vbatts/llama.cpp
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common : improve -ctv -ctk CLI arguments (#10806)

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* common : improve ctv ctk cli argument

* regenerate docs

* even better approach

* use std::vector
This commit is contained in:
Xuan Son Nguyen 2024-12-12 22:53:05 +01:00 • committed by GitHub
parent 274ec65af6
commit adffa6ffd5
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GPG key ID: B5690EEEBB952194
5 changed files with 60 additions and 51 deletions
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51
common/arg.cpp
View file

@ -145,6 +145,35 @@ static void common_params_handle_model_default(common_params & params) {
}
}
const std::vector<ggml_type> kv_cache_types = {
GGML_TYPE_F32,
GGML_TYPE_F16,
GGML_TYPE_BF16,
GGML_TYPE_Q8_0,
GGML_TYPE_Q4_0,
GGML_TYPE_Q4_1,
GGML_TYPE_IQ4_NL,
GGML_TYPE_Q5_0,
GGML_TYPE_Q5_1,
};
static ggml_type kv_cache_type_from_str(const std::string & s) {
for (const auto & type : kv_cache_types) {
if (ggml_type_name(type) == s) {
return type;
}
}
throw std::runtime_error("Unsupported cache type: " + s);
}
static std::string get_all_kv_cache_types() {
std::ostringstream msg;
for (const auto & type : kv_cache_types) {
msg << ggml_type_name(type) << (&type == &kv_cache_types.back() ? "" : ", ");
}
return msg.str();
}
//
// CLI argument parsing functions
//
@ -1174,18 +1203,28 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
).set_env("LLAMA_ARG_NO_KV_OFFLOAD"));
add_opt(common_arg(
{"-ctk", "--cache-type-k"}, "TYPE",
string_format("KV cache data type for K (default: %s)", params.cache_type_k.c_str()),
string_format(
"KV cache data type for K\n"
"allowed values: %s\n"
"(default: %s)",
get_all_kv_cache_types().c_str(),
ggml_type_name(params.cache_type_k)
),
[](common_params & params, const std::string & value) {
// TODO: get the type right here
params.cache_type_k = value;
params.cache_type_k = kv_cache_type_from_str(value);
}
).set_env("LLAMA_ARG_CACHE_TYPE_K"));
add_opt(common_arg(
{"-ctv", "--cache-type-v"}, "TYPE",
string_format("KV cache data type for V (default: %s)", params.cache_type_v.c_str()),
string_format(
"KV cache data type for V\n"
"allowed values: %s\n"
"(default: %s)",
get_all_kv_cache_types().c_str(),
ggml_type_name(params.cache_type_v)
),
[](common_params & params, const std::string & value) {
// TODO: get the type right here
params.cache_type_v = value;
params.cache_type_v = kv_cache_type_from_str(value);
}
).set_env("LLAMA_ARG_CACHE_TYPE_V"));
add_opt(common_arg(

36
common/common.cpp
View file

@ -1015,38 +1015,6 @@ struct llama_model_params common_model_params_to_llama(common_params & params) {
return mparams;
}
static ggml_type kv_cache_type_from_str(const std::string & s) {
if (s == "f32") {
return GGML_TYPE_F32;
}
if (s == "f16") {
return GGML_TYPE_F16;
}
if (s == "bf16") {
return GGML_TYPE_BF16;
}
if (s == "q8_0") {
return GGML_TYPE_Q8_0;
}
if (s == "q4_0") {
return GGML_TYPE_Q4_0;
}
if (s == "q4_1") {
return GGML_TYPE_Q4_1;
}
if (s == "iq4_nl") {
return GGML_TYPE_IQ4_NL;
}
if (s == "q5_0") {
return GGML_TYPE_Q5_0;
}
if (s == "q5_1") {
return GGML_TYPE_Q5_1;
}
throw std::runtime_error("Unsupported cache type: " + s);
}
struct llama_context_params common_context_params_to_llama(const common_params & params) {
auto cparams = llama_context_default_params();
@ -1081,8 +1049,8 @@ struct llama_context_params common_context_params_to_llama(const common_params &
cparams.pooling_type = LLAMA_POOLING_TYPE_RANK;
}
cparams.type_k = kv_cache_type_from_str(params.cache_type_k);
cparams.type_v = kv_cache_type_from_str(params.cache_type_v);
cparams.type_k = params.cache_type_k;
cparams.type_v = params.cache_type_v;
return cparams;
}

4
common/common.h
View file

@ -286,8 +286,8 @@ struct common_params {
bool warmup = true; // warmup run
bool check_tensors = false; // validate tensor data
std::string cache_type_k = "f16"; // KV cache data type for the K
std::string cache_type_v = "f16"; // KV cache data type for the V
ggml_type cache_type_k = GGML_TYPE_F16; // KV cache data type for the K
ggml_type cache_type_v = GGML_TYPE_F16; // KV cache data type for the V
// multimodal models (see examples/llava)
std::string mmproj = ""; // path to multimodal projector // NOLINT