// Mechanical adaptation of OA's output-saved LogSoftmax adjoint.
// Donor: source/cpp/lib/oa/ml/shader/compute/nn/softmax/logSoftmaxBwd.slang
import storage;
import attributes;
struct PushConstants {
uint forward_output_index;
uint output_gradient_index;
uint input_gradient_index;
uint outer_size;
uint dim_size;
uint inner_size;
};
[[vk::push_constant]] PushConstants push;
[[vk::binding(0, 0)]] RWByteAddressBuffer storage_buffers[];
// Separate read and write banks preserve the donor's barrier-safe reduction.
groupshared float reduction[2][256];
[kernel_name("log_softmax_backward")]
[domain("matrix")]
[variant("generic")]
[dtype("f32")]
[status("experimental")]
[shader("compute")]
[numthreads(256, 1, 1)]
void main(uint3 group_id : SV_GroupID, uint3 group_thread_id : SV_GroupThreadID) {
uint group = group_id.x;
uint lane = group_thread_id.x;
if (group >= push.outer_size * push.inner_size) {
return;
}
uint outer = group / push.inner_size;
uint inner = group % push.inner_size;
uint base = outer * push.dim_size * push.inner_size + inner;
uint read_bank = 0;
uint write_bank = 1;
float local_sum = 0.0f;
for (uint index = lane; index < push.dim_size; index += 256) {
local_sum += load_f32(
storage_buffers[push.output_gradient_index], base + index * push.inner_size
);
}
reduction[read_bank][lane] = local_sum;
GroupMemoryBarrierWithGroupSync();
for (uint width = 128; width > 0; width >>= 1) {
if (lane < width) {
reduction[write_bank][lane] =
reduction[read_bank][lane] + reduction[read_bank][lane + width];
}
GroupMemoryBarrierWithGroupSync();
uint previous_read_bank = read_bank;
read_bank = write_bank;
write_bank = previous_read_bank;
}
float gradient_sum = reduction[read_bank][0];
for (uint index = lane; index < push.dim_size; index += 256) {
uint element = base + index * push.inner_size;
float output = load_f32(storage_buffers[push.forward_output_index], element);
float upstream = load_f32(storage_buffers[push.output_gradient_index], element);
store_f32(
storage_buffers[push.input_gradient_index],
element,
upstream - exp(output) * gradient_sum
);
}
}