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Author SHA1 Message Date
d7bd3bfcad snapdragon: python SDK setup (Windows) (#27903)
* port setup-build.ps1 to setup_sdk.py, to facilitate installation of Hexagon and OpenCL SDKs on Windows

* rename setup_sdk.py -> setup-sdk.py

* flake8 fix: print() -> logger.info()

---------

Co-authored-by: Kristopher Urquhart <kurquhar@qti.qualcom.com>
2026-08-28 14:01:59 -07:00
Xuan-Son NguyenandGitHub 50f068ffff bench: add --tensor-read-lazy (#27881)
* bench: add --tensor-read-lazy

* rm the alias

* rename to LLAMA_LAZY_MODE_*
2026-08-28 20:51:05 +02:00
14 changed files with 397 additions and 25 deletions
+3 -3
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@@ -2735,9 +2735,9 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
"- auto: on, but only for tensors larger than 4 GiB\n"
"- off: always keep them resident",
[](common_params & params, const std::string & value) {
/**/ if (value == "on") { params.tensor_read_lazy = LLAMA_TENSOR_READ_LAZY_ON; }
else if (value == "auto") { params.tensor_read_lazy = LLAMA_TENSOR_READ_LAZY_AUTO; }
else if (value == "off") { params.tensor_read_lazy = LLAMA_TENSOR_READ_LAZY_OFF; }
/**/ if (value == "on") { params.lazy_mode = LLAMA_LAZY_MODE_ON; }
else if (value == "auto") { params.lazy_mode = LLAMA_LAZY_MODE_AUTO; }
else if (value == "off") { params.lazy_mode = LLAMA_LAZY_MODE_OFF; }
else { throw std::invalid_argument("invalid value"); }
}
).set_env("LLAMA_ARG_TENSOR_READ_LAZY"));
+1 -1
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@@ -1688,7 +1688,7 @@ struct llama_model_params common_model_params_to_llama(common_params & params) {
mparams.main_gpu = params.main_gpu;
mparams.split_mode = params.split_mode;
mparams.load_mode = params.load_mode;
mparams.tensor_read_lazy = params.tensor_read_lazy;
mparams.lazy_mode = params.lazy_mode;
mparams.tensor_split = params.tensor_split;
mparams.check_tensors = params.check_tensors;
mparams.use_extra_bufts = !params.no_extra_bufts;
+1 -1
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@@ -483,7 +483,7 @@ struct common_params {
enum llama_split_mode split_mode = LLAMA_SPLIT_MODE_LAYER; // how to split the model across GPUs
enum llama_load_mode load_mode = LLAMA_LOAD_MODE_AUTO; // how to load the model
enum llama_tensor_read_lazy tensor_read_lazy = LLAMA_TENSOR_READ_LAZY_AUTO; // on-demand reading of tensors marked by the arch
enum llama_lazy_mode lazy_mode = LLAMA_LAZY_MODE_AUTO; // on-demand reading of tensors marked by the arch
common_cpu_params cpuparams;
common_cpu_params cpuparams_batch;
+12 -1
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@@ -24,7 +24,18 @@ must be included in the .cat file digitally signed with a trusted certificate.
This document covers details on how to generate personal certificate files (.pfx) and how to configure the system
to allow for test signatures (aka test-signing).
## Install the latest Adreno OpenCL SDK
## Install Windows SDKs
The recommended method is `setup-sdk.py`:
```
> python scripts\snapdragon\setup-sdk.py --list-sdk-releases
> python scripts\snapdragon\setup-sdk.py --hexagon --opencl
```
It installs the selected SDKs under `C:\Qualcomm` and sets their corresponding environment variables for the current user. Start a new terminal after it completes; native Windows builds check all SDK paths before CMake runs.
Select the SDKs to install with `--hexagon` and `--opencl`; use both to prepare a dual-backend build. To select a different available version, pass it to the SDK option, for example `--hexagon 6.4.0.2`. SDK versions install side by side, so you can switch versions without deleting an existing installation. Use `--force` to reinstall the selected SDKs. Use a new CMake build directory after each switch because CMake caches the SDK paths.
