Keras - Backend Configuration

This chapter explains Keras backend implementations TensorFlow and Theano in detail. Let us go through each implementation one by one.


TensorFlow is an open source machine learning library used for numerical computational tasks developed by Google. Keras is a high level API built on top of TensorFlow or Theano. We know already how to install TensorFlow using pip.

If it is not installed, you can install using the below command −

pip install TensorFlow

Once we execute keras, we could see the configuration file is located at your home directory inside and go to .keras/keras.json.


   "image_data_format": "channels_last", 
   "epsilon": 1e-07, "floatx": "float32", "backend": "tensorflow" 


  • image_data_format represent the data format.

  • epsilon represents numeric constant. It is used to avoid DivideByZero error.

  • floatx represent the default data type float32. You can also change it to float16 or float64 using set_floatx() method.

  • image_data_format represent the data format.

Suppose, if the file is not created then move to the location and create using the below steps −

> cd home 
> mkdir .keras 
> vi keras.json

Remember, you should specify .keras as its folder name and add the above configuration inside keras.json file. We can perform some pre-defined operations to know backend functions.


Theano is an open source deep learning library that allows you to evaluate multi-dimensional arrays effectively. We can easily install using the below command −

pip install theano

By default, keras uses TensorFlow backend. If you want to change backend configuration from TensorFlow to Theano, just change the backend = theano in keras.json file. It is described below −


   "image_data_format": "channels_last", 
   "epsilon": 1e-07, 
   "floatx": "float32", 
   "backend": "theano" 

Now save your file, restart your terminal and start keras, your backend will be changed.

>>> import keras as k 
using theano backend.