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7 Commits

Author SHA1 Message Date
Aaron Teo 44cd8d91ff feat(ggml-cpu): enable z17 compile (#13182)
z17 compilation requires GCC 15.1.0 and onwards

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
2025-04-30 10:47:35 +01:00
Xuan-Son Nguyen 5933e6fdc9 arg : allow using -hf offline (#13202)
* arg : allow using -hf offline

* add more comments in code [no ci]
2025-04-30 10:46:32 +02:00
Xuan-Son Nguyen da84c04d8f docker : do not build tests (#13204)
* docker : do not build tests

* include "ggml-cpu.h"
2025-04-30 10:44:07 +02:00
xiaofei a0f7016d17 rpc : fix cache directory initialization (#13188)
Signed-off-by: xiaofei <hbuxiaofei@gmail.com>
2025-04-30 09:29:22 +03:00
Johannes Gäßler 19e899ce21 scripts: n_depth for compare-llama-bench [no ci] (#13201) 2025-04-29 23:32:04 +02:00
matteo e2e1ddb93a server : Prefilling assistant message in openai compatible API (#13174)
* Prefilling assistant message in openai compatible API

* fixed indentation

* fixed code convention

* simplify method usage

* no more than one assistant message at end of messages

* merge checks into prefill code

* Update examples/server/utils.hpp

---------

Co-authored-by: matteo <matteo@naspc.lan>
Co-authored-by: Xuan-Son Nguyen <thichthat@gmail.com>
2025-04-29 20:33:10 +02:00
Georgi Gerganov d9d398f84f sampling : when top-k <= 0 -> noop (#13173)
ggml-ci
2025-04-29 20:22:57 +03:00
15 changed files with 143 additions and 74 deletions
+2 -2
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@@ -14,9 +14,9 @@ WORKDIR /app
COPY . .
RUN if [ "$TARGETARCH" = "amd64" ]; then \
cmake -S . -B build -DCMAKE_BUILD_TYPE=Release -DGGML_NATIVE=OFF -DGGML_BACKEND_DL=ON -DGGML_CPU_ALL_VARIANTS=ON; \
cmake -S . -B build -DCMAKE_BUILD_TYPE=Release -DGGML_NATIVE=OFF -DLLAMA_BUILD_TESTS=OFF -DGGML_BACKEND_DL=ON -DGGML_CPU_ALL_VARIANTS=ON; \
elif [ "$TARGETARCH" = "arm64" ]; then \
cmake -S . -B build -DCMAKE_BUILD_TYPE=Release -DGGML_NATIVE=OFF -DGGML_CPU_ARM_ARCH=${GGML_CPU_ARM_ARCH}; \
cmake -S . -B build -DCMAKE_BUILD_TYPE=Release -DGGML_NATIVE=OFF -DLLAMA_BUILD_TESTS=OFF -DGGML_CPU_ARM_ARCH=${GGML_CPU_ARM_ARCH}; \
else \
echo "Unsupported architecture"; \
exit 1; \
+1 -1
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@@ -21,7 +21,7 @@ COPY . .
