WebGPU-Neural-Network-Trainer/shaders/neural/forward_dense_layer2.wgsl

@group(0) @binding(0) var<storage, read> hiddenActivations : array<f32>;
@group(0) @binding(1) var<storage, read_write> weightLayer2 : array<f32>;
@group(0) @binding(2) var<storage, read_write> biasLayer2 : array<f32>;
@group(0) @binding(3) var<storage, read_write> outputLogits : array<f32>;
@group(0) @binding(4) var<uniform> layer2Sizes : vec3<u32>;
// x = hiddenDim, y = numClasses, z = batchSize

@compute @workgroup_size(64)
fn main(@builtin(global_invocation_id) id : vec3<u32>) {
    let index = id.x;

    let hiddenDim  = layer2Sizes.x;
    let numClasses = layer2Sizes.y;
    let batchSize  = layer2Sizes.z;

    let total = batchSize * numClasses;
    if (index >= total) { return; }

    let sampleIndex = index / numClasses;
    let classIndex  = index % numClasses;

    var sum : f32 = biasLayer2[classIndex];

    let baseHiddenIndex = sampleIndex * hiddenDim;
    let baseWeightIndex = classIndex * hiddenDim;

    for (var i : u32 = 0u; i < hiddenDim; i++) {
        sum += hiddenActivations[baseHiddenIndex + i] *
               weightLayer2[baseWeightIndex + i];
    }

    outputLogits[index] = sum;
}