mirror of
https://github.com/ggerganov/llama.cpp.git
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7c7836d9d4
* Refactor shaders, extract GLSL code from ggml_vk_generate_shaders.py into vulkan-shaders directory * Improve debug log code * Add memory debug output option * Fix flake8 * Fix unnecessary high llama-3 VRAM use
45 lines
1.2 KiB
Plaintext
45 lines
1.2 KiB
Plaintext
#version 450
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#include "generic_head.comp"
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#include "types.comp"
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#extension GL_EXT_control_flow_attributes : enable
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#define BLOCK_SIZE 512
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layout(local_size_x = BLOCK_SIZE, local_size_y = 1, local_size_z = 1) in;
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layout (binding = 0) readonly buffer X {A_TYPE data_a[];};
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layout (binding = 1) writeonly buffer D {D_TYPE data_d[];};
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shared vec2 sum[BLOCK_SIZE];
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void main() {
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const uint row = gl_WorkGroupID.x;
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const uint tid = gl_LocalInvocationID.x;
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sum[tid] = vec2(0.0f, 0.0f);
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[[unroll]] for (uint col = tid; col < p.KX; col += BLOCK_SIZE) {
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const float xi = float(data_a[row*p.KX + col]);
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sum[tid].x += xi;
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sum[tid].y += xi * xi;
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}
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// sum up partial sums and write back result
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barrier();
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[[unroll]] for (int s = BLOCK_SIZE / 2; s > 0; s >>= 1) {
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if (tid < s) {
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sum[tid] += sum[tid + s];
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}
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barrier();
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}
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const float mean = sum[0].x / p.KX;
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const float var = sum[0].y / p.KX - mean * mean;
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const float inv_std = inversesqrt(var + p.param1);
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[[unroll]] for (uint col = tid; col < p.KX; col += BLOCK_SIZE) {
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data_d[row*p.KX + col] = D_TYPE((float(data_a[row*p.KX + col]) - mean) * inv_std);
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}
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}
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