RUN if [ "${CUDA_DOCKER_ARCH}" != "default" ]; then \
export CMAKE_ARGS="-DCMAKE_CUDA_ARCHITECTURES=${CUDA_DOCKER_ARCH}"; \
fi && \
cmake -B build -DGGML_NATIVE=OFF -DGGML_CUDA=ON -DLLAMA_CURL=ON -DGGML_BACKEND_DL=ON -DGGML_CPU_ALL_VARIANTS=ON ${CMAKE_ARGS} -DCMAKE_EXE_LINKER_FLAGS=-Wl,--allow-shlib-undefined . && \
cmake -B build -DGGML_NATIVE=OFF -DGGML_CUDA=ON -DGGML_BACKEND_DL=ON -DGGML_CPU_ALL_VARIANTS=ON -DLLAMA_BUILD_TESTS=OFF ${CMAKE_ARGS} -DCMAKE_EXE_LINKER_FLAGS=-Wl,--allow-shlib-undefined . && \
cmake --build build --config Release -j$(nproc)
RUN mkdir -p /app/lib && \
+1 -1
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@@ -17,7 +17,7 @@ RUN if [ "${GGML_SYCL_F16}" = "ON" ]; then \
&& export OPT_SYCL_F16="-DGGML_SYCL_F16=ON"; \
fi && \
echo "Building with dynamic libs" && \
cmake -B build -DGGML_NATIVE=OFF -DGGML_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DLLAMA_CURL=ON -DGGML_BACKEND_DL=ON -DGGML_CPU_ALL_VARIANTS=ON ${OPT_SYCL_F16} && \
cmake -B build -DGGML_NATIVE=OFF -DGGML_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DGGML_BACKEND_DL=ON -DGGML_CPU_ALL_VARIANTS=ON -DLLAMA_BUILD_TESTS=OFF ${OPT_SYCL_F16} && \
cmake --build build --config Release -j$(nproc)
RUN mkdir -p /app/lib && \
+1 -1
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@@ -22,7 +22,7 @@ ENV LD_LIBRARY_PATH=${ASCEND_TOOLKIT_HOME}/runtime/lib64/stub:$LD_LIBRARY_PATH
RUN echo "Building with static libs" && \
source /usr/local/Ascend/ascend-toolkit/set_env.sh --force && \
cmake -B build -DGGML_NATIVE=OFF -DGGML_CANN=ON -DBUILD_SHARED_LIBS=OFF && \
cmake -B build -DGGML_NATIVE=OFF -DGGML_CANN=ON -DBUILD_SHARED_LIBS=OFF -DLLAMA_BUILD_TESTS=OFF && \
cmake --build build --config Release --target llama-cli
# TODO: use image with NNRT
+1 -1
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@@ -35,7 +35,7 @@ COPY . .
RUN if [ "${MUSA_DOCKER_ARCH}" != "default" ]; then \
export CMAKE_ARGS="-DMUSA_ARCHITECTURES=${MUSA_DOCKER_ARCH}"; \
fi && \
cmake -B build -DGGML_NATIVE=OFF -DGGML_MUSA=ON -DLLAMA_CURL=ON -DGGML_BACKEND_DL=ON -DGGML_CPU_ALL_VARIANTS=ON ${CMAKE_ARGS} -DCMAKE_EXE_LINKER_FLAGS=-Wl,--allow-shlib-undefined . && \
cmake -B build -DGGML_NATIVE=OFF -DGGML_MUSA=ON -DLLAMA_BUILD_TESTS=OFF -DGGML_BACKEND_DL=ON -DGGML_CPU_ALL_VARIANTS=ON ${CMAKE_ARGS} -DCMAKE_EXE_LINKER_FLAGS=-Wl,--allow-shlib-undefined . && \
cmake --build build --config Release -j$(nproc)
RUN mkdir -p /app/lib && \
+1 -1
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@@ -40,7 +40,7 @@ WORKDIR /app
COPY . .
RUN HIPCXX="$(hipconfig -l)/clang" HIP_PATH="$(hipconfig -R)" \
cmake -S . -B build -DGGML_HIP=ON -DAMDGPU_TARGETS=$ROCM_DOCKER_ARCH -DGGML_BACKEND_DL=ON -DGGML_CPU_ALL_VARIANTS=ON -DCMAKE_BUILD_TYPE=Release -DLLAMA_CURL=ON \
cmake -S . -B build -DGGML_HIP=ON -DAMDGPU_TARGETS=$ROCM_DOCKER_ARCH -DGGML_BACKEND_DL=ON -DGGML_CPU_ALL_VARIANTS=ON -DCMAKE_BUILD_TYPE=Release -DLLAMA_BUILD_TESTS=OFF \
&& cmake --build build --config Release -j$(nproc)
RUN mkdir -p /app/lib \
+1 -1
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@@ -16,7 +16,7 @@ WORKDIR /app
COPY . .
