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refactor: template AttentionParams, rename .cuh to .h

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- Convert AttentionParams to a template struct supporting arbitrary types
- Rename attn_common.cuh -> attn_common.h (no CUDA-specific code remains)
- Include standard headers explicitly in each .cuh instead of via attn_common.cuh
- Allow .h files in csrc/ via .gitignore
This commit is contained in:
ViperEkura
2026-07-11 11:03:14 +08:00
parent b8b439b713
commit 8a8550184f
13 changed files with 80 additions and 64 deletions
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csrc/tests/attn_decode_test.cu
+8 -8
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@@ -28,7 +28,7 @@ struct DecodeScratch {
float* ml_part = nullptr;
};
static int decode_num_splits(const AttentionParams& p, int tiles_total) {
static int decode_num_splits(const AttentionParams<bf16>& p, int tiles_total) {
int sm_count = 0;
cudaDeviceGetAttribute(&sm_count, cudaDevAttrMultiProcessorCount, 0);
int base_blocks = p.kv_head * p.batch;
@@ -41,13 +41,13 @@ static int decode_num_splits(const AttentionParams& p, int tiles_total) {
// Launch the production decode path (tensor-core head-packing MMA on sm_80+,
// scalar fallback otherwise), mirroring dispatch_decode() in attn_decode.cu.
#ifndef ASTRAI_NO_MMA
static bool decode_use_mma(const AttentionParams& p) {
static bool decode_use_mma(const AttentionParams<bf16>& p) {
int G = p.q_head / p.kv_head;
return !p.use_mask && G > 1 && G <= 16;
}
template <int HEAD_DIM, int BC>
static void launch_mma_decode(AttentionParams& p, DecodeScratch& sc) {
static void launch_mma_decode(AttentionParams<bf16>& p, DecodeScratch& sc) {
int tiles_total = (p.kv_len + BC - 1) / BC;
p.num_splits = decode_num_splits(p, tiles_total);
p.o_part = sc.o_part;
@@ -59,7 +59,7 @@ static void launch_mma_decode(AttentionParams& p, DecodeScratch& sc) {
}
#endif
static void launch_scalar_decode(AttentionParams& p, DecodeScratch& sc) {
static void launch_scalar_decode(AttentionParams<bf16>& p, DecodeScratch& sc) {
int gs = p.q_head / p.kv_head;
int chunks_total = (p.kv_len + DC_CHUNK - 1) / DC_CHUNK;
p.num_splits = decode_num_splits(p, chunks_total);
@@ -72,14 +72,14 @@ static void launch_scalar_decode(AttentionParams& p, DecodeScratch& sc) {
}
template <int HEAD_DIM>
static void dispatch_decode_t(AttentionParams& p, DecodeScratch& sc) {
static void dispatch_decode_t(AttentionParams<bf16>& p, DecodeScratch& sc) {
#ifndef ASTRAI_NO_MMA
if (decode_use_mma(p)) { launch_mma_decode<HEAD_DIM, 32>(p, sc); return; }
#endif
launch_scalar_decode(p, sc);
}
static void dispatch_decode(AttentionParams& p, DecodeScratch& sc) {
static void dispatch_decode(AttentionParams<bf16>& p, DecodeScratch& sc) {
switch (p.head_dim) {
case 32: dispatch_decode_t<32>(p, sc); break;
case 64: dispatch_decode_t<64>(p, sc); break;
@@ -164,7 +164,7 @@ static void bench() {
for (size_t i=0;i<nKV;i++) tmp[i]=f2bf(randf());
cudaMemcpy(dV,tmp,nKV*2,cudaMemcpyHostToDevice);
AttentionParams p;
AttentionParams<bf16> p;
p.batch=B; p.q_head=Hq; p.kv_head=Hk; p.q_len=1; p.kv_len=sl; p.head_dim=D;
p.use_mask=0; p.is_causal=0; p.causal_offset=0;
p.scale=1.0f/sqrtf((float)D);
@@ -240,7 +240,7 @@ int main() {
cudaMemcpy(dV,tmp,nKV*2,cudaMemcpyHostToDevice);
cudaMemcpy(dMask,hMask,B*sl,cudaMemcpyHostToDevice);
AttentionParams p;
AttentionParams<bf16> p;
p.batch=B; p.q_head=Hq; p.kv_head=Hk; p.q_len=1; p.kv_len=sl; p.head_dim=D;
p.use_mask=0; p.is_causal=0; p.causal_offset=0;
p.scale=1.0f/sqrtf((float)D);