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llama-run : include temperature option (#10899)

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This commit updates the `examples/run/README.md` file to include a new
option for setting the temperature and updates the `run.cpp` file to
parse this option.

Signed-off-by: Eric Curtin <ecurtin@redhat.com>
This commit is contained in:
Eric Curtin 2024-12-23 00:21:40 +00:00 committed by GitHub
parent 7024d59e6a
commit dab76c92cc
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GPG Key ID: B5690EEEBB952194
2 changed files with 75 additions and 38 deletions
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2
examples/run/README.md
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@ -19,6 +19,8 @@ Options:
Context size (default: 2048)
-n, --ngl <value>
Number of GPU layers (default: 0)
--temp <value>
Temperature (default: 0.8)
-v, --verbose, --log-verbose
Set verbosity level to infinity (i.e. log all messages, useful for debugging)
-h, --help

111
examples/run/run.cpp
View File

@ -55,29 +55,51 @@ static int printe(const char * fmt, ...) {
class Opt {
public:
int init(int argc, const char ** argv) {
ctx_params = llama_context_default_params();
model_params = llama_model_default_params();
context_size_default = ctx_params.n_batch;
ngl_default = model_params.n_gpu_layers;
common_params_sampling sampling;
temperature_default = sampling.temp;
if (argc < 2) {
printe("Error: No arguments provided.\n");
print_help();
return 1;
}
// Parse arguments
if (parse(argc, argv)) {
printe("Error: Failed to parse arguments.\n");
help();
print_help();
return 1;
}
// If help is requested, show help and exit
if (help_) {
help();
if (help) {
print_help();
return 2;
}
ctx_params.n_batch = context_size >= 0 ? context_size : context_size_default;
model_params.n_gpu_layers = ngl >= 0 ? ngl : ngl_default;
temperature = temperature >= 0 ? temperature : temperature_default;
return 0; // Success
}
llama_context_params ctx_params;
llama_model_params model_params;
std::string model_;
std::string user_;
int context_size_ = -1, ngl_ = -1;
bool verbose_ = false;
std::string user;
int context_size = -1, ngl = -1;
float temperature = -1;
bool verbose = false;
private:
bool help_ = false;
int context_size_default = -1, ngl_default = -1;
float temperature_default = -1;
bool help = false;
bool parse_flag(const char ** argv, int i, const char * short_opt, const char * long_opt) {
return strcmp(argv[i], short_opt) == 0 || strcmp(argv[i], long_opt) == 0;
@ -89,6 +111,17 @@ class Opt {
}
option_value = std::atoi(argv[++i]);
return 0;
}
int handle_option_with_value(int argc, const char ** argv, int & i, float & option_value) {
if (i + 1 >= argc) {
return 1;
}
option_value = std::atof(argv[++i]);
return 0;
}
@ -96,18 +129,22 @@ class Opt {
bool options_parsing = true;
for (int i = 1, positional_args_i = 0; i < argc; ++i) {
if (options_parsing && (strcmp(argv[i], "-c") == 0 || strcmp(argv[i], "--context-size") == 0)) {
if (handle_option_with_value(argc, argv, i, context_size_) == 1) {
if (handle_option_with_value(argc, argv, i, context_size) == 1) {
return 1;
}
} else if (options_parsing && (strcmp(argv[i], "-n") == 0 || strcmp(argv[i], "--ngl") == 0)) {
if (handle_option_with_value(argc, argv, i, ngl_) == 1) {
if (handle_option_with_value(argc, argv, i, ngl) == 1) {
return 1;
}
} else if (options_parsing && strcmp(argv[i], "--temp") == 0) {
if (handle_option_with_value(argc, argv, i, temperature) == 1) {
return 1;
}
} else if (options_parsing &&
(parse_flag(argv, i, "-v", "--verbose") || parse_flag(argv, i, "-v", "--log-verbose"))) {
verbose_ = true;
verbose = true;
} else if (options_parsing && parse_flag(argv, i, "-h", "--help")) {
help_ = true;
help = true;
return 0;
} else if (options_parsing && strcmp(argv[i], "--") == 0) {
options_parsing = false;
@ -120,16 +157,16 @@ class Opt {
model_ = argv[i];
} else if (positional_args_i == 1) {
++positional_args_i;
user_ = argv[i];
user = argv[i];
} else {
user_ += " " + std::string(argv[i]);
user += " " + std::string(argv[i]);
}
}
return 0;
}
void help() const {
void print_help() const {
printf(
"Description:\n"
" Runs a llm\n"
@ -142,6 +179,8 @@ class Opt {
" Context size (default: %d)\n"
" -n, --ngl <value>\n"
" Number of GPU layers (default: %d)\n"
" --temp <value>\n"
" Temperature (default: %.1f)\n"
" -v, --verbose, --log-verbose\n"
" Set verbosity level to infinity (i.e. log all messages, useful for debugging)\n"
" -h, --help\n"
@ -170,7 +209,7 @@ class Opt {
" llama-run file://some-file3.gguf\n"
" llama-run --ngl 999 some-file4.gguf\n"
" llama-run --ngl 999 some-file5.gguf Hello World\n",
llama_context_default_params().n_batch, llama_model_default_params().n_gpu_layers);
context_size_default, ngl_default, temperature_default);
}
};
@ -495,12 +534,12 @@ class LlamaData {
return 1;
}
context = initialize_context(model, opt.context_size_);
context = initialize_context(model, opt);
if (!context) {
return 1;
}
sampler = initialize_sampler();
sampler = initialize_sampler(opt);
return 0;
}
@ -619,14 +658,12 @@ class LlamaData {
// Initializes the model and returns a unique pointer to it
llama_model_ptr initialize_model(Opt & opt) {
ggml_backend_load_all();
llama_model_params model_params = llama_model_default_params();
model_params.n_gpu_layers = opt.ngl_ >= 0 ? opt.ngl_ : model_params.n_gpu_layers;
resolve_model(opt.model_);
printe(
"\r%*s"
"\rLoading model",
get_terminal_width(), " ");
llama_model_ptr model(llama_load_model_from_file(opt.model_.c_str(), model_params));
llama_model_ptr model(llama_load_model_from_file(opt.model_.c_str(), opt.model_params));
if (!model) {
printe("%s: error: unable to load model from file: %s\n", __func__, opt.model_.c_str());
}
@ -636,10 +673,8 @@ class LlamaData {
}
// Initializes the context with the specified parameters
llama_context_ptr initialize_context(const llama_model_ptr & model, const int n_ctx) {
llama_context_params ctx_params = llama_context_default_params();
ctx_params.n_ctx = ctx_params.n_batch = n_ctx >= 0 ? n_ctx : ctx_params.n_batch;
llama_context_ptr context(llama_new_context_with_model(model.get(), ctx_params));
llama_context_ptr initialize_context(const llama_model_ptr & model, const Opt & opt) {
llama_context_ptr context(llama_new_context_with_model(model.get(), opt.ctx_params));
if (!context) {
printe("%s: error: failed to create the llama_context\n", __func__);
}
@ -648,10 +683,10 @@ class LlamaData {
}
// Initializes and configures the sampler
llama_sampler_ptr initialize_sampler() {
llama_sampler_ptr initialize_sampler(const Opt & opt) {
llama_sampler_ptr sampler(llama_sampler_chain_init(llama_sampler_chain_default_params()));
llama_sampler_chain_add(sampler.get(), llama_sampler_init_min_p(0.05f, 1));
llama_sampler_chain_add(sampler.get(), llama_sampler_init_temp(0.8f));
llama_sampler_chain_add(sampler.get(), llama_sampler_init_temp(opt.temperature));
llama_sampler_chain_add(sampler.get(), llama_sampler_init_dist(LLAMA_DEFAULT_SEED));
return sampler;
@ -798,9 +833,9 @@ static int apply_chat_template_with_error_handling(LlamaData & llama_data, const
}
// Helper function to handle user input
static int handle_user_input(std::string & user_input, const std::string & user_) {
if (!user_.empty()) {
user_input = user_;
static int handle_user_input(std::string & user_input, const std::string & user) {
if (!user.empty()) {
user_input = user;
return 0; // No need for interactive input
}
@ -832,17 +867,17 @@ static bool is_stdout_a_terminal() {
}
// Function to tokenize the prompt
static int chat_loop(LlamaData & llama_data, const std::string & user_) {
static int chat_loop(LlamaData & llama_data, const std::string & user) {
int prev_len = 0;
llama_data.fmtted.resize(llama_n_ctx(llama_data.context.get()));
static const bool stdout_a_terminal = is_stdout_a_terminal();
while (true) {
// Get user input
std::string user_input;
while (handle_user_input(user_input, user_)) {
while (handle_user_input(user_input, user)) {
}
add_message("user", user_.empty() ? user_input : user_, llama_data);
add_message("user", user.empty() ? user_input : user, llama_data);
int new_len;
if (apply_chat_template_with_error_handling(llama_data, true, new_len) < 0) {
return 1;
@ -854,7 +889,7 @@ static int chat_loop(LlamaData & llama_data, const std::string & user_) {
return 1;
}
if (!user_.empty()) {
if (!user.empty()) {
break;
}
@ -869,7 +904,7 @@ static int chat_loop(LlamaData & llama_data, const std::string & user_) {
static void log_callback(const enum ggml_log_level level, const char * text, void * p) {
const Opt * opt = static_cast<Opt *>(p);
if (opt->verbose_ || level == GGML_LOG_LEVEL_ERROR) {
if (opt->verbose || level == GGML_LOG_LEVEL_ERROR) {
printe("%s", text);
}
}
@ -890,11 +925,11 @@ int main(int argc, const char ** argv) {
}
if (!is_stdin_a_terminal()) {
if (!opt.user_.empty()) {
opt.user_ += "\n\n";
if (!opt.user.empty()) {
opt.user += "\n\n";
}
opt.user_ += read_pipe_data();
opt.user += read_pipe_data();
}
llama_log_set(log_callback, &opt);
@ -903,7 +938,7 @@ int main(int argc, const char ** argv) {
return 1;
}
if (chat_loop(llama_data, opt.user_)) {
if (chat_loop(llama_data, opt.user)) {
return 1;
}