vbatts/llama.cpp
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Merge remote-tracking branch 'origin/master' into sl/backend-sched

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slaren 2024-01-11 12:16:53 +01:00
commit c3681af783
8 changed files with 173 additions and 166 deletions
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62
examples/llava/clip.cpp
View file

@ -126,24 +126,7 @@ static struct ggml_tensor * get_tensor(struct ggml_context * ctx, const std::str
} }
static std::string get_ftype(int ftype) { static std::string get_ftype(int ftype) {
switch (ftype) { return ggml_type_name(static_cast<ggml_type>(ftype));
case 0:
return "f32";
case 1:
return "f16";
case 2:
return "q4_0";
case 3:
return "q4_1";
case 6:
return "q5_0";
case 7:
return "q5_1";
case 8:
return "q8_0";
default:
throw std::runtime_error(format("%s: Unrecognized file type: %d\n", __func__, ftype));
}
} }
// //
@ -533,6 +516,7 @@ struct clip_ctx * clip_model_load(const char * fname, const int verbosity = 1) {
buffer_size += n_tensors * 128 /* CLIP PADDING */; buffer_size += n_tensors * 128 /* CLIP PADDING */;
clip_ctx * new_clip = new clip_ctx; clip_ctx * new_clip = new clip_ctx;
#ifdef GGML_USE_CUBLAS #ifdef GGML_USE_CUBLAS
new_clip->backend = ggml_backend_cuda_init(0); new_clip->backend = ggml_backend_cuda_init(0);
printf("%s: CLIP using CUDA backend\n", __func__); printf("%s: CLIP using CUDA backend\n", __func__);
@ -543,6 +527,7 @@ struct clip_ctx * clip_model_load(const char * fname, const int verbosity = 1) {
printf("%s: CLIP using Metal backend\n", __func__); printf("%s: CLIP using Metal backend\n", __func__);
#endif #endif
if (!new_clip->backend) { if (!new_clip->backend) {
new_clip->backend = ggml_backend_cpu_init(); new_clip->backend = ggml_backend_cpu_init();
printf("%s: CLIP using CPU backend\n", __func__); printf("%s: CLIP using CPU backend\n", __func__);
@ -931,26 +916,8 @@ bool clip_model_quantize(const char * fname_inp, const char * fname_out, const i
ggml_type type = GGML_TYPE_Q4_1; ggml_type type = GGML_TYPE_Q4_1;
switch (itype) { assert(itype < GGML_TYPE_COUNT);
case 2: type = static_cast<ggml_type>(itype);
type = GGML_TYPE_Q4_0;
break;
case 3:
type = GGML_TYPE_Q4_1;
break;
case 6:
type = GGML_TYPE_Q5_0;
break;
case 7:
type = GGML_TYPE_Q5_1;
break;
case 8:
type = GGML_TYPE_Q8_0;
break;
default:
fprintf(stderr, "%s: invalid quantization type %d\n", __func__, itype);
return false;
};
auto * ctx_clip = clip_model_load(fname_inp, 2); auto * ctx_clip = clip_model_load(fname_inp, 2);
@ -1010,6 +977,10 @@ bool clip_model_quantize(const char * fname_inp, const char * fname_out, const i
if (quantize) { if (quantize) {
new_type = type; new_type = type;
if (new_type >= GGML_TYPE_Q2_K && name.find("embd") != std::string::npos) {
new_type = GGML_TYPE_Q8_0; // ggml_get_rows needs non K type
// fprintf(stderr, "%s: quantizing %s to %s\n", __func__, name.c_str(), ggml_type_name(new_type));
}
const size_t n_elms = ggml_nelements(cur); const size_t n_elms = ggml_nelements(cur);
float * f32_data; float * f32_data;
@ -1054,6 +1025,21 @@ bool clip_model_quantize(const char * fname_inp, const char * fname_out, const i
case GGML_TYPE_Q8_0: { case GGML_TYPE_Q8_0: {
new_size = ggml_quantize_q8_0(f32_data, new_data, n_elms, cur->ne[0], hist_cur.data()); new_size = ggml_quantize_q8_0(f32_data, new_data, n_elms, cur->ne[0], hist_cur.data());
} break; } break;
case GGML_TYPE_Q2_K: {
new_size = ggml_quantize_q2_K(f32_data, new_data, n_elms, cur->ne[0], hist_cur.data());
} break;
case GGML_TYPE_Q3_K: {
new_size = ggml_quantize_q3_K(f32_data, new_data, n_elms, cur->ne[0], hist_cur.data());
} break;
case GGML_TYPE_Q4_K: {
new_size = ggml_quantize_q4_K(f32_data, new_data, n_elms, cur->ne[0], hist_cur.data());
} break;
case GGML_TYPE_Q5_K: {
new_size = ggml_quantize_q5_K(f32_data, new_data, n_elms, cur->ne[0], hist_cur.data());
} break;
case GGML_TYPE_Q6_K: {
new_size = ggml_quantize_q6_K(f32_data, new_data, n_elms, cur->ne[0], hist_cur.data());
} break;
default: { default: {
fprintf(stderr, "%s: unsupported quantization type %d\n", __func__, new_type); fprintf(stderr, "%s: unsupported quantization type %d\n", __func__, new_type);
return false; return false;

4
examples/server/README.md
View file

@ -110,6 +110,10 @@ node index.js
``` ```
## API Endpoints ## API Endpoints
- **GET** `/health`: Returns the current state of the server:
- `{"status": "loading model"}` if the model is still being loaded.
