python-kerasHow can I use the set_session function from TensorFlow's Keras backend?

The set_session function from TensorFlow's Keras backend is used to set the global TensorFlow session in Keras. This allows users to customize the configuration and behavior of the TensorFlow session, such as setting the random seed, the number of threads, and the GPU memory fraction.

Example code

from keras import backend as K
import tensorflow as tf

# Configure the session
config = tf.ConfigProto()
config.gpu_options.allow_growth = True

# Set the session
K.set_session(tf.Session(config=config))

The code above shows how to use the set_session function to customize the TensorFlow session. The code first imports the Keras backend and TensorFlow modules. Then it creates a TensorFlow ConfigProto object and sets the GPU options to allow growth. Finally, it calls the set_session function and passes in a TensorFlow session object with the configuration.

Code explanation

• from keras import backend as K - imports the Keras backend module.
• import tensorflow as tf - imports the TensorFlow module.
• config = tf.ConfigProto() - creates a TensorFlow ConfigProto object.
• config.gpu_options.allow_growth = True - sets the GPU options to allow growth.
• K.set_session(tf.Session(config=config)) - calls the set_session function and passes in a TensorFlow session object with the configuration.

Helpful links

• Keras Backend Documentation
• TensorFlow Documentation

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