Normal¶
Random normal initializer which simulate a normal distribution with specified parameters.
Parameters¶
-
mu
Default →
0.0The mean of the normal distribution
-
sigma
Default →
1.0The standard deviation of the normal distribution
-
seed
Type →
int | NoneDefault →
NoneRandom number generation seed that can be set for reproducibility.
Examples¶
from river import optim
init = optim.initializers.Normal(mu=0, sigma=1, seed=42)
init(shape=1)
np.float64(0.4967141...)
init(shape=2)
array([-0.1382643 , 0.64768854])
Methods¶
call
Returns a fresh set of weights.
The return type is shape-dependent (a scalar when shape == 1, otherwise an array), and these values are routinely used as collections.defaultdict factories elsewhere, so the return is intentionally left dynamic.
Parameters
- shape —
int— defaults to1