Fixing the KeyError: 'acc' and KeyError: 'val_acc' Errors in Keras 2.3.x

Have you been using the 'History' object returned by the fit() functions of Keras to graph or visualize the training history of your models? And have you been getting a 'KeyError' type error such as the following since recent Keras upgrade and wondering why?

Traceback (most recent call last):
  File "lenet_mnist_keras.py", line 163, in <module>
    graph_training_history(history)
  File "lenet_mnist_keras.py", line 87, in graph_training_history
    plt.plot(history.history['acc'])
KeyError: 'acc'

The KeyError: 'acc' when attempting to read the history object

Traceback (most recent call last):
  File "lenet_mnist_keras.py", line 163, in <module>
    graph_training_history(history)
  File "lenet_mnist_keras.py", line 88, in graph_training_history
    plt.plot(history.history['val_acc'])
KeyError: 'val_acc'

The KeyError: 'val_acc' when attempting to read the history object

Well, this is due to a breaking change introduced in Keras release 2.3.0.

Fixing the Matplotlib PyPlot import errors

About a week back, I was reinstalling Keras, TensorFlow and all the other libraries after a reformat of my PC. When I started verifying the library installations, I came across a strange error. When I tried to run a simple deep learning model, Python runtime crashed. As soon as I execute the script I was getting the "python.exe has stopped working" error message (I'm using Windows 10).

Matplotlib is an important part of my deep learning workflows

A little bit of debugging narrowed down the error to the following line in my script.

import matplotlib.pyplot as plt

(I was using matplotlib to graph the training history of the model. See "How to Graph Model Training History in Keras")

The error did not occur if I simply import matplotlib. It only occurred when specifically importing the pyplot module.

import matplotlib
# no errors

import matplotlib.pyplot as plt
# crash!!!

This is a known issue due to some library conflicts in the installation, which should hopefully be fixed in a future release. Until then, if you're getting this error, you can fix it by following the steps below.

How to Graph Model Training History in Keras

When we are training a machine learning model in Keras, we usually keep track of how well the training is going (the accuracy and the loss of the model) using the values printed out in the console. Wouldn't it be great if we can visualize the training progress? Not only would it be easier to see how well the model trained, but it would also allow us to compare models.

Something like this?

Training accuracy and loss for 100 epochs

Well, you can actually do it quite easily, by using the History objects of Keras along with Matplotlib.