Either use the trimmed down version (optimized for CI) from
+5 -5
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@@ -214,10 +214,10 @@ extern "C" {
LLAMA_API const char * llama_load_mode_name(enum llama_load_mode load_mode);
LLAMA_API enum llama_load_mode llama_load_mode_from_str(const char * str);
enum llama_tensor_read_lazy {
LLAMA_TENSOR_READ_LAZY_OFF = 0, // always read the whole tensor up front
LLAMA_TENSOR_READ_LAZY_AUTO = 1, // lazy only for marked tensors larger than 4 GiB (requires mmap)
LLAMA_TENSOR_READ_LAZY_ON = 2, // read the rows of tensors marked by the arch on demand (requires mmap)
enum llama_lazy_mode {
LLAMA_LAZY_MODE_OFF = 0, // always read the whole tensor up front
LLAMA_LAZY_MODE_AUTO = 1, // lazy only for marked tensors larger than 4 GiB (requires mmap)
LLAMA_LAZY_MODE_ON = 2, // read the rows of tensors marked by the arch on demand (requires mmap)
};
enum llama_context_type {
@@ -321,7 +321,7 @@ extern "C" {
enum llama_split_mode split_mode; // how to split the model across multiple GPUs
enum llama_load_mode load_mode; // how to load the model
enum llama_tensor_read_lazy tensor_read_lazy; // on-demand reading of tensors marked by the arch
enum llama_lazy_mode lazy_mode; // on-demand reading of tensors marked by the arch
// the GPU that is used for the entire model when split_mode is LLAMA_SPLIT_MODE_NONE
int32_t main_gpu;
+12 -6
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@@ -11,6 +11,8 @@ import platform
import shutil
import logging
from sdk import validate_windows_sdks
logger = logging.getLogger("build")
@@ -65,6 +67,13 @@ def main():
logger.error(f"Error: Invalid target format '{args.target}'. Must be android[:serial]/adb[:serial], linux:[user@]host/lnx:[user@]host/ubuntu:[user@]host, or windows/wos.")
sys.exit(1)
if target_type == "windows":
logger.info("Windows target selected. Forcing native compilation...")
args.no_docker = True
if platform.system() != "Windows":
logger.warning("Warning: Windows compilation is intended to run on Windows arm64 hosts.")
validate_windows_sdks()
# Determine preset and check if it's debug
preset = args.preset
if preset:
@@ -120,12 +129,6 @@ def main():
jobs = args.jobs if args.jobs else os.cpu_count() or 4
if target_type == "windows":
logger.info("Windows target selected. Forcing native compilation...")
args.no_docker = True
if platform.system() != "Windows":
logger.warning("Warning: Windows compilation is intended to run on Windows arm64 hosts.")
if args.no_docker:
# Native/local host build
logger.info("Running native/local CMake build...")
@@ -258,3 +261,6 @@ if __name__ == "__main__":
except KeyboardInterrupt:
logger.info("\nInterrupted by user.")
sys.exit(130)
except RuntimeError as err:
logger.error("Error: %s", err)
sys.exit(1)
+62
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@@ -0,0 +1,62 @@
import os
from pathlib import Path
SDK_CONFIGS = (
{
"name": "Hexagon SDK",
"repo": "snapdragon-toolchain/hexagon-sdk",
"default_version": "6.6.0.0",
"parent_dir": "Hexagon_SDK",
"archive_prefix": "hexagon-sdk-v",
"markers": ("hexagon_sdk.json",),
},
{
"name": "OpenCL SDK",
"repo": "snapdragon-toolchain/opencl-sdk",
"default_version": "2.3.2",
"parent_dir": "OpenCL_SDK",
"archive_prefix": "adreno-opencl-sdk-v",
"markers": ("include/CL", "lib/OpenCL.lib"),
},
)
def is_valid_sdk(config, target_dir):
return target_dir.is_dir() and all((target_dir / marker).exists() for marker in config["markers"])
