SeedGenerator class
SeedGenerator class
keras.random.SeedGenerator(seed=None, name=None, **kwargs)
Generates variable seeds upon each call to a RNG-using function.
In Keras, all RNG-using methods (such as keras.random.normal())
are stateless, meaning that if you pass an integer seed to them
(such as seed=42), they will return the same values at each call.
In order to get different values at each call, you must use a
SeedGenerator instead as the seed argument. The SeedGenerator
object is stateful.
Example
seed_gen = keras.random.SeedGenerator(seed=42)
values = keras.random.normal(shape=(2, 3), seed=seed_gen)
new_values = keras.random.normal(shape=(2, 3), seed=seed_gen)
Usage in a layer:
class Dropout(keras.Layer):
def __init__(self, **kwargs):
super().__init__(**kwargs)
self.seed_generator = keras.random.SeedGenerator(1337)
def call(self, x, training=False):
if training:
return keras.random.dropout(
x, rate=0.5, seed=self.seed_generator
)
return x