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# Conflicts:
#	.github/workflows/build.yml
#	.gitignore
#	CMakeLists.txt
#	Makefile
#	Package.swift
#	README.md
#	ggml-cuda.cu
#	llama.cpp
#	llama.h
#	scripts/sync-ggml.sh
#	tests/CMakeLists.txt
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@LostRuins
LostRuins committed Dec 8, 2023
2 parents 930cdfb + fe680e3 commit ec21fa7
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Showing 34 changed files with 5,822 additions and 1,370 deletions.
3 changes: 3 additions & 0 deletions .gitignore
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Original file line number Diff line number Diff line change
Expand Up @@ -81,6 +81,7 @@ poetry.toml

# Test binaries
tests/test-grammar-parser
/tests/test-llama-grammar
tests/test-double-float
tests/test-grad0
tests/test-opt
Expand All @@ -92,6 +93,8 @@ tests/test-tokenizer-0-llama
tests/test-tokenizer-0-falcon
tests/test-tokenizer-1-llama
tests/test-tokenizer-1-bpe
/tests/test-rope
/tests/test-backend-ops

/koboldcpp_default.so
/koboldcpp_failsafe.so
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156 changes: 150 additions & 6 deletions common/common.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -279,8 +279,18 @@ bool gpt_params_parse_ex(int argc, char ** argv, gpt_params & params) {
break;
}
params.yarn_beta_slow = std::stof(argv[i]);
} else if (arg == "--memory-f32") {
params.memory_f16 = false;
} else if (arg == "--samplers") {
if (++i >= argc) {
invalid_param = true;
break;
}
sparams.samplers_sequence = parse_samplers_input(argv[i]);
} else if (arg == "--sampling-seq") {
if (++i >= argc) {
invalid_param = true;
break;
}
sparams.samplers_sequence = argv[i];
} else if (arg == "--top-p") {
if (++i >= argc) {
invalid_param = true;
Expand Down Expand Up @@ -499,6 +509,12 @@ bool gpt_params_parse_ex(int argc, char ** argv, gpt_params & params) {
params.infill = true;
} else if (arg == "-dkvc" || arg == "--dump-kv-cache") {
params.dump_kv_cache = true;
} else if (arg == "-nkvo" || arg == "--no-kv-offload") {
params.no_kv_offload = true;
} else if (arg == "-ctk" || arg == "--cache-type-k") {
params.cache_type_k = argv[++i];
} else if (arg == "-ctv" || arg == "--cache-type-v") {
params.cache_type_v = argv[++i];
} else if (arg == "--multiline-input") {
params.multiline_input = true;
} else if (arg == "--simple-io") {
Expand Down Expand Up @@ -679,6 +695,47 @@ bool gpt_params_parse_ex(int argc, char ** argv, gpt_params & params) {
std::istreambuf_iterator<char>(),
std::back_inserter(sparams.grammar)
);
} else if (arg == "--override-kv") {
if (++i >= argc) {
invalid_param = true;
break;
}
char * sep = strchr(argv[i], '=');
if (sep == nullptr || sep - argv[i] >= 128) {
fprintf(stderr, "error: Malformed KV override: %s\n", argv[i]);
invalid_param = true;
break;
}
struct llama_model_kv_override kvo;
std::strncpy(kvo.key, argv[i], sep - argv[i]);
kvo.key[sep - argv[i]] = 0;
sep++;
if (strncmp(sep, "int:", 4) == 0) {
sep += 4;
kvo.tag = LLAMA_KV_OVERRIDE_INT;
kvo.int_value = std::atol(sep);
} else if (strncmp(sep, "float:", 6) == 0) {
sep += 6;
kvo.tag = LLAMA_KV_OVERRIDE_FLOAT;
kvo.float_value = std::atof(sep);
} else if (strncmp(sep, "bool:", 5) == 0) {
sep += 5;
kvo.tag = LLAMA_KV_OVERRIDE_BOOL;
if (std::strcmp(sep, "true") == 0) {
kvo.bool_value = true;
} else if (std::strcmp(sep, "false") == 0) {
kvo.bool_value = false;
} else {
fprintf(stderr, "error: Invalid boolean value for KV override: %s\n", argv[i]);
invalid_param = true;
break;
}
} else {
fprintf(stderr, "error: Invalid type for KV override: %s\n", argv[i]);
invalid_param = true;
break;
}
params.kv_overrides.push_back(kvo);
#ifndef LOG_DISABLE_LOGS
// Parse args for logging parameters
} else if ( log_param_single_parse( argv[i] ) ) {
Expand Down Expand Up @@ -722,6 +779,11 @@ bool gpt_params_parse_ex(int argc, char ** argv, gpt_params & params) {
}
}

