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Make llama.com -h print to stdout

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This commit is contained in:
Justine Tunney 2023-05-10 04:55:59 -07:00
parent f312f706f4
commit ca990ef091
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GPG key ID: BE714B4575D6E328
5 changed files with 74 additions and 72 deletions
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2
libc/runtime/cosmo2.c
View file

@ -49,8 +49,6 @@ extern init_f *__init_array_start[] __attribute__((__weak__));
extern init_f *__init_array_end[] __attribute__((__weak__));
extern pthread_mutex_t __mmi_lock_obj;
struct CosmoTib *tib;
textstartup void cosmo(long *sp) {
int argc;
init_f **fp;

4
third_party/compiler_rt/compiler_rt.mk vendored
View file

@ -48,6 +48,10 @@ $(THIRD_PARTY_COMPILER_RT_A_OBJS): private \
$(OLD_CODE) \
-DCRT_HAS_128BIT
# these assembly files are safe to build on aarch64
o/$(MODE)/third_party/compiler_rt/comprt.o: third_party/compiler_rt/comprt.S
@$(COMPILE) -AOBJECTIFY.S $(OBJECTIFY.S) $(OUTPUT_OPTION) -c $<
THIRD_PARTY_COMPILER_RT_LIBS = $(foreach x,$(THIRD_PARTY_COMPILER_RT_ARTIFACTS),$($(x)))
THIRD_PARTY_COMPILER_RT_SRCS = $(foreach x,$(THIRD_PARTY_COMPILER_RT_ARTIFACTS),$($(x)_SRCS))
THIRD_PARTY_COMPILER_RT_HDRS = $(foreach x,$(THIRD_PARTY_COMPILER_RT_ARTIFACTS),$($(x)_HDRS))

2
third_party/compiler_rt/comprt.S vendored
View file

@ -3,7 +3,7 @@
// Nop ref this to force pull the license into linkage.
.section .yoink
huge_compiler_rt_license:
int3
ret
.endobj huge_compiler_rt_license,globl,hidden
.previous

