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llama : allow gguf RoPE keys to be overridden with defaults (#3240)

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Cebtenzzre 2023-09-20 12:12:47 -04:00 committed by GitHub
parent 65c2c1c5ab
commit a5661d7e71
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3 changed files with 27 additions and 39 deletions
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6
common/common.cpp
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@ -647,9 +647,9 @@ void gpt_print_usage(int /*argc*/, char ** argv, const gpt_params & params) {
printf(" --cfg-negative-prompt-file FNAME\n"); printf(" --cfg-negative-prompt-file FNAME\n");
printf(" negative prompt file to use for guidance. (default: empty)\n"); printf(" negative prompt file to use for guidance. (default: empty)\n");
printf(" --cfg-scale N strength of guidance (default: %f, 1.0 = disable)\n", params.cfg_scale); printf(" --cfg-scale N strength of guidance (default: %f, 1.0 = disable)\n", params.cfg_scale);
printf(" --rope-scale N RoPE context linear scaling factor, inverse of --rope-freq-scale (default: %g)\n", 1.0f/params.rope_freq_scale); printf(" --rope-scale N RoPE context linear scaling factor, inverse of --rope-freq-scale\n");
printf(" --rope-freq-base N RoPE base frequency, used by NTK-aware scaling (default: %.1f)\n", params.rope_freq_base); printf(" --rope-freq-base N RoPE base frequency, used by NTK-aware scaling (default: loaded from model)\n");
printf(" --rope-freq-scale N RoPE frequency linear scaling factor, inverse of --rope-scale (default: %g)\n", params.rope_freq_scale); printf(" --rope-freq-scale N RoPE frequency linear scaling factor (default: loaded from model)\n");
printf(" --ignore-eos ignore end of stream token and continue generating (implies --logit-bias 2-inf)\n"); printf(" --ignore-eos ignore end of stream token and continue generating (implies --logit-bias 2-inf)\n");
printf(" --no-penalize-nl do not penalize newline token\n"); printf(" --no-penalize-nl do not penalize newline token\n");
printf(" --memory-f32 use f32 instead of f16 for memory key+value (default: disabled)\n"); printf(" --memory-f32 use f32 instead of f16 for memory key+value (default: disabled)\n");

4
examples/server/server.cpp
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@ -701,8 +701,8 @@ static void server_print_usage(const char *argv0, const gpt_params &params,
printf(" -v, --verbose verbose output (default: %s)\n", server_verbose ? "enabled" : "disabled"); printf(" -v, --verbose verbose output (default: %s)\n", server_verbose ? "enabled" : "disabled");
printf(" -t N, --threads N number of threads to use during computation (default: %d)\n", params.n_threads); printf(" -t N, --threads N number of threads to use during computation (default: %d)\n", params.n_threads);
printf(" -c N, --ctx-size N size of the prompt context (default: %d)\n", params.n_ctx); printf(" -c N, --ctx-size N size of the prompt context (default: %d)\n", params.n_ctx);
printf(" --rope-freq-base N RoPE base frequency (default: %.1f)\n", params.rope_freq_base); printf(" --rope-freq-base N RoPE base frequency (default: loaded from model)\n");
printf(" --rope-freq-scale N RoPE frequency scaling factor (default: %g)\n", params.rope_freq_scale); printf(" --rope-freq-scale N RoPE frequency scaling factor (default: loaded from model)\n");
printf(" -b N, --batch-size N batch size for prompt processing (default: %d)\n", params.n_batch); printf(" -b N, --batch-size N batch size for prompt processing (default: %d)\n", params.n_batch);
printf(" --memory-f32 use f32 instead of f16 for memory key+value (default: disabled)\n"); printf(" --memory-f32 use f32 instead of f16 for memory key+value (default: disabled)\n");
printf(" not recommended: doubles context memory required and no measurable increase in quality\n"); printf(" not recommended: doubles context memory required and no measurable increase in quality\n");

