The Glorot normal initializer, aka Xavier normal initializer.
tfp.experimental.nn.initializers.glorot_normal(
seed=None
)
It draws samples from a truncated normal distribution centered on 0
with standard deviation (after truncation) given by
stddev = sqrt(2 / (fan_in + fan_out)) where fan_in is the number
of input units in the weight tensor and fan_out is the number of
output units in the weight tensor.
Returns |
|---|
init_fn
|
A python callable which takes a shape Tensor, dtype and an
optional scalar int number of batch dims and returns a randomly
initialized Tensor with the specified shape and dtype.
|
References:
Glorot et al., 2010
(pdf)
View source on GitHub