Traceback (most recent call last):
File "C:\data\2023-pothole\down\yolov7\train.py", line 595, in <module>
    device = select_device(opt.device, batch_size=opt.batch_size)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\data\2023-pothole\down\yolov7\utils\torch_utils.py", line 71, in select_device
    assert torch.cuda.is_available(), f'CUDA unavailable, invalid device {device} requested'  # check availability
    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
AssertionError: CUDA unavailable, invalid device 1 requested
(.venv) PS C:\data\2023-pothole\down\yolov7> python train.py --epochs 100 --workers 4 --device 1 --batch-size 32 --data data/pothole.yaml --img 640 640 --cfg cfg/training/yolov7_pothole-tiny.yaml --weights 'yolov7-tiny.pt' --name yolov7_tiny_pothole_fixed_res --hyp data/hyp.scratch.tiny.yaml # New Try 

Starting training for 100 epochs...

    Epoch   gpu_mem       box       obj       cls     total    labels  img_size
0%|                                                                                                                                                                           | 0/40 [00:03<?, ?it/s] 
Traceback (most recent call last):
File "C:\data\2023-pothole\down\yolov7\train.py", line 616, in <module>
    train(hyp, opt, device, tb_writer)
File "C:\data\2023-pothole\down\yolov7\train.py", line 361, in train
    pred = model(imgs)  # forward
File "C:\ProgramData\anaconda3\lib\site-packages\torch\nn\modules\module.py", line 1130, in _call_impl
    return forward_call(*input, **kwargs)
File "C:\data\2023-pothole\down\yolov7\models\yolo.py", line 599, in forward
    return self.forward_once(x, profile)  # single-scale inference, train
File "C:\data\2023-pothole\down\yolov7\models\yolo.py", line 625, in forward_once
    x = m(x)  # run
File "C:\ProgramData\anaconda3\lib\site-packages\torch\nn\modules\module.py", line 1130, in _call_impl
    return forward_call(*input, **kwargs)
File "C:\data\2023-pothole\down\yolov7\models\common.py", line 108, in forward
    return self.act(self.bn(self.conv(x)))
File "C:\ProgramData\anaconda3\lib\site-packages\torch\nn\modules\module.py", line 1130, in _call_impl
    return forward_call(*input, **kwargs)
File "C:\ProgramData\anaconda3\lib\site-packages\torch\nn\modules\batchnorm.py", line 168, in forward
    return F.batch_norm(
File "C:\ProgramData\anaconda3\lib\site-packages\torch\nn\functional.py", line 2438, in batch_norm
    return torch.batch_norm(
RuntimeError: CUDA out of memory. Tried to allocate 20.00 MiB (GPU 0; 4.00 GiB total capacity; 3.40 GiB already allocated; 0 bytes free; 3.46 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation.  See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF