @@ FusedOperator::FusedOperator(
   Process();
 }
 
-void FusedOperator::Process() {
+void NgraphOperator::Process() {
   auto& bdesc = pdesc_.Block(block_);
   for (auto& var : bdesc.AllVars()) {
     if (!(var->GetType() == proto::VarType::SELECTED_ROWS ||
@@ -251,8 +250,8 @@ void FusedOperator::Process() {
   }
 }
 
-void FusedOperator::RunImpl(const Scope& scope,
-                            const platform::Place& place) const {
+void NgraphOperator::RunImpl(const Scope& scope,
+                             const platform::Place& place) const {
   op_state ng_op_state = PARTIAL_TEST;
   auto& bdesc = pdesc_.Block(block_);
   for (auto* op : bdesc.AllOps()) {
@@ -266,19 +265,19 @@ void FusedOperator::RunImpl(const Scope& scope,
     ng_op_state = ng_op_state == PARTIAL_TEST ? FULL_TEST : FULL_TRAIN;
   }
 
-  NgraphOperator ngraph_op(scope, place, fused_ops_, var_type_map_,
-                           persistables_, fetches_, post_op_inputs_,
-                           ng_op_state);
-  ngraph_op.Run(scope, place);
+  NgraphEngine ngraph_engine(scope, place, fused_ops_, var_type_map_,
+                             persistables_, fetches_, post_op_inputs_,
+                             ng_op_state);
+  ngraph_engine.Run(scope, place);
 }
 
 std::unordered_map<std::string, std::shared_ptr<ngraph::Function>>
-    NgraphOperator::func_cache_ = {};
+    NgraphEngine::func_cache_ = {};
 
-std::shared_ptr<ngraph::runtime::Backend> NgraphOperator::backend_ =
+std::shared_ptr<ngraph::runtime::Backend> NgraphEngine::backend_ =
     ngraph::runtime::Backend::create("CPU");
 
-void NgraphOperator::GetNgInputShape(std::shared_ptr<OperatorBase> op) {
+void NgraphEngine::GetNgInputShape(std::shared_ptr<OperatorBase> op) {
   op->RuntimeInferShape(scope_, place_);
   for (auto& var_name_item : op->Inputs()) {
     for (auto& var_name : var_name_item.second) {
@@ -301,7 +300,7 @@ void NgraphOperator::GetNgInputShape(std::shared_ptr<OperatorBase> op) {
   }
 }
 
-void NgraphOperator::BuildNgNodes() {
+void NgraphEngine::BuildNgNodes() {
   for (auto& var_name : var_out_) {
     if (var_node_map_->find(var_name) == var_node_map_->end()) {
       auto* var = scope_.FindVar(var_name);
@@ -323,7 +322,7 @@ void NgraphOperator::BuildNgNodes() {
   }
 }
 
-void NgraphOperator::BuildNgIO() {
+void NgraphEngine::BuildNgIO() {
   std::unordered_set<std::string> inputs;
   std::unordered_set<std::string> outputs;
 
@@ -395,7 +394,7 @@ void NgraphOperator::BuildNgIO() {
   }
 }
 
-void NgraphOperator::BuildNgFunction() {
+void NgraphEngine::BuildNgFunction() {
   BuildNgNodes();
   ngraph_function_ = nullptr;
   ngraph::NodeVector func_outputs;
@@ -416,7 +415,7 @@ void NgraphOperator::BuildNgFunction() {
       std::make_shared<ngraph::Function>(func_outputs, func_inputs);
 }
 
-std::shared_ptr<std::string> NgraphOperator::GetCacheKey() {
+std::shared_ptr<std::string> NgraphEngine::GetCacheKey() {
   auto cache_key = std::make_shared<std::string>("");
   *cache_key += std::to_string(fused_ops_.size());
   for (auto& op : fused_ops_) {
@@ -444,7 +443,7 @@ std::shared_ptr<std::string> NgraphOperator::GetCacheKey() {
   return cache_key;
 }
 
-void NgraphOperator::GetNgFunction() {
+void NgraphEngine::GetNgFunction() {
   bool cache_on = true;
   if (cache_on) {
     std::string cache_key_val = *GetCacheKey();
@@ -459,8 +458,7 @@ void NgraphOperator::GetNgFunction() {
   }
 }
 
-void NgraphOperator::Run(const Scope& scope,
-                         const platform::Place& place) const {
+void NgraphEngine::Run(const Scope& scope, const platform::Place& place) const {
   std::vector<std::shared_ptr<ngraph::runtime::Tensor>> t_in;
   std::vector<std::shared_ptr<ngraph::runtime::Tensor>> t_out;
 
