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#!/usr/bin/env python3
"""Patch infer.m with TurboQuant integration."""
with open("/Users/carl/projects/turbomoe/flash_moe/metal_infer/infer.m") as f:
src = f.read()
# CHANGE 1: Constants
c1_old = """#define NUM_EXPERTS_PER_TOK 10
#define MOE_INTERMEDIATE 1024"""
c1_new = """#define NUM_EXPERTS_PER_TOK 10
// TurboQuant KV-cache compression (TurboMoE)
#define GPU_TQ_SEQ GPU_KV_SEQ
#define TQ_WORDS_PER_HEAD (HEAD_DIM / 16) // 16 for 2-bit (16 indices per uint32)
#define MOE_INTERMEDIATE 1024"""
assert c1_old in src, "CHANGE 1 anchor not found"
src = src.replace(c1_old, c1_new, 1)
print("✓ CHANGE 1: constants added")
# CHANGE 2: Struct
c2_old = """ id<MTLBuffer> buf_attn_out; // [NUM_ATTN_HEADS * HEAD_DIM floats] full attention output
id<MTLBuffer> buf_attn_gate; // [NUM_ATTN_HEADS * HEAD_DIM floats] sigmoid gate
// CMD3 GPU-side combine buffers"""
c2_new = """ id<MTLBuffer> buf_attn_out; // [NUM_ATTN_HEADS * HEAD_DIM floats] full attention output
id<MTLBuffer> buf_attn_gate; // [NUM_ATTN_HEADS * HEAD_DIM floats] sigmoid gate
// TurboQuant KV-cache compression (TurboMoE)
id<MTLBuffer> buf_tq_k_packed[NUM_FULL_ATTN_LAYERS]; // [GPU_TQ_SEQ, NUM_KV_HEADS, TQ_WORDS_PER_HEAD] uint32
id<MTLBuffer> buf_tq_k_norms[NUM_FULL_ATTN_LAYERS]; // [GPU_TQ_SEQ, NUM_KV_HEADS] float32
id<MTLBuffer> buf_tq_v_packed[NUM_FULL_ATTN_LAYERS]; // [GPU_TQ_SEQ, NUM_KV_HEADS, TQ_WORDS_PER_HEAD] uint32
id<MTLBuffer> buf_tq_v_norms[NUM_FULL_ATTN_LAYERS]; // [GPU_TQ_SEQ, NUM_KV_HEADS] float32
id<MTLBuffer> buf_tq_rot; // [HEAD_DIM * HEAD_DIM] float32 — orthogonal Pi
id<MTLBuffer> buf_tq_inv_rot; // [HEAD_DIM * HEAD_DIM] float32 — Pi^T
id<MTLBuffer> buf_tq_encode_k; // [NUM_KV_HEADS * HEAD_DIM] fp32
id<MTLBuffer> buf_tq_encode_v; // [NUM_KV_HEADS * HEAD_DIM] fp32
id<MTLBuffer> buf_tq_encode_k_norms; // [NUM_KV_HEADS] fp32
id<MTLBuffer> buf_tq_encode_v_norms; // [NUM_KV_HEADS] fp32
id<MTLComputePipelineState> tq_fused_attn_pipe;
id<MTLComputePipelineState> tq_encode_pipe;
id<MTLComputePipelineState> tq_pack_update_pipe;
id<MTLComputePipelineState> tq_dequant_pipe;
int use_tq_kv; // 1 = compressed KV, 0 = float KV
// CMD3 GPU-side combine buffers"""
assert c2_old in src, "CHANGE 2 anchor not found"
src = src.replace(c2_old, c2_new, 1)
print("✓ CHANGE 2: struct members added")
# CHANGE 3: Pipeline creation
c3_old = """ ctx->sigmoid_gate_pipe = makePipe(@"sigmoid_gate");
ctx->moe_combine_residual = makePipe(@"moe_combine_residual");"""
c3_new = """ ctx->sigmoid_gate_pipe = makePipe(@"sigmoid_gate");
ctx->tq_fused_attn_pipe = makePipe(@"tq_fused_attention");
ctx->tq_encode_pipe = makePipe(@"tq_encode_packed");
ctx->tq_pack_update_pipe = makePipe(@"tq_pack_update");
