normal_gaussian

normal_gaussian(
    mean: T,
    std: T,
    shape: &[i64] | &Vec<i64> | &[i64; _]
) -> Result<Tensor<T>, TensorError>

Create a Tensor with values drawn from a normal (Gaussian) distribution with specified mean and standard deviation. The normal distribution is a continuous probability distribution that is symmetric around its mean, showing the familiar bell-shaped curve.

Parameters:

mean: Mean (μ) of the distribution, determining the center of the bell curve.

std: Standard deviation (σ) of the distribution, determining the spread. Must be positive.

shape: Shape of the output tensor.

Returns:

Tensor with type T containing random values from the normal distribution.

Examples:

use hpt::{error::TensorError, ops::Random, Tensor};

fn main() -> Result<(), TensorError> {
    // Create a 10x10 tensor with normal distribution (μ=0.0, σ=1.0)
    let a = Tensor::<f32>::normal_gaussian(0.0, 1.0, &[10, 10])?;
    println!("{}", a);
    Ok(())
}

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