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9 Commits

Author SHA1 Message Date
Johannes Gäßler e4640d8fdf lookup: add print for drafting performance (#5450) 2024-02-11 12:44:51 +01:00
Xuan Son Nguyen 907e08c110 server : add llama2 chat template (#5425)
* server: add mistral chat template

* server: fix typo

* server: rename template mistral to llama2

* server: format_llama2: remove BOS

* server: validate "--chat-template" argument

* server: clean up using_chatml variable

Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com>

---------

Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com>
2024-02-11 12:16:22 +02:00
Ian Bull f026f8120f metal : use autoreleasepool to avoid memory leaks (#5437)
There appears to be a known memory leak when using the
`MLTCommandBuffer`. It is suggested to use `@autoreleasepool` in
[1,2]

[1] https://developer.apple.com/forums/thread/662721
[2] https://forums.developer.apple.com/forums/thread/120931

This change-set wraps the `ggml_metal_graph_compute` in a
`@autoreleasepool`.

This commit addresses https://github.com/ggerganov/llama.cpp/issues/5436
2024-02-10 12:53:28 +02:00
Georgi Gerganov cd9aea63b5 scripts : update sync scripts with new backends 2024-02-10 09:53:05 +02:00
Georgi Gerganov 43b65f5eb8 sync : ggml 2024-02-10 09:30:36 +02:00
Michael Podvitskiy 4633d93af0 ggml : add abort_callback for cpu backend (ggml/725)
* a way to use abort_callback with the cpu backend

* whisper update
2024-02-10 09:29:21 +02:00
Neuman Vong 4b7b38bef5 vulkan: Set limit for task concurrency (#5427)
A common default for the maximum number of open files is 256, which can
lead to `asyncio.gather(*tasks)` failing with Too many open files.

    $ python ggml_vk_generate_shaders.py --glslc=$ANDROID_NDK_PATH/shader-tools/darwin-x86_64/glslc
    ggml_vulkan: Generating and compiling shaders to SPIR-V
    Traceback (most recent call last):
      File "/Users/neuman/Code.noindex/github/llama.cpp/ggml_vk_generate_shaders.py", line 2326, in <module>
        asyncio.run(main())
      File "/Users/neuman/Code.noindex/miniforge3/lib/python3.10/asyncio/runners.py", line 44, in run
        return loop.run_until_complete(main)
      File "/Users/neuman/Code.noindex/miniforge3/lib/python3.10/asyncio/base_events.py", line 649, in run_until_complete
        return future.result()
      File "/Users/neuman/Code.noindex/github/llama.cpp/ggml_vk_generate_shaders.py", line 2294, in main
        await asyncio.gather(*tasks)
    [...snip...]
    OSError: [Errno 24] Too many open files

This change sets a reasonable concurrency limit for tasks (and therefore
open files), without significant impact on run time.
2024-02-09 19:30:19 +01:00
Daniel Bevenius e00d2a62dd llava : add requirements.txt and update README.md (#5428)
* llava: add requirements.txt and update README.md

This commit adds a `requirements.txt` file to the `examples/llava`
directory. This file contains the required Python packages to run the
scripts in the `examples/llava` directory.

The motivation of this to make it easier for users to run the scripts in
`examples/llava`. This will avoid users from having to possibly run into
missing package issues if the packages are not installed on their system.

Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com>

* llava: fix typo in llava-surgery.py output

Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com>

---------

Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com>
2024-02-09 15:00:59 +02:00
Riley Stewart 7c777fcd5d server : fix prompt caching for repeated prompts (#5420) 2024-02-09 12:49:49 +02:00
16 changed files with 148 additions and 24 deletions
+9 -3
View File
@@ -29,19 +29,25 @@ git clone https://huggingface.co/liuhaotian/llava-v1.5-7b
git clone https://huggingface.co/openai/clip-vit-large-patch14-336
```
2. Use `llava-surgery.py` to split the LLaVA model to LLaMA and multimodel projector constituents:
2. Install the required Python packages:
```sh
pip install -r examples/llava/requirements.txt
```
3. Use `llava-surgery.py` to split the LLaVA model to LLaMA and multimodel projector constituents:
```sh
python ./examples/llava/llava-surgery.py -m ../llava-v1.5-7b
```
3. Use `convert-image-encoder-to-gguf.py` to convert the LLaVA image encoder to GGUF:
4. Use `convert-image-encoder-to-gguf.py` to convert the LLaVA image encoder to GGUF:
```sh
python ./examples/llava/convert-image-encoder-to-gguf.py -m ../clip-vit-large-patch14-336 --llava-projector ../llava-v1.5-7b/llava.projector --output-dir ../llava-v1.5-7b
```
4. Use `convert.py` to convert the LLaMA part of LLaVA to GGUF:
5. Use `convert.py` to convert the LLaMA part of LLaVA to GGUF:
```sh
python ./convert.py ../llava-v1.5-7b
+1 -1
View File
@@ -42,5 +42,5 @@ if len(clip_tensors) > 0:
torch.save(checkpoint, path)
print("Done!")
print(f"Now you can convert {args.model} to a a regular LLaMA GGUF file.")
print(f"Now you can convert {args.model} to a regular LLaMA GGUF file.")
print(f"Also, use {args.model}/llava.projector to prepare a llava-encoder.gguf file.")
+3
View File
@@ -0,0 +1,3 @@
-r ../../requirements/requirements-convert.txt
pillow~=10.2.0
torch~=2.1.1
+11 -1
View File
@@ -1,7 +1,9 @@
#include "common.h"
#include "ggml.h"
#include "llama.h"
#include <cmath>
#include <cstdint>
#include <cstdio>
#include <string>
#include <vector>
@@ -73,6 +75,8 @@ int main(int argc, char ** argv){
int n_drafted = 0;
int n_accept = 0;
int64_t t_draft_us = 0;
int n_past = inp.size();
bool has_eos = false;
@@ -160,7 +164,7 @@ int main(int argc, char ** argv){
// generate n_pred tokens through prompt lookup
auto prompt_lookup = [&]() -> void {
int inp_size = inp.size();
const int inp_size = inp.size();
for (int ngram_size = ngram_max ; ngram_size > ngram_min; --ngram_size){
const llama_token * ngram = &inp[inp_size - ngram_size];
@@ -191,8 +195,12 @@ int main(int argc, char ** argv){
return;
};
const int64_t t_start_draft_us = ggml_time_us();
prompt_lookup();
t_draft_us += ggml_time_us() - t_start_draft_us;
llama_decode(ctx, batch_tgt);
++n_past;
@@ -210,6 +218,8 @@ int main(int argc, char ** argv){
LOG_TEE("n_draft = %d\n", n_draft);
LOG_TEE("n_predict = %d\n", n_predict);
LOG_TEE("n_drafted = %d\n", n_drafted);
LOG_TEE("t_draft = %.2f ms, %.2f us per token, %.2f tokens per second\n",
t_draft_us*1e-3, 1.0f*t_draft_us/n_drafted, n_drafted/(1e-6*t_draft_us));
LOG_TEE("n_accept = %d\n", n_accept);
LOG_TEE("accept = %.3f%%\n", 100.0f * n_accept / n_drafted);
+6 -2
View File
@@ -15,9 +15,13 @@
using json = nlohmann::json;
inline static json oaicompat_completion_params_parse(