RUN cmake -B build -DGGML_NATIVE=OFF -DGGML_VULKAN=1 -DLLAMA_CURL=1 -DGGML_BACKEND_DL=ON -DGGML_CPU_ALL_VARIANTS=ON && \
RUN cmake -B build -DGGML_NATIVE=OFF -DGGML_VULKAN=1 -DLLAMA_BUILD_TESTS=OFF -DGGML_BACKEND_DL=ON -DGGML_CPU_ALL_VARIANTS=ON && \
cmake --build build --config Release -j$(nproc)
RUN mkdir -p /app/lib && \
+83 -47
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@@ -43,6 +43,25 @@ std::initializer_list<enum llama_example> mmproj_examples = {
// TODO: add LLAMA_EXAMPLE_SERVER when it's ready
};
static std::string read_file(const std::string & fname) {
std::ifstream file(fname);
if (!file) {
throw std::runtime_error(string_format("error: failed to open file '%s'\n", fname.c_str()));
}
std::string content((std::istreambuf_iterator<char>(file)), std::istreambuf_iterator<char>());
file.close();
return content;
}
static void write_file(const std::string & fname, const std::string & content) {
std::ofstream file(fname);
if (!file) {
throw std::runtime_error(string_format("error: failed to open file '%s'\n", fname.c_str()));
}
file << content;
file.close();
}
common_arg & common_arg::set_examples(std::initializer_list<enum llama_example> examples) {
this->examples = std::move(examples);
return *this;
@@ -200,9 +219,11 @@ struct curl_slist_ptr {
static bool curl_perform_with_retry(const std::string & url, CURL * curl, int max_attempts, int retry_delay_seconds) {
int remaining_attempts = max_attempts;
char * method = nullptr;
curl_easy_getinfo(curl, CURLINFO_EFFECTIVE_METHOD, &method);
while (remaining_attempts > 0) {
LOG_INF("%s: Trying to download from %s (attempt %d of %d)...\n", __func__ , url.c_str(), max_attempts - remaining_attempts + 1, max_attempts);
LOG_INF("%s: %s %s (attempt %d of %d)...\n", __func__ , method, url.c_str(), max_attempts - remaining_attempts + 1, max_attempts);
CURLcode res = curl_easy_perform(curl);
if (res == CURLE_OK) {
@@ -213,6 +234,7 @@ static bool curl_perform_with_retry(const std::string & url, CURL * curl, int ma
LOG_WRN("%s: curl_easy_perform() failed: %s, retrying after %d milliseconds...\n", __func__, curl_easy_strerror(res), exponential_backoff_delay);
remaining_attempts--;
if (remaining_attempts == 0) break;
std::this_thread::sleep_for(std::chrono::milliseconds(exponential_backoff_delay));
}
@@ -231,8 +253,6 @@ static bool common_download_file_single(const std::string & url, const std::stri
return false;
}
bool force_download = false;
// Set the URL, allow to follow http redirection
curl_easy_setopt(curl.get(), CURLOPT_URL, url.c_str());
curl_easy_setopt(curl.get(), CURLOPT_FOLLOWLOCATION, 1L);
@@ -256,7 +276,7 @@ static bool common_download_file_single(const std::string & url, const std::stri
// If the file exists, check its JSON metadata companion file.
std::string metadata_path = path + ".json";
nlohmann::json metadata;
nlohmann::json metadata; // TODO @ngxson : get rid of this json, use regex instead
std::string etag;
std::string last_modified;
@@ -266,7 +286,7 @@ static bool common_download_file_single(const std::string & url, const std::stri
if (metadata_in.good()) {
try {
metadata_in >> metadata;
LOG_INF("%s: previous metadata file found %s: %s\n", __func__, metadata_path.c_str(), metadata.dump().c_str());
LOG_DBG("%s: previous metadata file found %s: %s\n", __func__, metadata_path.c_str(), metadata.dump().c_str());
if (metadata.contains("url") && metadata.at("url").is_string()) {
auto previous_url = metadata.at("url").get<std::string>();
if (previous_url != url) {
@@ -296,7 +316,10 @@ static bool common_download_file_single(const std::string & url, const std::stri
};
common_load_model_from_url_headers headers;
bool head_request_ok = false;
bool should_download = !file_exists; // by default, we should download if the file does not exist
// get ETag to see if the remote file has changed
{
typedef size_t(*CURLOPT_HEADERFUNCTION_PTR)(char *, size_t, size_t, void *);
auto header_callback = [](char * buffer, size_t /*size*/, size_t n_items, void * userdata) -> size_t {
@@ -325,23 +348,28 @@ static bool common_download_file_single(const std::string & url, const std::stri
curl_easy_setopt(curl.get(), CURLOPT_HEADERFUNCTION, static_cast<CURLOPT_HEADERFUNCTION_PTR>(header_callback));
curl_easy_setopt(curl.get(), CURLOPT_HEADERDATA, &headers);
bool was_perform_successful = curl_perform_with_retry(url, curl.get(), CURL_MAX_RETRY, CURL_RETRY_DELAY_SECONDS);
// we only allow retrying once for HEAD requests
// this is for the use case of using running offline (no internet), retrying can be annoying
bool was_perform_successful = curl_perform_with_retry(url, curl.get(), 1, 0);
