python-tensorflowHow can I release GPU memory when using Python TensorFlow?

To release GPU memory when using Python TensorFlow, you can use the tf.keras.backend.clear_session() function. This will clear the session and release all GPU memory. For example:

import tensorflow as tf

tf.keras.backend.clear_session()

This will clear the current session, releasing all GPU memory.

You can also use the tf.keras.backend.get_session().close() function to close the current session and release all GPU memory. For example:

import tensorflow as tf

tf.keras.backend.get_session().close()

This will close the current session, releasing all GPU memory.

You can also use the tf.keras.backend.get_session().run(tf.global_variables_initializer()) function to initialize all variables and release all GPU memory. For example:

import tensorflow as tf

tf.keras.backend.get_session().run(tf.global_variables_initializer())

This will initialize all variables, releasing all GPU memory.

You can also use the tf.keras.backend.get_session().reset() function to reset the session and release all GPU memory. For example:

import tensorflow as tf

tf.keras.backend.get_session().reset()

This will reset the session, releasing all GPU memory.

You can also use the tf.keras.backend.get_session().flush() function to flush the session and release all GPU memory. For example:

import tensorflow as tf

tf.keras.backend.get_session().flush()

This will flush the session, releasing all GPU memory.

Helpful links

• https://www.tensorflow.org/api_docs/python/tf/keras/backend
• https://www.tensorflow.org/guide/gpu

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