- `{"status": "error"}` if the model failed to load.
- `{"status": "ok"}` if the model is successfully loaded and the server is ready for further requests mentioned below.
- **POST** `/completion`: Given a `prompt`, it returns the predicted completion. - **POST** `/completion`: Given a `prompt`, it returns the predicted completion.

211
examples/server/server.cpp
View file

@ -26,6 +26,7 @@
#include <mutex> #include <mutex>
#include <chrono> #include <chrono>
#include <condition_variable> #include <condition_variable>
#include <atomic>
#ifndef SERVER_VERBOSE #ifndef SERVER_VERBOSE
#define SERVER_VERBOSE 1 #define SERVER_VERBOSE 1
@ -146,9 +147,15 @@ static std::vector<uint8_t> base64_decode(const std::string & encoded_string)
// parallel // parallel
// //
enum server_state {
SERVER_STATE_LOADING_MODEL, // Server is starting up, model not fully loaded yet
SERVER_STATE_READY, // Server is ready and model is loaded
SERVER_STATE_ERROR // An error occurred, load_model failed
};
enum task_type { enum task_type {
COMPLETION_TASK, TASK_TYPE_COMPLETION,
CANCEL_TASK TASK_TYPE_CANCEL,
}; };
struct task_server { struct task_server {
@ -1395,7 +1402,7 @@ struct llama_server_context
task.data = std::move(data); task.data = std::move(data);
task.infill_mode = infill; task.infill_mode = infill;
task.embedding_mode = embedding; task.embedding_mode = embedding;
task.type = COMPLETION_TASK; task.type = TASK_TYPE_COMPLETION;
task.multitask_id = multitask_id; task.multitask_id = multitask_id;
// when a completion task's prompt array is not a singleton, we split it into multiple requests // when a completion task's prompt array is not a singleton, we split it into multiple requests
@ -1517,7 +1524,7 @@ struct llama_server_context
std::unique_lock<std::mutex> lock(mutex_tasks); std::unique_lock<std::mutex> lock(mutex_tasks);
task_server task; task_server task;
task.id = id_gen++; task.id = id_gen++;
task.type = CANCEL_TASK; task.type = TASK_TYPE_CANCEL;
task.target_id = task_id; task.target_id = task_id;
queue_tasks.push_back(task); queue_tasks.push_back(task);
condition_tasks.notify_one(); condition_tasks.notify_one();
@ -1553,7 +1560,7 @@ struct llama_server_context
queue_tasks.erase(queue_tasks.begin()); queue_tasks.erase(queue_tasks.begin());
switch (task.type) switch (task.type)
{ {
case COMPLETION_TASK: { case TASK_TYPE_COMPLETION: {
llama_client_slot *slot = get_slot(json_value(task.data, "slot_id", -1)); llama_client_slot *slot = get_slot(json_value(task.data, "slot_id", -1));
if (slot == nullptr) if (slot == nullptr)
{ {
@ -1582,7 +1589,7 @@ struct llama_server_context
break; break;
} }
} break; } break;
case CANCEL_TASK: { // release slot linked with the task id case TASK_TYPE_CANCEL: { // release slot linked with the task id
for (auto & slot : slots) for (auto & slot : slots)
{ {
if (slot.task_id == task.target_id) if (slot.task_id == task.target_id)
@ -2453,7 +2460,6 @@ static void server_params_parse(int argc, char **argv, server_params &sparams,
} }
} }
static std::string random_string() static std::string random_string()
{ {
static const std::string str("0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz"); static const std::string str("0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz");
