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https://github.com/ggml-org/llama.cpp.git
synced 2026-11-11 22:32:07 +01:00
vulkan: Multi-pass softmax for large number of cols (#17892)
When the number of cols is large, split each row across multiple workgroups. There are three phases that communicate partial results through temp buffers: (1) compute max partials (2) take max of partials, compute sum(exp(x-max)) partials (3) sum partials, compute scaled result
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#version 450
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#include "soft_max_large_common.glsl"
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void main() {
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const uint tid = gl_LocalInvocationID.x;
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const uint rowx = gl_WorkGroupID.y;
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const uint wg_start = gl_WorkGroupID.x * BLOCK_SIZE * num_iters;
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const uint32_t i03 = rowx / (p.ne01 * p.ne02);
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const uint32_t i02 = (rowx - i03 * p.ne01 * p.ne02) / p.ne01;
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const uint32_t i01 = rowx % p.ne01;
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uint rowy_start = 0;
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if (p.KY > 0) {
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rowy_start = i01 * p.nb11 + (i02 % p.ne12) * p.nb12 + (i03 % p.ne13) * p.nb13;
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}
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if (rowx >= p.nrows_x) {
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return;
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}
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float slope = get_slope(rowx);
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// Find max
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FLOAT_TYPE max_val = p.has_sinks == 0 ? uintBitsToFloat(0xFF800000) : data_c[i02];
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[[unroll]] for (uint col0 = wg_start, idx = 0; idx < num_iters; col0 += BLOCK_SIZE, ++idx) {
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const uint col = col0 + tid;
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FLOAT_TYPE a = FLOAT_TYPE(0);
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if (col < p.KX) {
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a = data_a[rowx * p.KX + col];
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}
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FLOAT_TYPE b = FLOAT_TYPE(0);
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if (p.KY > 0 && col < p.KX) {
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b = data_b[rowy_start + col];
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}
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FLOAT_TYPE v = a * p.scale + slope * b;
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if (col < p.KX) {
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max_val = max(max_val, v);
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}
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}
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// reduce across the workgroup
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vals[tid] = max_val;
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barrier();
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[[unroll]] for (uint s = BLOCK_SIZE / 2; s > 0; s >>= 1) {
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if (tid < s) {
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vals[tid] = max(vals[tid], vals[tid + s]);
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}
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barrier();
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}
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if (tid == 0) {
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max_val = vals[0];
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data_m[rowx * gl_NumWorkGroups.x + gl_WorkGroupID.x] = max_val;
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}
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}
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@@ -0,0 +1,79 @@
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#version 450
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#include "soft_max_large_common.glsl"
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void main() {
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const uint tid = gl_LocalInvocationID.x;
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const uint rowx = gl_WorkGroupID.y;
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const uint wg_start = gl_WorkGroupID.x * BLOCK_SIZE * num_iters;
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const uint32_t i03 = rowx / (p.ne01 * p.ne02);
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const uint32_t i02 = (rowx - i03 * p.ne01 * p.ne02) / p.ne01;
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const uint32_t i01 = rowx % p.ne01;
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uint rowy_start = 0;
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if (p.KY > 0) {
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rowy_start = i01 * p.nb11 + (i02 % p.ne12) * p.nb12 + (i03 % p.ne13) * p.nb13;
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}
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if (rowx >= p.nrows_x) {
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return;
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}
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float slope = get_slope(rowx);
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// Find max
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FLOAT_TYPE max_val = p.has_sinks == 0 ? uintBitsToFloat(0xFF800000) : data_c[i02];
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[[unroll]] for (uint i = 0; i < gl_NumWorkGroups.x; i += BLOCK_SIZE) {
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if (i + tid < gl_NumWorkGroups.x) {
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max_val = max(max_val, data_m[rowx * gl_NumWorkGroups.x + i + tid]);
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}
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}