ctx->tq_dequant_pipe = makePipe(@"tq_dequant_all");
if (!ctx->tq_fused_attn_pipe) {
fprintf(stderr, "[metal] WARNING: tq_fused_attention not available -- TurboQuant disabled\\n");
} else {
printf("[metal] TurboQuant pipelines ready\\n");
}
ctx->moe_combine_residual = makePipe(@"moe_combine_residual");"""
assert c3_old in src, "CHANGE 3 anchor not found"
src = src.replace(c3_old, c3_new, 1)
print("✓ CHANGE 3: pipeline creation added")
# CHANGE 4: Buffer allocation
c4_old = """ ctx->buf_attn_gate = [ctx->device newBufferWithLength:NUM_ATTN_HEADS * HEAD_DIM * sizeof(float)
options:MTLResourceStorageModeShared];
printf("[metal] GPU attention buffers:"""
c4_new = """ ctx->buf_attn_gate = [ctx->device newBufferWithLength:NUM_ATTN_HEADS * HEAD_DIM * sizeof(float)
options:MTLResourceStorageModeShared];
// TurboQuant KV-cache buffers (compressed)
{
size_t tq_packed_size = (size_t)GPU_TQ_SEQ * NUM_KV_HEADS * TQ_WORDS_PER_HEAD * sizeof(uint32_t);
size_t tq_norm_size = (size_t)GPU_TQ_SEQ * NUM_KV_HEADS * sizeof(float);
size_t rot_size = (size_t)HEAD_DIM * HEAD_DIM * sizeof(float);
size_t encode_kv_size = NUM_KV_HEADS * HEAD_DIM * sizeof(float);
size_t encode_norms_size = NUM_KV_HEADS * sizeof(float);
for (int i = 0; i < NUM_FULL_ATTN_LAYERS; i++) {
ctx->buf_tq_k_packed[i] = [ctx->device newBufferWithLength:tq_packed_size
options:MTLResourceStorageModeShared];
ctx->buf_tq_k_norms[i] = [ctx->device newBufferWithLength:tq_norm_size
options:MTLResourceStorageModeShared];
ctx->buf_tq_v_packed[i] = [ctx->device newBufferWithLength:tq_packed_size
options:MTLResourceStorageModeShared];
ctx->buf_tq_v_norms[i] = [ctx->device newBufferWithLength:tq_norm_size
options:MTLResourceStorageModeShared];
}
ctx->buf_tq_rot = [ctx->device newBufferWithLength:rot_size options:MTLResourceStorageModeShared];
ctx->buf_tq_inv_rot = [ctx->device newBufferWithLength:rot_size options:MTLResourceStorageModeShared];
ctx->buf_tq_encode_k = [ctx->device newBufferWithLength:encode_kv_size options:MTLResourceStorageModeShared];
ctx->buf_tq_encode_v = [ctx->device newBufferWithLength:encode_kv_size options:MTLResourceStorageModeShared];
ctx->buf_tq_encode_k_norms = [ctx->device newBufferWithLength:encode_norms_size options:MTLResourceStorageModeShared];
ctx->buf_tq_encode_v_norms = [ctx->device newBufferWithLength:encode_norms_size options:MTLResourceStorageModeShared];
// Generate orthogonal rotation matrix Pi via QR decomposition (seeded)
float *Q = (float *)malloc(HEAD_DIM * HEAD_DIM * sizeof(float));
srand(42);
for (int i = 0; i < HEAD_DIM * HEAD_DIM; i++) Q[i] = (float)(rand() % 1000 - 500) / 500.0f;
for (int j = 0; j < HEAD_DIM; j++) {
for (int i = 0; i < HEAD_DIM; i++) {
float dot = 0.0f;