if (!was_perform_successful) {
return false;
head_request_ok = false;
}
long http_code = 0;
curl_easy_getinfo(curl.get(), CURLINFO_RESPONSE_CODE, &http_code);
if (http_code != 200) {
// HEAD not supported, we don't know if the file has changed
// force trigger downloading
force_download = true;
LOG_ERR("%s: HEAD invalid http status code received: %ld\n", __func__, http_code);
if (http_code == 200) {
head_request_ok = true;
} else {
LOG_WRN("%s: HEAD invalid http status code received: %ld\n", __func__, http_code);
head_request_ok = false;
}
}
bool should_download = !file_exists || force_download;
if (!should_download) {
// if head_request_ok is false, we don't have the etag or last-modified headers
// we leave should_download as-is, which is true if the file does not exist
if (head_request_ok) {
// check if ETag or Last-Modified headers are different
// if it is, we need to download the file again
if (!etag.empty() && etag != headers.etag) {
LOG_WRN("%s: ETag header is different (%s != %s): triggering a new download\n", __func__, etag.c_str(), headers.etag.c_str());
should_download = true;
@@ -350,6 +378,7 @@ static bool common_download_file_single(const std::string & url, const std::stri
should_download = true;
}
}
if (should_download) {
std::string path_temporary = path + ".downloadInProgress";
if (file_exists) {
@@ -424,13 +453,15 @@ static bool common_download_file_single(const std::string & url, const std::stri
{"etag", headers.etag},
{"lastModified", headers.last_modified}
});
std::ofstream(metadata_path) << metadata.dump(4);
LOG_INF("%s: file metadata saved: %s\n", __func__, metadata_path.c_str());
write_file(metadata_path, metadata.dump(4));
LOG_DBG("%s: file metadata saved: %s\n", __func__, metadata_path.c_str());
if (rename(path_temporary.c_str(), path.c_str()) != 0) {
LOG_ERR("%s: unable to rename file: %s to %s\n", __func__, path_temporary.c_str(), path.c_str());
return false;
}
} else {
LOG_INF("%s: using cached file: %s\n", __func__, path.c_str());
}
return true;
@@ -605,16 +636,37 @@ static struct common_hf_file_res common_get_hf_file(const std::string & hf_repo_
// Important: the User-Agent must be "llama-cpp" to get the "ggufFile" field in the response
// User-Agent header is already set in common_remote_get_content, no need to set it here
// we use "=" to avoid clashing with other component, while still being allowed on windows
std::string cached_response_fname = "manifest=" + hf_repo + "=" + tag + ".json";
string_replace_all(cached_response_fname, "/", "_");
std::string cached_response_path = fs_get_cache_file(cached_response_fname);
// make the request
common_remote_params params;
params.headers = headers;
auto res = common_remote_get_content(url, params);
long res_code = res.first;
std::string res_str(res.second.data(), res.second.size());
long res_code = 0;
std::string res_str;
bool use_cache = false;
try {
auto res = common_remote_get_content(url, params);
res_code = res.first;
res_str = std::string(res.second.data(), res.second.size());
} catch (const std::exception & e) {
LOG_WRN("error: failed to get manifest: %s\n", e.what());
LOG_WRN("try reading from cache\n");
// try to read from cache
try {
res_str = read_file(cached_response_path);
res_code = 200;
use_cache = true;
} catch (const std::exception & e) {
throw std::runtime_error("error: failed to get manifest (check your internet connection)");
}
}
std::string ggufFile;
std::string mmprojFile;
if (res_code == 200) {
if (res_code == 200 || res_code == 304) {
// extract ggufFile.rfilename in json, using regex
{
std::regex pattern("\"ggufFile\"[\\s\\S]*?\"rfilename\"\\s*:\\s*\"([^\"]+)\"");
@@ -631,6 +683,10 @@ static struct common_hf_file_res common_get_hf_file(const std::string & hf_repo_
mmprojFile = match[1].str();
}
}
if (!use_cache) {
// if not using cached response, update the cache file
write_file(cached_response_path, res_str);
}
} else if (res_code == 401) {
throw std::runtime_error("error: model is private or does not exist; if you are accessing a gated model, please provide a valid HF token");
} else {
@@ -1142,6 +1198,9 @@ bool common_params_parse(int argc, char ** argv, common_params & params, llama_e
fprintf(stderr, "%s\n", ex.what());
ctx_arg.params = params_org;
return false;
} catch (std::exception & ex) {
fprintf(stderr, "%s\n", ex.what());
exit(1); // for other exceptions, we exit with status code 1
}
return true;
@@ -1442,13 +1501,9 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
{"-f", "--file"}, "FNAME",
"a file containing the prompt (default: none)",