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// reduce across the workgroup
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vals[tid] = max_val;
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barrier();
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[[unroll]] for (uint s = BLOCK_SIZE / 2; s > 0; s >>= 1) {
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if (tid < s) {
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vals[tid] = max(max_val, vals[tid + s]);
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}
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barrier();
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}
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max_val = vals[0];
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barrier();
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FLOAT_TYPE sum = FLOAT_TYPE(0.0f);
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// Compute sum{exp(x - max)}
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[[unroll]] for (uint col0 = wg_start, idx = 0; idx < num_iters; col0 += BLOCK_SIZE, ++idx) {
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const uint col = col0 + tid;
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if (col >= p.KX) {
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break;
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}
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// compute exp(a*scale+b*slope), add it to sum
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const uint i = rowx * p.KX + col;
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FLOAT_TYPE val;
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val = exp(FLOAT_TYPE(data_a[i]) * p.scale + (p.KY > 0 ? slope * FLOAT_TYPE(data_b[rowy_start + col]) : FLOAT_TYPE(0.0f)) - max_val);
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sum += val;
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data_d[i] = D_TYPE(val);
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}
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// reduce across the workgroup
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vals[tid] = sum;
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barrier();
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[[unroll]] for (uint s = BLOCK_SIZE / 2; s > 0; s >>= 1) {
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if (tid < s) {
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vals[tid] += vals[tid + s];
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}
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barrier();
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}
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if (tid == 0) {
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sum = vals[0];
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data_s[rowx * gl_NumWorkGroups.x + gl_WorkGroupID.x] = sum;
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}
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}
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@@ -0,0 +1,65 @@
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#version 450
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#include "soft_max_large_common.glsl"
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shared FLOAT_TYPE sumsh[BLOCK_SIZE];
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void main() {
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const uint tid = gl_LocalInvocationID.x;
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const uint rowx = gl_WorkGroupID.y;
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const uint wg_start = gl_WorkGroupID.x * BLOCK_SIZE * num_iters;
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const uint32_t i03 = rowx / (p.ne01 * p.ne02);
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const uint32_t i02 = (rowx - i03 * p.ne01 * p.ne02) / p.ne01;
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const uint32_t i01 = rowx % p.ne01;
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uint rowy_start = 0;
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if (p.KY > 0) {
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rowy_start = i01 * p.nb11 + (i02 % p.ne12) * p.nb12 + (i03 % p.ne13) * p.nb13;
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}
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if (rowx >= p.nrows_x) {
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return;
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}
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FLOAT_TYPE max_val = p.has_sinks == 0 ? uintBitsToFloat(0xFF800000) : data_c[i02];
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FLOAT_TYPE sum = FLOAT_TYPE(0.0f);
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[[unroll]] for (uint i = 0; i < gl_NumWorkGroups.x; i += BLOCK_SIZE) {
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if (i + tid < gl_NumWorkGroups.x) {
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max_val = max(max_val, data_m[rowx * gl_NumWorkGroups.x + i + tid]);
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sum += data_s[rowx * gl_NumWorkGroups.x + i + tid];
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}
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}
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// reduce across the workgroup
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vals[tid] = max_val;
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sumsh[tid] = sum;
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barrier();
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[[unroll]] for (uint s = BLOCK_SIZE / 2; s > 0; s >>= 1) {
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if (tid < s) {
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vals[tid] = max(max_val, vals[tid + s]);
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sumsh[tid] += sumsh[tid + s];
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}
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barrier();
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}
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max_val = vals[0];
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sum = sumsh[0];
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if (p.has_sinks != 0) {
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sum += FLOAT_TYPE(exp(FLOAT_TYPE(data_c[i02]) - max_val));
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}