@@ -545,7 +543,6 @@ void NgraphOperator::Run(const Scope& scope,
   }
 
   backend_->call(ngraph_function_, t_out, t_in);
-}  // NgraphOperator::RunImpl
+}  // NgraphEngine::RunImpl
 }  // namespace framework
 }  // namespace paddle
-#endif

paddle/fluid/framework/ngraph_operator.h

@@ -14,8 +14,6 @@ limitations under the License. */
 
 #pragma once
 
-#ifdef PADDLE_WITH_NGRAPH
-
 #include <algorithm>
 #include <string>
 #include <unordered_map>
@@ -34,14 +32,14 @@ limitations under the License. */
 namespace paddle {
 namespace framework {
 
-class FusedOperator : public OperatorBase {
+class NgraphOperator : public OperatorBase {
  public:
   static std::vector<
       std::vector<std::vector<std::unique_ptr<OperatorBase>>::iterator>>
-  FusedOpIntervals(
+  NgraphOpIntervals(
       std::vector<std::unique_ptr<paddle::framework::OperatorBase>>* ops);
 
-  explicit FusedOperator(
+  explicit NgraphOperator(
       const ProgramDesc& prog, size_t block_id,
       std::vector<std::unique_ptr<OperatorBase>>::iterator start,
       std::vector<std::unique_ptr<OperatorBase>>::iterator end,
@@ -64,4 +62,3 @@ class FusedOperator : public OperatorBase {
 };
 }  // namespace framework
 }  // namespace paddle
-#endif

paddle/fluid/inference/analysis/passes/ir_graph_build_pass.cc

@@ -44,9 +44,10 @@ void IrGraphBuildPass::RunImpl(Argument *argument) {
     argument->SetMainProgram(program.release());
   } else if (argument->model_program_path_valid() &&
              argument->model_params_path_valid()) {
-    auto program =
-        LoadModel(argument->model_program_path(), argument->model_params_path(),
-                  argument->scope_ptr(), place, argument->model_from_memory());
+    auto program = LoadModel(
+        argument->model_program_path(), argument->model_params_path(),
+        argument->scope_ptr(), place,
+        argument->model_from_memory_valid() && argument->model_from_memory());
     argument->SetMainProgram(program.release());
   } else {
     PADDLE_THROW(

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

-set(INFERENCE_EXTRA_DEPS paddle_inference_api paddle_fluid_api ir_pass_manager analysis_predictor)
+set(INFERENCE_EXTRA_DEPS paddle_inference_api paddle_fluid_api ir_pass_manager analysis_predictor benchmark)
 
 if(WITH_GPU AND TENSORRT_FOUND)
     set(INFERENCE_EXTRA_DEPS ${INFERENCE_EXTRA_DEPS} analysis ${analysis_deps} ir_pass_manager analysis_predictor)

paddle/fluid/inference/tests/api/tester_helper.h

@@ -30,8 +30,10 @@
 #include "paddle/fluid/inference/api/helper.h"
 #include "paddle/fluid/inference/tests/api/config_printer.h"
 #include "paddle/fluid/inference/tests/test_helper.h"
+#include "paddle/fluid/inference/utils/benchmark.h"
 #include "paddle/fluid/platform/profiler.h"
 
+DEFINE_string(model_name, "", "model name");
 DEFINE_string(infer_model, "", "model path");
 DEFINE_string(infer_data, "", "data file");
 DEFINE_int32(batch_size, 1, "batch size.");
@@ -40,6 +42,8 @@ DEFINE_bool(test_all_data, false, "Test the all dataset in data file.");
 DEFINE_int32(num_threads, 1, "Running the inference program in multi-threads.");
 DEFINE_bool(use_analysis, true,
             "Running the inference program in analysis mode.");
+DEFINE_bool(record_benchmark, false,
+            "Record benchmark after profiling the model");
 
 DECLARE_bool(profile);
 DECLARE_int32(paddle_num_threads);
@@ -192,8 +196,16 @@ void TestOneThreadPrediction(
         predictor->Run(inputs[j], outputs, batch_size);
       }
     }
-    PrintTime(batch_size, num_times, 1, 0, run_timer.toc() / num_times,
-              inputs.size());
+
+    double latency = run_timer.toc() / num_times;
+    PrintTime(batch_size, num_times, 1, 0, latency, inputs.size());
+    if (FLAGS_record_benchmark) {
+      Benchmark benchmark;
+      benchmark.SetName(FLAGS_model_name);
+      benchmark.SetBatchSize(batch_size);
+      benchmark.SetLatency(latency);
+      benchmark.PersistToFile("benchmark_record.txt");
+    }
   }
 }
 

paddle/fluid/inference/tests/api/trt_models_tester.cc

@@ -135,6 +135,9 @@ TEST(TensorRT_resnext50, compare) {
 
 TEST(TensorRT_resnext50, profile) {
   std::string model_dir = FLAGS_infer_model + "/resnext50";
+  // Set FLAGS_record_benchmark to true to record benchmark to file.
+  // FLAGS_record_benchmark=true;
+  FLAGS_model_name = "resnext50";
   profile(model_dir, /* use_analysis */ true, FLAGS_use_tensorrt);
 }
 