54
llama.cpp
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@ -929,23 +929,22 @@ static const size_t kB = 1024;
static const size_t MB = kB*kB; static const size_t MB = kB*kB;
static const size_t GB = kB*kB*kB; static const size_t GB = kB*kB*kB;
// default hparams (LLaMA 7B)
struct llama_hparams { struct llama_hparams {
uint32_t n_vocab = 32000; uint32_t n_vocab;
uint32_t n_ctx_train = 2048; // the context size used during training uint32_t n_ctx_train; // context size the model was trained on
uint32_t n_ctx = 512; // the context size used during inference uint32_t n_ctx; // context size used during inference
uint32_t n_embd = 4096; uint32_t n_embd;
uint32_t n_head = 32; uint32_t n_head;
uint32_t n_head_kv = 32; uint32_t n_head_kv;
uint32_t n_layer = 32; uint32_t n_layer;
uint32_t n_rot = 64; uint32_t n_rot;
uint32_t n_ff = 11008; uint32_t n_ff;
float f_norm_eps = 1e-5; float f_norm_eps;
float f_norm_rms_eps = 1e-5; float f_norm_rms_eps;
float rope_freq_base = 10000.0f; float rope_freq_base;
float rope_freq_scale = 1.0f; float rope_freq_scale;
bool operator!=(const llama_hparams & other) const { bool operator!=(const llama_hparams & other) const {
return static_cast<bool>(memcmp(this, &other, sizeof(llama_hparams))); // NOLINT return static_cast<bool>(memcmp(this, &other, sizeof(llama_hparams))); // NOLINT
@ -1076,7 +1075,7 @@ struct llama_model {
std::string name = "n/a"; std::string name = "n/a";
llama_hparams hparams; llama_hparams hparams = {};
llama_vocab vocab; llama_vocab vocab;
struct ggml_tensor * tok_embeddings; struct ggml_tensor * tok_embeddings;
@ -1674,29 +1673,18 @@ static void llm_load_hparams(
hparams.n_head_kv = hparams.n_head; hparams.n_head_kv = hparams.n_head;
GGUF_GET_KEY(ctx, hparams.n_head_kv, gguf_get_val_u32, GGUF_TYPE_UINT32, false, kv(LLM_KV_ATTENTION_HEAD_COUNT_KV)); GGUF_GET_KEY(ctx, hparams.n_head_kv, gguf_get_val_u32, GGUF_TYPE_UINT32, false, kv(LLM_KV_ATTENTION_HEAD_COUNT_KV));
// TODO: manually setting rope freq base and scale should override this // rope_freq_base (optional)
// FIXME: partial fix when the param specified is not the default value, but if (rope_freq_base == 0.0f) {
// will not work for overriding the model value to the params default rope_freq_base = 10000.0f;
GGUF_GET_KEY(ctx, rope_freq_base, gguf_get_val_f32, GGUF_TYPE_FLOAT32, false, kv(LLM_KV_ROPE_FREQ_BASE));
llama_context_params defaults = llama_context_default_params();
// rope_freq_base
{
float ropebase = 10000.0f;
GGUF_GET_KEY(ctx, ropebase, gguf_get_val_f32, GGUF_TYPE_FLOAT32, false, kv(LLM_KV_ROPE_FREQ_BASE));
if (ropebase != 10000.0f && rope_freq_base == defaults.rope_freq_base) {
rope_freq_base = ropebase;
}
} }
// rope_freq_scale (inverse of the kv) is optional // rope_freq_scale (inverse of the kv) is optional
{ if (rope_freq_scale == 0.0f) {
float ropescale = 1.0f; float ropescale = 1.0f;
GGUF_GET_KEY(ctx, ropescale, gguf_get_val_f32, GGUF_TYPE_FLOAT32, false, kv(LLM_KV_ROPE_SCALE_LINEAR)); GGUF_GET_KEY(ctx, ropescale, gguf_get_val_f32, GGUF_TYPE_FLOAT32, false, kv(LLM_KV_ROPE_SCALE_LINEAR));
if (ropescale != 1.0f && rope_freq_scale == defaults.rope_freq_scale) {
rope_freq_scale = 1.0f/ropescale; rope_freq_scale = 1.0f/ropescale;
} }
}
// sanity check for n_rot (optional) // sanity check for n_rot (optional)
{ {
@ -6188,8 +6176,8 @@ struct llama_context_params llama_context_default_params() {
/*.n_gpu_layers =*/ 0, /*.n_gpu_layers =*/ 0,
/*.main_gpu =*/ 0, /*.main_gpu =*/ 0,
/*.tensor_split =*/ nullptr, /*.tensor_split =*/ nullptr,
/*.rope_freq_base =*/ 10000.0f, /*.rope_freq_base =*/ 0.0f,
/*.rope_freq_scale =*/ 1.0f, /*.rope_freq_scale =*/ 0.0f,
/*.progress_callback =*/ nullptr, /*.progress_callback =*/ nullptr,
/*.progress_callback_user_data =*/ nullptr, /*.progress_callback_user_data =*/ nullptr,
/*.low_vram =*/ false, /*.low_vram =*/ false,