const json &body /* openai api json semantics */)
const json &body, /* openai api json semantics */
const std::string &chat_template)
{
json llama_params;
std::string formatted_prompt = chat_template == "chatml"
? format_chatml(body["messages"]) // OpenAI 'messages' to chatml (with <|im_start|>,...)
: format_llama2(body["messages"]); // OpenAI 'messages' to llama2 (with [INST],...)
llama_params["__oaicompat"] = true;
@@ -30,7 +34,7 @@ inline static json oaicompat_completion_params_parse(
// https://platform.openai.com/docs/api-reference/chat/create
llama_sampling_params default_sparams;
llama_params["model"] = json_value(body, "model", std::string("unknown"));
llama_params["prompt"] = format_chatml(body["messages"]); // OpenAI 'messages' to llama.cpp 'prompt'
llama_params["prompt"] = formatted_prompt;
llama_params["cache_prompt"] = json_value(body, "cache_prompt", false);
llama_params["temperature"] = json_value(body, "temperature", 0.0);
llama_params["top_k"] = json_value(body, "top_k", default_sparams.top_k);
+24 -6
View File
@@ -36,6 +36,7 @@ struct server_params
std::string hostname = "127.0.0.1";
std::vector<std::string> api_keys;
std::string public_path = "examples/server/public";
std::string chat_template = "chatml";
int32_t port = 8080;
int32_t read_timeout = 600;
int32_t write_timeout = 600;
@@ -1592,10 +1593,6 @@ struct llama_server_context
LOG_TEE("slot %d : in cache: %i tokens | to process: %i tokens\n", slot.id, slot.n_past, slot.num_prompt_tokens_processed);
}
LOG_TEE("slot %d : kv cache rm - [%d, end)\n", slot.id, (int) system_tokens.size() + slot.n_past);
llama_kv_cache_seq_rm(ctx, slot.id, system_tokens.size() + slot.n_past, -1);
slot.cache_tokens = prompt_tokens;
if (slot.n_past == slot.num_prompt_tokens && slot.n_past > 0)
@@ -1609,6 +1606,10 @@ struct llama_server_context
}
}
LOG_TEE("slot %d : kv cache rm - [%d, end)\n", slot.id, (int) system_tokens.size() + slot.n_past);
llama_kv_cache_seq_rm(ctx, slot.id, system_tokens.size() + slot.n_past, -1);
LOG_VERBOSE("prompt ingested", {
{"n_past", slot.n_past},
{"cached", tokens_to_str(ctx, slot.cache_tokens.cbegin(), slot.cache_tokens.cbegin() + slot.n_past)},
@@ -1859,6 +1860,8 @@ static void server_print_usage(const char *argv0, const gpt_params &params,
printf(" types: int, float, bool. example: --override-kv tokenizer.ggml.add_bos_token=bool:false\n");
printf(" -gan N, --grp-attn-n N set the group attention factor to extend context size through self-extend(default: 1=disabled), used together with group attention width `--grp-attn-w`");
printf(" -gaw N, --grp-attn-w N set the group attention width to extend context size through self-extend(default: 512), used together with group attention factor `--grp-attn-n`");
printf(" --chat-template FORMAT_NAME");
printf(" set chat template, possible valus is: llama2, chatml (default %s)", sparams.chat_template.c_str());
printf("\n");
}
@@ -2290,6 +2293,21 @@ static void server_params_parse(int argc, char **argv, server_params &sparams,
log_set_target(stdout);
LOG_INFO("logging to file is disabled.", {});
}
else if (arg == "--chat-template")
{
if (++i >= argc)
{
invalid_param = true;
break;
}
std::string value(argv[i]);
if (value != "chatml" && value != "llama2") {
fprintf(stderr, "error: chat template can be \"llama2\" or \"chatml\", but got: %s\n", value.c_str());
invalid_param = true;
