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llama.cpp/ggml/src/ggml-vulkan/vulkan-shaders/rms_norm_back.comp
Rémy O 61d4f39dfe vulkan: implement more backpropagation operators (#11914)
* vulkan: implement GGML_OP_ROPE_BACK

* vulkan: implement GGML_OP_RMS_NORM_BACK

* vulkan: implement GGML_OP_SILU_BACK

* vulkan: implement GGML_OP_SOFTMAX_BACK
2025-02-25 12:04:45 +01:00

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#version 450
#include "generic_head.comp"
#include "types.comp"
#extension GL_EXT_control_flow_attributes : enable
#define BLOCK_SIZE 512
layout(local_size_x = BLOCK_SIZE, local_size_y = 1, local_size_z = 1) in;
layout (binding = 0) readonly buffer G {A_TYPE data_a[];};
layout (binding = 1) readonly buffer X {B_TYPE data_b[];};
layout (binding = 2) writeonly buffer D {D_TYPE data_d[];};
shared FLOAT_TYPE sum_xx[BLOCK_SIZE];
shared FLOAT_TYPE sum_xg[BLOCK_SIZE];
void main() {
const uint row = gl_WorkGroupID.z * 262144 + gl_WorkGroupID.y * 512 + gl_WorkGroupID.x;
const uint tid = gl_LocalInvocationID.x;
// Compute derivative of x[i]/norm(x) = g[i]/norm(x) - x[i] dot(x,g)/KX / norm(x)^1.5
// partial sums for thread in warp
sum_xx[tid] = FLOAT_TYPE(0.0f);
sum_xg[tid] = FLOAT_TYPE(0.0f);
[[unroll]] for (uint col = tid; col < p.KX; col += BLOCK_SIZE) {
const FLOAT_TYPE gi = FLOAT_TYPE(data_a[row*p.KX + col]);
const FLOAT_TYPE xi = FLOAT_TYPE(data_b[row*p.KX + col]);
sum_xx[tid] += xi * xi;
sum_xg[tid] += xi * gi;
}
// sum up partial sums and write back result
barrier();
[[unroll]] for (int s = BLOCK_SIZE / 2; s > 0; s >>= 1) {
if (tid < s) {
sum_xx[tid] += sum_xx[tid + s];
sum_xg[tid] += sum_xg[tid + s];
}
barrier();
}
const FLOAT_TYPE eps = FLOAT_TYPE(p.param1);
const FLOAT_TYPE mean = sum_xx[0] / FLOAT_TYPE(p.KX);
const FLOAT_TYPE scale_g = inversesqrt(mean + eps);
const FLOAT_TYPE scale_x = -scale_g * sum_xg[0] / (sum_xx[0] + FLOAT_TYPE(p.KX) * eps);
[[unroll]] for (uint col = tid; col < p.KX; col += BLOCK_SIZE) {
data_d[row*p.KX + col] = D_TYPE(
scale_g * FLOAT_TYPE(data_a[row*p.KX + col]) +
scale_x * FLOAT_TYPE(data_b[row*p.KX + col]));
}
}