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Inifinite generation via context swapping (#71)

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Georgi Gerganov 2023-03-25 21:36:22 +02:00
parent 03f7e33560
commit e2d490dafd
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GPG Key ID: 449E073F9DC10735
4 changed files with 100 additions and 40 deletions
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8
examples/chat.sh
View File

@ -7,4 +7,10 @@
cd `dirname $0`
cd ..
./main -m ./models/7B/ggml-model-q4_0.bin -b 128 -n 256 --repeat_penalty 1.0 --color -i -r "User:" -f prompts/chat-with-bob.txt
# Important:
#
# "--keep 48" is based on the contents of prompts/chat-with-bob.txt
#
./main -m ./models/7B/ggml-model-q4_0.bin -c 2048 -b 1024 -n 256 --keep 48 \
--repeat_penalty 1.0 --color -i \
-r "User:" -f prompts/chat-with-bob.txt

9
examples/common.cpp
View File

@ -112,6 +112,12 @@ bool gpt_params_parse(int argc, char ** argv, gpt_params & params) {
}
params.n_batch = std::stoi(argv[i]);
params.n_batch = std::min(512, params.n_batch);
} else if (arg == "--keep") {
if (++i >= argc) {
invalid_param = true;
break;
}
params.n_keep = std::stoi(argv[i]);
} else if (arg == "-m" || arg == "--model") {
if (++i >= argc) {
invalid_param = true;
@ -134,7 +140,7 @@ bool gpt_params_parse(int argc, char ** argv, gpt_params & params) {
params.use_mlock = true;
} else if (arg == "--mtest") {
params.mem_test = true;
} else if (arg == "--verbose_prompt") {
} else if (arg == "--verbose-prompt") {
params.verbose_prompt = true;
} else if (arg == "-r" || arg == "--reverse-prompt") {
if (++i >= argc) {
@ -210,6 +216,7 @@ void gpt_print_usage(int /*argc*/, char ** argv, const gpt_params & params) {
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 number of tokens to keep from the initial prompt\n");
if (ggml_mlock_supported()) {
fprintf(stderr, " --mlock force system to keep model in RAM rather than swapping or compressing\n");
}

1
examples/common.h
View File

@ -21,6 +21,7 @@ struct gpt_params {
int32_t n_parts = -1; // amount of model parts (-1 = determine from model dimensions)
int32_t n_ctx = 512; // context size
int32_t n_batch = 8; // batch size for prompt processing
int32_t n_keep = 0; // number of tokens to keep from initial prompt
// sampling parameters
int32_t top_k = 40;

