tf.keras.backend.clear_session

TensorFlow 1 version

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Destroys the current TF graph and session, and creates a new one.

View aliases

Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.keras.backend.clear_session

tf.keras.backend.clear_session()

Used in the notebooks

Used in the guide
Training checkpoints Writing custom layers and models with Keras The Keras functional API Save and serialize models with Keras

Calling clear_session() releases the global graph state that Keras is holding on to; resets the counters used for naming layers and variables in Keras; and resets the learning phase. This helps avoid clutter from old models and layers, especially when memory is limited, and a common use-case for clear_session is releasing memory when building models and layers in a loop.

import tensorflow as tf 
layers = [tf.keras.layers.Dense(10) for _ in range(10)] 
new_layer = tf.keras.layers.Dense(10) 
print(new_layer.name) 
dense_10 
tf.keras.backend.set_learning_phase(1) 
print(tf.keras.backend.learning_phase()) 
1 
tf.keras.backend.clear_session() 
new_layer = tf.keras.layers.Dense(10) 
print(new_layer.name) 
dense 
print(tf.keras.backend.learning_phase()) 
0