首先我使用Tensorflow 1.15和Keras 2.2.4。
我在Jupyter笔记本中运行了以下代码：
from keras.datasets import imdb
from keras import preprocessing
max_features = 10000
maxlen = 20
(x_train, y_train), (x_test, y_test) = imdb.load_data(
num_words=max_features)
x_train = preprocessing.sequence.pad_sequences(x_train, maxlen=maxlen)
x_test = preprocessing.sequence.pad_sequences(x_test, maxlen=maxlen)
它给了我一个错误：
Downloading data from https://s3.amazonaws.com/text-datasets/imdb.npz
17465344/17464789 [==============================] - 8s 0us/step
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-6-609d113f6ed2> in <module>
6
7 (x_train, y_train), (x_test, y_test) = imdb.load_data(
----> 8 num_words=max_features)
9
10 x_train = preprocessing.sequence.pad_sequences(x_train, maxlen=maxlen)
~.condaenvstensorflow_envlibsite-packageskerasdatasetsimdb.py in load_data(path, num_words, skip_top, maxlen, seed, start_char, oov_char, index_from, **kwargs)
57 file_hash='599dadb1135973df5b59232a0e9a887c')
58 with np.load(path) as f:
---> 59 x_train, labels_train = f['x_train'], f['y_train']
60 x_test, labels_test = f['x_test'], f['y_test']
61
~.condaenvstensorflow_envlibsite-packagesnumpylibnpyio.py in __getitem__(self, key)
260 return format.read_array(bytes,
261 allow_pickle=self.allow_pickle,
--> 262 pickle_kwargs=self.pickle_kwargs)
263 else:
264 return self.zip.read(key)
~.condaenvstensorflow_envlibsite-packagesnumpylibformat.py in read_array(fp, allow_pickle, pickle_kwargs)
720 # The array contained Python objects. We need to unpickle the data.
721 if not allow_pickle:
--> 722 raise ValueError("Object arrays cannot be loaded when "
723 "allow_pickle=False")
724 if pickle_kwargs is None:
ValueError: Object arrays cannot be loaded when allow_pickle=False
它怎么了？我从"Python深度学习"一书中获得了这段代码。
感谢
numpy加载大量数据时，需要将allow_pickle设置为True。您应该手动更改。
np.load("place of bumpy file.npy", allow_pickle=True)
我认为imdb内部有numpy负载。