@ -2790,15 +2796,117 @@ int main(int argc, char **argv)
{"system_info", llama_print_system_info()}, {"system_info", llama_print_system_info()},
}); });
// load the model httplib::Server svr;
if (!llama.load_model(params))
std::atomic<server_state> state{SERVER_STATE_LOADING_MODEL};
svr.set_default_headers({{"Server", "llama.cpp"},
{"Access-Control-Allow-Origin", "*"},
{"Access-Control-Allow-Headers", "content-type"}});
svr.Get("/health", [&](const httplib::Request&, httplib::Response& res) {
server_state current_state = state.load();
switch(current_state) {
case SERVER_STATE_READY:
res.set_content(R"({"status": "ok"})", "application/json");
res.status = 200; // HTTP OK
break;
case SERVER_STATE_LOADING_MODEL:
res.set_content(R"({"status": "loading model"})", "application/json");
res.status = 503; // HTTP Service Unavailable
break;
case SERVER_STATE_ERROR:
res.set_content(R"({"status": "error", "error": "Model failed to load"})", "application/json");
res.status = 500; // HTTP Internal Server Error
break;
}
});
svr.set_logger(log_server_request);
svr.set_exception_handler([](const httplib::Request &, httplib::Response &res, std::exception_ptr ep)
{
const char fmt[] = "500 Internal Server Error\n%s";
char buf[BUFSIZ];
try
{
std::rethrow_exception(std::move(ep));
}
catch (std::exception &e)
{
snprintf(buf, sizeof(buf), fmt, e.what());
}
catch (...)
{
snprintf(buf, sizeof(buf), fmt, "Unknown Exception");
}
res.set_content(buf, "text/plain; charset=utf-8");
res.status = 500;
});
svr.set_error_handler([](const httplib::Request &, httplib::Response &res)
{
if (res.status == 401)
{
res.set_content("Unauthorized", "text/plain; charset=utf-8");
}
if (res.status == 400)
{
res.set_content("Invalid request", "text/plain; charset=utf-8");
}
else if (res.status == 404)
{
res.set_content("File Not Found", "text/plain; charset=utf-8");
res.status = 404;
}
});
// set timeouts and change hostname and port
svr.set_read_timeout (sparams.read_timeout);
svr.set_write_timeout(sparams.write_timeout);
if (!svr.bind_to_port(sparams.hostname, sparams.port))
{ {
fprintf(stderr, "\ncouldn't bind to server socket: hostname=%s port=%d\n\n", sparams.hostname.c_str(), sparams.port);
return 1; return 1;
} }
llama.initialize(); // Set the base directory for serving static files
svr.set_base_dir(sparams.public_path);
httplib::Server svr; // to make it ctrl+clickable:
LOG_TEE("\nllama server listening at http://%s:%d\n\n", sparams.hostname.c_str(), sparams.port);
std::unordered_map<std::string, std::string> log_data;
log_data["hostname"] = sparams.hostname;
log_data["port"] = std::to_string(sparams.port);
if (!sparams.api_key.empty()) {
log_data["api_key"] = "api_key: ****" + sparams.api_key.substr(sparams.api_key.length() - 4);
}
LOG_INFO("HTTP server listening", log_data);
// run the HTTP server in a thread - see comment below
std::thread t([&]()
{
if (!svr.listen_after_bind())
{
state.store(SERVER_STATE_ERROR);
return 1;
}
return 0;
});
// load the model
if (!llama.load_model(params))
{
state.store(SERVER_STATE_ERROR);
return 1;
} else {
llama.initialize();
state.store(SERVER_STATE_READY);
}
// Middleware for API key validation // Middleware for API key validation
