// Mechanically adapted from OA C++:
// source/cpp/lib/oa/ml/shader/compute/nn/softmax/softmaxScaledMaskedN32.slang
import storage;
import attributes;
struct PushConstants {
uint scores_index;
uint mask_index;
uint output_index;
uint rows;
uint columns;
float scale;
};
[[vk::push_constant]] PushConstants push;
[[vk::binding(0, 0)]] RWByteAddressBuffer storage_buffers[];
groupshared float shared_maximum[32];
groupshared float shared_sum[32];
float reduce_maximum_32(float value, uint lane) {
float accumulator = value;
shared_maximum[lane] = accumulator;
GroupMemoryBarrierWithGroupSync();
for (uint stride = 16; stride > 0; stride >>= 1) {
if (lane < stride) {
accumulator = max(accumulator, shared_maximum[lane + stride]);
shared_maximum[lane] = accumulator;
}
GroupMemoryBarrierWithGroupSync();
}
return shared_maximum[0];
}
float reduce_sum_32(float value, uint lane) {
float accumulator = value;
shared_sum[lane] = accumulator;
GroupMemoryBarrierWithGroupSync();
for (uint stride = 16; stride > 0; stride >>= 1) {
if (lane < stride) {
accumulator += shared_sum[lane + stride];
shared_sum[lane] = accumulator;
}
GroupMemoryBarrierWithGroupSync();
}
return shared_sum[0];
}
[kernel_name("softmax_scaled_masked_n32")]
[domain("ml")]
[variant("n32")]
[dtype("f32")]
[status("experimental")]
[shader("compute")]
[numthreads(32, 1, 1)]
void main(uint3 group_id : SV_GroupID, uint3 group_thread_id : SV_GroupThreadID) {
uint row = group_id.x;
uint lane = group_thread_id.x;
if (row >= push.rows) {
return;
}
uint base = row * push.columns;
bool active = lane < push.columns;
float value = -3.402823466e+38f;
if (active) {
value = load_f32(storage_buffers[push.scores_index], base + lane) * push.scale;
value += load_f32(storage_buffers[push.mask_index], base + lane);
}
float row_maximum = reduce_maximum_32(value, lane);
float exponent = active ? exp(value - row_maximum) : 0.0;
float inverse_sum = 1.0 / reduce_sum_32(exponent, lane);
if (active) {
store_f32(storage_buffers[push.output_index], base + lane, exponent * inverse_sum);
}
}