Function batchnorm_scalar 

pub fn batchnorm_scalar(
    input: &[f32],
    n: usize,
    c: usize,
    gamma: &[f32],
    beta: &[f32],
    eps: f32,
    running_mean: &mut [f32],
    running_var: &mut [f32],
    output: &mut [f32],
    momentum: f32,
    training: bool,
)

Scalar reference implementation of BatchNorm.

Arguments

• input - Flattened [N, C] tensor (row-major).
• n - Batch size (N).
• c - Number of channels (C).
• gamma - Per-channel scale, length C.
• beta - Per-channel bias, length C.
• eps - Small constant for numerical stability.
• running_mean - Running mean per channel, length C. Updated in training.
• running_var - Running variance per channel, length C. Updated in training.
• output - Output buffer, same shape as input.
• momentum - EMA momentum for running stats update.
• training - If true, compute batch stats and update running stats. If false, use running stats for normalization.

Panics

Panics if buffer sizes are inconsistent with n * c.