for (int k = 0; k < j; k++) dot += Q[k * HEAD_DIM + i] * Q[k * HEAD_DIM + j];
Q[j * HEAD_DIM + i] -= dot * Q[j * HEAD_DIM + i];
}
float norm = 0.0f;
for (int k = 0; k < HEAD_DIM; k++) norm += Q[k * HEAD_DIM + j] * Q[k * HEAD_DIM + j];
norm = sqrtf(norm + 1e-8f);
for (int k = 0; k < HEAD_DIM; k++) Q[j * HEAD_DIM + k] /= norm;
}
float *rot_ptr = (float *)[ctx->buf_tq_rot contents];
float *inv_ptr = (float *)[ctx->buf_tq_inv_rot contents];
memcpy(rot_ptr, Q, HEAD_DIM * HEAD_DIM * sizeof(float));
for (int i = 0; i < HEAD_DIM; i++)
for (int j = 0; j < HEAD_DIM; j++)
inv_ptr[i * HEAD_DIM + j] = rot_ptr[j * HEAD_DIM + i];
free(Q);
printf("[metal] TurboQuant: %d layers x %.1f KB/layer KV\\n",
NUM_FULL_ATTN_LAYERS, (double)(tq_packed_size * 2 + tq_norm_size * 2) / 1e3);
ctx->use_tq_kv = (getenv("TQ_KV") && atoi(getenv("TQ_KV")) == 1) ? 1 : 0;
if (ctx->use_tq_kv && !ctx->tq_fused_attn_pipe) {
fprintf(stderr, "[metal] TQ_KV=1 but TurboQuant pipelines unavailable -- falling back\\n");
ctx->use_tq_kv = 0;
}
if (ctx->use_tq_kv) printf("[metal] TurboQuant KV compression ENABLED\\n");
}
printf("[metal] GPU attention buffers:"""
assert c4_old in src, "CHANGE 4 anchor not found"
src = src.replace(c4_old, c4_new, 1)
print("✓ CHANGE 4: buffer allocation added")
# CHANGE 5: KV cache update hook
c5_old = """ if (g_metal && g_metal->attn_scores_pipe && fa_idx >= 0 && fa_idx < NUM_FULL_ATTN_LAYERS) {
memcpy((float *)[g_metal->buf_kv_k[fa_idx] contents] + cache_pos * kv_dim,
k_out, kv_dim * sizeof(float));
memcpy((float *)[g_metal->buf_kv_v[fa_idx] contents] + cache_pos * kv_dim,
v_out, kv_dim * sizeof(float));
}
kv->len++;
// Scaled dot-product attention (GQA)"""
c5_new = """ if (g_metal && g_metal->attn_scores_pipe && fa_idx >= 0 && fa_idx < NUM_FULL_ATTN_LAYERS) {
memcpy((float *)[g_metal->buf_kv_k[fa_idx] contents] + cache_pos * kv_dim,
k_out, kv_dim * sizeof(float));
memcpy((float *)[g_metal->buf_kv_v[fa_idx] contents] + cache_pos * kv_dim,
v_out, kv_dim * sizeof(float));
}
// TurboQuant KV cache update — compress and append to compressed cache
if (g_metal && g_metal->use_tq_kv && g_metal->tq_pack_update_pipe) {
int tq_fa_idx = fa_idx;
uint32_t pos32 = (uint32_t)cache_pos;
uint32_t GPU_TQ_SEQ32 = GPU_TQ_SEQ;
float *encode_k = (float *)[g_metal->buf_tq_encode_k contents];
float *encode_v = (float *)[g_metal->buf_tq_encode_v contents];
float *encode_k_norms = (float *)[g_metal->buf_tq_encode_k_norms contents];
float *encode_v_norms = (float *)[g_metal->buf_tq_encode_v_norms contents];
memcpy(encode_k, k_out, NUM_KV_HEADS * HEAD_DIM * sizeof(float));
memcpy(encode_v, v_out, NUM_KV_HEADS * HEAD_DIM * sizeof(float));
for (int kv_h = 0; kv_h < NUM_KV_HEADS; kv_h++) {
float k_sq = 0.0f, v_sq = 0.0f;
for (int d = 0; d < HEAD_DIM; d++) {