[](common_params & params, const std::string & value) {
std::ifstream file(value);
if (!file) {
throw std::runtime_error(string_format("error: failed to open file '%s'\n", value.c_str()));
}
params.prompt = read_file(value);
// store the external file name in params
params.prompt_file = value;
std::copy(std::istreambuf_iterator<char>(file), std::istreambuf_iterator<char>(), back_inserter(params.prompt));
if (!params.prompt.empty() && params.prompt.back() == '\n') {
params.prompt.pop_back();
}
@@ -1458,11 +1513,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
{"-sysf", "--system-prompt-file"}, "FNAME",
"a file containing the system prompt (default: none)",
[](common_params & params, const std::string & value) {
std::ifstream file(value);
if (!file) {
throw std::runtime_error(string_format("error: failed to open file '%s'\n", value.c_str()));
}
std::copy(std::istreambuf_iterator<char>(file), std::istreambuf_iterator<char>(), back_inserter(params.system_prompt));
params.system_prompt = read_file(value);
if (!params.system_prompt.empty() && params.system_prompt.back() == '\n') {
params.system_prompt.pop_back();
}
@@ -1887,15 +1938,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
{"--grammar-file"}, "FNAME",
"file to read grammar from",
[](common_params & params, const std::string & value) {
std::ifstream file(value);
if (!file) {
throw std::runtime_error(string_format("error: failed to open file '%s'\n", value.c_str()));
}
std::copy(
std::istreambuf_iterator<char>(file),
std::istreambuf_iterator<char>(),
std::back_inserter(params.sampling.grammar)
);
params.sampling.grammar = read_file(value);
}
).set_sparam());
add_opt(common_arg(
@@ -2815,14 +2858,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
"list of built-in templates:\n%s", list_builtin_chat_templates().c_str()
),
[](common_params & params, const std::string & value) {
std::ifstream file(value);
if (!file) {
throw std::runtime_error(string_format("error: failed to open file '%s'\n", value.c_str()));
}
std::copy(
std::istreambuf_iterator<char>(file),
std::istreambuf_iterator<char>(),
std::back_inserter(params.chat_template));
params.chat_template = read_file(value);
}
).set_examples({LLAMA_EXAMPLE_MAIN, LLAMA_EXAMPLE_SERVER}).set_env("LLAMA_ARG_CHAT_TEMPLATE_FILE"));
add_opt(common_arg(
+2 -1
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@@ -304,8 +304,9 @@ int main(int argc, char * argv[]) {
get_backend_memory(&free_mem, &total_mem);
}
const char * cache_dir = nullptr;
std::string cache_dir_str = fs_get_cache_directory() + "rpc/";
std::string cache_dir_str;
if (params.use_cache) {
cache_dir_str = fs_get_cache_directory() + "rpc/";
if (!fs_create_directory_with_parents(cache_dir_str)) {
fprintf(stderr, "Failed to create cache directory: %s\n", cache_dir_str.c_str());
return 1;
+22
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@@ -642,9 +642,31 @@ static json oaicompat_completion_params_parse(
throw std::runtime_error("Cannot use custom grammar constraints with tools.");
}
// if the assistant message appears at the end of list, we do not add end-of-turn token
// for ex. this can be useful to modify the reasoning process in reasoning models
bool prefill_assistant_message = !inputs.messages.empty() && inputs.messages.back().role == "assistant";
common_chat_msg last_message;
if (prefill_assistant_message) {
last_message = inputs.messages.back();
inputs.messages.pop_back();
/* sanity check, max one assistant message at the end of the list */
if (!inputs.messages.empty() && inputs.messages.back().role == "assistant"){
throw std::runtime_error("Cannot have 2 or more assistant messages at the end of the list.");
}
inputs.extract_reasoning = false;
inputs.add_generation_prompt = true;
}
// Apply chat template to the list of messages
auto chat_params = common_chat_templates_apply(tmpls, inputs);
/* Append assistant prefilled message */
if (prefill_assistant_message) {
chat_params.prompt += last_message.content;
}
llama_params["chat_format"] = static_cast<int>(chat_params.format);
llama_params["prompt"] = chat_params.prompt;
if (!chat_params.grammar.empty()) {
+6 -2
View File
@@ -352,10 +352,14 @@ function(ggml_add_cpu_backend_variant_impl tag_name)
# TODO: Separation to determine activation of VX/VXE/VXE2
if (${S390X_M} MATCHES "8561|8562")
message(STATUS "z15 target")
list(APPEND ARCH_FLAGS -march=z15 -mtune=z15)
list(APPEND ARCH_FLAGS -march=z15)
elseif (${S390X_M} MATCHES "3931")
message(STATUS "z16 target")
list(APPEND ARCH_FLAGS -march=z16 -mtune=z16)
list(APPEND ARCH_FLAGS -march=z16)
elseif (${S390X_M} MATCHES "9175|9176")