136
third_party/ggml/common.cc vendored
View file

@ -302,7 +302,7 @@ bool gpt_params_parse(int argc, char ** argv, gpt_params & params) {
}
params.n_parts = std::stoi(argv[i]);
} else if (arg == "-h" || arg == "--help") {
gpt_print_usage(argc, argv, default_params);
gpt_print_usage(stdout, argc, argv, default_params);
exit(0);
} else if (arg == "--random-prompt") {
params.random_prompt = true;
@ -320,13 +320,13 @@ bool gpt_params_parse(int argc, char ** argv, gpt_params & params) {
params.input_suffix = argv[i];
} else {
fprintf(stderr, "error: unknown argument: %s\n", arg.c_str());
gpt_print_usage(argc, argv, default_params);
gpt_print_usage(stderr, argc, argv, default_params);
exit(1);
}
}
if (invalid_param) {
fprintf(stderr, "error: invalid parameter for argument: %s\n", arg.c_str());
gpt_print_usage(argc, argv, default_params);
gpt_print_usage(stderr, argc, argv, default_params);
exit(1);
}
@ -363,75 +363,75 @@ bool gpt_params_parse(int argc, char ** argv, gpt_params & params) {
return true;
}
void gpt_print_usage(int /*argc*/, char ** argv, const gpt_params & params) {
fprintf(stderr, "usage: %s [options]\n", argv[0]);
fprintf(stderr, "\n");
fprintf(stderr, "options:\n");
fprintf(stderr, " -h, --help show this help message and exit\n");
fprintf(stderr, " -v, --verbose print plenty of helpful information, e.g. prompt\n");
fprintf(stderr, " -i, --interactive run in interactive mode\n");
fprintf(stderr, " --interactive-first run in interactive mode and wait for input right away\n");
fprintf(stderr, " -ins, --instruct run in instruction mode (use with Alpaca models)\n");
fprintf(stderr, " --multiline-input allows you to write or paste multiple lines without ending each in '\\'\n");
fprintf(stderr, " -r PROMPT, --reverse-prompt PROMPT\n");
fprintf(stderr, " run in interactive mode and poll user input upon seeing PROMPT (can be\n");
fprintf(stderr, " specified more than once for multiple prompts).\n");
fprintf(stderr, " --color colorise output to distinguish prompt and user input from generations\n");
fprintf(stderr, " -s SEED, --seed SEED RNG seed (default: -1, use random seed for < 0)\n");
fprintf(stderr, " -t N, --threads N number of threads to use during computation (default: %d)\n", params.n_threads);
fprintf(stderr, " -p PROMPT, --prompt PROMPT\n");
fprintf(stderr, " prompt to start generation with (default: Companion AI)\n");
fprintf(stderr, " --random-prompt start with a randomized prompt.\n");
fprintf(stderr, " --in-prefix STRING string to prefix user inputs with (default: empty)\n");
fprintf(stderr, " --in-suffix STRING string to suffix after user inputs with (default: empty)\n");
fprintf(stderr, " -f FNAME, --file FNAME\n");
fprintf(stderr, " text file containing prompt (default: Companion AI)\n");
fprintf(stderr, " -C FNAME, --prompt_cache FNAME\n");
fprintf(stderr, " path of cache for fast prompt reload (default: .prompt.jtlp)\n");
fprintf(stderr, " -n N, --n_predict N number of tokens to predict (default: %d, -1 = infinity)\n", params.n_predict);
fprintf(stderr, " --top_k N top-k sampling (default: %d, 0 = disabled)\n", params.top_k);
fprintf(stderr, " --top_p N top-p sampling (default: %.1f, 1.0 = disabled)\n", (double)params.top_p);
fprintf(stderr, " --tfs N tail free sampling, parameter z (default: %.1f, 1.0 = disabled)\n", (double)params.tfs_z);
fprintf(stderr, " --typical N locally typical sampling, parameter p (default: %.1f, 1.0 = disabled)\n", (double)params.typical_p);
fprintf(stderr, " --repeat_last_n N last n tokens to consider for penalize (default: %d, 0 = disabled, -1 = ctx_size)\n", params.repeat_last_n);
fprintf(stderr, " --repeat_penalty N penalize repeat sequence of tokens (default: %.1f, 1.0 = disabled)\n", (double)params.repeat_penalty);
fprintf(stderr, " --presence_penalty N repeat alpha presence penalty (default: %.1f, 0.0 = disabled)\n", (double)params.presence_penalty);
fprintf(stderr, " --frequency_penalty N repeat alpha frequency penalty (default: %.1f, 0.0 = disabled)\n", (double)params.frequency_penalty);
fprintf(stderr, " --mirostat N use Mirostat sampling.\n");
fprintf(stderr, " Top K, Nucleus, Tail Free and Locally Typical samplers are ignored if used.\n");
fprintf(stderr, " (default: %d, 0 = disabled, 1 = Mirostat, 2 = Mirostat 2.0)\n", params.mirostat);
