HTTP Error 403: rate limit exceeded when loading model
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- Dominant language
- Python
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Description
🐛 Bug
To Reproduce
Steps to reproduce the behavior:
- import torch
- model = torch.hub.load('pytorch/vision:v1.9.0','resnet50', pretrained=True)
Expected behavior
Load the model
Environment
Google Colab and also local with the latest pytorch and torchvision installed
Error Output
HTTPError Traceback (most recent call last)
in ()
1 import torchvision
2
----> 3 model = torch.hub.load('pytorch/vision:v1.9.0','resnet50', pretrained=True)
8 frames
/usr/lib/python3.7/urllib/request.py in http_error_default(self, req, fp, code, msg, hdrs)
647 class HTTPDefaultErrorHandler(BaseHandler):
648 def http_error_default(self, req, fp, code, msg, hdrs):
--> 649 raise HTTPError(req.full_url, code, msg, hdrs, fp)
650
651 class HTTPRedirectHandler(BaseHandler):
HTTPError: HTTP Error 403: rate limit exceeded
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reproducing the issue with the reported torch.hub.load('pytorch/vision:v1.9.0','resnet50', pretrained=True) call in Google Colab or a local installation. Inspect the torch.hub loading path and the reported HTTP 403 response to determine whether the failure is in torchvision or GitHub rate limiting. Done would require an agreed fix and a successful model load, but the issue does not specify the intended change or a named test.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- github, python, pytorch
- Domain
- computer-vision, machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100