# NOTE: Only available from GCC 15.1.0 onwards. Any z17 machine with compile issues must first verify their GCC version.
message(STATUS "z17 target")
list(APPEND ARCH_FLAGS -march=z17)
else()
message(STATUS "Unknown target")
message(WARNING "Unknown target. If you are compiling for z14 and earlier, you might have to add -DGGML_VXE=OFF.")
+1
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@@ -1232,6 +1232,7 @@ extern "C" {
"will be removed in the future (see https://github.com/ggml-org/llama.cpp/pull/9896#discussion_r1800920915)");
/// @details Top-K sampling described in academic paper "The Curious Case of Neural Text Degeneration" https://arxiv.org/abs/1904.09751
/// Setting k <= 0 makes this a noop
LLAMA_API struct llama_sampler * llama_sampler_init_top_k (int32_t k);
/// @details Nucleus sampling described in academic paper "The Curious Case of Neural Text Degeneration" https://arxiv.org/abs/1904.09751
+18 -15
View File
@@ -19,9 +19,9 @@ logger = logging.getLogger("compare-llama-bench")
# Properties by which to differentiate results per commit:
KEY_PROPERTIES = [
"cpu_info", "gpu_info", "backends", "n_gpu_layers", "model_filename", "model_type", "n_batch", "n_ubatch",
"embeddings", "cpu_mask", "cpu_strict", "poll", "n_threads", "type_k", "type_v", "use_mmap", "no_kv_offload",
"split_mode", "main_gpu", "tensor_split", "flash_attn", "n_prompt", "n_gen"
"cpu_info", "gpu_info", "backends", "n_gpu_layers", "tensor_buft_overrides", "model_filename", "model_type",
"n_batch", "n_ubatch", "embeddings", "cpu_mask", "cpu_strict", "poll", "n_threads", "type_k", "type_v",
"use_mmap", "no_kv_offload", "split_mode", "main_gpu", "tensor_split", "flash_attn", "n_prompt", "n_gen", "n_depth"
]
# Properties that are boolean and are converted to Yes/No for the table:
@@ -30,11 +30,11 @@ BOOL_PROPERTIES = ["embeddings", "cpu_strict", "use_mmap", "no_kv_offload", "fla
# Header names for the table:
PRETTY_NAMES = {
"cpu_info": "CPU", "gpu_info": "GPU", "backends": "Backends", "n_gpu_layers": "GPU layers",
"model_filename": "File", "model_type": "Model", "model_size": "Model size [GiB]",
"model_n_params": "Num. of par.", "n_batch": "Batch size", "n_ubatch": "Microbatch size",
"embeddings": "Embeddings", "cpu_mask": "CPU mask", "cpu_strict": "CPU strict", "poll": "Poll",
"n_threads": "Threads", "type_k": "K type", "type_v": "V type", "split_mode": "Split mode", "main_gpu": "Main GPU",
"no_kv_offload": "NKVO", "flash_attn": "FlashAttention", "tensor_split": "Tensor split", "use_mmap": "Use mmap",
"tensor_buft_overrides": "Tensor overrides", "model_filename": "File", "model_type": "Model", "model_size": "Model size [GiB]",
"model_n_params": "Num. of par.", "n_batch": "Batch size", "n_ubatch": "Microbatch size", "embeddings": "Embeddings",
"cpu_mask": "CPU mask", "cpu_strict": "CPU strict", "poll": "Poll", "n_threads": "Threads", "type_k": "K type", "type_v": "V type",
"use_mmap": "Use mmap", "no_kv_offload": "NKVO", "split_mode": "Split mode", "main_gpu": "Main GPU", "tensor_split": "Tensor split",
"flash_attn": "FlashAttention",
}
DEFAULT_SHOW = ["model_type"] # Always show these properties by default.
