How to fix 'Object arrays cannot be loaded when allow_pickle=False' for imdb.load_data() function?

Question

Here's a trick to force imdb.load_data to allow pickle by, in your notebook, replacing this line:

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

by this:

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

This issue is still up on keras git. I hope it gets solved as soon as possible. Until then, try downgrading your numpy version to 1.16.2. It seems to solve the problem.

!pip install numpy==1.16.1
import numpy as np

This version of numpy has the default value of allow_pickle as True.

Following this issue on GitHub, the official solution is to edit the imdb.py file. This fix worked well for me without the need to downgrade numpy. Find the imdb.py file at tensorflow/python/keras/datasets/imdb.py (full path for me was: C:\Anaconda\Lib\site-packages\tensorflow\python\keras\datasets\imdb.py - other installs will be different) and change line 85 as per the diff:

-  with np.load(path) as f:
+  with np.load(path, allow_pickle=True) as f:

The reason for the change is security to prevent the Python equivalent of an SQL injection in a pickled file. The change above will ONLY effect the imdb data and you therefore retain the security elsewhere (by not downgrading numpy).

I just used allow_pickle = True as an argument to np.load() and it worked for me.

np.load(path, allow_pickle=True)

In my case worked with:

np.load(path, allow_pickle=True)

I think the answer from cheez (https://stackoverflow.com/users/122933/cheez) is the easiest and most effective one. I'd elaborate a little bit over it so it would not modify a numpy function for the whole session period.

My suggestion is below. I´m using it to download the reuters dataset from keras which is showing the same kind of error:

old = np.load
np.load = lambda *a,**k: old(*a,**k,allow_pickle=True)

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

np.load = old
del(old)

You can try changing the flag's value

np.load(training_image_names_array,allow_pickle=True)