auto validate_api_key = [&sparams](const httplib::Request &req, httplib::Response &res) -> bool { auto validate_api_key = [&sparams](const httplib::Request &req, httplib::Response &res) -> bool {
@ -2826,10 +2934,6 @@ int main(int argc, char **argv)
return false; return false;
}; };
svr.set_default_headers({{"Server", "llama.cpp"},
{"Access-Control-Allow-Origin", "*"},
{"Access-Control-Allow-Headers", "content-type"}});
// this is only called if no index.html is found in the public --path // this is only called if no index.html is found in the public --path
svr.Get("/", [](const httplib::Request &, httplib::Response &res) svr.Get("/", [](const httplib::Request &, httplib::Response &res)
{ {
@ -2937,8 +3041,6 @@ int main(int argc, char **argv)
} }
}); });
svr.Get("/v1/models", [&params](const httplib::Request&, httplib::Response& res) svr.Get("/v1/models", [&params](const httplib::Request&, httplib::Response& res)
{ {
std::time_t t = std::time(0); std::time_t t = std::time(0);
@ -3157,81 +3259,6 @@ int main(int argc, char **argv)
return res.set_content(result.result_json.dump(), "application/json; charset=utf-8"); return res.set_content(result.result_json.dump(), "application/json; charset=utf-8");
}); });
svr.set_logger(log_server_request);
svr.set_exception_handler([](const httplib::Request &, httplib::Response &res, std::exception_ptr ep)
{
const char fmt[] = "500 Internal Server Error\n%s";
char buf[BUFSIZ];
try
{
std::rethrow_exception(std::move(ep));
}
catch (std::exception &e)
{
snprintf(buf, sizeof(buf), fmt, e.what());
}
catch (...)
{
snprintf(buf, sizeof(buf), fmt, "Unknown Exception");
}
res.set_content(buf, "text/plain; charset=utf-8");
res.status = 500;
});
svr.set_error_handler([](const httplib::Request &, httplib::Response &res)
{
if (res.status == 401)
{
res.set_content("Unauthorized", "text/plain; charset=utf-8");
}
if (res.status == 400)
{
res.set_content("Invalid request", "text/plain; charset=utf-8");
}
else if (res.status == 404)
{
res.set_content("File Not Found", "text/plain; charset=utf-8");
res.status = 404;
}
});
// set timeouts and change hostname and port
svr.set_read_timeout (sparams.read_timeout);
svr.set_write_timeout(sparams.write_timeout);
if (!svr.bind_to_port(sparams.hostname, sparams.port))
{
fprintf(stderr, "\ncouldn't bind to server socket: hostname=%s port=%d\n\n", sparams.hostname.c_str(), sparams.port);
return 1;
}
// Set the base directory for serving static files
svr.set_base_dir(sparams.public_path);
// to make it ctrl+clickable:
LOG_TEE("\nllama server listening at http://%s:%d\n\n", sparams.hostname.c_str(), sparams.port);
std::unordered_map<std::string, std::string> log_data;
log_data["hostname"] = sparams.hostname;
log_data["port"] = std::to_string(sparams.port);
if (!sparams.api_key.empty()) {
log_data["api_key"] = "api_key: ****" + sparams.api_key.substr(sparams.api_key.length() - 4);
}
LOG_INFO("HTTP server listening", log_data);
// run the HTTP server in a thread - see comment below
std::thread t([&]()
{
if (!svr.listen_after_bind())
{
return 1;
}
return 0;
});
// GG: if I put the main loop inside a thread, it crashes on the first request when build in Debug!? // GG: if I put the main loop inside a thread, it crashes on the first request when build in Debug!?
