Applying Glorotnormal Initializer In Tensorflow - Latest Information & Updates 2026

Web Reference: Used to make the behavior of the initializer deterministic. Note that an initializer seeded with an integer or None (unseeded) will produce the same random values across multiple calls. To get different random values across multiple calls, use as seed an instance of keras.backend.SeedGenerator. View source. If you need to configure your initializer via various arguments (e.g. stddev argument in RandomNormal), you should implement it as a subclass of keras.initializers.Initializer. Aug 15, 2021 · How to apply the initializer to the tf.Variable function? Am I on the right track? def initialize_parameters (): initializer = tf.keras.initializers.GlorotNormal...

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