@@ -281,12 +281,12 @@ def get_rows(properties):
The returned rows are unique in terms of property combinations.
"""
select_string = ", ".join(
[f"tb.{p}" for p in properties] + ["tb.n_prompt", "tb.n_gen", "AVG(tb.avg_ts)", "AVG(tc.avg_ts)"])
[f"tb.{p}" for p in properties] + ["tb.n_prompt", "tb.n_gen", "tb.n_depth", "AVG(tb.avg_ts)", "AVG(tc.avg_ts)"])
equal_string = " AND ".join(
[f"tb.{p} = tc.{p}" for p in KEY_PROPERTIES] + [
f"tb.build_commit = '{hexsha8_baseline}'", f"tc.build_commit = '{hexsha8_compare}'"]
)
group_order_string = ", ".join([f"tb.{p}" for p in properties] + ["tb.n_gen", "tb.n_prompt"])
group_order_string = ", ".join([f"tb.{p}" for p in properties] + ["tb.n_gen", "tb.n_prompt", "tb.n_depth"])
query = (f"SELECT {select_string} FROM test tb JOIN test tc ON {equal_string} "
f"GROUP BY {group_order_string} ORDER BY {group_order_string};")
return cursor.execute(query).fetchall()
@@ -309,7 +309,7 @@ else:
rows_full = get_rows(KEY_PROPERTIES)
properties_different = []
for i, kp_i in enumerate(KEY_PROPERTIES):
if kp_i in DEFAULT_SHOW or kp_i == "n_prompt" or kp_i == "n_gen":
if kp_i in DEFAULT_SHOW or kp_i in ["n_prompt", "n_gen", "n_depth"]:
continue
for row_full in rows_full:
if row_full[i] != rows_full[0][i]:
@@ -340,17 +340,20 @@ else:
table = []
for row in rows_show:
n_prompt = int(row[-4])
n_gen = int(row[-3])
n_prompt = int(row[-5])
n_gen = int(row[-4])
n_depth = int(row[-3])
if n_prompt != 0 and n_gen == 0:
test_name = f"pp{n_prompt}"
elif n_prompt == 0 and n_gen != 0:
test_name = f"tg{n_gen}"
else:
test_name = f"pp{n_prompt}+tg{n_gen}"
if n_depth != 0:
test_name = f"{test_name}@d{n_depth}"
# Regular columns test name avg t/s values Speedup
# VVVVVVVVVVVVV VVVVVVVVV VVVVVVVVVVVVVV VVVVVVV
table.append(list(row[:-4]) + [test_name] + list(row[-2:]) + [float(row[-1]) / float(row[-2])])
table.append(list(row[:-5]) + [test_name] + list(row[-2:]) + [float(row[-1]) / float(row[-2])])
# Some a-posteriori fixes to make the table contents prettier:
for bool_property in BOOL_PROPERTIES:
@@ -376,7 +379,7 @@ if "gpu_info" in show:
for gns in GPU_NAME_STRIP:
row_table[ip] = row_table[ip].replace(gns, "")
gpu_names = row_table[ip].split("/")
gpu_names = row_table[ip].split(", ")
num_gpus = len(gpu_names)
all_names_the_same = len(set(gpu_names)) == 1
if len(gpu_names) >= 2 and all_names_the_same:
+2 -1
View File
@@ -232,7 +232,7 @@ static void llama_sampler_top_k_impl(llama_token_data_array * cur_p, int32_t k)
// }
if (k <= 0) {
k = cur_p->size;
return;
}
k = std::min(k, (int) cur_p->size);
@@ -298,6 +298,7 @@ static void llama_sampler_top_k_impl(llama_token_data_array * cur_p, int32_t k)
}
cur_p->sorted = true;
}
cur_p->size = k;
}
+1
View File
@@ -1,4 +1,5 @@
#include "ggml.h"
#include "ggml-cpu.h"
#include "llama.h"
#include "common.h"