Aliases:
tf.initializers.lecun_normaltf.keras.initializers.lecun_normal
tf.keras.initializers.lecun_normal(seed=None)
Defined in tensorflow/python/ops/init_ops.py.
LeCun normal initializer.
It draws samples from a truncated normal distribution centered on 0
with stddev = sqrt(1 / fan_in)
where fan_in is the number of input units in the weight tensor.
Arguments:
seed: A Python integer. Used to seed the random generator.
Returns:
An initializer.
References: - Self-Normalizing Neural Networks, Klambauer et al., 2017 (pdf) - Efficient Backprop, Lecun et al., 1998