如何修复imdb.load_data（）函数的“ allow_pickle = False时无法加载对象数组”？

Question

我正在尝试使用 Google Colab中
的IMDb数据集实现二进制分类示例。我之前已经实现了此模型。但是，几天后我再次尝试执行此操作时，它value error: 'Object arrays cannot be loaded when allow_pickle=False'为load_data（）函数返回了。

我的代码：

from keras.datasets import imdb
(train_data, train_labels), (test_data, test_labels) = imdb.load_data(num_words=10000)

错误：

ValueError                                Traceback (most recent call last)
<ipython-input-1-2ab3902db485> in <module>()
      1 from keras.datasets import imdb
----> 2 (train_data, train_labels), (test_data, test_labels) = imdb.load_data(num_words=10000)

2 frames
/usr/local/lib/python3.6/dist-packages/keras/datasets/imdb.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

/usr/local/lib/python3.6/dist-packages/numpy/lib/npyio.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)

/usr/local/lib/python3.6/dist-packages/numpy/lib/format.py in read_array(fp, allow_pickle, pickle_kwargs)
    690         # The array contained Python objects. We need to unpickle the data.
    691         if not allow_pickle:
--> 692             raise ValueError("Object arrays cannot be loaded when "
    693                              "allow_pickle=False")
    694         if pickle_kwargs is None:

ValueError: Object arrays cannot be loaded when allow_pickle=False

Answer 1

这是一个强制imdb.load_data在笔记本中允许泡菜代替此行的技巧：

(train_data, train_labels), (test_data, test_labels) = imdb.load_data(num_words=10000)

这样：

import numpy as np
# save np.load
np_load_old = np.load

# modify the default parameters of np.load
np.load = lambda *a,**k: np_load_old(*a, allow_pickle=True, **k)

# call load_data with allow_pickle implicitly set to true
(train_data, train_labels), (test_data, test_labels) = imdb.load_data(num_words=10000)

# restore np.load for future normal usage
np.load = np_load_old