在vllm上层接口可以直接通过参数tensor_parallel_size设置,来将模型分布在 tensor_parallel_size 个 GPU 上进行并行计算,每个 GPU 负责处理模型的一部分张量。 vllm中与tp并行有关的操作主要在vllm/distributed中。 vllm/distributed/parallel_state.py initialize_model
model="your-model-name", # 模型名称或路径 tensor_parallel_size=4, # 使用 4 个 GPU 进行张量并行 ) # 定义输入和采样参数 prompts = [ "What is the capital of France?", "Explain the theory of relativity.", "Write a short story about a robot.", "How does photosynthesis work?" ] samp...
MegatronLM的第一篇论文【Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism】是2020年出的,针对billion级别的模型进行训练,例如具有38亿参数的类GPT-2的transformer模型和具有39亿参数的BERT模型。 分布式训练的模型并行有两种方式,一种是层间并行(inter-layer),也就是Pipeline流水...
--enforce-eager However, when I run it with--tensor-parallel-size 4, the model does not finish loading and the server crashes after about 10 minutes: $python -m vllm.entrypoints.openai.api_server \ --model meta-llama/Meta-Llama-3-8B-Instruct \ --download-dir /mnt/nvme/models/ \ --...
max_model_len=MAX_MODEL_LENGTH, ) tensor_parallel_size参数改为2,使用2张卡; 2.用多线程调用api: def send_request(prompt): response = simple_chat(prompt) return response with concurrent.futures.ThreadPoolExecutor(max_workers=10) as executor: ...
Tensor parallelism takes place at the level of nn.Modules; it partitions specific modules in the model across tensor parallel ranks. This is in addition to the existing partition of the set of modules used in pipeline parallelism. When a module is partitioned through tensor parallelism, it...
ppl.pmx/model_zoo/llama/modeling/static_batching/Model.py at master · openppl-public/ppl.pmx (github.com) Linear汇总结果 如上文,Attention层最后一个Linear、MLP层最后一个Linear都需要汇总结果,需要使用all_reduce算子。 ppl.pmx/torch_function/RowParallelLinear.py at master · openppl-public/ppl.pmx...
为了实现这一点,TensorFlow需要初始化一个"model parallel group"。 这个警告通常意味着在尝试初始化或加入模型并行组时,该组已经被初始化了。这可能不会影响模型的运行,但它可能表明有代码的重复执行或者初始化过程存在某种不预期的行为。 如果你遇到这个警告并且确定它不会导致任何问题,你可以选择忽略它。然而,如果...
TensorParallel、DTensor、2D parallel、TorchDynamo、AOTAutograd、PrimTorch和TorchInductor TorchDynamo是借助Python Frame Evaluation Hooks能安全地获取PyTorch程序; AOTAutograd重载PyTorch autograd engine,作为一个 tracing autodiff,用于生成超前的backward trace。
RuntimeError: {'errCode': 'EA0000', 'message': 'Tensor temp_iou_ub appiles buffer size(156160B) more than available buffer size(14528B). File path: /usr/local/Ascend/ascend-toolkit/6.3.RC1/opp/built-in/op_impl/ai_core/tbe/impl/non_max_suppression_v7.py, line 1014 ...