fix multi-thread exec of trt, test=develop (#19379)

Author: Shixiaowei02

paddle/fluid/inference/tensorrt/engine.cc

@@ -35,8 +35,15 @@ void TensorRTEngine::Build(const DescType &paddle_model) {
 void TensorRTEngine::Execute(int batch_size, std::vector<void *> *buffers,
                              cudaStream_t stream) {
   freshDeviceId();
+  const std::thread::id tid = std::this_thread::get_id();
   batch_size_ = batch_size;
-  infer_context_->enqueue(batch_size, buffers->data(), stream, nullptr);
+  if (infer_context_.find(tid) == infer_context_.end()) {
+    PADDLE_ENFORCE_NOT_NULL(
+        infer_engine_,
+        "You should build engine first and then set the context.");
+    infer_context_[tid].reset(infer_engine_->createExecutionContext());
+  }
+  infer_context_[tid]->enqueue(batch_size, buffers->data(), stream, nullptr);
   cudaStreamSynchronize(stream);
   SetRuntimeBatch(batch_size);
 }
@@ -111,8 +118,6 @@ void TensorRTEngine::FreezeNetwork() {
 
   infer_engine_.reset(infer_builder_->buildCudaEngine(*infer_network_));
   PADDLE_ENFORCE(infer_engine_ != nullptr, "build cuda engine failed!");
-
-  infer_context_.reset(infer_engine_->createExecutionContext());
 }
 
 nvinfer1::ITensor *TensorRTEngine::DeclareInput(const std::string &name,

paddle/fluid/inference/tensorrt/engine.h

@@ -128,7 +128,6 @@ class TensorRTEngine {
         &inference::Singleton<plugin::PluginFactoryTensorRT>::Global()));
     PADDLE_ENFORCE(infer_engine_ != nullptr,
                    "build cuda engine failed when deserialize engine info.!");
-    infer_context_.reset(infer_engine_->createExecutionContext());
   }
 
   void SetRuntimeBatch(size_t batch_size);
@@ -200,7 +199,8 @@ class TensorRTEngine {
   infer_ptr<nvinfer1::IBuilder> infer_builder_;
   infer_ptr<nvinfer1::INetworkDefinition> infer_network_;
   infer_ptr<nvinfer1::ICudaEngine> infer_engine_;
-  infer_ptr<nvinfer1::IExecutionContext> infer_context_;
+  std::unordered_map<std::thread::id, infer_ptr<nvinfer1::IExecutionContext>>
+      infer_context_;
   infer_ptr<nvinfer1::IHostMemory> ihost_memory_;
   std::unordered_map<nvinfer1::ITensor*, float> quant_dynamic_range_;
 };  // class TensorRTEngine