if (!params.kv_overrides.empty()) {
params.kv_overrides.emplace_back(llama_model_kv_override());
params.kv_overrides.back().key[0] = 0;
}

return true;
}

Expand Down Expand Up @@ -762,6 +824,8 @@ 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 \';\', for example: \"top_k;tfs;typical;top_p;min_p;temp\"\n");
printf(" --sampling-seq simplified sequence for samplers that will be used (default: %s)\n", sparams.samplers_sequence.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);
printf(" --min-p N min-p sampling (default: %.1f, 0.0 = disabled)\n", (double)sparams.min_p);
Expand Down Expand Up @@ -799,8 +863,6 @@ void gpt_print_usage(int /*argc*/, char ** argv, const gpt_params & params) {
printf(" --yarn-beta-fast N YaRN: low correction dim or beta (default: %.1f)\n", params.yarn_beta_fast);
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(" --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(" --temp N temperature (default: %.1f)\n", (double)sparams.temp);
printf(" --logits-all return logits for all tokens in the batch (default: disabled)\n");
printf(" --hellaswag compute HellaSwag score over random tasks from datafile supplied with -f\n");
Expand Down Expand Up @@ -841,6 +903,12 @@ void gpt_print_usage(int /*argc*/, char ** argv, const gpt_params & params) {
printf(" --verbose-prompt print prompt before generation\n");
printf(" -dkvc, --dump-kv-cache\n");
printf(" verbose print of the KV cache\n");
printf(" -nkvo, --no-kv-offload\n");
printf(" disable KV offload\n");
printf(" -ctk TYPE, --cache-type-k TYPE\n");
printf(" KV cache data type for K (default: %s)\n", params.cache_type_k.c_str());
printf(" -ctv TYPE, --cache-type-v TYPE\n");
printf(" KV cache data type for V (default: %s)\n", params.cache_type_v.c_str());
printf(" --simple-io use basic IO for better compatibility in subprocesses and limited consoles\n");
printf(" --lora FNAME apply LoRA adapter (implies --no-mmap)\n");
printf(" --lora-scaled FNAME S apply LoRA adapter with user defined scaling S (implies --no-mmap)\n");
Expand All @@ -851,6 +919,9 @@ void gpt_print_usage(int /*argc*/, char ** argv, const gpt_params & params) {
printf(" draft model for speculative decoding (default: %s)\n", params.model.c_str());
printf(" -ld LOGDIR, --logdir LOGDIR\n");
printf(" path under which to save YAML logs (no logging if unset)\n");
printf(" --override-kv KEY=TYPE:VALUE\n");
printf(" advanced option to override model metadata by key. may be specified multiple times.\n");
printf(" types: int, float, bool. example: --override-kv tokenizer.ggml.add_bos_token=bool:false\n");
printf("\n");
#ifndef LOG_DISABLE_LOGS
log_print_usage();
Expand Down Expand Up @@ -887,6 +958,48 @@ std::string gpt_random_prompt(std::mt19937 & rng) {
GGML_UNREACHABLE();
}

//
// String parsing
//

std::string parse_samplers_input(std::string input) {
std::string output = "";
// since samplers names are written multiple ways
// make it ready for both system names and input names
std::unordered_map<std::string, char> samplers_symbols {
{"top_k", 'k'},
{"top-k", 'k'},
{"top_p", 'p'},
{"top-p", 'p'},
{"nucleus", 'p'},
{"typical_p", 'y'},
{"typical-p", 'y'},
{"typical", 'y'},
{"min_p", 'm'},
{"min-p", 'm'},
{"tfs_z", 'f'},
{"tfs-z", 'f'},
{"tfs", 'f'},
{"temp", 't'},
{"temperature",'t'}
};
// expected format example: "temp;top_k;tfs_z;typical_p;top_p;min_p"
size_t separator = input.find(';');
while (separator != input.npos) {
std::string name = input.substr(0,separator);
input = input.substr(separator+1);
separator = input.find(';');

if (samplers_symbols.find(name) != samplers_symbols.end()) {
output += samplers_symbols[name];
}
}
if (samplers_symbols.find(input) != samplers_symbols.end()) {
output += samplers_symbols[input];
}
return output;
}

//
// Model utils
//
Expand All @@ -901,10 +1014,39 @@ struct llama_model_params llama_model_params_from_gpt_params(const gpt_params &
mparams.tensor_split = params.tensor_split;
mparams.use_mmap = params.use_mmap;
mparams.use_mlock = params.use_mlock;
if (params.kv_overrides.empty()) {
mparams.kv_overrides = NULL;
} else {
GGML_ASSERT(params.kv_overrides.back().key[0] == 0 && "KV overrides not terminated with empty key");
mparams.kv_overrides = params.kv_overrides.data();
}

return mparams;
}

static ggml_type kv_cache_type_from_str(const std::string & s) {
if (s == "f16") {
return GGML_TYPE_F16;
}
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 == "q5_0") {
return GGML_TYPE_Q5_0;
}
if (s == "q5_1") {
return GGML_TYPE_Q5_1;
}

throw std::runtime_error("Invalid cache type: " + s);
}

struct llama_context_params llama_context_params_from_gpt_params(const gpt_params & params) {
auto cparams = llama_context_default_params();