paddle/fluid/inference/utils/benchmark.cc

@@ -30,7 +30,7 @@ std::string Benchmark::SerializeToString() const {
   ss << '\n';
 
   ss << name_ << "\t";
-  ss << batch_size_ << "\t";
+  ss << batch_size_ << "\t\t";
   ss << num_threads_ << "\t";
   ss << latency_ << "\t";
   ss << 1000.0 / latency_;

paddle/fluid/inference/utils/visualizer.cc

@@ -26,9 +26,6 @@ DEFINE_string(model_dir, "", "model directory");
 DEFINE_string(model_program_path, "", "model program path");
 DEFINE_string(model_params_path, "", "model params path");
 
-USE_PASS(graph_viz_pass);
-USE_PASS(graph_to_program_pass);
-
 using paddle::inference::analysis::Argument;
 
 namespace paddle {
@@ -40,7 +37,6 @@ void Visualizer::SetArgument(Argument *argument) { argument_ = argument; }
 bool Visualizer::Run() {
   paddle::framework::InitDevices(false);
   paddle::inference::analysis::Analyzer().Run(argument_);
-
   return true;
 }
 
@@ -77,7 +73,7 @@ int main(int argc, char *argv[]) {
 
   // Only 1 pass, default filename is 0_ir_origin.dot
   // For more details, looking for paddle::inference::analysis::IRPassManager
-  argument.SetIrAnalysisPasses({"graph_viz_pass"});
+  argument.SetIrAnalysisPasses({"infer_clean_graph_pass", "graph_viz_pass"});
 
   std::unique_ptr<paddle::framework::Scope> scope{
       new paddle::framework::Scope()};
@@ -90,3 +86,7 @@ int main(int argc, char *argv[]) {
 
   return 0;
 }
+
+USE_PASS(infer_clean_graph_pass);
+USE_PASS(graph_viz_pass);
+USE_PASS(graph_to_program_pass);

paddle/fluid/operators/activation_op.h

@@ -301,23 +301,22 @@ template <typename T>
 struct GeluFunctor : public BaseActivationFunctor<T> {
   template <typename Device, typename X, typename Out>
   void operator()(Device d, X x, Out out) const {
-    auto temp =
-        ((x * static_cast<T>(M_SQRT1_2)).erf()).template cast<T>().eval();
+    auto temp = (x * static_cast<T>(M_SQRT1_2)).erf();
     out.device(d) = x * static_cast<T>(0.5) * (static_cast<T>(1) + temp);
   }
 };
 
 template <typename T>
 struct GeluGradFunctor : BaseActivationFunctor<T> {
-  bool Inplace() const { return IsInplace("gelu"); }
   template <typename Device, typename X, typename Out, typename dOut,
             typename dX>
   void operator()(Device d, X x, Out out, dOut dout, dX dx) const {
-    auto temp = (static_cast<T>(0.5 * M_2_SQRTPI * M_SQRT1_2) * x *
-                 ((-static_cast<T>(0.5) * x.square()).exp()))
-                    .template cast<T>()
-                    .eval();
-    dx.device(d) = dout * (out / x + temp);
+    auto first = static_cast<T>(0.5) *
+                 (static_cast<T>(1) + ((x * static_cast<T>(M_SQRT1_2)).erf()));
+
+    auto second = static_cast<T>(0.5 * M_2_SQRTPI * M_SQRT1_2) * x *
+                  (-static_cast<T>(0.5) * x.square()).exp();
+    dx.device(d) = dout * (first + second);
   }
 };
 

paddle/fluid/operators/distributed/brpc_client.cc

@@ -158,7 +158,7 @@ ChannelQueuePtr BRPCClient::GetChannel(const std::string& ep) {
   for (int i = 0; i < FLAGS_brpc_channel_num; ++i) {
     std::shared_ptr<ChannelContext> c(new ChannelContext());
     if (c->channel.Init(ep.c_str(), &options) != 0) {
-      LOG(ERROR) << "Fail to initialize channel";
+      LOG(FATAL) << "Fail to initialize channel";
       return nullptr;
     }
 

paddle/fluid/operators/distributed/grpc_client.cc

@@ -390,8 +390,7 @@ void GRPCClient::Proceed() {
       VLOG(3) << c->GetVarHandlePtr()->String() << " process";
       c->Process();
     } else if (c->status_.error_code() == grpc::StatusCode::DEADLINE_EXCEEDED) {
-      // FIXME(gongwb): parse error_details?
-      LOG(ERROR) << c->GetVarHandlePtr()->String()
+      LOG(FATAL) << c->GetVarHandlePtr()->String()
                  << " meets grpc error, error_code:" << c->status_.error_code()
                  << " error_message:" << c->status_.error_message()
                  << " error_details:" << c->status_.error_details();