Add back 24.05 response sending path

src/infer_request.cc

@@ -484,7 +484,7 @@ InferRequest::Exec(const bool is_decoupled)
     {
       bi::scoped_lock<bi::interprocess_mutex> lock{
           *(ipc_message->ResponseMutex())};
-      stub->SendIPCMessage(ipc_message);
+      stub->SendIPCUtilsMessage(ipc_message);
       ipc_message->ResponseCondition()->wait(lock);
     }
 

src/infer_request.h

@@ -96,6 +96,7 @@ class InferRequest {
   InferenceTrace& GetTrace();
   uint32_t ReleaseFlags();
   void SetReleaseFlags(const uint32_t& flags);
+  intptr_t GetResponseFactoryAddress() { return response_factory_address_; }
 
 #ifdef TRITON_PB_STUB
   std::shared_ptr<InferResponse> Exec(const bool is_decoupled);

src/ipc_message.cc

@@ -56,6 +56,21 @@ IPCMessage::Create(
       new IPCMessage(ipc_message_shm, response_mutex_shm, response_cond_shm));
 }
 
+std::unique_ptr<IPCMessage>
+IPCMessage::Create(
+    IPCMessageShm* ipc_message_shm,
+    bi::managed_external_buffer::handle_t& message_handle)
+{
+  return std::unique_ptr<IPCMessage>(
+      new IPCMessage(ipc_message_shm, message_handle));
+}
+
+AllocatedSharedMemory<IPCMessageShm>&
+IPCMessage::GetAllocatedSharedMemory()
+{
+  return ipc_message_shm_;
+}
+
 std::unique_ptr<IPCMessage>
 IPCMessage::LoadFromSharedMemory(
     std::unique_ptr<SharedMemoryManager>& shm_pool,
@@ -133,4 +148,12 @@ IPCMessage::IPCMessage(
   ipc_message_handle_ = ipc_message_shm_.handle_;
 }
 
+IPCMessage::IPCMessage(
+    IPCMessageShm* ipc_message_shm,
+    bi::managed_external_buffer::handle_t& handle)
+{
+  ipc_message_handle_ = handle;
+  ipc_message_shm_ptr_ = ipc_message_shm;
+}
+
 }}};  // namespace triton::backend::python

src/ipc_message.h

@@ -97,6 +97,10 @@ class IPCMessage {
   static std::unique_ptr<IPCMessage> Create(
       const std::unique_ptr<SharedMemoryManager>& shm_pool,
       bool inline_response);
+
+  static std::unique_ptr<IPCMessage> Create(
+      IPCMessageShm* ipc_message_shm,
+      bi::managed_external_buffer::handle_t& message_handle);
   static std::unique_ptr<IPCMessage> LoadFromSharedMemory(
       std::unique_ptr<SharedMemoryManager>& shm_pool,
       bi::managed_external_buffer::handle_t message_handle);
@@ -108,6 +112,7 @@ class IPCMessage {
   bi::interprocess_mutex* ResponseMutex();
   bi::managed_external_buffer::handle_t& Args();
   bi::managed_external_buffer::handle_t ShmHandle();
+  AllocatedSharedMemory<IPCMessageShm>& GetAllocatedSharedMemory();
 
  private:
   AllocatedSharedMemory<IPCMessageShm> ipc_message_shm_;
@@ -129,6 +134,10 @@ class IPCMessage {
       AllocatedSharedMemory<IPCMessageShm>& ipc_message_shm,
       AllocatedSharedMemory<bi::interprocess_mutex>& response_mutex_shm,
       AllocatedSharedMemory<bi::interprocess_condition>& response_cond_shm);
+
+  IPCMessage(
+      IPCMessageShm* ipc_message_shm,
+      bi::managed_external_buffer::handle_t& handle);
 };
 
 }}};  // namespace triton::backend::python

src/pb_stub.cc

@@ -653,27 +653,19 @@ Stub::ProcessRequests(RequestBatch* request_batch_shm_ptr)
 {
   py::list py_request_list =
       LoadRequestsFromSharedMemory(request_batch_shm_ptr);
-  std::unique_ptr<IPCMessage> execute_response =
-      IPCMessage::Create(shm_pool_, false /* Inline response */);
-  execute_response->Command() = PYTHONSTUB_ExecuteResponse;
+  std::unique_ptr<IPCMessage> execute_response;
 