Expand All @@ -914,7 +1056,6 @@ struct llama_context_params llama_context_params_from_gpt_params(const gpt_param
cparams.n_threads_batch = params.n_threads_batch == -1 ? params.n_threads : params.n_threads_batch;
cparams.mul_mat_q = params.mul_mat_q;
cparams.seed = params.seed;
cparams.f16_kv = params.memory_f16;
cparams.logits_all = params.logits_all;
cparams.embedding = params.embedding;
cparams.rope_scaling_type = params.rope_scaling_type;
Expand All @@ -925,6 +1066,10 @@ struct llama_context_params llama_context_params_from_gpt_params(const gpt_param
cparams.yarn_beta_fast = params.yarn_beta_fast;
cparams.yarn_beta_slow = params.yarn_beta_slow;
cparams.yarn_orig_ctx = params.yarn_orig_ctx;
cparams.offload_kqv = !params.no_kv_offload;

cparams.type_k = kv_cache_type_from_str(params.cache_type_k);
cparams.type_v = kv_cache_type_from_str(params.cache_type_v);

return cparams;
}
Expand Down Expand Up @@ -1337,7 +1482,6 @@ void dump_non_result_info_yaml(FILE * stream, const gpt_params & params, const l
}
fprintf(stream, "lora_base: %s\n", params.lora_base.c_str());
fprintf(stream, "main_gpu: %d # default: 0\n", params.main_gpu);
fprintf(stream, "memory_f32: %s # default: false\n", !params.memory_f16 ? "true" : "false");
fprintf(stream, "mirostat: %d # default: 0 (disabled)\n", sparams.mirostat);
fprintf(stream, "mirostat_ent: %f # default: 5.0\n", sparams.mirostat_tau);
fprintf(stream, "mirostat_lr: %f # default: 0.1\n", sparams.mirostat_eta);
Expand Down
15 changes: 13 additions & 2 deletions common/common.h
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Original file line number Diff line number Diff line change
Expand Up @@ -94,6 +94,8 @@ struct gpt_params {
std::vector<std::string> antiprompt; // string upon seeing which more user input is prompted
std::string logdir = ""; // directory in which to save YAML log files

std::vector<llama_model_kv_override> kv_overrides;

// TODO: avoid tuple, use struct
std::vector<std::tuple<std::string, float>> lora_adapter; // lora adapter path with user defined scale
std::string lora_base = ""; // base model path for the lora adapter
Expand All @@ -106,7 +108,6 @@ struct gpt_params {
size_t hellaswag_tasks = 400; // number of tasks to use when computing the HellaSwag score

bool mul_mat_q = true; // if true, use mul_mat_q kernels instead of cuBLAS
bool memory_f16 = true; // use f16 instead of f32 for memory kv
bool random_prompt = false; // do not randomize prompt if none provided
bool use_color = false; // use color to distinguish generations and inputs
bool interactive = false; // interactive mode
Expand All @@ -131,10 +132,14 @@ struct gpt_params {
bool verbose_prompt = false; // print prompt tokens before generation
bool infill = false; // use infill mode
bool dump_kv_cache = false; // dump the KV cache contents for debugging purposes
bool no_kv_offload = false; // disable KV offloading

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

// multimodal models (see examples/llava)
std::string mmproj = ""; // path to multimodal projector
std::string image = ""; // path to an image file
std::string image = ""; // path to an image file
};

bool gpt_params_parse_ex(int argc, char ** argv, gpt_params & params);
Expand All @@ -149,6 +154,12 @@ std::string gpt_random_prompt(std::mt19937 & rng);

void process_escapes(std::string& input);

//
// String parsing
//

std::string parse_samplers_input(std::string input);

//
// Model utils
//
Expand Down
2 changes: 1 addition & 1 deletion common/grammar-parser.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -190,7 +190,7 @@ namespace grammar_parser {
pos = parse_space(pos + 1, is_nested);
} else if (*pos == '*' || *pos == '+' || *pos == '?') { // repetition operator
if (last_sym_start == out_elements.size()) {
throw std::runtime_error(std::string("expecting preceeding item to */+/? at ") + pos);
throw std::runtime_error(std::string("expecting preceding item to */+/? at ") + pos);
}

// apply transformation to previous symbol (last_sym_start to end) according to
Expand Down
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