RuntimeError: set_storage_offset is not allowed on a Tensor created from .data or .detach().

错误提示信息:

If your intent is to change the metadata of a Tensor (such as sizes / strides / storage / storage_offset)
without autograd tracking the change, remove the .data / .detach() call and wrap the change in a `with torch.no_grad():` block.
For example, change:
    x.data.set_(y)
to:
    with torch.no_grad():
        x.set_(y)

出错的代码:feature.data.t_(), target.data.sub_(1)

按照提示修改

with torch.no_grad():

   feature.t_(), target.sub_(1)

就可以啦o(* ̄▽ ̄*)ブ

Using device: cuda training 0%| | 0/30000 [00:00<?, ?it/s] 第0轮 最终误差0.0025133900344371796 0%| | 1/30000 [00:00<3:34:01, 2.34it/s] c:\Users\cw\Desktop\model_HOT.py:192: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature. checkpoint = torch.load('model_HOT.pth', map_location=device) D:\Aconda\envs\pytorch\lib\site-packages\torch\functional.py:534: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at C:\actions-runner\_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\native\TensorShape.cpp:3596.) return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] Traceback (most recent call last): File "c:\Users\cw\Desktop\model_HOT.py", line 215, in <module> u_pred = U(xyt) File "D:\Aconda\envs\pytorch\lib\site-packages\torch\nn\modules\module
最新发布
03-08
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