-  AllocatedSharedMemory<ResponseBatch> response_batch =
-      shm_pool_->Construct<ResponseBatch>();
-  ResponseBatch* response_batch_shm_ptr =
-      reinterpret_cast<ResponseBatch*>(response_batch.data_.get());
-  execute_response->Args() = response_batch.handle_;
+  std::optional<AllocatedSharedMemory<char>> response_batch;
   bool has_exception = false;
   std::string error_string;
   std::unique_ptr<PbString> error_string_shm;
+  std::string err_message;
 
   ScopedDefer execute_finalize([this] { stub_message_queue_->Pop(); });
   ScopedDefer _(
       [this, &execute_response] { SendIPCMessage(execute_response); });
-
+  py::object execute_return;
   try {
-    response_batch_shm_ptr->has_error = false;
-    response_batch_shm_ptr->is_error_set = false;
-
     if (!py::hasattr(model_instance_, "execute")) {
       std::string message = "Python model " + model_context_.PythonModelPath() +
                             " does not implement `execute` method.";
@@ -683,8 +675,7 @@ Stub::ProcessRequests(RequestBatch* request_batch_shm_ptr)
     {
       NVTX_RANGE(nvtx_, "PyExecute " + name_);
 
-      py::object execute_return =
-          model_instance_.attr("execute")(py_request_list);
+      execute_return = model_instance_.attr("execute")(py_request_list);
 
       bool is_coroutine = py::module::import("asyncio")
                               .attr("iscoroutine")(execute_return)
@@ -696,10 +687,12 @@ Stub::ProcessRequests(RequestBatch* request_batch_shm_ptr)
         } else {
           py::object coroutine_return =
               RunCoroutine(execute_return, false /* in_background */);
-          ProcessReturnedResponses(py_request_list, coroutine_return);
+          ProcessReturnedResponses(
+              py_request_list, coroutine_return, response_batch);
         }
       } else {
-        ProcessReturnedResponses(py_request_list, execute_return);
+        ProcessReturnedResponses(
+            py_request_list, execute_return, response_batch);
       }
     }
   }
@@ -713,16 +706,23 @@ Stub::ProcessRequests(RequestBatch* request_batch_shm_ptr)
   }
 
   if (has_exception) {
-    std::string err_message =
-        std::string(
-            "Failed to process the request(s) for model '" + name_ +
-            "', message: ") +
-        error_string;
+    err_message = std::string(
+                      "Failed to process the request(s) for model '" + name_ +
+                      "', message: ") +
+                  error_string;
     LOG_ERROR << err_message.c_str();
+    if (!response_batch) {
+      response_batch = shm_pool_->Construct<char>(
+          sizeof(ResponseBatch) + sizeof(IPCMessageShm));
+    }
+    ResponseBatch* response_batch_shm_ptr = reinterpret_cast<ResponseBatch*>(
+        response_batch.value().data_.get() + sizeof(IPCMessageShm));
+
     response_batch_shm_ptr->has_error = true;
     error_string_shm = PbString::Create(shm_pool_, err_message);
     response_batch_shm_ptr->error = error_string_shm->ShmHandle();
     response_batch_shm_ptr->is_error_set = true;
+    response_batch_shm_ptr->batch_size = 0;
     // Once the error is sent to the backend, the backend is supposed to close
     // all response factories if not already closed, so closing all response
     // senders if not already closed to prevent the model from sending more
@@ -731,12 +731,47 @@ Stub::ProcessRequests(RequestBatch* request_batch_shm_ptr)
       InferRequest* request = py_request.cast<InferRequest*>();
       request->GetResponseSender()->Close();
     }
+  } else {
+    if (!response_batch) {
+      response_batch = shm_pool_->Construct<char>(
+          sizeof(ResponseBatch) + sizeof(IPCMessageShm));
+      ResponseBatch* response_batch_shm_ptr = reinterpret_cast<ResponseBatch*>(
+          response_batch.value().data_.get() + sizeof(IPCMessageShm));
+      response_batch_shm_ptr->batch_size = 0;
+    }
+    ResponseBatch* response_batch_shm_ptr = reinterpret_cast<ResponseBatch*>(
+        response_batch.value().data_.get() + sizeof(IPCMessageShm));
+    response_batch_shm_ptr->has_error = false;
+    response_batch_shm_ptr->is_error_set = false;
+  }
+
+  execute_response = IPCMessage::Create(
+      reinterpret_cast<IPCMessageShm*>(response_batch.value().data_.get()),
+      response_batch.value().handle_);
+  execute_response->Args() =
+      response_batch.value().handle_ + sizeof(IPCMessageShm);
+  execute_response->InlineResponse() = false;
+  execute_response->Command() = PYTHONSTUB_ExecuteResponse;
+  _.Complete();
+  execute_finalize.Complete();
+}
+
+void
+Stub::ProcessResponse(InferResponse* response)
+{
+  response->SaveToSharedMemory(shm_pool_, false /* copy_gpu */);
+
+  for (auto& output_tensor : response->OutputTensors()) {
+    if (!output_tensor->IsCPU()) {
+      gpu_tensors_.push_back(output_tensor);
+    }
   }
 }
 