// "Bus error: 10" - this is on macOS, it does not crash on Linux // "Bus error: 10" - this is on macOS, it does not crash on Linux
//std::thread t2([&]() //std::thread t2([&]()

4
ggml-metal.m
View file

@ -1067,6 +1067,8 @@ bool ggml_metal_graph_compute(
GGML_ASSERT(!"unsupported op"); GGML_ASSERT(!"unsupported op");
} }
[encoder pushDebugGroup:[NSString stringWithCString:ggml_op_desc(dst) encoding:NSUTF8StringEncoding]];
const int64_t ne00 = src0 ? src0->ne[0] : 0; const int64_t ne00 = src0 ? src0->ne[0] : 0;
const int64_t ne01 = src0 ? src0->ne[1] : 0; const int64_t ne01 = src0 ? src0->ne[1] : 0;
const int64_t ne02 = src0 ? src0->ne[2] : 0; const int64_t ne02 = src0 ? src0->ne[2] : 0;
@ -2423,6 +2425,8 @@ bool ggml_metal_graph_compute(
GGML_ASSERT(false); GGML_ASSERT(false);
} }
} }
[encoder popDebugGroup];
} }
if (encoder != nil) { if (encoder != nil) {

32
ggml.c
View file

@ -132,7 +132,7 @@ void ggml_print_backtrace(void) {
"-ex", "bt -frame-info source-and-location", "-ex", "bt -frame-info source-and-location",
"-ex", "detach", "-ex", "detach",
"-ex", "quit", "-ex", "quit",
NULL); (char *) NULL);
} else { } else {
waitpid(pid, NULL, 0); waitpid(pid, NULL, 0);
} }
@ -4315,13 +4315,13 @@ struct ggml_tensor * ggml_set_2d_inplace(
static struct ggml_tensor * ggml_cpy_impl( static struct ggml_tensor * ggml_cpy_impl(
struct ggml_context * ctx, struct ggml_context * ctx,
struct ggml_tensor * a, struct ggml_tensor * a,
struct ggml_tensor * b, struct ggml_tensor * b) {
bool inplace) {
GGML_ASSERT(ggml_nelements(a) == ggml_nelements(b)); GGML_ASSERT(ggml_nelements(a) == ggml_nelements(b));
bool is_node = false; bool is_node = false;
if (!inplace && (a->grad || b->grad)) { if (a->grad || b->grad) {
// inplace is false and either one have a grad
is_node = true; is_node = true;
} }
@ -4345,14 +4345,7 @@ struct ggml_tensor * ggml_cpy(
struct ggml_context * ctx, struct ggml_context * ctx,
struct ggml_tensor * a, struct ggml_tensor * a,
struct ggml_tensor * b) { struct ggml_tensor * b) {
return ggml_cpy_impl(ctx, a, b, false); return ggml_cpy_impl(ctx, a, b);
}
struct ggml_tensor * ggml_cpy_inplace(
struct ggml_context * ctx,
struct ggml_tensor * a,
struct ggml_tensor * b) {
return ggml_cpy_impl(ctx, a, b, true);
} }
struct ggml_tensor * ggml_cast( struct ggml_tensor * ggml_cast(
@ -4376,15 +4369,14 @@ struct ggml_tensor * ggml_cast(
static struct ggml_tensor * ggml_cont_impl( static struct ggml_tensor * ggml_cont_impl(
struct ggml_context * ctx, struct ggml_context * ctx,
struct ggml_tensor * a, struct ggml_tensor * a) {
bool inplace) {
bool is_node = false; bool is_node = false;
if (!inplace && a->grad) { if (a->grad) {
is_node = true; is_node = true;
} }
struct ggml_tensor * result = inplace ? ggml_view_tensor(ctx, a) : ggml_dup_tensor(ctx, a); struct ggml_tensor * result = ggml_dup_tensor(ctx, a);
ggml_format_name(result, "%s (cont)", a->name); ggml_format_name(result, "%s (cont)", a->name);
result->op = GGML_OP_CONT; result->op = GGML_OP_CONT;
@ -4397,13 +4389,7 @@ static struct ggml_tensor * ggml_cont_impl(
struct ggml_tensor * ggml_cont( struct ggml_tensor * ggml_cont(
struct ggml_context * ctx, struct ggml_context * ctx,
struct ggml_tensor * a) { struct ggml_tensor * a) {
return ggml_cont_impl(ctx, a, false); return ggml_cont_impl(ctx, a);
}
struct ggml_tensor * ggml_cont_inplace(
struct ggml_context * ctx,
struct ggml_tensor * a) {
return ggml_cont_impl(ctx, a, true);
} }
// make contiguous, with new shape // make contiguous, with new shape

