He normal initializer.

Inherits From: VarianceScaling, Initializer

Also available via the shortcut function tf.keras.initializers.he_normal.

It draws samples from a truncated normal distribution centered on 0 with stddev = sqrt(2 / fan_in) where fan_in is the number of input units in the weight tensor.


# Standalone usage:
initializer = tf.keras.initializers.HeNormal()
values = initializer(shape=(2, 2))
# Usage in a Keras layer:
initializer = tf.keras.initializers.HeNormal()
layer = tf.keras.layers.Dense(3, kernel_initializer=initializer)