如何解决torchvision MNIST HTTPError：HTTP 错误 403：禁止
我正在尝试复制此网页 https://adversarial-ml-tutorial.org/adversarial_examples/
中介绍的此实验我获得了 jupyter notebook 并加载到我的本地主机中，然后使用 Jupiter notebook 打开它。当我运行以下代码以使用以下代码获取数据集时：
from torchvision import datasets,transforms
from torch.utils.data import DataLoader
mnist_train = datasets.MNIST("../data",train=True,download=True,transform=transforms.ToTensor())
mnist_test = datasets.MNIST("../data",train=False,transform=transforms.ToTensor())
train_loader = DataLoader(mnist_train,batch_size = 100,shuffle=True)
test_loader = DataLoader(mnist_test,shuffle=False)
我收到以下错误：
Downloading http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz to ../data\MNIST\raw\train-images-idx3-ubyte.gz
0/? [00:00<?,?it/s]
---------------------------------------------------------------------------
HTTPError Traceback (most recent call last)
<ipython-input-15-e6f62798f426> in <module>
2 from torch.utils.data import DataLoader
3
----> 4 mnist_train = datasets.MNIST("../data",transform=transforms.ToTensor())
5 mnist_test = datasets.MNIST("../data",transform=transforms.ToTensor())
6 train_loader = DataLoader(mnist_train,shuffle=True)
~\Anaconda3\lib\site-packages\torchvision\datasets\mnist.py in __init__(self,root,train,transform,target_transform,download)
77
78 if download:
---> 79 self.download()
80
81 if not self._check_exists():
~\Anaconda3\lib\site-packages\torchvision\datasets\mnist.py in download(self)
144 for url,md5 in self.resources:
145 filename = url.rpartition('/')[2]
--> 146 download_and_extract_archive(url,download_root=self.raw_folder,filename=filename,md5=md5)
147
148 # process and save as torch files
~\Anaconda3\lib\site-packages\torchvision\datasets\utils.py in download_and_extract_archive(url,download_root,extract_root,filename,md5,remove_finished)
254 filename = os.path.basename(url)
255
--> 256 download_url(url,md5)
257
258 archive = os.path.join(download_root,filename)
~\Anaconda3\lib\site-packages\torchvision\datasets\utils.py in download_url(url,md5)
82 )
83 else:
---> 84 raise e
85 # check integrity of downloaded file
86 if not check_integrity(fpath,md5):
~\Anaconda3\lib\site-packages\torchvision\datasets\utils.py in download_url(url,md5)
70 urllib.request.urlretrieve(
71 url,fpath,---> 72 reporthook=gen_bar_updater()
73 )
74 except (urllib.error.URLError,IOError) as e: # type: ignore[attr-defined]
~\Anaconda3\lib\urllib\request.py in urlretrieve(url,reporthook,data)
245 url_type,path = splittype(url)
246
--> 247 with contextlib.closing(urlopen(url,data)) as fp:
248 headers = fp.info()
249
~\Anaconda3\lib\urllib\request.py in urlopen(url,data,timeout,cafile,capath,cadefault,context)
220 else:
221 opener = _opener
--> 222 return opener.open(url,timeout)
223
224 def install_opener(opener):
~\Anaconda3\lib\urllib\request.py in open(self,fullurl,timeout)
529 for processor in self.process_response.get(protocol,[]):
530 meth = getattr(processor,meth_name)
--> 531 response = meth(req,response)
532
533 return response
~\Anaconda3\lib\urllib\request.py in http_response(self,request,response)
639 if not (200 <= code < 300):
640 response = self.parent.error(
--> 641 'http',response,code,msg,hdrs)
642
643 return response
~\Anaconda3\lib\urllib\request.py in error(self,proto,*args)
567 if http_err:
568 args = (dict,'default','http_error_default') + orig_args
--> 569 return self._call_chain(*args)
570
571 # XXX probably also want an abstract factory that knows when it makes
~\Anaconda3\lib\urllib\request.py 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
~\Anaconda3\lib\urllib\request.py in http_error_default(self,req,fp,hdrs)
647 class HTTPDefaultErrorHandler(BaseHandler):
648 def http_error_default(self,hdrs):
--> 649 raise HTTPError(req.full_url,hdrs,fp)
650
651 class HTTPRedirectHandler(BaseHandler):
HTTPError: HTTP Error 403: Forbidden
非常感谢您对解决此问题的任何帮助。 我也可以直接从链接下载数据集，但我不知道如何使用它！
解决方法
是的，这是一个已知错误：https://github.com/pytorch/vision/issues/3500
可能的解决方案是修补 MNIST download 方法。
但它需要安装 wget。
对于 Linux：
sudo apt install wget
对于 Windows：
choco install wget
import os
import subprocess as sp
from torchvision.datasets.mnist import MNIST,read_image_file,read_label_file
from torchvision.datasets.utils import extract_archive
def patched_download(self):
"""wget patched download method.
"""
if self._check_exists():
return
os.makedirs(self.raw_folder,exist_ok=True)
os.makedirs(self.processed_folder,exist_ok=True)
# download files
for url,md5 in self.resources:
filename = url.rpartition('/')[2]
download_root = os.path.expanduser(self.raw_folder)
extract_root = None
remove_finished = False
if extract_root is None:
extract_root = download_root
if not filename:
filename = os.path.basename(url)
# Use wget to download archives
sp.run(["wget",url,"-P",download_root])
archive = os.path.join(download_root,filename)
print("Extracting {} to {}".format(archive,extract_root))
extract_archive(archive,extract_root,remove_finished)
# process and save as torch files
print('Processing...')
training_set = (
read_image_file(os.path.join(self.raw_folder,'train-images-idx3-ubyte')),read_label_file(os.path.join(self.raw_folder,'train-labels-idx1-ubyte'))
)
test_set = (
read_image_file(os.path.join(self.raw_folder,'t10k-images-idx3-ubyte')),'t10k-labels-idx1-ubyte'))
)
with open(os.path.join(self.processed_folder,self.training_file),'wb') as f:
torch.save(training_set,f)
with open(os.path.join(self.processed_folder,self.test_file),'wb') as f:
torch.save(test_set,f)
print('Done!')
MNIST.download = patched_download
mnist_train = MNIST("../data",train=True,download=True,transform=transforms.ToTensor())
mnist_test = MNIST("../data",train=False,transform=transforms.ToTensor())
train_loader = DataLoader(mnist_train,batch_size=1,shuffle=True)
test_loader = DataLoader(mnist_test,shuffle=False)
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