fprintf(stderr, " --mirostat_lr N Mirostat learning rate, parameter eta (default: %.1f)\n", (double)params.mirostat_eta);
fprintf(stderr, " --mirostat_ent N Mirostat target entropy, parameter tau (default: %.1f)\n", (double)params.mirostat_tau);
fprintf(stderr, " -l TOKEN_ID(+/-)BIAS, --logit-bias TOKEN_ID(+/-)BIAS\n");
fprintf(stderr, " modifies the likelihood of token appearing in the completion,\n");
fprintf(stderr, " i.e. `--logit-bias 15043+1` to increase likelihood of token ' Hello',\n");
fprintf(stderr, " or `--logit-bias 15043-1` to decrease likelihood of token ' Hello'\n");
fprintf(stderr, " --repeat_last_n N last n tokens to consider for penalize (default: %d)\n", params.repeat_last_n);
fprintf(stderr, " --repeat_penalty N penalize repeat sequence of tokens (default: %.1f)\n", (double)params.repeat_penalty);
fprintf(stderr, " -c N, --ctx_size N size of the prompt context (default: %d)\n", params.n_ctx);
fprintf(stderr, " --ignore-eos ignore end of stream token and continue generating (implies --logit-bias 2-inf)\n");
fprintf(stderr, " --no-penalize-nl do not penalize newline token\n");
fprintf(stderr, " --memory_f32 use f32 instead of f16 for memory key+value\n");
fprintf(stderr, " --temp N temperature (default: %.1f)\n", (double)params.temp);
fprintf(stderr, " --n_parts N number of model parts (default: -1 = determine from dimensions)\n");
fprintf(stderr, " -b N, --batch_size N batch size for prompt processing (default: %d)\n", params.n_batch);
fprintf(stderr, " --perplexity compute perplexity over the prompt\n");
fprintf(stderr, " --keep NUM|STR number of tokens to keep from the initial prompt, or substring\n");
fprintf(stderr, " to search for within prompt that divides the actual prompt from\n");
fprintf(stderr, " its initial example text (default: %d, -1 = all)\n", params.n_keep);
void gpt_print_usage(FILE *f, int /*argc*/, char ** argv, const gpt_params & params) {
fprintf(f, "usage: %s [options]\n", argv[0]);
fprintf(f, "\n");
fprintf(f, "options:\n");
fprintf(f, " -h, --help show this help message and exit\n");
fprintf(f, " -v, --verbose print plenty of helpful information, e.g. prompt\n");
fprintf(f, " -i, --interactive run in interactive mode\n");
fprintf(f, " --interactive-first run in interactive mode and wait for input right away\n");
fprintf(f, " -ins, --instruct run in instruction mode (use with Alpaca models)\n");
fprintf(f, " --multiline-input allows you to write or paste multiple lines without ending each in '\\'\n");
fprintf(f, " -r PROMPT, --reverse-prompt PROMPT\n");
fprintf(f, " run in interactive mode and poll user input upon seeing PROMPT (can be\n");
fprintf(f, " specified more than once for multiple prompts).\n");
fprintf(f, " --color colorise output to distinguish prompt and user input from generations\n");
fprintf(f, " -s SEED, --seed SEED RNG seed (default: -1, use random seed for < 0)\n");
fprintf(f, " -t N, --threads N number of threads to use during computation (default: %d)\n", params.n_threads);
fprintf(f, " -p PROMPT, --prompt PROMPT\n");
fprintf(f, " prompt to start generation with (default: Companion AI)\n");
fprintf(f, " --random-prompt start with a randomized prompt.\n");
fprintf(f, " --in-prefix STRING string to prefix user inputs with (default: empty)\n");
fprintf(f, " --in-suffix STRING string to suffix after user inputs with (default: empty)\n");
fprintf(f, " -f FNAME, --file FNAME\n");
fprintf(f, " text file containing prompt (default: Companion AI)\n");
fprintf(f, " -C FNAME, --prompt_cache FNAME\n");
fprintf(f, " path of cache for fast prompt reload (default: .prompt.jtlp)\n");
fprintf(f, " -n N, --n_predict N number of tokens to predict (default: %d, -1 = infinity)\n", params.n_predict);
fprintf(f, " --top_k N top-k sampling (default: %d, 0 = disabled)\n", params.top_k);
fprintf(f, " --top_p N top-p sampling (default: %.1f, 1.0 = disabled)\n", (double)params.top_p);
fprintf(f, " --tfs N tail free sampling, parameter z (default: %.1f, 1.0 = disabled)\n", (double)params.tfs_z);
fprintf(f, " --typical N locally typical sampling, parameter p (default: %.1f, 1.0 = disabled)\n", (double)params.typical_p);
