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cont : migrate the rest of the inputs out of llama_context

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ggml-ci
This commit is contained in:
Georgi Gerganov
2025-02-28 18:01:25 +02:00
parent 7f02ee562e
commit 9cab53c7dd
5 changed files with 645 additions and 577 deletions
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53
src/llama-graph.h
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@@ -93,6 +93,7 @@ public:
//
// TODO: can become more granular in the future
// TODO: move all methods that do not require things from llama_context to llm_build_context
class llama_graph_i {
public:
llama_graph_i(llama_graph_type type);
@@ -109,28 +110,28 @@ public:
ggml_tensor * cur,
const char * name,
const llama_ubatch & ubatch,
int il) = 0;
int il) const = 0;
// apply control vector for layer il
virtual ggml_tensor * build_cvec(
ggml_context * ctx0,
ggml_tensor * cur,
int il) = 0;
int il) const = 0;
// do mat_mul, while optionally apply lora
virtual ggml_tensor * build_lora_mm(
ggml_context * ctx0,
ggml_tensor * w,
ggml_tensor * cur) = 0;
ggml_tensor * cur) const = 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;
ggml_tensor * ids) const = 0;
virtual ggml_tensor * build_rope_factors(int il) = 0;
virtual ggml_tensor * build_rope_factors(int il) const = 0;
// note: optionally set the backend to be the same as the bbuf's backend
virtual ggml_tensor * build_rope_shift(
@@ -138,7 +139,7 @@ public:
ggml_tensor * cur,
ggml_tensor * shift,
ggml_tensor * factors,
ggml_backend_buffer * bbuf) = 0;
ggml_backend_buffer * bbuf) const = 0;
// graph build API (context-specific)
@@ -146,26 +147,31 @@ public:
llama_graph_result * res,
ggml_context * ctx0,
ggml_tensor * tok_embd,
const llama_ubatch & ubatch) const = 0; // note these methods will become const, i.e. they don't mutate the llama_context that implements them
const llama_ubatch & ubatch) const = 0;
virtual ggml_tensor * build_inp_pos(
llama_graph_result * res,
ggml_context * ctx0,
int32_t n_tokens) = 0;
int32_t n_tokens) const = 0;
virtual ggml_tensor * build_inp_pos_bucket(
llama_graph_result * res,
ggml_context * ctx0,
int32_t n_tokens) = 0;
int32_t n_tokens) const = 0;
virtual ggml_tensor * build_inp_out_ids(
ggml_context * ctx0) = 0;
llama_graph_result * res,
ggml_context * ctx0) const = 0;
virtual ggml_tensor * build_inp_mean(
llama_graph_result * res,
ggml_context * ctx0,
int32_t n_tokens) = 0;
int32_t n_tokens) const = 0;
virtual ggml_tensor * build_inp_cls(
llama_graph_result * res,
ggml_context * ctx0,
int32_t n_tokens) = 0;
int32_t n_tokens) const = 0;
virtual llama_graph_input_attn_ptr build_attn_inp(
llama_graph_result * res,
@@ -197,17 +203,16 @@ public:
int il) const;
virtual ggml_tensor * build_inp_cross_embd(
ggml_context * ctx0);
virtual ggml_tensor * build_inp_cross_kq_mask(
ggml_context * ctx0,
int32_t n_tokens);
llama_graph_result * res,
ggml_context * ctx0) const;
virtual ggml_tensor * build_inp_s_copy(
ggml_context * ctx0);
llama_graph_result * res,
ggml_context * ctx0) const;
virtual ggml_tensor * build_inp_s_mask(
ggml_context * ctx0);
llama_graph_result * res,
ggml_context * ctx0) const;
virtual ggml_tensor * build_copy_mask_state(
ggml_context * ctx0,
@@ -216,7 +221,7 @@ public:
ggml_tensor * state_copy,
ggml_tensor * state_mask,
int32_t n_state,
int32_t n_seqs);
int32_t n_seqs) const;
virtual ggml_tensor * build_mamba_layer(
ggml_context * ctx0,
@@ -225,7 +230,7 @@ public:
ggml_tensor * state_copy,
ggml_tensor * state_mask,
const llama_ubatch & ubatch,
int il);
int il) const;
virtual ggml_tensor * build_rwkv_token_shift_load(
ggml_context * ctx0,
@@ -233,13 +238,13 @@ public:
ggml_tensor * state_copy,
ggml_tensor * state_mask,
const llama_ubatch & ubatch,
int il);
int il) const;
virtual ggml_tensor * build_rwkv_token_shift_store(
ggml_context * ctx0,
ggml_tensor * token_shift,
const llama_ubatch & ubatch,
int il);
int il) const;
virtual ggml_tensor * build_rwkv6_time_mix(
ggml_context * ctx0,
@@ -249,5 +254,5 @@ public:
ggml_tensor * state_copy,
ggml_tensor * state_mask,
const llama_ubatch & ubatch,
int il);
int il) const;
};