我正在尝试在我的计算机中实现此code,我所遇到的问题是运行以下代码会出现错误:
fashion_mnist = keras.datasets.fashion_mnist
(X_train_full, y_train_full), (X_test, y_test) = (fashion_mnist.load_data())
X_valid, X_train = X_train_full[:5000], X_train_full[5000:]
y_valid, y_train = y_train_full[:5000], y_train_full[5000:]
错误:
~\Anaconda3\lib\site-packages\tensorflow_core\python\keras\utils\data_utils.py in get_file(fname, origin, untar, md5_hash, file_hash, cache_subdir, hash_algorithm, extract, archive_format, cache_dir)
251 urlretrieve(origin, fpath, dl_progress)
252 except HTTPError as e:
--> 253 raise Exception(error_msg.format(origin, e.code, e.msg))
254 except URLError as e:
255 raise Exception(error_msg.format(origin, e.errno, e.reason))
Exception: URL fetch failure on https://storage.googleapis.com/tensorflow/tf-keras-datasets/train-labels-idx1-ubyte.gz: 403 -- Forbidden
但是如果我尝试单独下载数据,不会出现Forbidden错误,我尝试加载数据而不从Google]下载,但出现了另一个错误
中解包和准备数据?--------------------------------------------------------------------------- TypeError Traceback (most recent call last) <ipython-input-13-68fe7d0ac27a> in <module> 1 fashion_mnist = keras.datasets.fashion_mnist ----> 2 (X_train_full, y_train_full), (X_test, y_test) = (fashion_mnist) 3 X_valid, X_train = X_train_full[:5000], X_train_full[5000:] 4 y_valid, y_train = y_train_full[:5000], y_train_full[5000:] TypeError: cannot unpack non-iterable module object
最后,我决定不使用
load_data()
方法,但仍然是相同的错误,是否有任何方法可以在不使用上述方法的情况下从[train-labels-idx1-ubyte
PS:我尝试使用VPN,但仍响应被禁止
我正在尝试在计算机上实现此代码,我所面临的问题是运行以下代码会出现错误:fashion_mnist = keras.datasets.fashion_mnist(X_train_full,y_train_full),(...
如果下载正确,则需要指定路径。