/* * SPDX-FileCopyrightText: Copyright (c) 2022-2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved. * SPDX-License-Identifier: Apache-2.0 * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * 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. */ #include #include "tensorrt_llm/common/logger.h" #include "tensorrt_llm/executor/executor.h" #include "tensorrt_llm/plugins/api/tllmPlugin.h" namespace tlc = tensorrt_llm::common; namespace tle = tensorrt_llm::executor; int main(int argc, char* argv[]) { // Register the TRT-LLM plugins initTrtLlmPlugins(); if (argc != 2) { TLLM_LOG_ERROR("Usage: %s ", argv[0]); return 1; } // Create the executor for this engine tle::SizeType32 beamWidth = 1; auto executorConfig = tle::ExecutorConfig(beamWidth); // Select which tensors should be dumped auto debugConfig = tle::DebugConfig(); debugConfig.setDebugTensorNames({"host_request_types"}); executorConfig.setDebugConfig(debugConfig); auto trtEnginePath = argv[1]; auto executor = tle::Executor(trtEnginePath, tle::ModelType::kDECODER_ONLY, executorConfig); // Create the request tle::SizeType32 maxNewTokens = 2; tle::VecTokens inputTokens{1, 2, 3, 4}; auto request = tle::Request(inputTokens, maxNewTokens); // Enqueue the request auto requestId = executor.enqueueRequest(request); // Wait for the response auto responses = executor.awaitResponses(requestId); // Get outputTokens auto outputTokens = responses.at(0).getResult().outputTokenIds.at(beamWidth - 1); TLLM_LOG_INFO("Output tokens: %s", tlc::vec2str(outputTokens).c_str()); return 0; }