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Prelim support for past context.

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This commit is contained in:
Adam Treat 2023-04-09 10:27:35 -04:00
parent 91a2602d93
commit 6ce4089c4f
3 changed files with 23 additions and 13 deletions
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25
gptj.cpp
View File

@ -419,7 +419,7 @@ bool gptj_eval(
const int d_key = n_embd/n_head;
static size_t buf_size = 256u*1024*1024;
static size_t buf_size = 1024u*1024*1024;
static void * buf = malloc(buf_size);
if (mem_per_token > 0 && mem_per_token*N > buf_size) {
@ -670,8 +670,7 @@ bool GPTJ::isModelLoaded() const
}
void GPTJ::prompt(const std::string &prompt, std::function<bool(const std::string&)> response,
int32_t n_predict, int32_t top_k, float top_p, float temp,
int32_t n_batch) {
PromptContext &ctx, int32_t n_predict, int32_t top_k, float top_p, float temp, int32_t n_batch) {
if (!isModelLoaded()) {
std::cerr << "GPT-J ERROR: prompt won't work with an unloaded model!\n";
@ -679,32 +678,38 @@ void GPTJ::prompt(const std::string &prompt, std::function<bool(const std::strin
}
const int64_t t_main_start_us = ggml_time_us();
int n_past = 0;
int64_t t_sample_us = 0;
int64_t t_predict_us = 0;
int64_t t_prompt_us = 0;
std::vector<float> logits;
// tokenize the prompt
std::vector<gpt_vocab::id> embd_inp = ::gpt_tokenize(d_ptr->vocab, prompt);
n_predict = std::min(n_predict, d_ptr->model.hparams.n_ctx - (int) embd_inp.size());
ctx.n_past = std::min(ctx.n_past, 1024);
// n_batch = embd_inp.size();
std::cout << "The past was: " << ctx.n_past;
fflush(stdout);
std::vector<gpt_vocab::id> embd;
std::vector<gpt_vocab::id> resp;
// determine the required inference memory per token:
static bool initialized = false;
size_t mem_per_token = 0;
gptj_eval(d_ptr->model, d_ptr->n_threads, 0, { 0, 1, 2, 3 }, logits, mem_per_token);
if (!initialized) {
gptj_eval(d_ptr->model, d_ptr->n_threads, 0, { 0, 1, 2, 3 }, ctx.logits, mem_per_token);
initialized = true;
}
for (int i = embd.size(); i < embd_inp.size() + n_predict; i++) {
// predict
if (embd.size() > 0) {
const int64_t t_start_us = ggml_time_us();
if (!gptj_eval(d_ptr->model, d_ptr->n_threads, n_past, embd, logits, mem_per_token)) {
if (!gptj_eval(d_ptr->model, d_ptr->n_threads, ctx.n_past, embd, ctx.logits, mem_per_token)) {
std::cerr << "GPT-J ERROR: Failed to predict\n";
return;
}
@ -712,7 +717,7 @@ void GPTJ::prompt(const std::string &prompt, std::function<bool(const std::strin
t_predict_us += ggml_time_us() - t_start_us;
}
n_past += embd.size();
ctx.n_past += embd.size();
embd.clear();
resp.clear();
@ -728,7 +733,7 @@ void GPTJ::prompt(const std::string &prompt, std::function<bool(const std::strin
{
const int64_t t_start_sample_us = ggml_time_us();
id = gpt_sample_top_k_top_p(d_ptr->vocab, logits.data() + (logits.size() - n_vocab), top_k, top_p, temp, d_ptr->rng);
id = gpt_sample_top_k_top_p(d_ptr->vocab, ctx.logits.data() + (ctx.logits.size() - n_vocab), top_k, top_p, temp, d_ptr->rng);
t_sample_us += ggml_time_us() - t_start_sample_us;
}

8
gptj.h
View File

@ -13,9 +13,13 @@ public:
bool loadModel(const std::string &modelPath, std::istream &fin);
bool isModelLoaded() const;
struct PromptContext {
std::vector<float> logits;
int32_t n_past = 0; // number of tokens in past conversation
};
void prompt(const std::string &prompt, std::function<bool(const std::string&)> response,
int32_t n_predict = 200, int32_t top_k = 40, float top_p = 0.9f, float temp = 0.9f,
int32_t n_batch = 9);
PromptContext &ctx, int32_t n_predict = 200, int32_t top_k = 40, float top_p = 0.9f,
float temp = 0.9f, int32_t n_batch = 9);
private:
GPTJPrivate *d_ptr;

3
llm.cpp
View File

@ -75,7 +75,8 @@ bool GPTJObject::prompt(const QString &prompt)
m_stopGenerating = false;
auto func = std::bind(&GPTJObject::handleResponse, this, std::placeholders::_1);
emit responseStarted();
m_gptj->prompt(prompt.toStdString(), func);
static GPTJ::PromptContext ctx;
m_gptj->prompt(prompt.toStdString(), func, ctx, 4096 /*number of chars to predict*/);
emit responseStopped();
return true;
}