GPU选择debug-7
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@ -217,16 +217,16 @@ def train(hyp, opt, device, data_list,id,callbacks): # hyp is path/to/hyp.yaml
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best_fitness, start_epoch, epochs = smart_resume(ckpt, optimizer, ema, weights, epochs, resume)
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del ckpt, csd
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# DP mode
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if cuda and RANK == -1 and torch.cuda.device_count() > 1:
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LOGGER.warning('WARNING: DP not recommended, use torch.distributed.run for best DDP Multi-GPU results.\n'
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'See Multi-GPU Tutorial at https://github.com/ultralytics/yolov5/issues/475 to get started.')
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model = torch.nn.DataParallel(model)
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# # DP mode
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# if cuda and RANK == -1 and torch.cuda.device_count() > 1:
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# LOGGER.warning('WARNING: DP not recommended, use torch.distributed.run for best DDP Multi-GPU results.\n'
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# 'See Multi-GPU Tutorial at https://github.com/ultralytics/yolov5/issues/475 to get started.')
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# model = torch.nn.DataParallel(model)
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# SyncBatchNorm
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if opt.sync_bn and cuda and RANK != -1:
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model = torch.nn.SyncBatchNorm.convert_sync_batchnorm(model).to(device)
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LOGGER.info('Using SyncBatchNorm()')
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# # SyncBatchNorm
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# if opt.sync_bn and cuda and RANK != -1:
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# model = torch.nn.SyncBatchNorm.convert_sync_batchnorm(model).to(device)
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# LOGGER.info('Using SyncBatchNorm()')
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print("Trainloader")
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# Trainloader
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