dendog
1
I am loading two keras models, right now I am doing it sequentially:
page_encoder = tf.keras.models.load_model(PAGE_MODEL_PATH, compile=False)
query_encoder = tf.keras.models.load_model(QUERY_MODEL_PATH, compile=False)
As the models are fairly large - I would like to do this in parallel, any help would be appreciated!
Hi @dendog ,
I think you can load Keras models in parallel using Python multiprocessing
module to load each model in a separate process.
def model_loading(models_path):
return tf.keras.models.load_model(models_path)
model1 = 'path_to_model1'
model2 = 'path_to_model2'
__main__:
model1_parallel = multiprocessing.Process(target=model_loading, args=(model1,))
model2_parallel = multiprocessing.Process(target=model_loading, args=(model2,))
model1_parallel.start()
model2_parallel.start()
model1_parallel.join()
model2_parallel.join()
For more information you can use this python multiprocessing documentation.