Does calling tf.keras.backend.clear_session() fully release memory when using subclassed Models with custom training loops?
Goal: Verify whether invoking tf.keras.backend.clear_session() after each training iteration completely frees memory when the model is a subclassed Model that implements a custom train_step . Constraint: The Keras FAQ recommends clear_session() to counter the gradual RAM growth seen with repeated fit() calls on Sequential models, but anecdotal reports sugges
keras