cuda: load ragged attention entry point on Windows
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@@ -61,6 +61,9 @@ typedef int (*fn_attention_absorb_batch)(ColiCudaTensor *kv_b,float *ctx,const f
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typedef int (*fn_attention_absorb_batch_dev)(ColiCudaTensor *kv_b_shard,float *ctx_dev, const float *q_dev,const float *latent_dev,const float *rope_dev, int S,int H,int Q,int R,int V,int K,int T,float scale);
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typedef int (*fn_attention_absorb_kvdev)(ColiCudaTensor *kv_b,float *ctx,const float *q, const float *latent_dev,const float *rope_dev,int H,int Q,int R,int V,int K,int T, float scale);
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typedef int (*fn_attention_project_batch)(ColiCudaTensor *kv_b,ColiCudaTensor *o_proj, float *out,const float *q,const float *latent, const float *rope,int S,int H,int Q,int R, int V,int K,int T,float attention_scale);
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typedef int (*fn_attention_project_ragged)(ColiCudaTensor *kv_b,ColiCudaTensor *o_proj,
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float *out,const float *q,const float *const *latent,const float *const *rope,
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const int *lengths,int S,int H,int Q,int R,int V,int K,int max_t,float attention_scale);
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typedef int (*fn_attention_project_batch_dev)(ColiCudaTensor *kv_b,ColiCudaTensor *o_proj, float *out,const float *q_dev,const float *latent_dev,const float *rope_dev, int S,int H,int Q,int R,int V,int K,int T,float scale);
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typedef int (*fn_attention_project_batch_dev_out)(ColiCudaTensor *kv_b,ColiCudaTensor *o_proj, float *out_dev,const float *q_dev,const float *latent_dev,const float *rope_dev, int S,int H,int Q,int R,int V,int K,int T,float scale);
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typedef int (*fn_pipe_add)(int device,float *x_dev,const float *t_dev,size_t n);
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@@ -107,6 +110,7 @@ static struct {
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fn_attention_absorb_batch_dev attention_absorb_batch_dev;
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fn_attention_absorb_kvdev attention_absorb_kvdev;
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fn_attention_project_batch attention_project_batch;
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fn_attention_project_ragged attention_project_ragged;
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fn_attention_project_batch_dev attention_project_batch_dev;
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fn_attention_project_batch_dev_out attention_project_batch_dev_out;
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fn_pipe_add pipe_add;
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@@ -200,6 +204,7 @@ static int coli_cuda_load(void){
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RESOLVE(attention_absorb_batch_dev, fn_attention_absorb_batch_dev)
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RESOLVE(attention_absorb_kvdev, fn_attention_absorb_kvdev)
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RESOLVE(attention_project_batch, fn_attention_project_batch)
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RESOLVE(attention_project_ragged, fn_attention_project_ragged)
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RESOLVE(attention_project_batch_dev, fn_attention_project_batch_dev)
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RESOLVE(attention_project_batch_dev_out, fn_attention_project_batch_dev_out)
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RESOLVE(pipe_add, fn_pipe_add)
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@@ -342,6 +347,14 @@ int coli_cuda_attention_project_batch(ColiCudaTensor *kv_b,ColiCudaTensor *o_pro
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return g_cuda.attention_project_batch(kv_b, o_proj, out, q, latent, rope, S, H, Q, R, V, K, T, attention_scale);
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}
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int coli_cuda_attention_project_ragged(ColiCudaTensor *kv_b,ColiCudaTensor *o_proj,
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float *out,const float *q,const float *const *latent,const float *const *rope,
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const int *lengths,int S,int H,int Q,int R,int V,int K,int max_t,float attention_scale){
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if(!coli_cuda_load()) return 0;
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return g_cuda.attention_project_ragged(kv_b,o_proj,out,q,latent,rope,lengths,
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S,H,Q,R,V,K,max_t,attention_scale);
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}
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int coli_cuda_attention_project_batch_dev(ColiCudaTensor *kv_b,ColiCudaTensor *o_proj, float *out,const float *q_dev,const float *latent_dev,const float *rope_dev, int S,int H,int Q,int R,int V,int K,int T,float scale){
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if(!g_cuda.available){ return 0; }
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return g_cuda.attention_project_batch_dev(kv_b, o_proj, out, q_dev, latent_dev, rope_dev, S, H, Q, R, V, K, T, scale);
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