AttributeError: ‘int‘ object has no attribute ‘type‘

最新推荐文章于 2025-03-13 14:33:31 发布

绝区零高手

最新推荐文章于 2025-03-13 14:33:31 发布

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本文链接：https://blog.youkuaiyun.com/m0_56841969/article/details/143973836

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对mm系列真的是又爱又恨，很方便做baseline又特别容易报错，有时候报的错还解决不了。

报错内容：

Traceback (most recent call last): 
  File "tools/train.py", line 237, in <module>
    main()
  File "tools/train.py", line 226, in main
    train_detector(
  File "/root/miniconda3/lib/python3.8/site-packages/mmdet/apis/train.py", line 246, in train_detector
    runner.run(data_loaders, cfg.workflow)
  File "/root/miniconda3/lib/python3.8/site-packages/mmcv/runner/epoch_based_runner.py", line 136, in run
    epoch_runner(data_loaders[i], **kwargs)
  File "/root/miniconda3/lib/python3.8/site-packages/mmcv/runner/epoch_based_runner.py", line 53, in train
    self.run_iter(data_batch, train_mode=True, **kwargs)
  File "/root/miniconda3/lib/python3.8/site-packages/mmcv/runner/epoch_based_runner.py", line 31, in run_iter
    outputs = self.model.train_step(data_batch, self.optimizer,
  File "/root/miniconda3/lib/python3.8/site-packages/mmcv/parallel/data_parallel.py", line 76, in train_step
    inputs, kwargs = self.scatter(inputs, kwargs, self.device_ids)
  File "/root/miniconda3/lib/python3.8/site-packages/mmcv/parallel/data_parallel.py", line 55, in scatter
    return scatter_kwargs(inputs, kwargs, device_ids, dim=self.dim)
  File "/root/miniconda3/lib/python3.8/site-packages/mmcv/parallel/scatter_gather.py", line 60, in scatter_kwargs
    inputs = scatter(inputs, target_gpus, dim) if inputs else []
  File "/root/miniconda3/lib/python3.8/site-packages/mmcv/parallel/scatter_gather.py", line 50, in scatter
    return scatter_map(inputs)
  File "/root/miniconda3/lib/python3.8/site-packages/mmcv/parallel/scatter_gather.py", line 35, in scatter_map
    return list(zip(*map(scatter_map, obj)))
  File "/root/miniconda3/lib/python3.8/site-packages/mmcv/parallel/scatter_gather.py", line 40, in scatter_map
    out = list(map(type(obj), zip(*map(scatter_map, obj.items()))))
  File "/root/miniconda3/lib/python3.8/site-packages/mmcv/parallel/scatter_gather.py", line 35, in scatter_map
    return list(zip(*map(scatter_map, obj)))
  File "/root/miniconda3/lib/python3.8/site-packages/mmcv/parallel/scatter_gather.py", line 33, in scatter_map
    return Scatter.forward(target_gpus, obj.data)
  File "/root/miniconda3/lib/python3.8/site-packages/mmcv/parallel/_functions.py", line 75, in forward
    streams = [_get_stream(device) for device in target_gpus]
  File "/root/miniconda3/lib/python3.8/site-packages/mmcv/parallel/_functions.py", line 75, in <listcomp>
    streams = [_get_stream(device) for device in target_gpus]
  File "/root/miniconda3/lib/python3.8/site-packages/torch/nn/parallel/_functions.py", line 117, in _get_stream
    if device.type == "cpu":
AttributeError: 'int' object has no attribute 'type'

报错原因：可能是原先代码用了多卡训练，返回的是列表如['0','1']，然后我这里只有单卡，返回的是整数0被识别了，就产生了错误，得在源头上让单卡是0的情况也被识别成功。

解决方法：为了不动pytorch包下的文件，我这里改了mmdet的内容。

#自定义一个函数
def safe_get_stream(device):
    if isinstance(device, int):  
        device = torch.device(f'cuda:{device}')
    return _get_stream(device)


#改写原先的_get_stream方法
class Scatter:

    @staticmethod
    def forward(target_gpus: List[int], input: Union[List, Tensor]) -> tuple:
        input_device = get_input_device(input)
        streams = None
        if input_device == -1 and target_gpus != [-1]:
            # Perform CPU to GPU copies in a background stream
            streams = [safe_get_stream(device) for device in target_gpus]

        outputs = scatter(input, target_gpus, streams)
        # Synchronize with the copy stream
        if streams is not None:
            synchronize_stream(outputs, target_gpus, streams)

        return tuple(outputs) if isinstance(outputs, list) else (outputs, )