 void
 Stub::ProcessReturnedResponses(
-    py::list py_requests, py::object py_responses_obj)
+    py::list py_requests, py::object py_responses_obj,
+    std::optional<AllocatedSharedMemory<char>>& response_batch)
 {
   // Return if there is nothing to process.
   if (py::isinstance<py::none>(py_responses_obj)) {
@@ -784,12 +819,40 @@ Stub::ProcessReturnedResponses(
             "return list, found type '" +
             std::string(py::str(py_responses[i].get_type())) + "'.");
       }
-      std::shared_ptr<InferResponse> response =
-          py_responses[i].cast<std::shared_ptr<InferResponse>>();
-      request->GetResponseSender()->Send(
+
+      InferResponse* response = py_responses[i].cast<InferResponse*>();
+      request->GetResponseSender()->UpdateStateAndCounters(
           response, TRITONSERVER_RESPONSE_COMPLETE_FINAL);
     }
   }
+  // Return all the created responses using response_batch. The reason
+  // that both of the paths are available is that sending the responses
+  // using response_batch is faster than using `response_sender`.
+  response_batch = std::move(shm_pool_->Construct<char>(
+      sizeof(IPCMessageShm) +
+      requests_size * sizeof(bi::managed_external_buffer::handle_t) +
+      sizeof(ResponseBatch)));
+  ResponseBatch* response_batch_shm_ptr = reinterpret_cast<ResponseBatch*>(
+      response_batch.value().data_.get() + sizeof(IPCMessageShm));
+
+  bi::managed_external_buffer::handle_t* responses_shm_handle =
+      reinterpret_cast<bi::managed_external_buffer::handle_t*>(
+          response_batch.value().data_.get() + sizeof(ResponseBatch) +
+          sizeof(IPCMessageShm));
+
+  for (size_t i = 0; i < responses_size; i++) {
+    // Check the return type of execute function.
+    InferRequest* infer_request = py_requests[i].cast<InferRequest*>();
+    InferResponse* infer_response = py_responses[i].cast<InferResponse*>();
+    if (!py::isinstance<py::none>(py_responses[i])) {
+      infer_response->PruneOutputTensors(infer_request->RequestedOutputNames());
+      ProcessResponse(infer_response);
+      responses_shm_handle[i] = infer_response->ShmHandle();
+    } else {
+      responses_shm_handle[i] = 0;
+    }
+  }
+  response_batch_shm_ptr->batch_size = requests_size;
 }
 
 py::object

src/pb_stub.h

@@ -254,7 +254,10 @@ class Stub {
   void ProcessRequests(RequestBatch* request_batch_shm_ptr);
 
   void ProcessReturnedResponses(
-      py::list py_requests, py::object py_responses_obj);
+      py::list py_requests, py::object py_responses_obj,
+      std::optional<AllocatedSharedMemory<char>>& response_batch);
+
+  void ProcessResponse(InferResponse* response);
 
   py::object GetAsyncEventLoop();