TypeError: 'torch._C.Node' object is not subscriptable

[lonngxiang]

Traceback (most recent call last):
File "D:/openai/CLIP/test1.py", line 7, in
model, preprocess = clip.load("ViT-B/32", device=device)
File "D:\openai\CLIP\clip\clip.py", line 133, in load
model.apply(patch_device)
File "D:\conda\envs\my_pytorch\lib\site-packages\torch\nn\modules\module.py", line 445, in apply
module.apply(fn)
File "D:\conda\envs\my_pytorch\lib\site-packages\torch\nn\modules\module.py", line 445, in apply
module.apply(fn)
File "D:\conda\envs\my_pytorch\lib\site-packages\torch\nn\modules\module.py", line 446, in apply
fn(self)
File "D:\openai\CLIP\clip\clip.py", line 130, in patch_device
if "value" in node.attributeNames() and str(node["value"]).startswith("cuda"):
TypeError: 'torch._C.Node' object is not subscriptable

[jongwook]

Likely related to PyTorch 1.8. Please try loading with jit=False or stick to torch 1.7.1. See #49 for more info.

[maksimovkonstantin]

@jongwook This very unclear and strange solution helped me microsoft/nni#2574 - so If someone will face the same problem - just import torchvision

[fuqichen1998]

@jongwook This very unclear and strange solution helped me microsoft/nni#2574 - so If someone will face the same problem - just import torchvision

This doesn't work for me.

[samuela]

FWIW I've found the same error on Ubuntu 20.04, with PyTorch 2.0.0 and CLIP a9b1bf5.

Update: setting jit=False fixes it for me

[dreamlychina]

FWIW I've found the same error on Ubuntu 20.04, with PyTorch 2.0.0 and CLIP a9b1bf5.

Update: setting jit=False fixes it for me

thanks, It is helpful for me。

[jamt9000]

For torch 2.0.0 this is working to monkeypatch the subscript operator:

import torch
import clip

# From https://github.com/pytorch/pytorch/blob/2efe4d809fdc94501fc38bf429e9a8d4205b51b6/torch/utils/tensorboard/_pytorch_graph.py#L384
def _node_get(node: torch._C.Node, key: str):
    """Gets attributes of a node which is polymorphic over return type."""
    sel = node.kindOf(key)
    return getattr(node, sel)(key)

torch._C.Node.__getitem__ = _node_get

model, preprocess = clip.load('ViT-B/32', jit=True)