120
examples/main/main.cpp
View File

@ -44,8 +44,20 @@ enum console_state {
static console_state con_st = CONSOLE_STATE_DEFAULT;
static bool con_use_color = false;
void set_console_state(console_state new_st)
{
void enable_console_colors() {
#if defined (_WIN32)
if (params.use_color) {
// Enable ANSI colors on Windows 10+
unsigned long dwMode = 0;
void* hConOut = GetStdHandle((unsigned long)-11); // STD_OUTPUT_HANDLE (-11)
if (hConOut && hConOut != (void*)-1 && GetConsoleMode(hConOut, &dwMode) && !(dwMode & 0x4)) {
SetConsoleMode(hConOut, dwMode | 0x4); // ENABLE_VIRTUAL_TERMINAL_PROCESSING (0x4)
}
}
#endif
}
void set_console_state(console_state new_st) {
if (!con_use_color) return;
// only emit color code if state changed
if (new_st != con_st) {
@ -96,6 +108,14 @@ int main(int argc, char ** argv) {
return 0;
}
if (params.embedding) {
printf("\n************\n");
printf("%s: please use the 'embedding' tool for embedding calculations\n", __func__);
printf("************\n\n");
return 0;
}
if (params.n_ctx > 2048) {
fprintf(stderr, "%s: warning: model does not support context sizes greater than 2048 tokens (%d specified);"
"expect poor results\n", __func__, params.n_ctx);
@ -165,8 +185,6 @@ int main(int argc, char ** argv) {
return 0;
}
int n_past = 0;
// Add a space in front of the first character to match OG llama tokenizer behavior
params.prompt.insert(0, 1, ' ');
@ -175,7 +193,13 @@ int main(int argc, char ** argv) {
const int n_ctx = llama_n_ctx(ctx);
params.n_predict = std::min(params.n_predict, n_ctx - (int) embd_inp.size());
if ((int) embd_inp.size() > n_ctx - 4) {
fprintf(stderr, "%s: error: prompt is too long (%d tokens, max %d)\n", __func__, (int) embd_inp.size(), n_ctx - 4);
return 1;
}
params.n_keep = std::min(params.n_keep, (int) embd_inp.size());
//params.n_predict = std::min(params.n_predict, n_ctx - (int) embd_inp.size());
// prefix & suffix for instruct mode
const auto inp_pfx = ::llama_tokenize(ctx, "\n\n### Instruction:\n\n", true);
@ -206,6 +230,13 @@ int main(int argc, char ** argv) {
for (int i = 0; i < (int) embd_inp.size(); i++) {
fprintf(stderr, "%6d -> '%s'\n", embd_inp[i], llama_token_to_str(ctx, embd_inp[i]));
}
if (params.n_keep > 0) {
fprintf(stderr, "%s: static prompt based on n_keep: '", __func__);
for (int i = 0; i < params.n_keep; i++) {
fprintf(stderr, "%s", llama_token_to_str(ctx, embd_inp[i]));
}
fprintf(stderr, "'\n");
}
fprintf(stderr, "\n");
}
@ -232,14 +263,12 @@ int main(int argc, char ** argv) {
fprintf(stderr, "Input prefix: '%s'\n", params.input_prefix.c_str());
}
}
fprintf(stderr, "sampling parameters: temp = %f, top_k = %d, top_p = %f, repeat_last_n = %i, repeat_penalty = %f\n", params.temp, params.top_k, params.top_p, params.repeat_last_n, params.repeat_penalty);
fprintf(stderr, "sampling: temp = %f, top_k = %d, top_p = %f, repeat_last_n = %i, repeat_penalty = %f\n", params.temp, params.top_k, params.top_p, params.repeat_last_n, params.repeat_penalty);
fprintf(stderr, "generate: n_ctx = %d, n_batch = %d, n_predict = %d, n_keep = %d\n", n_ctx, params.n_batch, params.n_predict, params.n_keep);
fprintf(stderr, "\n\n");
std::vector<llama_token> embd;
int last_n_size = params.repeat_last_n;
std::vector<llama_token> last_n_tokens(last_n_size);
// TODO: replace with ring-buffer
std::vector<llama_token> last_n_tokens(n_ctx);
std::fill(last_n_tokens.begin(), last_n_tokens.end(), 0);
if (params.interactive) {
@ -252,27 +281,42 @@ int main(int argc, char ** argv) {
is_interacting = params.interactive_start || params.instruct;
}
int input_consumed = 0;
bool input_noecho = false;
int remaining_tokens = params.n_predict;
int n_past = 0;
int n_remain = params.n_predict;
int n_consumed = 0;
#if defined (_WIN32)
if (params.use_color) {
// Enable ANSI colors on Windows 10+
unsigned long dwMode = 0;
void* hConOut = GetStdHandle((unsigned long)-11); // STD_OUTPUT_HANDLE (-11)
if (hConOut && hConOut != (void*)-1 && GetConsoleMode(hConOut, &dwMode) && !(dwMode & 0x4)) {
SetConsoleMode(hConOut, dwMode | 0x4); // ENABLE_VIRTUAL_TERMINAL_PROCESSING (0x4)
