I load the model into keras with model.load () and find that the first prediction takes more than 10 times longer than calculated than to follow the predictions, any ideas why this might happen, or suggestions, it would be highly recognized that speeding up the prediction cycle entry level will be greatly appreciated.
I am using a Tensorflow server with processor processing.
Thanks for the help, Denym
Ok, so I found an answer that works for me:
, keras model.load, json/yaml .h5 keras.
model.load 5 , , .
json .h5 10 100 , , , , , .
Source: https://habr.com/ru/post/1684794/More articles:Combine rank and amount in sql - sqlHow to sign a private key in RSA X509 certificate - swift3Server without NodeJS server / Native node_modules - node.jsQuery Doesn't work correctly in php using mysqli - phpHow to call the async method in a method that returns Task? - c #Find available range from table in SQL Server - sql-serverngx-infinite scroll with percentage height not showing - htmlWhat are the differences between KTable and GlobalKTable and leftJoin () vs outerJoin ()? - apache-kafkaQt - Android app immediately fires - c ++there is an asynchronous problem in redis - redisAll Articles