lognormal_like

lognormal_like(
    x: &Tensor<T>,
    mean: T,
    std: T
) -> Result<Tensor<T>, TensorError>

Same as lognormal but the shape will be based on x. Creates a Tensor with values drawn from a log-normal distribution with parameters mean and std of the underlying normal distribution.

Parameters:

x: Input Tensor to derive the shape from

mean: Mean (μ) of the underlying normal distribution.

std: Standard deviation (σ) of the underlying normal distribution. Must be positive.

Returns:

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

Examples:

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

fn main() -> Result<(), TensorError> {
    // Create an initial tensor
    let x = Tensor::<f32>::randn(&[10, 10])?;
    
    // Create a new tensor with same shape as x but with log-normal distribution
    let l = x.lognormal_like(0.0, 1.0)?;
    println!("{}", l);
    Ok(())
}

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