WebGPU-Neural-Network-Trainer/shaders/neural/gradients_dense_layer1.wgsl

@group(0) @binding(0)
var<storage, read> inputImages : array<f32>; 
// [batchSize * inputDimension]

@group(0) @binding(1)
var<storage, read> gradientHidden : array<f32>; 
// [batchSize * hiddenDimension]

@group(0) @binding(2)
var<storage, read_write> gradientWeightLayer1 : array<f32>; 
// [inputDimension * hiddenDimension]

@group(0) @binding(3)
var<storage, read_write> gradientBiasLayer1 : array<f32>; 
// [hiddenDimension]

@group(0) @binding(4)
var<uniform> layer1Sizes : vec3<u32>; 
// x = inputDimension, y = hiddenDimension, z = batchSize


@compute @workgroup_size(64)
fn main(@builtin(global_invocation_id) id : vec3<u32>) {

    let index = id.x;

    let inputDimension  = layer1Sizes.x;
    let hiddenDimension = layer1Sizes.y;
    let batchSize       = layer1Sizes.z;

    // We launch:
    //   inputDimension * hiddenDimension   threads for weight gradients
    //   + hiddenDimension                  threads for bias gradients
    let totalWeightElements = inputDimension * hiddenDimension;
    let totalBiasElements   = hiddenDimension;
    let totalElements       = totalWeightElements + totalBiasElements;

    if (index >= totalElements) {
        return;
    }

    // ---- Region 1: Weight gradients dW1 (0 .. totalWeightElements-1) ----
    if (index < totalWeightElements) {

        // Map flat index into (inputIndex, hiddenIndex)
        let hiddenIndex : u32 = index / inputDimension;
        let inputIndex  : u32 = index % inputDimension;

        var sum : f32 = 0.0;

        // dW1[inputIndex, hiddenIndex] = sum over batch of
        //    inputImages[b, inputIndex] * gradientHidden[b, hiddenIndex]
        for (var batchIndex : u32 = 0u; batchIndex < batchSize; batchIndex = batchIndex + 1u) {

            let inputValue = inputImages[ batchIndex * inputDimension + inputIndex ];

            let hiddenGradient = gradientHidden[ batchIndex * hiddenDimension + hiddenIndex ];

            sum = sum + inputValue * hiddenGradient;

        }

        gradientWeightLayer1[ index ] = sum;
        return;
    }

    // ---- Region 2: Bias gradients db1 (totalWeightElements .. end) ----
    let biasIndex : u32 = index - totalWeightElements;

    if (biasIndex < hiddenDimension) {

        var sumBias : f32 = 0.0;

        // db1[hiddenIndex] = sum over batch of gradientHidden[b, hiddenIndex]
        for (var batchIndex : u32 = 0u; batchIndex < batchSize; batchIndex = batchIndex + 1u) {

            let hiddenGradient = gradientHidden[ batchIndex * hiddenDimension + biasIndex ];

            sumBias = sumBias + hiddenGradient;

        }

        gradientBiasLayer1[ biasIndex ] = sumBias;
    }
}