fprintf(f, " --repeat_last_n N last n tokens to consider for penalize (default: %d, 0 = disabled, -1 = ctx_size)\n", params.repeat_last_n);
fprintf(f, " --repeat_penalty N penalize repeat sequence of tokens (default: %.1f, 1.0 = disabled)\n", (double)params.repeat_penalty);
fprintf(f, " --presence_penalty N repeat alpha presence penalty (default: %.1f, 0.0 = disabled)\n", (double)params.presence_penalty);
fprintf(f, " --frequency_penalty N repeat alpha frequency penalty (default: %.1f, 0.0 = disabled)\n", (double)params.frequency_penalty);
fprintf(f, " --mirostat N use Mirostat sampling.\n");
fprintf(f, " Top K, Nucleus, Tail Free and Locally Typical samplers are ignored if used.\n");
fprintf(f, " (default: %d, 0 = disabled, 1 = Mirostat, 2 = Mirostat 2.0)\n", params.mirostat);
fprintf(f, " --mirostat_lr N Mirostat learning rate, parameter eta (default: %.1f)\n", (double)params.mirostat_eta);
fprintf(f, " --mirostat_ent N Mirostat target entropy, parameter tau (default: %.1f)\n", (double)params.mirostat_tau);
fprintf(f, " -l TOKEN_ID(+/-)BIAS, --logit-bias TOKEN_ID(+/-)BIAS\n");
fprintf(f, " modifies the likelihood of token appearing in the completion,\n");
fprintf(f, " i.e. `--logit-bias 15043+1` to increase likelihood of token ' Hello',\n");
fprintf(f, " or `--logit-bias 15043-1` to decrease likelihood of token ' Hello'\n");
fprintf(f, " --repeat_last_n N last n tokens to consider for penalize (default: %d)\n", params.repeat_last_n);
fprintf(f, " --repeat_penalty N penalize repeat sequence of tokens (default: %.1f)\n", (double)params.repeat_penalty);
fprintf(f, " -c N, --ctx_size N size of the prompt context (default: %d)\n", params.n_ctx);
fprintf(f, " --ignore-eos ignore end of stream token and continue generating (implies --logit-bias 2-inf)\n");
fprintf(f, " --no-penalize-nl do not penalize newline token\n");
fprintf(f, " --memory_f32 use f32 instead of f16 for memory key+value\n");
fprintf(f, " --temp N temperature (default: %.1f)\n", (double)params.temp);
fprintf(f, " --n_parts N number of model parts (default: -1 = determine from dimensions)\n");
fprintf(f, " -b N, --batch_size N batch size for prompt processing (default: %d)\n", params.n_batch);
fprintf(f, " --perplexity compute perplexity over the prompt\n");
fprintf(f, " --keep NUM|STR number of tokens to keep from the initial prompt, or substring\n");
fprintf(f, " to search for within prompt that divides the actual prompt from\n");
fprintf(f, " its initial example text (default: %d, -1 = all)\n", params.n_keep);
if (llama_mlock_supported()) {
fprintf(stderr, " --mlock force system to keep model in RAM rather than swapping or compressing\n");
fprintf(f, " --mlock force system to keep model in RAM rather than swapping or compressing\n");
}
if (llama_mmap_supported()) {
fprintf(stderr, " --no-mmap do not memory-map model (slower load but may reduce pageouts if not using mlock)\n");
fprintf(f, " --no-mmap do not memory-map model (slower load but may reduce pageouts if not using mlock)\n");
}
fprintf(stderr, " --mtest compute maximum memory usage\n");
fprintf(stderr, " --verbose-prompt print prompt before generation\n");
fprintf(stderr, " --lora FNAME apply LoRA adapter (implies --no-mmap)\n");
fprintf(stderr, " --lora-base FNAME optional model to use as a base for the layers modified by the LoRA adapter\n");
fprintf(stderr, " -m FNAME, --model FNAME\n");
fprintf(stderr, " model path (default: %s)\n", params.model.c_str());
fprintf(stderr, "\n");
fprintf(f, " --mtest compute maximum memory usage\n");
fprintf(f, " --verbose-prompt print prompt before generation\n");
fprintf(f, " --lora FNAME apply LoRA adapter (implies --no-mmap)\n");
fprintf(f, " --lora-base FNAME optional model to use as a base for the layers modified by the LoRA adapter\n");
fprintf(f, " -m FNAME, --model FNAME\n");
fprintf(f, " model path (default: %s)\n", params.model.c_str());
fprintf(f, "\n");
}
std::string gpt_random_prompt(std::mt19937 & rng) {

2
third_party/ggml/common.h vendored
View file

@ -74,7 +74,7 @@ struct gpt_params {
bool gpt_params_parse(int argc, char ** argv, gpt_params & params);
void gpt_print_usage(int argc, char ** argv, const gpt_params & params);
void gpt_print_usage(FILE *f, int argc, char ** argv, const gpt_params & params);
std::string gpt_random_prompt(std::mt19937 & rng);