context : introduce llama_graph_i

ggml-ci

src/CMakeLists.txt

@@ -15,6 +15,7 @@ add_library(llama
             llama-chat.cpp
             llama-context.cpp
             llama-grammar.cpp
+            llama-graph.cpp
             llama-hparams.cpp
             llama-impl.cpp
             llama-kv-cache.cpp

src/llama-context.h

@@ -3,6 +3,7 @@
 #include "llama.h"
 #include "llama-batch.h"
 #include "llama-cparams.h"
+#include "llama-graph.h"
 #include "llama-model.h"
 #include "llama-kv-cache.h"
 #include "llama-adapter.h"
@@ -16,7 +17,7 @@
 
 using llama_loras = std::unordered_map<struct llama_adapter_lora *, float>;
 
-struct llama_context {
+struct llama_context : public llama_graph_i {
     llama_context(const llama_model & model);
     virtual ~llama_context();
 
@@ -129,137 +130,6 @@ struct llama_context {
 
     virtual ggml_tensor * build_rope_factors(int il);
 
-    // graph build API (context-specific)
-
-    virtual ggml_tensor * build_inp_embd(
-            ggml_context * ctx0,
-             ggml_tensor * tok_embd,
-      const llama_ubatch & ubatch) = 0;
-
-    virtual ggml_tensor * build_inp_pos(
-            ggml_context * ctx0,
-                 int32_t   n_tokens) = 0;
-
-    virtual ggml_tensor * build_inp_out_ids(
-            ggml_context * ctx0,
-                 int32_t   n_tokens,
-                    bool   worst_case) = 0;
-
-    virtual ggml_tensor * build_inp_mean(
-            ggml_context * ctx0,
-                 int32_t   n_tokens) = 0;
-
-    virtual ggml_tensor * build_inp_cls(
-            ggml_context * ctx0,
-                 int32_t   n_tokens) = 0;
-
-    virtual void build_attn_inp(
-            ggml_context * ctx0,
-                 int32_t   n_tokens,
-                    bool   causal,
-                    bool   swa,
-                    bool   worst_case) = 0;
-
-    virtual void build_attn_kv_store(
-            ggml_context * ctx0,
-             ggml_cgraph * graph,
-             ggml_tensor * k_cur,
-             ggml_tensor * v_cur,
-                 int32_t   n_tokens,
-                 int64_t   il,
-                 bool      worst_case) = 0;
-
-    virtual ggml_tensor * build_attn_qkv(
-            ggml_context * ctx0,
-             ggml_cgraph * graph,
-             ggml_tensor * wo,
-             ggml_tensor * wo_b,
-             ggml_tensor * q_cur,
-                 int32_t   n_tokens,
-                 float     kq_scale,
-                 int       il,
-                 bool      worst_case) = 0;
-
-    virtual ggml_tensor * build_soft_max_ext(
-            ggml_context * ctx0,
-             ggml_tensor * kq,
-                 float     kq_scale) = 0;
-
-    virtual void build_k_shift(
-            ggml_context * ctx0,
-             ggml_cgraph * graph) = 0;
-
-    // find holes from the beginning of the KV cache and fill them by moving data from the end of the cache
-    virtual void build_defrag(
-            ggml_context * ctx0,
-             ggml_cgraph * graph) = 0;
-
-    virtual ggml_tensor * build_inp_embd_enc(
-            ggml_context * ctx0,
-                 int32_t   n_tokens,
-                    bool   worst_case) = 0;
-
-    virtual ggml_tensor * build_inp_KQ_mask_cross(
-            ggml_context * ctx0,
-                 int32_t   n_tokens,
-                    bool   worst_case) = 0;
-
-    virtual ggml_tensor * build_inp_s_copy(
-            ggml_context * ctx0,
-                    bool   worst_case) = 0;
-
-    virtual ggml_tensor * build_inp_s_mask(
-            ggml_context * ctx0,
-                    bool   worst_case) = 0;
-
-    virtual ggml_tensor * build_copy_mask_state(
-            ggml_context * ctx0,
-             ggml_cgraph * graph,
-             ggml_tensor * s,
-             ggml_tensor * state_copy,
-             ggml_tensor * state_mask,
-                 int32_t   n_tokens,
-                 int32_t   n_state,
-                 int32_t   n_seqs,
-                    bool   worst_case) = 0;
-
-    virtual ggml_tensor * build_mamba_layer(
-            ggml_context * ctx0,
-             ggml_cgraph * graph,
-             ggml_tensor * cur,
-             ggml_tensor * state_copy,
-             ggml_tensor * state_mask,
-      const llama_ubatch & ubatch,
-                     int   il,
-                    bool   worst_case) = 0;
-
-    virtual ggml_tensor * build_rwkv_token_shift_load(
-            ggml_context * ctx0,
-             ggml_cgraph * graph,
-             ggml_tensor * state_copy,
-             ggml_tensor * state_mask,
-      const llama_ubatch & ubatch,
-                     int   il,
-                    bool   worst_case) = 0;
-
-    virtual ggml_tensor * build_rwkv_token_shift_store(
-            ggml_context * ctx0,
-             ggml_tensor * token_shift,
-      const llama_ubatch & ubatch,
-                     int   il,
-                    bool   worst_case) = 0;
-
-    virtual ggml_tensor * build_rwkv6_time_mix(
-            ggml_context * ctx0,
-             ggml_cgraph * graph,
-             ggml_tensor * cur,
-             ggml_tensor * x_prev,
-             ggml_tensor * state_copy,
-             ggml_tensor * state_mask,
-      const llama_ubatch & ubatch,
-                     int   il,
-                    bool   worst_case) = 0;
-
     // state save/load
 
