Downloading MNIST dataset with torchvision gives HTTP Error 403

🐛 Bug

I’m getting a 403 error when I try to download MNIST dataset with torchvision 0.4.2.

To Reproduce

../.local/lib/python3.6/site-packages/torchvision/datasets/mnist.py:68: in __init__
    self.download()
../.local/lib/python3.6/site-packages/torchvision/datasets/mnist.py:135: in download
    download_and_extract_archive(url, download_root=self.raw_folder, filename=filename)
../.local/lib/python3.6/site-packages/torchvision/datasets/utils.py:248: in download_and_extract_archive
    download_url(url, download_root, filename, md5)
../.local/lib/python3.6/site-packages/torchvision/datasets/utils.py:96: in download_url
    raise e
../.local/lib/python3.6/site-packages/torchvision/datasets/utils.py:84: in download_url
    reporthook=gen_bar_updater()
/usr/local/lib/python3.6/urllib/request.py:248: in urlretrieve
    with contextlib.closing(urlopen(url, data)) as fp:
/usr/local/lib/python3.6/urllib/request.py:223: in urlopen
    return opener.open(url, data, timeout)
/usr/local/lib/python3.6/urllib/request.py:532: in open
    response = meth(req, response)
/usr/local/lib/python3.6/urllib/request.py:642: in http_response
    'http', request, response, code, msg, hdrs)
/usr/local/lib/python3.6/urllib/request.py:570: in error
    return self._call_chain(*args)
/usr/local/lib/python3.6/urllib/request.py:504: in _call_chain
    result = func(*args)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <urllib.request.HTTPDefaultErrorHandler object at 0x7efbf9edaac8>
req = <urllib.request.Request object at 0x7efbf9eda8d0>
fp = <http.client.HTTPResponse object at 0x7efbf9edaf98>, code = 403
msg = 'Forbidden', hdrs = <http.client.HTTPMessage object at 0x7efbf9ea22b0>

    def http_error_default(self, req, fp, code, msg, hdrs):
>       raise HTTPError(req.full_url, code, msg, hdrs, fp)
E       urllib.error.HTTPError: HTTP Error 403: Forbidden

Environment

• torch==1.3.1
• torchvision==0.4.2

Additional context

https://app.circleci.com/jobs/github/PyTorchLightning/pytorch-lightning/6877

[nvcastet]

@eduardo4jesus You could patch your model script at the top using:

from six.moves import urllib
opener = urllib.request.build_opener()
opener.addheaders = [('User-agent', 'Mozilla/5.0')]
urllib.request.install_opener(opener)

It will use that user agent for the entire script assuming the opener does not get overwritten somewhere else.

[andresgtn]

copy this snippet at the top of your notebook, run it, and then just load your datasets as usual…

from six.moves import urllib opener = urllib.request.build_opener() opener.addheaders = [('User-agent', 'Mozilla/5.0')] urllib.request.install_opener(opener)