break;
}
sparams.chat_template = value;
}
else if (arg == "--override-kv")
{
if (++i >= argc) {
@@ -2743,13 +2761,13 @@ int main(int argc, char **argv)
// TODO: add mount point without "/v1" prefix -- how?
svr.Post("/v1/chat/completions", [&llama, &validate_api_key](const httplib::Request &req, httplib::Response &res)
svr.Post("/v1/chat/completions", [&llama, &validate_api_key, &sparams](const httplib::Request &req, httplib::Response &res)
{
res.set_header("Access-Control-Allow-Origin", req.get_header_value("Origin"));
if (!validate_api_key(req, res)) {
return;
}
json data = oaicompat_completion_params_parse(json::parse(req.body));
json data = oaicompat_completion_params_parse(json::parse(req.body), sparams.chat_template);
const int task_id = llama.queue_tasks.get_new_id();
llama.queue_results.add_waiting_task_id(task_id);
+30
View File
@@ -167,6 +167,34 @@ static T json_value(const json &body, const std::string &key, const T &default_v
: default_value;
}
inline std::string format_llama2(std::vector<json> messages)
{
std::ostringstream output;
bool is_inside_turn = false;
for (auto it = messages.begin(); it != messages.end(); ++it) {
if (!is_inside_turn) {
output << "[INST] ";
}
std::string role = json_value(*it, "role", std::string("user"));
std::string content = json_value(*it, "content", std::string(""));
if (role == "system") {
output << "<<SYS>>\n" << content << "\n<<SYS>>\n\n";
is_inside_turn = true;
} else if (role == "user") {
output << content << " [/INST]";
is_inside_turn = true;
} else {
output << " " << content << " </s>";
is_inside_turn = false;
}
}
LOG_VERBOSE("format_llama2", {{"text", output.str()}});
return output.str();
}
inline std::string format_chatml(std::vector<json> messages)
{
std::ostringstream chatml_msgs;
@@ -180,6 +208,8 @@ inline std::string format_chatml(std::vector<json> messages)
chatml_msgs << "<|im_start|>assistant" << '\n';
LOG_VERBOSE("format_chatml", {{"text", chatml_msgs.str()}});
return chatml_msgs.str();
}
+22 -4
View File
@@ -653,6 +653,9 @@ struct ggml_backend_cpu_context {
int n_threads;
void * work_data;
size_t work_size;
ggml_abort_callback abort_callback;
void * abort_callback_data;
};
GGML_CALL static const char * ggml_backend_cpu_name(ggml_backend_t backend) {
@@ -691,6 +694,9 @@ GGML_CALL static ggml_backend_graph_plan_t ggml_backend_cpu_graph_plan_create(gg
cpu_plan->cplan.work_data = malloc(cpu_plan->cplan.work_size);
}
cpu_plan->cplan.abort_callback = cpu_ctx->abort_callback;
cpu_plan->cplan.abort_callback_data = cpu_ctx->abort_callback_data;
return cpu_plan;
}
@@ -721,9 +727,11 @@ GGML_CALL static bool ggml_backend_cpu_graph_compute(ggml_backend_t backend, str
cpu_ctx->work_data = realloc(cpu_ctx->work_data, cplan.work_size);
cpu_ctx->work_size = cplan.work_size;
}
cplan.work_data = cpu_ctx->work_data;
cplan.abort_callback = cpu_ctx->abort_callback;
cplan.abort_callback_data = cpu_ctx->abort_callback_data;
ggml_graph_compute(cgraph, &cplan);
return true;
}
@@ -759,9 +767,11 @@ static struct ggml_backend_i cpu_backend_i = {
ggml_backend_t ggml_backend_cpu_init(void) {
struct ggml_backend_cpu_context * ctx = malloc(sizeof(struct ggml_backend_cpu_context));
ctx->n_threads = GGML_DEFAULT_N_THREADS;
ctx->work_data = NULL;
ctx->work_size = 0;
ctx->n_threads = GGML_DEFAULT_N_THREADS;
ctx->work_data = NULL;
ctx->work_size = 0;