     virtual size_t state_get_size()                                 = 0;

src/llama-graph.cpp

@@ -0,0 +1 @@
+#include "llama-graph.h"

src/llama-graph.h

@@ -0,0 +1,164 @@
+#pragma once
+
+#include <cstdint>
+
+struct ggml_cgraph;
+struct ggml_context;
+struct ggml_tensor;
+struct llama_ubatch;
+
+// TODO: pass to llama_model graph build
+class llama_graph_i {
+public:
+    // apply control vector for layer il
+    virtual ggml_tensor * build_cvec(
+            ggml_context * ctx0,
+             ggml_tensor * cur,
+                     int   il) = 0;
+
+    // do mat_mul, while optionally apply lora
+    virtual ggml_tensor * build_lora_mm(
+            ggml_context * ctx0,
+             ggml_tensor * w,
+             ggml_tensor * cur) = 0;
+
+    // do mat_mul_id, while optionally apply lora
+    virtual ggml_tensor * build_lora_mm_id(
+            ggml_context * ctx0,
+             ggml_tensor * w,   // struct ggml_tensor * as
+             ggml_tensor * cur, // struct ggml_tensor * b
+             ggml_tensor * ids) = 0;
+
+    virtual ggml_tensor * build_rope_factors(int il) = 0;
+
+    // graph build API (context-specific)
+
+    virtual ggml_tensor * build_inp_embd(
+            ggml_context * ctx0,
+             ggml_tensor * tok_embd,
+      const llama_ubatch & ubatch) = 0;
+
+    virtual ggml_tensor * build_inp_pos(
+            ggml_context * ctx0,
+                 int32_t   n_tokens) = 0;
+
+    virtual ggml_tensor * build_inp_out_ids(
+            ggml_context * ctx0,
+                 int32_t   n_tokens,
+                    bool   worst_case) = 0;
+
+    virtual ggml_tensor * build_inp_mean(
+            ggml_context * ctx0,
+                 int32_t   n_tokens) = 0;
+
+    virtual ggml_tensor * build_inp_cls(
+            ggml_context * ctx0,
+                 int32_t   n_tokens) = 0;
+
+    virtual void build_attn_inp(
+            ggml_context * ctx0,
+                 int32_t   n_tokens,
+                    bool   causal,
+                    bool   swa,
+                    bool   worst_case) = 0;
+
+    virtual void build_attn_kv_store(
+            ggml_context * ctx0,
+             ggml_cgraph * graph,
+             ggml_tensor * k_cur,
+             ggml_tensor * v_cur,
+                 int32_t   n_tokens,
+                 int64_t   il,
+                 bool      worst_case) = 0;
+
+    virtual ggml_tensor * build_attn_qkv(
+            ggml_context * ctx0,
+             ggml_cgraph * graph,
+             ggml_tensor * wo,
+             ggml_tensor * wo_b,
+             ggml_tensor * q_cur,
+                 int32_t   n_tokens,
+                 float     kq_scale,
+                 int       il,
+                 bool      worst_case) = 0;
+
