18 Random number functions

8.12

18 Random number functions🔗ℹ

procedure
(random-normal mu sigma) → scalar?
mu : scalar?
sigma : scalar?

Returns a random number sampled from the normal distribution with a mean of mu and a standard deviation of sigma.

procedure
(random-standard-normal) → scalar?

Returns a random number sampled from the normal distribution with a mean of 0.0 and a standard deviation of 1.0.

procedure
(random-tensor mean variance s) → tensor?
  mean : scalar?
  variance : scalar?
  s : (listof natural?)

Generates a tensor of shape s where the scalars are drawn from a normal distribution with a mean given by mean and the standard deviation given by (sqrt variance).

1	Overview
2	Entry points
3	List functions
4	Tensor functions
5	Extended Functions
6	Automatic Differentiation
7	Differentiable extended numerical functions
8	Non-differentiable extended numerical functions
9	Base-rank (non-extended) differentiable functions
10	Boolean comparison functions
11	Tensorized comparison functions
12	Hyperparameters
13	Gradient Descent Functions and Hyperparameters
14	Layer functions
15	Loss Functions
16	Building blocks for neural networks
17	He Initialization
18	Random number functions
19	Models and Accuracy
20	Logging
21	Utilities
22	Setting tensor implementations