vbatts/llama.cpp
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add checkpoint file version for future compatibility

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xaedes 2023-08-26 21:04:01 +02:00
parent 6a20f7a2f0
commit 167dd2dcec
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1 changed files with 12 additions and 0 deletions
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examples/train-text-from-scratch/train-text-from-scratch.cpp
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@ -239,6 +239,7 @@ struct my_llama_model {
const char * LLM_KV_OPTIMIZER_TYPE = "optimizer.type";
const char * LLM_KV_OPTIMIZER_TYPE_ADAM = "adam";
const char * LLM_KV_OPTIMIZER_TYPE_LBFGS = "lbfgs";
const char * LLM_KV_OPTIMIZER_FILE_VERSION = "optimizer.file_version";
const char * LLM_KV_OPTIMIZER_CONVERGENCE_PAST_COUNT = "optimizer.convergence_past_count";
const char * LLM_KV_OPTIMIZER_PARAMETER_COUNT_LOW = "optimizer.parameter_count.low";
const char * LLM_KV_OPTIMIZER_PARAMETER_COUNT_HIGH = "optimizer.parameter_count.high";
@ -269,6 +270,7 @@ const char * LLM_TENSOR_OPTIMIZER_LBFGS_MEMORY_YS = "optimizer.lbfgs.m
const char * LLM_TENSOR_OPTIMIZER_LBFGS_MEMORY_S = "optimizer.lbfgs.memory_s";
const char * LLM_TENSOR_OPTIMIZER_LBFGS_MEMORY_Y = "optimizer.lbfgs.memory_y";
const char * LLM_KV_TRAINING_FILE_VERSION = "training.file_version";
const char * LLM_KV_TRAINING_ITERATION_COUNT = "training.iteration_count";
const char * LLM_KV_TRAINING_SAMPLE_COUNT = "training.sample_count";
const char * LLM_KV_TRAINING_TOKEN_COUNT = "training.token_count";
@ -1519,6 +1521,10 @@ void read_tensor_by_name(struct ggml_tensor * dst, struct ggml_context * ctx, co
void load_opt_context_gguf(struct gguf_context * fctx, struct ggml_context * f_ggml_ctx, struct ggml_opt_context * opt) {
// NOTE: gguf_context must be initialized with f_ggml_ctx and no_alloc=false, otherwise tensor data can not be read
uint32_t file_version;
GGUF_GET_KEY(fctx, file_version, gguf_get_val_u32, GGUF_TYPE_UINT32, true, LLM_KV_OPTIMIZER_FILE_VERSION);
GGML_ASSERT(file_version == 0);
GGUF_GET_KEY(fctx, opt->params.past, gguf_get_val_u32, GGUF_TYPE_UINT32, true, LLM_KV_OPTIMIZER_CONVERGENCE_PAST_COUNT);
GGUF_GET_KEY(fctx, opt->iter, gguf_get_val_u32, GGUF_TYPE_UINT32, true, LLM_KV_OPTIMIZER_ITERATION_COUNT);
@ -1576,6 +1582,7 @@ void load_opt_context_gguf(struct gguf_context * fctx, struct ggml_context * f_g
}
void save_opt_context_gguf(struct gguf_context * fctx, struct ggml_opt_context * opt) {
gguf_set_val_u32(fctx, LLM_KV_OPTIMIZER_FILE_VERSION, 0);
gguf_set_val_u32(fctx, LLM_KV_OPTIMIZER_CONVERGENCE_PAST_COUNT, opt->params.past);
// gguf v1 only supports values with up to 32-bit precision,
@ -1868,6 +1875,10 @@ void save_llama_model_file(const char * filename, const char * fn_vocab_model, s
void load_checkpoint_gguf(struct gguf_context * fctx, struct ggml_context * f_ggml_ctx, struct my_llama_model * model, struct ggml_opt_context * opt) {
load_llama_model_gguf(fctx, f_ggml_ctx, model);
uint32_t file_version;
GGUF_GET_KEY(fctx, file_version, gguf_get_val_u32, GGUF_TYPE_UINT32, true, LLM_KV_TRAINING_FILE_VERSION);
GGML_ASSERT(file_version == 0);
GGUF_GET_KEY(fctx, model->train_its, gguf_get_val_u32, GGUF_TYPE_UINT32, true, LLM_KV_TRAINING_ITERATION_COUNT);
GGUF_GET_KEY(fctx, model->train_samples, gguf_get_val_u32, GGUF_TYPE_UINT32, true, LLM_KV_TRAINING_SAMPLE_COUNT);
GGUF_GET_KEY(fctx, model->train_tokens, gguf_get_val_u32, GGUF_TYPE_UINT32, true, LLM_KV_TRAINING_TOKEN_COUNT);
@ -1878,6 +1889,7 @@ void load_checkpoint_gguf(struct gguf_context * fctx, struct ggml_context * f_gg
void save_checkpoint_gguf(struct gguf_context * fctx, const char * fn_vocab_model, struct my_llama_model * model, struct ggml_opt_context * opt) {
save_llama_model_gguf(fctx, fn_vocab_model, model);
gguf_set_val_u32(fctx, LLM_KV_TRAINING_FILE_VERSION, 0);
gguf_set_val_u32(fctx, LLM_KV_TRAINING_ITERATION_COUNT, model->train_its);
gguf_set_val_u32(fctx, LLM_KV_TRAINING_SAMPLE_COUNT, model->train_samples);
gguf_set_val_u32(fctx, LLM_KV_TRAINING_TOKEN_COUNT, model->train_tokens);