Question

我正在尝试在计算机中实现此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并没有出现“禁止”错误，我尝试加载数据而不从 Google 下载它，但是又出现了另一个错误

---------------------------------------------------------------------------
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解压缩和准备 train-labels-idx1-ubyte 中的数据，而无需使用上面的方法？

PS：我尝试使用VPN，但仍然响应“禁止”

Answer 1

如果下载正确，则需要指定路径。

您是否尝试过Here中记载的(X_train_full, y_train_full), (X_test, y_test) = fashion_mnist.load_data (path="%yourLocalPath%")？ tensorflow docs

如果不是这样，那么您因为居住在TensorFlow被禁止的地方而遇到的第一个错误就是使用VPN。

用Keras实现神经网络

1 个答案: