server : add "samplers" param to control the samplers order (#5494)

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Alexey Parfenov 2024-02-16 11:33:25 +00:00 committed by GitHub
parent 5f5808ca7b
commit 6dcc02d244
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6 changed files with 74 additions and 30 deletions

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@ -341,7 +341,7 @@ bool gpt_params_parse_ex(int argc, char ** argv, gpt_params & params) {
break;
}
const auto sampler_names = string_split(argv[i], ';');
sparams.samplers_sequence = sampler_types_from_names(sampler_names);
sparams.samplers_sequence = sampler_types_from_names(sampler_names, true);
} else if (arg == "--sampling-seq") {
if (++i >= argc) {
invalid_param = true;
@ -964,7 +964,8 @@ void gpt_print_usage(int /*argc*/, char ** argv, const gpt_params & params) {
printf(" -n N, --n-predict N number of tokens to predict (default: %d, -1 = infinity, -2 = until context filled)\n", params.n_predict);
printf(" -c N, --ctx-size N size of the prompt context (default: %d, 0 = loaded from model)\n", params.n_ctx);
printf(" -b N, --batch-size N batch size for prompt processing (default: %d)\n", params.n_batch);
printf(" --samplers samplers that will be used for generation in the order, separated by \';\' (default: %s)\n", sampler_type_names.c_str());
printf(" --samplers samplers that will be used for generation in the order, separated by \';\'\n");
printf(" (default: %s)\n", sampler_type_names.c_str());
printf(" --sampling-seq simplified sequence for samplers that will be used (default: %s)\n", sampler_type_chars.c_str());
printf(" --top-k N top-k sampling (default: %d, 0 = disabled)\n", sparams.top_k);
printf(" --top-p N top-p sampling (default: %.1f, 1.0 = disabled)\n", (double)sparams.top_p);
@ -1133,34 +1134,50 @@ std::vector<std::string> string_split(std::string input, char separator) {
return parts;
}
std::vector<llama_sampler_type> sampler_types_from_names(const std::vector<std::string> & names) {
std::vector<llama_sampler_type> sampler_types_from_names(const std::vector<std::string> & names, bool allow_alt_names) {
std::unordered_map<std::string, llama_sampler_type> sampler_canonical_name_map {
{"top_k", llama_sampler_type::TOP_K},
{"top_p", llama_sampler_type::TOP_P},
{"typical_p", llama_sampler_type::TYPICAL_P},
{"min_p", llama_sampler_type::MIN_P},
{"tfs_z", llama_sampler_type::TFS_Z},
{"temperature", llama_sampler_type::TEMPERATURE}
};
// since samplers names are written multiple ways
// make it ready for both system names and input names
std::unordered_map<std::string, llama_sampler_type> sampler_name_map {
{"top_k", llama_sampler_type::TOP_K},
std::unordered_map<std::string, llama_sampler_type> sampler_alt_name_map {
{"top-k", llama_sampler_type::TOP_K},
{"top_p", llama_sampler_type::TOP_P},
{"top-p", llama_sampler_type::TOP_P},
{"nucleus", llama_sampler_type::TOP_P},
{"typical_p", llama_sampler_type::TYPICAL_P},
{"typical-p", llama_sampler_type::TYPICAL_P},
{"typical", llama_sampler_type::TYPICAL_P},
{"min_p", llama_sampler_type::MIN_P},
{"min-p", llama_sampler_type::MIN_P},
{"tfs_z", llama_sampler_type::TFS_Z},
{"tfs-z", llama_sampler_type::TFS_Z},
{"tfs", llama_sampler_type::TFS_Z},
{"temp", llama_sampler_type::TEMP},
{"temperature", llama_sampler_type::TEMP}
{"temp", llama_sampler_type::TEMPERATURE}
};
std::vector<llama_sampler_type> sampler_types;
sampler_types.reserve(names.size());
for (const auto& name : names) {
const auto sampler_item = sampler_name_map.find(name);
if (sampler_item != sampler_name_map.end()) {
for (const auto & name : names)
{
auto sampler_item = sampler_canonical_name_map.find(name);
if (sampler_item != sampler_canonical_name_map.end())
{
sampler_types.push_back(sampler_item->second);
}
else
{
if (allow_alt_names)
{
sampler_item = sampler_alt_name_map.find(name);
if (sampler_item != sampler_alt_name_map.end())
{
sampler_types.push_back(sampler_item->second);
}
}
}
}
return sampler_types;
}
@ -1172,7 +1189,7 @@ std::vector<llama_sampler_type> sampler_types_from_chars(const std::string & nam
{'y', llama_sampler_type::TYPICAL_P},
{'m', llama_sampler_type::MIN_P},
{'f', llama_sampler_type::TFS_Z},
{'t', llama_sampler_type::TEMP}
{'t', llama_sampler_type::TEMPERATURE}
};
std::vector<llama_sampler_type> sampler_types;
@ -1188,12 +1205,12 @@ std::vector<llama_sampler_type> sampler_types_from_chars(const std::string & nam
std::string sampler_type_to_name_string(llama_sampler_type sampler_type) {
switch (sampler_type) {
case llama_sampler_type::TOP_K: return "top_k";
case llama_sampler_type::TFS_Z: return "tfs_z";
case llama_sampler_type::TYPICAL_P: return "typical_p";
case llama_sampler_type::TOP_P: return "top_p";
case llama_sampler_type::MIN_P: return "min_p";
case llama_sampler_type::TEMP: return "temp";
case llama_sampler_type::TOP_K: return "top_k";
case llama_sampler_type::TFS_Z: return "tfs_z";
case llama_sampler_type::TYPICAL_P: return "typical_p";
case llama_sampler_type::TOP_P: return "top_p";
case llama_sampler_type::MIN_P: return "min_p";
case llama_sampler_type::TEMPERATURE: return "temperature";
default : return "";
}
}

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@ -165,7 +165,7 @@ void process_escapes(std::string& input);
// String utils
//
std::vector<llama_sampler_type> sampler_types_from_names(const std::vector<std::string> & names);
std::vector<llama_sampler_type> sampler_types_from_names(const std::vector<std::string> & names, bool allow_alt_names);
std::vector<llama_sampler_type> sampler_types_from_chars(const std::string & names_string);
std::vector<std::string> string_split(std::string input, char separator);
std::string sampler_type_to_name_string(llama_sampler_type sampler_type);

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@ -139,7 +139,7 @@ static void sampler_queue(
case llama_sampler_type::TYPICAL_P: llama_sample_typical (ctx_main, &cur_p, typical_p, min_keep); break;
case llama_sampler_type::TOP_P : llama_sample_top_p (ctx_main, &cur_p, top_p, min_keep); break;
case llama_sampler_type::MIN_P : llama_sample_min_p (ctx_main, &cur_p, min_p, min_keep); break;
case llama_sampler_type::TEMP:
case llama_sampler_type::TEMPERATURE:
if (dynatemp_range > 0) {
float dynatemp_min = std::max(0.0f, temp - dynatemp_range);
float dynatemp_max = std::max(0.0f, temp + dynatemp_range);

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@ -10,12 +10,12 @@
// sampler types
enum class llama_sampler_type : char {
TOP_K = 'k',
TOP_P = 'p',
MIN_P = 'm',
TFS_Z = 'f',
TYPICAL_P = 'y',
TEMP = 't'
TOP_K = 'k',
TOP_P = 'p',
MIN_P = 'm',
TFS_Z = 'f',
TYPICAL_P = 'y',
TEMPERATURE = 't'
};
// sampling parameters
@ -45,7 +45,7 @@ typedef struct llama_sampling_params {
llama_sampler_type::TYPICAL_P,
llama_sampler_type::TOP_P,
llama_sampler_type::MIN_P,
llama_sampler_type::TEMP
llama_sampler_type::TEMPERATURE
};
std::string grammar; // optional BNF-like grammar to constrain sampling

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@ -204,6 +204,8 @@ node index.js
`system_prompt`: Change the system prompt (initial prompt of all slots), this is useful for chat applications. [See more](#change-system-prompt-on-runtime)
`samplers`: The order the samplers should be applied in. An array of strings representing sampler type names. If a sampler is not set, it will not be used. If a sampler is specified more than once, it will be applied multiple times. (default: `["top_k", "tfs_z", "typical_p", "top_p", "min_p", "temperature"]` - these are all the available values)
### Result JSON
- Note: When using streaming mode (`stream`) only `content` and `stop` will be returned until end of completion.

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@ -672,6 +672,24 @@ struct llama_server_context
}
}
const auto &samplers_sequence = data.find("samplers");
if (samplers_sequence != data.end() && samplers_sequence->is_array())
{
std::vector<std::string> sampler_names;
for (const auto &sampler_name : *samplers_sequence)
{
if (sampler_name.is_string())
{
sampler_names.emplace_back(sampler_name);
}
}
slot->sparams.samplers_sequence = sampler_types_from_names(sampler_names, false);
}
else
{
slot->sparams.samplers_sequence = default_sparams.samplers_sequence;
}
if (multimodal)
{
const auto &images_data = data.find("image_data");
@ -1026,6 +1044,12 @@ struct llama_server_context
const auto eos_bias = slot.sparams.logit_bias.find(llama_token_eos(model));
const bool ignore_eos = eos_bias != slot.sparams.logit_bias.end() &&
eos_bias->second < 0.0f && std::isinf(eos_bias->second);
std::vector<std::string> samplers_sequence;
for (const auto &sampler_type : slot.sparams.samplers_sequence)
{
samplers_sequence.emplace_back(sampler_type_to_name_string(sampler_type));
}
return json {
{"n_ctx", slot.n_ctx},
{"model", params.model_alias},
@ -1056,6 +1080,7 @@ struct llama_server_context
{"logit_bias", slot.sparams.logit_bias},
{"n_probs", slot.sparams.n_probs},
{"grammar", slot.sparams.grammar},
{"samplers", samplers_sequence}
};
}