深度学习tensorrtllm_backend是用来干嘛的 attention deep learning,一、文章信息《TA-STAN:ADeepSpatial-TemporalAttentionLearningFrameworkforRegionalTrafficAccidentRiskPrediction》西南交通大学2019年发表在“InternationalJointConferenceonNeuralNetworks”上的一
tensorrtllm_backend TensorRT-LLM(Low Level Model)是NVIDIA推出的一个深度学习模型后端,用于加速深度学习模型的训练和推理。它通过将模型的计算图转换为LLVM中间表示,然后使用TensorRT引擎进行优化和加速,从而实现对深度学习模型的高效处理。 TensorRT-LLM具有以下特点:...
model_name = "tensorrt_llm" inputs = [ utils.prepare_tensor("input_ids", output0, FLAGS.protocol), utils.prepare_tensor("decoder_input_ids", decoder_input_id, FLAGS.protocol), utils.prepare_tensor("input_lengths", output1, FLAGS.protocol), ...
triton_backend The backend to use for the model. Set to tensorrtllm to utilize the C++ TRT-LLM backend implementation. Set to python to utlize the TRT-LLM Python runtime. triton_max_batch_size The maximum batch size that the Triton model instance will run with. Note that for the tensorrt...
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64 python3 tools/fill_template.py -i llama_ifb/tensorrt_llm/config.pbtxt triton_backend:tensorrtllm,triton_max_batch_size:64,decoupled_mode:False,max_beam_width:1,engine_dir:${ENGINE_PATH},max_tokens_in_paged_kv_cache:2560,max_attention_window_size:2560,kv_cache_free_gpu_mem_fraction:0.5...
cd tensorrtllm_backend git lfs install git submodule update --init --recursive # Specify the build args for the dockerfile. BASE_IMAGE=nvcr.io/nvidia/pytorch:24.03-py3 BASE_IMAGE=nvcr.io/nvidia/pytorch:24.04-py3 TRT_VERSION=10.0.1.6 TRT_URL_x86=https://developer.nvidia.com/downl...
64 python3 tools/fill_template.py -i llama_ifb/tensorrt_llm/config.pbtxt triton_backend:tensorrtllm,triton_max_batch_size:64,decoupled_mode:False,max_beam_width:1,engine_dir:${ENGINE_PATH},max_tokens_in_paged_kv_cache:2560,max_attention_window_size:2560,kv_cache_free_gpu_mem_fraction:0.5...
The Triton TensorRT-LLM Backend. Contribute to triton-inference-server/tensorrtllm_backend development by creating an account on GitHub.
build engine过程比较简单,参照TensorRT-LLM仓库的examples/llama/README即可 单机单卡构建: cd TensorRT-LLM/examples/llama python3 build.py --model_dir=/temp_data/LLM_test/llama/skyline2006/llama-7b --use_weight_only--remove_input_padding --world_size=1--dtype=float16 --use_gpt_attention_plugi...