float kd = encode_k[kv_h * HEAD_DIM + d];
float vd = encode_v[kv_h * HEAD_DIM + d];
k_sq += kd * kd; v_sq += vd * vd;
}
encode_k_norms[kv_h] = sqrtf(k_sq + RMS_NORM_EPS);
encode_v_norms[kv_h] = sqrtf(v_sq + RMS_NORM_EPS);
}
id<MTLCommandBuffer> tq_cmd = [g_metal->queue commandBuffer];
id<MTLComputeCommandEncoder> tq_enc = [tq_cmd computeCommandEncoder];
[tq_enc setComputePipelineState:g_metal->tq_pack_update_pipe];
[tq_enc setBuffer:encode_k offset:0 atIndex:0];
[tq_enc setBuffer:encode_v offset:0 atIndex:1];
[tq_enc setBuffer:(float *)[g_metal->buf_tq_rot contents] offset:0 atIndex:2];
[tq_enc setBuffer:(uint32_t *)[g_metal->buf_tq_k_packed[tq_fa_idx] contents] offset:0 atIndex:3];
[tq_enc setBuffer:encode_k_norms offset:0 atIndex:4];
[tq_enc setBuffer:(uint32_t *)[g_metal->buf_tq_v_packed[tq_fa_idx] contents] offset:0 atIndex:5];
[tq_enc setBuffer:encode_v_norms offset:0 atIndex:6];
[tq_enc setBytes:&pos32 offset:0 atIndex:7];
[tq_enc setBytes:&GPU_TQ_SEQ32 offset:0 atIndex:8];
[tq_enc dispatchThreadgroups:MTLSizeMake(NUM_KV_HEADS * TQ_WORDS_PER_HEAD, 1, 1)
threadsPerThreadgroup:MTLSizeMake(32, 1, 1)];
[tq_enc endEncoding];
[tq_cmd commit];
[tq_cmd waitUntilCompleted];
}
kv->len++;
// Scaled dot-product attention (GQA)"""
assert c5_old in src, "CHANGE 5 anchor not found"
src = src.replace(c5_old, c5_new, 1)
print("✓ CHANGE 5: KV cache update hook added")
# CHANGE 6: Add TurboQuant dispatch before Enc A1
c6_old = """ // Enc A1: attn_scores_batched
{
id<MTLComputeCommandEncoder> enc = [cmd_fused computeCommandEncoder];
[enc setComputePipelineState:g_metal->attn_scores_pipe];
[enc setBuffer:g_metal->buf_attn_q offset:0 atIndex:0];
[enc setBuffer:g_metal->buf_kv_k[fa_idx] offset:0 atIndex:1];
[enc setBuffer:g_metal->buf_attn_scores offset:0 atIndex:2];
[enc setBytes:&hd length:4 atIndex:3];
[enc setBytes:&kvd length:4 atIndex:4];
[enc setBytes:&sl length:4 atIndex:5];
[enc setBytes:&seq_stride length:4 atIndex:6];
[enc setBytes:&scale length:4 atIndex:7];
[enc setBytes:&hpkv length:4 atIndex:8];
[enc setBytes:&sl length:4 atIndex:9];
uint32_t total_tgs = sl * NUM_ATTN_HEADS;
[enc dispatchThreadgroups:MTLSizeMake(total_tgs, 1, 1)
threadsPerThreadgroup:MTLSizeMake(256, 1, 1)];
[enc endEncoding];
}"""
c6_new = """ // TurboQuant fused attention: 1 dispatch instead of 3 (Enc A1+A2+A3)
if (g_metal->use_tq_kv && g_metal->tq_fused_attn_pipe) {
uint32_t T_kv32 = sl;
uint32_t causal_offset32 = 0;
uint32_t GPU_TQ_SEQ32 = GPU_TQ_SEQ;
id<MTLComputeCommandEncoder> enc = [cmd_fused computeCommandEncoder];
[enc setComputePipelineState:g_metal->tq_fused_attn_pipe];
[enc setBuffer:g_metal->buf_attn_q offset:0 atIndex:0];
[enc setBuffer:g_metal->buf_attn_gate offset:0 atIndex:1];
