// AdamW-owned in-place FP32 update over stable parameter and moment storage.
import storage;
import attributes;
struct PushConstants {
uint parameter_index;
uint gradient_index;
uint first_moment_index;
uint second_moment_index;
uint element_count;
uint step;
float learning_rate;
float beta1;
float beta2;
float epsilon;
float weight_decay;
};
[[vk::push_constant]] PushConstants push;
[[vk::binding(0, 0)]] RWByteAddressBuffer storage_buffers[];
[kernel_name("adamw")]
[domain("ml")]
[variant("generic")]
[dtype("f32")]
[status("experimental")]
[shader("compute")]
[numthreads(256, 1, 1)]
void main(uint3 dispatch_thread_id : SV_DispatchThreadID) {
uint index = dispatch_thread_id.x;
if (index >= push.element_count) {
return;
}
float parameter = load_f32(storage_buffers[push.parameter_index], index);
float gradient = load_f32(storage_buffers[push.gradient_index], index);
float first_moment = load_f32(storage_buffers[push.first_moment_index], index);
float second_moment = load_f32(storage_buffers[push.second_moment_index], index);
parameter -= push.learning_rate * push.weight_decay * parameter;
float next_first_moment = push.beta1 * first_moment + (1.0f - push.beta1) * gradient;
float next_second_moment = push.beta2 * second_moment
+ (1.0f - push.beta2) * gradient * gradient;
float first_hat = next_first_moment / (1.0f - pow(push.beta1, float(push.step)));
float second_hat = next_second_moment / (1.0f - pow(push.beta2, float(push.step)));
parameter -= push.learning_rate * first_hat / (sqrt(second_hat) + push.epsilon);
store_f32(storage_buffers[push.parameter_index], index, parameter);
store_f32(storage_buffers[push.first_moment_index], index, next_first_moment);
store_f32(storage_buffers[push.second_moment_index], index, next_second_moment);
}