Re-upload weights for old model with new serialization

Some of the oldest models we have (including resnets) have been serialized with a legacy format which, while is mostly compatible with the current code, has some corner cases that do not work as expected anymore, see https://github.com/pytorch/pytorch/issues/31615 (basically, if the data is in a BytesIO object it doesn’t work).

Here is a snippet to reproduce the problem:

import urllib.request
import io

url = 'https://download.pytorch.org/models/resnet50-19c8e357.pth'
path = './tmp.pth'
urllib.request.urlretrieve(url, path)

with open(path, "rb") as fd:
    buf = io.BytesIO(fd.read())
    
state_dict = torch.load(buf, "cpu")

This fails. We should re-save those weights and re-upload them (while keeping the old files around for BC) and update the paths in the model files to use the new files. This code re-downloads the old files and re-serializes it with the new format

import urllib.request
import io

url = 'https://download.pytorch.org/models/resnet18-5c106cde.pth'
path = './tmp.pth'
urllib.request.urlretrieve(url, path)

torch.save(torch.load(path), path)

with open(path, "rb") as fd:
    buf = io.BytesIO(fd.read())

state_dict = torch.load(buf, "cpu")

One thing to keep in mind is if changing the default weights files (while being equivalent to the old models) won’t bring unexpected changes / issues to some users, as it will trigger a re-download of the file, which might fail because of many reasons (the server doesn’t have access to internet, files have been manually downloaded, etc).

[NicolasHug]

For ref, the following classifications model urls raise an UnpicklingError:

• resnet34-333f7ec4.pth
• alexnet-owt-4df8aa71.pth
• squeezenet1_0-a815701f.pth
• resnet152-b121ed2d.pth
• squeezenet1_1-f364aa15.pth
• resnet50-19c8e357.pth
• resnet101-5d3b4d8f.pth
• resnet18-5c106cde.pth

[BIGBALLON]

Thanks, @NicolasHug, the new weight can be loaded!