[enc setBuffer:(uint32_t *)[g_metal->buf_tq_k_packed[fa_idx] contents] offset:0 atIndex:2];
[enc setBuffer:(float *)[g_metal->buf_tq_k_norms[fa_idx] contents] offset:0 atIndex:3];
[enc setBuffer:(uint32_t *)[g_metal->buf_tq_v_packed[fa_idx] contents] offset:0 atIndex:4];
[enc setBuffer:(float *)[g_metal->buf_tq_v_norms[fa_idx] contents] offset:0 atIndex:5];
[enc setBuffer:(float *)[g_metal->buf_tq_rot contents] offset:0 atIndex:6];
[enc setBuffer:(float *)[g_metal->buf_tq_inv_rot contents] offset:0 atIndex:7];
[enc setBuffer:g_metal->buf_attn_out offset:0 atIndex:8];
[enc setBytes:&T_kv32 length:4 atIndex:9];
[enc setBytes:&GPU_TQ_SEQ32 length:4 atIndex:10];
[enc setBytes:&causal_offset32 length:4 atIndex:11];
[enc dispatchThreadgroups:MTLSizeMake(NUM_ATTN_HEADS * 256, 1, 1)
threadsPerThreadgroup:MTLSizeMake(256, 1, 1)];
[enc endEncoding];
} else {
// Enc A1: attn_scores_batched
{
id<MTLComputeCommandEncoder> enc = [cmd_fused computeCommandEncoder];
[enc setComputePipelineState:g_metal->attn_scores_pipe];
[enc setBuffer:g_metal->buf_attn_q offset:0 atIndex:0];
[enc setBuffer:g_metal->buf_kv_k[fa_idx] offset:0 atIndex:1];
[enc setBuffer:g_metal->buf_attn_scores offset:0 atIndex:2];
[enc setBytes:&hd length:4 atIndex:3];
[enc setBytes:&kvd length:4 atIndex:4];
[enc setBytes:&sl length:4 atIndex:5];
[enc setBytes:&seq_stride length:4 atIndex:6];
[enc setBytes:&scale length:4 atIndex:7];
[enc setBytes:&hpkv length:4 atIndex:8];
[enc setBytes:&sl length:4 atIndex:9];
uint32_t total_tgs = sl * NUM_ATTN_HEADS;
[enc dispatchThreadgroups:MTLSizeMake(total_tgs, 1, 1)
threadsPerThreadgroup:MTLSizeMake(256, 1, 1)];
[enc endEncoding];
}"""
assert c6_old in src, "CHANGE 6 anchor not found"
src = src.replace(c6_old, c6_new, 1)
print("✓ CHANGE 6: TurboQuant attention dispatch added")
# CHANGE 7: Close else after attn_values
c7_old = """ [enc setBytes:&hpkv length:4 atIndex:7];
uint32_t total_threads = HEAD_DIM * NUM_ATTN_HEADS;
uint32_t tgs = (total_threads + 255) / 256;
[enc dispatchThreadgroups:MTLSizeMake(tgs, 1, 1)
threadsPerThreadgroup:MTLSizeMake(256, 1, 1)];
[enc endEncoding];
}"""
c7_new = """ [enc setBytes:&hpkv length:4 atIndex:7];
uint32_t total_threads = HEAD_DIM * NUM_ATTN_HEADS;
uint32_t tgs = (total_threads + 255) / 256;
[enc dispatchThreadgroups:MTLSizeMake(tgs, 1, 1)
threadsPerThreadgroup:MTLSizeMake(256, 1, 1)];
[enc endEncoding];
} // end else (non-TurboQuant path)
}"""
assert c7_old in src, "CHANGE 7 anchor not found"
src = src.replace(c7_old, c7_new, 1)
print("✓ CHANGE 7: else block closed")
with open("/Users/carl/projects/turbomoe/flash_moe/metal_infer/infer.m", "w") as f:
f.write(src)
print("\nAll changes applied successfully.")
print("Next: cat turboquant/turboquant.metal >> metal_infer/shaders.metal")