ctx->abort_callback = NULL;
ctx->abort_callback_data = NULL;
ggml_backend_t cpu_backend = malloc(sizeof(struct ggml_backend));
@@ -783,6 +793,14 @@ void ggml_backend_cpu_set_n_threads(ggml_backend_t backend_cpu, int n_threads) {
ctx->n_threads = n_threads;
}
void ggml_backend_cpu_set_abort_callback(ggml_backend_t backend_cpu, ggml_abort_callback abort_callback, void * abort_callback_data) {
GGML_ASSERT(ggml_backend_is_cpu(backend_cpu));
struct ggml_backend_cpu_context * ctx = (struct ggml_backend_cpu_context *)backend_cpu->context;
ctx->abort_callback = abort_callback;
ctx->abort_callback_data = abort_callback_data;
}
GGML_CALL ggml_backend_buffer_t ggml_backend_cpu_buffer_from_ptr(void * ptr, size_t size) {
return ggml_backend_buffer_init(ggml_backend_cpu_buffer_type(), cpu_backend_buffer_i_from_ptr, ptr, size);
}
+3 -2
View File
@@ -83,8 +83,9 @@ extern "C" {
GGML_API ggml_backend_t ggml_backend_cpu_init(void);
GGML_API GGML_CALL bool ggml_backend_is_cpu (ggml_backend_t backend);
GGML_API void ggml_backend_cpu_set_n_threads(ggml_backend_t backend_cpu, int n_threads);
GGML_API GGML_CALL bool ggml_backend_is_cpu (ggml_backend_t backend);
GGML_API void ggml_backend_cpu_set_n_threads (ggml_backend_t backend_cpu, int n_threads);
GGML_API void ggml_backend_cpu_set_abort_callback(ggml_backend_t backend_cpu, ggml_abort_callback abort_callback, void * abort_callback_data);
// Create a backend buffer from an existing pointer
GGML_API GGML_CALL ggml_backend_buffer_t ggml_backend_cpu_buffer_from_ptr(void * ptr, size_t size);
+2
View File
@@ -687,6 +687,7 @@ static bool ggml_metal_graph_compute(
struct ggml_metal_context * ctx,
struct ggml_cgraph * gf) {
@autoreleasepool {
MTLComputePassDescriptor * edesc = MTLComputePassDescriptor.computePassDescriptor;
edesc.dispatchType = MTLDispatchTypeSerial;
@@ -2272,6 +2273,7 @@ static bool ggml_metal_graph_compute(
[[MTLCaptureManager sharedCaptureManager] stopCapture];
}
}
return true;
}
+1 -1
View File
@@ -16649,7 +16649,7 @@ struct ggml_compute_state_shared {
atomic_int node_n; // active graph node
atomic_int node_task; // active graph node task phase
bool (*abort_callback)(void * data); // abort ggml_graph_compute when true
ggml_abort_callback abort_callback; // abort ggml_graph_compute when true
void * abort_callback_data;
};
+7 -2
View File
@@ -567,6 +567,11 @@ extern "C" {
static const size_t GGML_TENSOR_SIZE = sizeof(struct ggml_tensor);
// Abort callback
// If not NULL, called before ggml computation
// If it returns true, the computation is aborted
typedef bool (*ggml_abort_callback)(void * data);
// the compute plan that needs to be prepared for ggml_graph_compute()
// since https://github.com/ggerganov/ggml/issues/287
struct ggml_cplan {
@@ -576,8 +581,8 @@ extern "C" {
int n_threads;
// abort ggml_graph_compute when true
bool (*abort_callback)(void * data);
void * abort_callback_data;
ggml_abort_callback abort_callback;
void * abort_callback_data;
};
enum ggml_cgraph_eval_order {
+10 -1
View File
@@ -2067,6 +2067,8 @@ type_names = {
K_QUANTS_PER_ITERATION = 2
ASYNCIO_CONCURRENCY = 64
output_dir = gettempdir()
lock = asyncio.Lock()
@@ -2291,7 +2293,14 @@ async def main():
tasks.append(string_to_spv("rope_neox_f32", rope_neox_src, {"A_TYPE": "float", "D_TYPE": "float"}))
tasks.append(string_to_spv("rope_neox_f16", rope_neox_src, {"A_TYPE": "float16_t", "D_TYPE": "float16_t"}))
