GPU选择debug-3
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@ -305,7 +305,7 @@ def train_R0DY(params_str, id):
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from app.yolov5.train_server import train_start
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from app.yolov5.train_server import train_start
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params = TrainParams()
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params = TrainParams()
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params.read_from_str(params_str)
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params.read_from_str(params_str)
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print(params.get('device').default)
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print(params.get('device').value)
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data_list = file_tool.get_file(ori_path=params.get('DatasetDir').value, type_list=params.get('CLASS_NAMES').value)
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data_list = file_tool.get_file(ori_path=params.get('DatasetDir').value, type_list=params.get('CLASS_NAMES').value)
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weights = params.get('resumeModPath').value # 初始化模型绝对路径
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weights = params.get('resumeModPath').value # 初始化模型绝对路径
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img_size = params.get('img_size').value
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img_size = params.get('img_size').value
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@ -608,6 +608,7 @@ def main(opt,data_list,id,callbacks=Callbacks()):
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opt.save_dir = str(increment_path(Path(opt.project) / opt.name, exist_ok=opt.exist_ok))
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opt.save_dir = str(increment_path(Path(opt.project) / opt.name, exist_ok=opt.exist_ok))
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# DDP mode
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# DDP mode
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print('\n','opt.device:',opt.device,'\n')
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device = select_device(opt.device, batch_size=opt.batch_size)
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device = select_device(opt.device, batch_size=opt.batch_size)
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print('\n','device:',device,'\n')
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print('\n','device:',device,'\n')
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# if LOCAL_RANK != -1:
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# if LOCAL_RANK != -1:
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