python - kaggle 无法下载 resnet50 预训练模型

Question

我正在尝试在 Kaggle 内核上使用 resnet50 预训练模型。

但是，当我运行以下代码时，发生错误并且无法下载预训练模型。我怎样才能让它工作？

from keras.applications.resnet50 import ResNet50
from keras.preprocessing import image
from keras.applications.resnet50 import preprocess_input, decode_predictions
import numpy as np

model = ResNet50(weights='imagenet', include_top=False)

错误:

-> 1318 encode_chunked=req.has_header('Transfer-encoding')) 1319
except OSError as err: # timeout error ...

Exception: URL fetch failure on https://github.com/fchollet/deep-learning-models/releases/download/v0.2/resnet50_weights_tf_dim_ordering_tf_kernels_notop.h5: None -- [Errno -2] Name or service not known

所有日志:

Using TensorFlow backend. /opt/conda/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: compiletime version 3.5 of module 'tensorflow.python.framework.fast_tensor_util' does not match runtime version 3.6 return f(*args, **kwds)

Downloading data from https://github.com/fchollet/deep-learning-models/releases/download/v0.2/resnet50_weights_tf_dim_ordering_tf_kernels_notop.h5

--------------------------------------------------------------------------- gaierror Traceback (most recent call last) /opt/conda/lib/python3.6/urllib/request.py in do_open(self, http_class, req, **http_conn_args) 1317
h.request(req.get_method(), req.selector, req.data, headers, -> 1318 encode_chunked=req.has_header('Transfer-encoding')) 1319
except OSError as err: # timeout error

/opt/conda/lib/python3.6/http/client.py in request(self, method, url, body, headers, encode_chunked) 1238 """Send a complete request to the server.""" -> 1239 self._send_request(method, url, body, headers, encode_chunked) 1240

/opt/conda/lib/python3.6/http/client.py in _send_request(self, method, url, body, headers, encode_chunked) 1284 body = _encode(body, 'body') -> 1285 self.endheaders(body, encode_chunked=encode_chunked) 1286

/opt/conda/lib/python3.6/http/client.py in endheaders(self, message_body, encode_chunked) 1233 raise CannotSendHeader() -> 1234 self._send_output(message_body, encode_chunked=encode_chunked) 1235

/opt/conda/lib/python3.6/http/client.py in _send_output(self, message_body, encode_chunked) 1025 del self._buffer[:] -> 1026 self.send(msg) 1027

/opt/conda/lib/python3.6/http/client.py in send(self, data) 963 if self.auto_open: --> 964 self.connect() 965 else:

/opt/conda/lib/python3.6/http/client.py in connect(self) 1391 -> 1392 super().connect() 1393

/opt/conda/lib/python3.6/http/client.py in connect(self) 935 self.sock = self._create_connection( --> 936 (self.host,self.port), self.timeout, self.source_address) 937 self.sock.setsockopt(socket.IPPROTO_TCP, socket.TCP_NODELAY, 1)

/opt/conda/lib/python3.6/socket.py in create_connection(address, timeout, source_address) 703 err = None --> 704 for res in getaddrinfo(host, port, 0, SOCK_STREAM): 705 af, socktype, proto, canonname, sa = res

/opt/conda/lib/python3.6/socket.py in getaddrinfo(host, port, family, type, proto, flags) 744 addrlist = [] --> 745 for res in _socket.getaddrinfo(host, port, family, type, proto, flags): 746 af, socktype, proto, canonname, sa = res

gaierror: [Errno -2] Name or service not known

During handling of the above exception, another exception occurred:

URLError Traceback (most recent call last) /opt/conda/lib/python3.6/site-packages/Keras-2.0.6-py3.6.egg/keras/utils/data_utils.py in get_file(fname, origin, untar, md5_hash, file_hash, cache_subdir, hash_algorithm, extract, archive_format, cache_dir) 219 try: --> 220 urlretrieve(origin, fpath, dl_progress) 221 except URLError as e:

/opt/conda/lib/python3.6/urllib/request.py in urlretrieve(url, filename, reporthook, data) 247 --> 248 with contextlib.closing(urlopen(url, data)) as fp: 249 headers = fp.info()

/opt/conda/lib/python3.6/urllib/request.py in urlopen(url, data, timeout, cafile, capath, cadefault, context) 222 opener = _opener --> 223 return opener.open(url, data, timeout) 224

/opt/conda/lib/python3.6/urllib/request.py in open(self, fullurl, data, timeout) 525 --> 526 response = self._open(req, data) 527

/opt/conda/lib/python3.6/urllib/request.py in _open(self, req, data) 543 result = self._call_chain(self.handle_open, protocol, protocol + --> 544 '_open', req) 545 if result:

/opt/conda/lib/python3.6/urllib/request.py in _call_chain(self, chain, kind, meth_name, *args) 503 func = getattr(handler, meth_name) --> 504 result = func(*args) 505 if result is not None:

/opt/conda/lib/python3.6/urllib/request.py in https_open(self, req)
1360 return self.do_open(http.client.HTTPSConnection, req, -> 1361 context=self._context, check_hostname=self._check_hostname) 1362

/opt/conda/lib/python3.6/urllib/request.py in do_open(self, http_class, req, **http_conn_args) 1319 except OSError as err: # timeout error -> 1320 raise URLError(err) 1321 r = h.getresponse()

URLError:

During handling of the above exception, another exception occurred:

Exception Traceback (most recent call last) in () 4 import numpy as np 5 ----> 6 model = ResNet50(weights='imagenet', include_top=False)

/opt/conda/lib/python3.6/site-packages/Keras-2.0.6-py3.6.egg/keras/applications/resnet50.py in ResNet50(include_top, weights, input_tensor, input_shape, pooling, classes) 261 WEIGHTS_PATH_NO_TOP, 262 cache_subdir='models', --> 263 md5_hash='a268eb855778b3df3c7506639542a6af') 264 model.load_weights(weights_path) 265 if K.backend() == 'theano':

/opt/conda/lib/python3.6/site-packages/Keras-2.0.6-py3.6.egg/keras/utils/data_utils.py in get_file(fname, origin, untar, md5_hash, file_hash, cache_subdir, hash_algorithm, extract, archive_format, cache_dir) 220 urlretrieve(origin, fpath, dl_progress) 221 except URLError as e: --> 222 raise Exception(error_msg.format(origin, e.errno, e.reason)) 223 except HTTPError as e: 224 raise Exception(error_msg.format(origin, e.code, e.msg))

Exception: URL fetch failure on https://github.com/fchollet/deep-learning-models/releases/download/v0.2/resnet50_weights_tf_dim_ordering_tf_kernels_notop.h5: None -- [Errno -2] Name or service not known

Answer 1

互联网设置在 kaggle 上默认关闭。如果你打开它，你可以下载预训练的模型。
在内核的右侧，您将看到可以在那里启用 Internet 的设置。