vbatts/llama.cpp
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llama : increase inference graph size up to 4096 nodes

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This commit is contained in:
Georgi Gerganov 2023-11-03 21:59:02 +02:00
parent b1592ea054
commit e50ab5af5b
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GPG key ID: 449E073F9DC10735
1 changed files with 11 additions and 9 deletions
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llama.cpp
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@ -91,6 +91,8 @@
#define LLAMA_ATTRIBUTE_FORMAT(...) #define LLAMA_ATTRIBUTE_FORMAT(...)
#endif #endif
#define LLAMA_MAX_NODES 4096
// //
// logging // logging
// //
@ -3580,7 +3582,7 @@ struct llm_build_context {
} }
struct ggml_cgraph * build_llama() { struct ggml_cgraph * build_llama() {
struct ggml_cgraph * gf = ggml_new_graph(ctx0); struct ggml_cgraph * gf = ggml_new_graph_custom(ctx0, LLAMA_MAX_NODES, false);
GGML_ASSERT(n_embd_head == hparams.n_rot); GGML_ASSERT(n_embd_head == hparams.n_rot);
@ -3692,7 +3694,7 @@ struct llm_build_context {
} }
struct ggml_cgraph * build_baichuan() { struct ggml_cgraph * build_baichuan() {
struct ggml_cgraph * gf = ggml_new_graph(ctx0); struct ggml_cgraph * gf = ggml_new_graph_custom(ctx0, LLAMA_MAX_NODES, false);
struct ggml_tensor * cur; struct ggml_tensor * cur;
struct ggml_tensor * inpL; struct ggml_tensor * inpL;
@ -3812,7 +3814,7 @@ struct llm_build_context {
} }
struct ggml_cgraph * build_falcon() { struct ggml_cgraph * build_falcon() {
struct ggml_cgraph * gf = ggml_new_graph(ctx0); struct ggml_cgraph * gf = ggml_new_graph_custom(ctx0, LLAMA_MAX_NODES, false);
struct ggml_tensor * cur; struct ggml_tensor * cur;
struct ggml_tensor * inpL; struct ggml_tensor * inpL;
@ -3934,7 +3936,7 @@ struct llm_build_context {
} }
struct ggml_cgraph * build_starcoder() { struct ggml_cgraph * build_starcoder() {
struct ggml_cgraph * gf = ggml_new_graph(ctx0); struct ggml_cgraph * gf = ggml_new_graph_custom(ctx0, LLAMA_MAX_NODES, false);
struct ggml_tensor * cur; struct ggml_tensor * cur;
struct ggml_tensor * pos; struct ggml_tensor * pos;
@ -4033,7 +4035,7 @@ struct llm_build_context {
} }
struct ggml_cgraph * build_persimmon() { struct ggml_cgraph * build_persimmon() {
struct ggml_cgraph * gf = ggml_new_graph(ctx0); struct ggml_cgraph * gf = ggml_new_graph_custom(ctx0, LLAMA_MAX_NODES, false);
const int64_t n_rot = n_embd_head / 2; const int64_t n_rot = n_embd_head / 2;
@ -4243,7 +4245,7 @@ struct llm_build_context {
} }
struct ggml_cgraph * build_refact() { struct ggml_cgraph * build_refact() {
struct ggml_cgraph * gf = ggml_new_graph(ctx0); struct ggml_cgraph * gf = ggml_new_graph_custom(ctx0, LLAMA_MAX_NODES, false);
struct ggml_tensor * cur; struct ggml_tensor * cur;
struct ggml_tensor * inpL; struct ggml_tensor * inpL;
@ -4334,7 +4336,7 @@ struct llm_build_context {
} }
struct ggml_cgraph * build_bloom() { struct ggml_cgraph * build_bloom() {
struct ggml_cgraph * gf = ggml_new_graph(ctx0); struct ggml_cgraph * gf = ggml_new_graph_custom(ctx0, LLAMA_MAX_NODES, false);
struct ggml_tensor * cur; struct ggml_tensor * cur;
struct ggml_tensor * inpL; struct ggml_tensor * inpL;
@ -4428,7 +4430,7 @@ struct llm_build_context {
} }
struct ggml_cgraph * build_mpt() { struct ggml_cgraph * build_mpt() {
struct ggml_cgraph * gf = ggml_new_graph(ctx0); struct ggml_cgraph * gf = ggml_new_graph_custom(ctx0, LLAMA_MAX_NODES, false);
struct ggml_tensor * cur; struct ggml_tensor * cur;
struct ggml_tensor * inpL; struct ggml_tensor * inpL;
@ -8169,7 +8171,7 @@ struct llama_context * llama_new_context_with_model(
{ {
static const size_t tensor_alignment = 32; static const size_t tensor_alignment = 32;
// the compute buffer is used to store the tensor and graph structs, while the allocator buffer is used for the tensor data // the compute buffer is used to store the tensor and graph structs, while the allocator buffer is used for the tensor data
ctx->buf_compute.resize(ggml_tensor_overhead()*GGML_DEFAULT_GRAPH_SIZE + ggml_graph_overhead()); ctx->buf_compute.resize(ggml_tensor_overhead()*LLAMA_MAX_NODES + ggml_graph_overhead());
// create measure allocator // create measure allocator
ctx->alloc = ggml_allocr_new_measure(tensor_alignment); ctx->alloc = ggml_allocr_new_measure(tensor_alignment);