update llm_api_sh
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1d1a8e9339
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@ -17,15 +17,6 @@ if args.gpus:
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)
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)
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os.environ["CUDA_VISIBLE_DEVICES"] = args.gpus
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os.environ["CUDA_VISIBLE_DEVICES"] = args.gpus
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#-------------global-----------------
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# parser.add_argument('--model-path-address',
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# default="THUDM/chatglm2-6b@localhost@20002",
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# nargs="+",
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# type=str,
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# help="model path, host, and port, formatted as model-path@host@path")
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# multi_worker_args = parser.parse_args()
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# 0,controller, model_worker, openai_api_server
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# 0,controller, model_worker, openai_api_server
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# 1, 命令行选项
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# 1, 命令行选项
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# 2,LOG_PATH
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# 2,LOG_PATH
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@ -69,9 +60,7 @@ def launch_worker(item):
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log_name = item.split("/")[-1].split("\\")[-1].replace("-","_").replace("@","_").replace(".","_")
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log_name = item.split("/")[-1].split("\\")[-1].replace("-","_").replace("@","_").replace(".","_")
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# 先分割model-path-address,在传到string_args中分析参数
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# 先分割model-path-address,在传到string_args中分析参数
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args.model_path,args.worker_host, args.worker_port = item.split("@")
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args.model_path,args.worker_host, args.worker_port = item.split("@")
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print( args.model_path,args.worker_host, args.worker_port)
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print("*"*80)
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print("*"*80)
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worker_str_args = string_args(args,worker_args)
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worker_str_args = string_args(args,worker_args)
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print(worker_str_args)
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print(worker_str_args)
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worker_sh = base_launch_sh.format("model_worker",worker_str_args,LOG_PATH,f"worker_{log_name}")
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worker_sh = base_launch_sh.format("model_worker",worker_str_args,LOG_PATH,f"worker_{log_name}")
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