await asyncio.gather(*tasks)
# Helper to decorate tasks with semaphore acquisition.
async def withSemaphore(sem, task):
async with sem:
return await task
# Run tasks concurrently guarded by a concurrency limit.
sem = asyncio.Semaphore(ASYNCIO_CONCURRENCY)
await asyncio.gather(*(withSemaphore(sem, task) for task in tasks))
with open("ggml-vulkan-shaders.hpp", "w") as f:
f.write("#include <cstdint>\n\n")
+12
View File
@@ -97,6 +97,8 @@ if [ -f $SRC_LLAMA/ggml-src.patch ]; then
# src/ggml-cuda.cu -> ggml-cuda.cu
# src/ggml-cuda.h -> ggml-cuda.h
# src/ggml-impl.h -> ggml-impl.h
# src/ggml-kompute.cpp -> ggml-kompute.cpp
# src/ggml-kompute.h -> ggml-kompute.h
# src/ggml-metal.h -> ggml-metal.h
# src/ggml-metal.m -> ggml-metal.m
# src/ggml-mpi.h -> ggml-mpi.h
@@ -105,6 +107,10 @@ if [ -f $SRC_LLAMA/ggml-src.patch ]; then
# src/ggml-opencl.h -> ggml-opencl.h
# src/ggml-quants.c -> ggml-quants.c
# src/ggml-quants.h -> ggml-quants.h
# src/ggml-sycl.cpp -> ggml-sycl.cpp
# src/ggml-sycl.h -> ggml-sycl.h
# src/ggml-vulkan.cpp -> ggml-vulkan.cpp
# src/ggml-vulkan.h -> ggml-vulkan.h
# include/ggml/ggml.h -> ggml.h
# include/ggml/ggml-alloc.h -> ggml-alloc.h
# include/ggml/ggml-backend.h -> ggml-backend.h
@@ -123,6 +129,8 @@ if [ -f $SRC_LLAMA/ggml-src.patch ]; then
-e 's/src\/ggml-cuda\.cu/ggml-cuda.cu/g' \
-e 's/src\/ggml-cuda\.h/ggml-cuda.h/g' \
-e 's/src\/ggml-impl\.h/ggml-impl.h/g' \
-e 's/src\/ggml-kompute\.cpp/ggml-kompute.cpp/g' \
-e 's/src\/ggml-kompute\.h/ggml-kompute.h/g' \
-e 's/src\/ggml-metal\.h/ggml-metal.h/g' \
-e 's/src\/ggml-metal\.m/ggml-metal.m/g' \
-e 's/src\/ggml-mpi\.h/ggml-mpi.h/g' \
@@ -131,6 +139,10 @@ if [ -f $SRC_LLAMA/ggml-src.patch ]; then
-e 's/src\/ggml-opencl\.h/ggml-opencl.h/g' \
-e 's/src\/ggml-quants\.c/ggml-quants.c/g' \
-e 's/src\/ggml-quants\.h/ggml-quants.h/g' \
-e 's/src\/ggml-sycl\.cpp/ggml-sycl.cpp/g' \
-e 's/src\/ggml-sycl\.h/ggml-sycl.h/g' \
-e 's/src\/ggml-vulkan\.cpp/ggml-vulkan.cpp/g' \
-e 's/src\/ggml-vulkan\.h/ggml-vulkan.h/g' \
-e 's/include\/ggml\/ggml\.h/ggml.h/g' \
-e 's/include\/ggml\/ggml-alloc\.h/ggml-alloc.h/g' \
-e 's/include\/ggml\/ggml-backend\.h/ggml-backend.h/g' \
+1 -1
View File
@@ -1 +1 @@
475cbad5c1c834e31e26a2283bc1413181644360
2c7cf49810d523b9632da393a9e8270b60bf3b24
+6
View File
@@ -7,6 +7,8 @@ cp -rpv ../ggml/src/ggml-backend.c ./ggml-backend.c
cp -rpv ../ggml/src/ggml-cuda.cu ./ggml-cuda.cu
cp -rpv ../ggml/src/ggml-cuda.h ./ggml-cuda.h
cp -rpv ../ggml/src/ggml-impl.h ./ggml-impl.h
cp -rpv ../ggml/src/ggml-kompute.cpp ./ggml-kompute.cpp
cp -rpv ../ggml/src/ggml-kompute.h ./ggml-kompute.h
cp -rpv ../ggml/src/ggml-metal.h ./ggml-metal.h
cp -rpv ../ggml/src/ggml-metal.m ./ggml-metal.m
cp -rpv ../ggml/src/ggml-metal.metal ./ggml-metal.metal
@@ -16,6 +18,10 @@ cp -rpv ../ggml/src/ggml-opencl.cpp ./ggml-opencl.cpp
cp -rpv ../ggml/src/ggml-opencl.h ./ggml-opencl.h
cp -rpv ../ggml/src/ggml-quants.c ./ggml-quants.c
cp -rpv ../ggml/src/ggml-quants.h ./ggml-quants.h
cp -rpv ../ggml/src/ggml-sycl.cpp ./ggml-sycl.cpp
cp -rpv ../ggml/src/ggml-sycl.h ./ggml-sycl.h
cp -rpv ../ggml/src/ggml-vulkan.cpp ./ggml-vulkan.cpp
cp -rpv ../ggml/src/ggml-vulkan.h ./ggml-vulkan.h
cp -rpv ../ggml/include/ggml/ggml.h ./ggml.h
cp -rpv ../ggml/include/ggml/ggml-alloc.h ./ggml-alloc.h
cp -rpv ../ggml/include/ggml/ggml-backend.h ./ggml-backend.h