Download pretrained model

model = torchvision.models.detection.fasterrcnn_resnet50_fpn(pretrained=True)

when I try to this line of code to download pretrained fasterrcnn model, I got the following error message. I can’t figure out what’s wrong with it, and there is no related solution after I search, Is there someone can help me?

Downloading: "" to /root/.cache/torch/hub/checkpoints/fasterrcnn_resnet50_fpn_coco-258fb6c6.pth
gaierror                                  Traceback (most recent call last)
/opt/conda/lib/python3.7/urllib/ in do_open(self, http_class, req, **http_conn_args)
   1349                 h.request(req.get_method(), req.selector,, headers,
-> 1350                           encode_chunked=req.has_header('Transfer-encoding'))
   1351             except OSError as err: # timeout error

/opt/conda/lib/python3.7/http/ in request(self, method, url, body, headers, encode_chunked)
   1276         """Send a complete request to the server."""
-> 1277         self._send_request(method, url, body, headers, encode_chunked)

/opt/conda/lib/python3.7/http/ in _send_request(self, method, url, body, headers, encode_chunked)
   1322             body = _encode(body, 'body')
-> 1323         self.endheaders(body, encode_chunked=encode_chunked)

/opt/conda/lib/python3.7/http/ in endheaders(self, message_body, encode_chunked)
   1271             raise CannotSendHeader()
-> 1272         self._send_output(message_body, encode_chunked=encode_chunked)

/opt/conda/lib/python3.7/http/ in _send_output(self, message_body, encode_chunked)
   1031         del self._buffer[:]
-> 1032         self.send(msg)

/opt/conda/lib/python3.7/http/ in send(self, data)
    971             if self.auto_open:
--> 972                 self.connect()
    973             else:

/opt/conda/lib/python3.7/http/ in connect(self)
-> 1439             super().connect()

/opt/conda/lib/python3.7/http/ in connect(self)
    943         self.sock = self._create_connection(
--> 944             (,self.port), self.timeout, self.source_address)
    945         self.sock.setsockopt(socket.IPPROTO_TCP, socket.TCP_NODELAY, 1)

/opt/conda/lib/python3.7/ in create_connection(address, timeout, source_address)
    706     err = None
--> 707     for res in getaddrinfo(host, port, 0, SOCK_STREAM):
    708         af, socktype, proto, canonname, sa = res

/opt/conda/lib/python3.7/ in getaddrinfo(host, port, family, type, proto, flags)
    751     addrlist = []
--> 752     for res in _socket.getaddrinfo(host, port, family, type, proto, flags):
    753         af, socktype, proto, canonname, sa = res

gaierror: [Errno -3] Temporary failure in name resolution

During handling of the above exception, another exception occurred:

URLError                                  Traceback (most recent call last)
<ipython-input-47-bfd4a803a437> in <module>
      4 # load a model pre-trained pre-trained on COCO
----> 5 model = torchvision.models.detection.fasterrcnn_resnet50_fpn(pretrained=True)
      7 # replace the classifier with a new one, that has

/opt/conda/lib/python3.7/site-packages/torchvision/models/detection/ in fasterrcnn_resnet50_fpn(pretrained, progress, num_classes, pretrained_backbone, trainable_backbone_layers, **kwargs)
    360     if pretrained:
    361         state_dict = load_state_dict_from_url(model_urls['fasterrcnn_resnet50_fpn_coco'],
--> 362                                               progress=progress)
    363         model.load_state_dict(state_dict)
    364     return model

/opt/conda/lib/python3.7/site-packages/torch/ in load_state_dict_from_url(url, model_dir, map_location, progress, check_hash, file_name)
    553             r =  # r is Optional[Match[str]]
    554             hash_prefix = if r else None
--> 555         download_url_to_file(url, cached_file, hash_prefix, progress=progress)
    557     if _is_legacy_zip_format(cached_file):

/opt/conda/lib/python3.7/site-packages/torch/ in download_url_to_file(url, dst, hash_prefix, progress)
    423     # certificates in older Python
    424     req = Request(url, headers={"User-Agent": "torch.hub"})
--> 425     u = urlopen(req)
    426     meta =
    427     if hasattr(meta, 'getheaders'):

/opt/conda/lib/python3.7/urllib/ in urlopen(url, data, timeout, cafile, capath, cadefault, context)
    220     else:
    221         opener = _opener
--> 222     return, data, timeout)
    224 def install_opener(opener):

/opt/conda/lib/python3.7/urllib/ in open(self, fullurl, data, timeout)
    523             req = meth(req)
--> 525         response = self._open(req, data)
    527         # post-process response

/opt/conda/lib/python3.7/urllib/ in _open(self, req, data)
    541         protocol = req.type
    542         result = self._call_chain(self.handle_open, protocol, protocol +
--> 543                                   '_open', req)
    544         if result:
    545             return result

/opt/conda/lib/python3.7/urllib/ in _call_chain(self, chain, kind, meth_name, *args)
    501         for handler in handlers:
    502             func = getattr(handler, meth_name)
--> 503             result = func(*args)
    504             if result is not None:
    505                 return result

/opt/conda/lib/python3.7/urllib/ in https_open(self, req)
   1391         def https_open(self, req):
   1392             return self.do_open(http.client.HTTPSConnection, req,
-> 1393                 context=self._context, check_hostname=self._check_hostname)
   1395         https_request = AbstractHTTPHandler.do_request_

/opt/conda/lib/python3.7/urllib/ in do_open(self, http_class, req, **http_conn_args)
   1350                           encode_chunked=req.has_header('Transfer-encoding'))
   1351             except OSError as err: # timeout error
-> 1352                 raise URLError(err)
   1353             r = h.getresponse()
   1354         except:

URLError: <urlopen error [Errno -3] Temporary failure in name resolution>

The error indicates that the download failed due to an issue in the name resolution.
I’ve just re-downloaded the pretrained model and cannot reproduce the issue so could you just rerun the code and check, if it was just a temporal issue?

I use this line of code in kaggle competition, I have tried several times re-downloaded the pretrained model, but still get the same error message.Here is my kaggle notebook where the code is in.
ps: maybe you can run this notebook to reproduce the issue, most of the code is copied from other notebooks.

Maybe there is something wrong with my notebook or some constrains with kaggle notebook, but I can’t figure out why. And even though I try the code in a new notebook, I still wouldn’t make it work.

Oh, I find the reason why it happened, I turned off the internet option in settings of the notebook, it should be turned on.