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FLOAT_TYPE rcpdivisor = 1.0/sum;
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[[unroll]] for (uint col0 = wg_start, idx = 0; idx < num_iters; col0 += BLOCK_SIZE, ++idx) {
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const uint col = col0 + tid;
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if (col >= p.KX) {
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continue;
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}
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data_d[rowx*p.KX + col] *= D_TYPE(rcpdivisor);
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}
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}
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@@ -0,0 +1,53 @@
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#extension GL_EXT_control_flow_attributes : enable
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layout (push_constant) uniform parameter
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{
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uint KX;
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uint KY;
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uint ne00;
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uint ne01;
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uint ne02;
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uint ne12;
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uint ne13;
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uint nb11;
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uint nb12;
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uint nb13;
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float scale;
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float max_bias;
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float m0;
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float m1;
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uint n_head_log2;
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uint nrows_x;
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uint has_sinks;
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} p;
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#include "types.glsl"
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layout(constant_id = 0) const uint BLOCK_SIZE = 128;
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layout(local_size_x_id = 0, local_size_y = 1, local_size_z = 1) in;
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layout(constant_id = 1) const uint num_iters = 4;
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layout (binding = 0) readonly buffer X {A_TYPE data_a[];};
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layout (binding = 1) readonly buffer Y {B_TYPE data_b[];};
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layout (binding = 2) readonly buffer Z {float data_c[];};
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layout (binding = 3) buffer D {D_TYPE data_d[];};
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layout (binding = 4) buffer M {float data_m[];};
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layout (binding = 5) buffer S {float data_s[];};
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shared FLOAT_TYPE vals[BLOCK_SIZE];
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float get_slope(uint rowx) {
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float slope = 1.0f;
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// ALiBi
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if (p.max_bias > 0.0f) {
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const uint h = (rowx / p.ne01) % p.ne02; // head index
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const float base = h < p.n_head_log2 ? p.m0 : p.m1;
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const uint exp = h < p.n_head_log2 ? h + 1 : 2*(h - p.n_head_log2) + 1;
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slope = pow(base, exp);
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}
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return slope;
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}
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@@ -899,6 +899,13 @@ void process_shaders() {
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string_to_spv("soft_max_f32_f16", "soft_max.comp", merge_maps(base_dict, {{"A_TYPE", "float"}, {"B_TYPE", "float16_t"}, {"D_TYPE", "float"}}));
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string_to_spv("soft_max_back_f32", "soft_max_back.comp", merge_maps(base_dict, {{"A_TYPE", "float"}, {"B_TYPE", "float"}, {"D_TYPE", "float"}}));
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string_to_spv("soft_max_large1_f32", "soft_max_large1.comp", merge_maps(base_dict, {{"A_TYPE", "float"}, {"B_TYPE", "float"}, {"D_TYPE", "float"}}));
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string_to_spv("soft_max_large2_f32", "soft_max_large2.comp", merge_maps(base_dict, {{"A_TYPE", "float"}, {"B_TYPE", "float"}, {"D_TYPE", "float"}}));
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string_to_spv("soft_max_large3_f32", "soft_max_large3.comp", merge_maps(base_dict, {{"A_TYPE", "float"}, {"B_TYPE", "float"}, {"D_TYPE", "float"}}));
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string_to_spv("soft_max_large1_f32_f16", "soft_max_large1.comp", merge_maps(base_dict, {{"A_TYPE", "float"}, {"B_TYPE", "float16_t"}, {"D_TYPE", "float"}}));
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string_to_spv("soft_max_large2_f32_f16", "soft_max_large2.comp", merge_maps(base_dict, {{"A_TYPE", "float"}, {"B_TYPE", "float16_t"}, {"D_TYPE", "float"}}));
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string_to_spv("soft_max_large3_f32_f16", "soft_max_large3.comp", merge_maps(base_dict, {{"A_TYPE", "float"}, {"B_TYPE", "float16_t"}, {"D_TYPE", "float"}}));
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string_to_spv("rope_norm_f32", "rope_norm.comp", {{"A_TYPE", "float"}, {"ROPE_D_TYPE", "float"}});
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string_to_spv("rope_norm_f16", "rope_norm.comp", {{"A_TYPE", "float16_t"}, {"ROPE_D_TYPE", "float16_t"}});
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string_to_spv("rope_norm_f16_rte", "rope_norm.comp", {{"A_TYPE", "float16_t"}, {"ROPE_D_TYPE", "float16_t"}, {"RTE16", "1"}});
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