}
}
#endif
// the first thing we will do is to output the prompt, so set color accordingly
enable_console_colors();
set_console_state(CONSOLE_STATE_PROMPT);
while (remaining_tokens > 0 || params.interactive) {
std::vector<llama_token> embd;
while (n_remain > 0 || params.interactive) {
// predict
if (embd.size() > 0) {
// infinite text generation via context swapping
// if we run out of context:
// - take the n_keep first tokens from the original prompt (via n_past)
// - take half of the last (n_ctx - n_keep) tokens and recompute the logits in a batch
if (n_past + (int) embd.size() > n_ctx) {
const int n_left = n_past - params.n_keep;
n_past = params.n_keep;
// insert n_left/2 tokens at the start of embd from last_n_tokens
embd.insert(embd.begin(), last_n_tokens.begin() + n_ctx - n_left/2 - embd.size(), last_n_tokens.end() - embd.size());
//printf("\n---\n");
//printf("resetting: '");
//for (int i = 0; i < (int) embd.size(); i++) {
// printf("%s", llama_token_to_str(ctx, embd[i]));
//}
//printf("'\n");
//printf("\n---\n");
}
if (llama_eval(ctx, embd.data(), embd.size(), n_past, params.n_threads)) {
fprintf(stderr, "%s : failed to eval\n", __func__);
return 1;
@ -282,7 +326,7 @@ int main(int argc, char ** argv) {
n_past += embd.size();
embd.clear();
if ((int) embd_inp.size() <= input_consumed && !is_interacting) {
if ((int) embd_inp.size() <= n_consumed && !is_interacting) {
// out of user input, sample next token
const float top_k = params.top_k;
const float top_p = params.top_p;
@ -298,7 +342,9 @@ int main(int argc, char ** argv) {
logits[llama_token_eos()] = 0;
}
id = llama_sample_top_p_top_k(ctx, last_n_tokens.data(), last_n_tokens.size(), top_k, top_p, temp, repeat_penalty);
id = llama_sample_top_p_top_k(ctx,
last_n_tokens.data() + n_ctx - params.repeat_last_n,
params.repeat_last_n, top_k, top_p, temp, repeat_penalty);
last_n_tokens.erase(last_n_tokens.begin());
last_n_tokens.push_back(id);
@ -321,14 +367,14 @@ int main(int argc, char ** argv) {
input_noecho = false;
// decrement remaining sampling budget
--remaining_tokens;
--n_remain;
} else {
// some user input remains from prompt or interaction, forward it to processing
while ((int) embd_inp.size() > input_consumed) {
embd.push_back(embd_inp[input_consumed]);
while ((int) embd_inp.size() > n_consumed) {
embd.push_back(embd_inp[n_consumed]);
last_n_tokens.erase(last_n_tokens.begin());
last_n_tokens.push_back(embd_inp[input_consumed]);
++input_consumed;
last_n_tokens.push_back(embd_inp[n_consumed]);
++n_consumed;
if ((int) embd.size() >= params.n_batch) {
break;
}
@ -343,13 +389,13 @@ int main(int argc, char ** argv) {
fflush(stdout);
}
// reset color to default if we there is no pending user input
if (!input_noecho && (int)embd_inp.size() == input_consumed) {
if (!input_noecho && (int)embd_inp.size() == n_consumed) {
set_console_state(CONSOLE_STATE_DEFAULT);
}
// in interactive mode, and not currently processing queued inputs;
// check if we should prompt the user for more
if (params.interactive && (int) embd_inp.size() <= input_consumed) {
if (params.interactive && (int) embd_inp.size() <= n_consumed) {
// check for reverse prompt
std::string last_output;
for (auto id : last_n_tokens) {
@ -371,7 +417,7 @@ int main(int argc, char ** argv) {
set_console_state(CONSOLE_STATE_USER_INPUT);
if (params.instruct) {
input_consumed = embd_inp.size();
n_consumed = embd_inp.size();
embd_inp.insert(embd_inp.end(), inp_pfx.begin(), inp_pfx.end());
printf("\n> ");
@ -405,7 +451,7 @@ int main(int argc, char ** argv) {
embd_inp.insert(embd_inp.end(), inp_sfx.begin(), inp_sfx.end());
}
remaining_tokens -= line_inp.size();
n_remain -= line_inp.size();
input_noecho = true; // do not echo this again
}
@ -426,8 +472,8 @@ int main(int argc, char ** argv) {
}
// In interactive mode, respect the maximum number of tokens and drop back to user input when reached.
if (params.interactive && remaining_tokens <= 0) {
remaining_tokens = params.n_predict;
if (params.interactive && n_remain <= 0) {
n_remain = params.n_predict;
is_interacting = true;
}
}