+    virtual ggml_tensor * build_soft_max_ext(
+            ggml_context * ctx0,
+             ggml_tensor * kq,
+                 float     kq_scale) = 0;
+
+    virtual void build_k_shift(
+            ggml_context * ctx0,
+             ggml_cgraph * graph) = 0;
+
+    // find holes from the beginning of the KV cache and fill them by moving data from the end of the cache
+    virtual void build_defrag(
+            ggml_context * ctx0,
+             ggml_cgraph * graph) = 0;
+
+    virtual ggml_tensor * build_inp_embd_enc(
+            ggml_context * ctx0,
+                 int32_t   n_tokens,
+                    bool   worst_case) = 0;
+
+    virtual ggml_tensor * build_inp_KQ_mask_cross(
+            ggml_context * ctx0,
+                 int32_t   n_tokens,
+                    bool   worst_case) = 0;
+
+    virtual ggml_tensor * build_inp_s_copy(
+            ggml_context * ctx0,
+                    bool   worst_case) = 0;
+
+    virtual ggml_tensor * build_inp_s_mask(
+            ggml_context * ctx0,
+                    bool   worst_case) = 0;
+
+    virtual ggml_tensor * build_copy_mask_state(
+            ggml_context * ctx0,
+             ggml_cgraph * graph,
+             ggml_tensor * s,
+             ggml_tensor * state_copy,
+             ggml_tensor * state_mask,
+                 int32_t   n_tokens,
+                 int32_t   n_state,
+                 int32_t   n_seqs,
+                    bool   worst_case) = 0;
+
+    virtual ggml_tensor * build_mamba_layer(
+            ggml_context * ctx0,
+             ggml_cgraph * graph,
+             ggml_tensor * cur,
+             ggml_tensor * state_copy,
+             ggml_tensor * state_mask,
+      const llama_ubatch & ubatch,
+                     int   il,
+                    bool   worst_case) = 0;
+
+    virtual ggml_tensor * build_rwkv_token_shift_load(
+            ggml_context * ctx0,
+             ggml_cgraph * graph,
+             ggml_tensor * state_copy,
+             ggml_tensor * state_mask,
+      const llama_ubatch & ubatch,
+                     int   il,
+                    bool   worst_case) = 0;
+
+    virtual ggml_tensor * build_rwkv_token_shift_store(
+            ggml_context * ctx0,
+             ggml_tensor * token_shift,
+      const llama_ubatch & ubatch,
+                     int   il,
+                    bool   worst_case) = 0;
+
+    virtual ggml_tensor * build_rwkv6_time_mix(
+            ggml_context * ctx0,
+             ggml_cgraph * graph,
+             ggml_tensor * cur,
+             ggml_tensor * x_prev,
+             ggml_tensor * state_copy,
+             ggml_tensor * state_mask,
+      const llama_ubatch & ubatch,
+                     int   il,
+                    bool   worst_case) = 0;
+};