13
ggml.h
View file

@ -218,7 +218,9 @@
#define GGML_MAX_PARAMS 2048 #define GGML_MAX_PARAMS 2048
#define GGML_MAX_CONTEXTS 64 #define GGML_MAX_CONTEXTS 64
#define GGML_MAX_SRC 10 #define GGML_MAX_SRC 10
#ifndef GGML_MAX_NAME
#define GGML_MAX_NAME 64 #define GGML_MAX_NAME 64
#endif
#define GGML_MAX_OP_PARAMS 64 #define GGML_MAX_OP_PARAMS 64
#define GGML_DEFAULT_N_THREADS 4 #define GGML_DEFAULT_N_THREADS 4
#define GGML_DEFAULT_GRAPH_SIZE 2048 #define GGML_DEFAULT_GRAPH_SIZE 2048
@ -1161,12 +1163,6 @@ extern "C" {
struct ggml_tensor * a, struct ggml_tensor * a,
struct ggml_tensor * b); struct ggml_tensor * b);
// a -> b, in-place, return view(b)
GGML_API struct ggml_tensor * ggml_cpy_inplace(
struct ggml_context * ctx,
struct ggml_tensor * a,
struct ggml_tensor * b);
GGML_API struct ggml_tensor * ggml_cast( GGML_API struct ggml_tensor * ggml_cast(
struct ggml_context * ctx, struct ggml_context * ctx,
struct ggml_tensor * a, struct ggml_tensor * a,
@ -1177,11 +1173,6 @@ extern "C" {
struct ggml_context * ctx, struct ggml_context * ctx,
struct ggml_tensor * a); struct ggml_tensor * a);
// make contiguous, in-place
GGML_API struct ggml_tensor * ggml_cont_inplace(
struct ggml_context * ctx,
struct ggml_tensor * a);
// make contiguous, with new shape // make contiguous, with new shape
GGML_API struct ggml_tensor * ggml_cont_1d( GGML_API struct ggml_tensor * ggml_cont_1d(
struct ggml_context * ctx, struct ggml_context * ctx,

11
llama.cpp
View file

@ -2835,6 +2835,7 @@ static void llm_load_hparams(
ml.get_key(LLM_KV_ATTENTION_LAYERNORM_EPS, hparams.f_norm_eps); ml.get_key(LLM_KV_ATTENTION_LAYERNORM_EPS, hparams.f_norm_eps);
switch (hparams.n_layer) { switch (hparams.n_layer) {
case 24: model.type = e_model::MODEL_1B; break;
case 32: model.type = e_model::MODEL_3B; break; case 32: model.type = e_model::MODEL_3B; break;
default: model.type = e_model::MODEL_UNKNOWN; default: model.type = e_model::MODEL_UNKNOWN;
} }
@ -3151,7 +3152,15 @@ static void llm_load_print_meta(llama_model_loader & ml, llama_model & model) {
LLAMA_LOG_INFO("%s: rope_finetuned = %s\n", __func__, hparams.rope_finetuned ? "yes" : "unknown"); LLAMA_LOG_INFO("%s: rope_finetuned = %s\n", __func__, hparams.rope_finetuned ? "yes" : "unknown");
LLAMA_LOG_INFO("%s: model type = %s\n", __func__, llama_model_type_name(model.type)); LLAMA_LOG_INFO("%s: model type = %s\n", __func__, llama_model_type_name(model.type));
LLAMA_LOG_INFO("%s: model ftype = %s\n", __func__, llama_model_ftype_name(model.ftype).c_str()); LLAMA_LOG_INFO("%s: model ftype = %s\n", __func__, llama_model_ftype_name(model.ftype).c_str());
LLAMA_LOG_INFO("%s: model params = %.2f B\n", __func__, ml.n_elements*1e-9); if (ml.n_elements >= 1e12) {
LLAMA_LOG_INFO("%s: model params = %.2f T\n", __func__, ml.n_elements*1e-12);
} else if (ml.n_elements >= 1e9) {
LLAMA_LOG_INFO("%s: model params = %.2f B\n", __func__, ml.n_elements*1e-9);
} else if (ml.n_elements >= 1e6) {
LLAMA_LOG_INFO("%s: model params = %.2f M\n", __func__, ml.n_elements*1e-6);
} else {
LLAMA_LOG_INFO("%s: model params = %.2f K\n", __func__, ml.n_elements*1e-3);
}
if (ml.n_bytes < GiB) { if (ml.n_bytes < GiB) {
LLAMA_LOG_INFO("%s: model size = %.2f MiB (%.2f BPW) \n", __func__, ml.n_bytes/1024.0/1024.0, ml.n_bytes*8.0/ml.n_elements); LLAMA_LOG_INFO("%s: model size = %.2f MiB (%.2f BPW) \n", __func__, ml.n_bytes/1024.0/1024.0, ml.n_bytes*8.0/ml.n_elements);
} else { } else {

2
scripts/sync-ggml.last
View file

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