def get_hexagon_tools_dir(hexagon_dir):
tools_parent = hexagon_dir / "tools" / "HEXAGON_Tools"
if not tools_parent.is_dir():
raise RuntimeError(f"Expected Hexagon tools directory in {tools_parent}")
tools_dirs = [path for path in tools_parent.iterdir() if path.is_dir()]
if len(tools_dirs) != 1:
raise RuntimeError(f"Expected one Hexagon tools directory in {tools_parent}")
return tools_dirs[0]
def validate_windows_sdks():
hexagon_config, opencl_config = SDK_CONFIGS
hexagon_dir = os.environ.get("HEXAGON_SDK_ROOT")
tools_dir = os.environ.get("HEXAGON_TOOLS_ROOT")
opencl_dir = os.environ.get("OPENCL_SDK_ROOT")
missing = []
expected_tools_dir = None
if not hexagon_dir or not is_valid_sdk(hexagon_config, Path(hexagon_dir)):
missing.append("HEXAGON_SDK_ROOT")
else:
try:
expected_tools_dir = get_hexagon_tools_dir(Path(hexagon_dir))
except RuntimeError:
pass
if not tools_dir or not expected_tools_dir or Path(tools_dir) != expected_tools_dir:
missing.append("HEXAGON_TOOLS_ROOT")
if not opencl_dir or not is_valid_sdk(opencl_config, Path(opencl_dir)):
missing.append("OPENCL_SDK_ROOT")
if missing:
raise RuntimeError(
f"Missing or invalid Windows SDK paths: {', '.join(missing)}. "
"Run scripts/snapdragon/setup-sdk.py first."
)
+233
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@@ -0,0 +1,233 @@
#!/usr/bin/env python3
#
# Install Windows on Snapdragon SDKs for llama.cpp.
#
import sys
import os
import argparse
import shutil
import logging
import json
import hashlib
import tarfile
import tempfile
from pathlib import Path
from urllib.error import HTTPError, URLError
from urllib.request import Request, urlopen
from sdk import SDK_CONFIGS, get_hexagon_tools_dir, is_valid_sdk
logger = logging.getLogger("setup_sdk")
DEFAULT_SDK_BASE_DIR = r"C:\Qualcomm"
def get_sdk_releases(config):
request = Request(
f"https://api.github.com/repos/{config['repo']}/releases?per_page=100",
headers={"Accept": "application/vnd.github+json", "User-Agent": "llama.cpp"},
)
try:
with urlopen(request, timeout=30) as response:
releases = json.load(response)
except (HTTPError, URLError, TimeoutError) as err:
raise RuntimeError(f"Cannot query {config['name']} releases: {err}") from err
result = []
for release in releases:
if release["draft"] or release["prerelease"]:
continue
version = release["tag_name"].removeprefix("v")
archive_name = f"{config['archive_prefix']}{version}-arm64-wos.tar.xz"
for asset in release["assets"]:
if asset["name"] != archive_name:
continue
result.append({
"version": version,
"name": asset["name"],
"url": asset["browser_download_url"],
"sha256": (asset.get("digest") or "").removeprefix("sha256:"),
})
return result
def list_sdk_releases():
for config in SDK_CONFIGS:
logger.info("%s:", config["name"])
releases = get_sdk_releases(config)
if not releases:
logger.info(" no Windows on Snapdragon releases found")
continue
for release in releases:
logger.info(" %s: %s", release["version"], release["name"])
def get_sdk_release(config, version):
version = version or config["default_version"]
version = version.removeprefix("v")
for release in get_sdk_releases(config):
if release["version"] == version:
if not release["sha256"]:
raise RuntimeError(f"{config['name']} {version} does not provide a SHA-256 digest")
return release
raise RuntimeError(
f"No Windows on Snapdragon release for {config['name']} {version}. "
"Run scripts/snapdragon/setup-sdk.py --list-sdk-releases to see available versions."
)
def sha256sum(path):
digest = hashlib.sha256()
with open(path, "rb") as file:
for chunk in iter(lambda: file.read(1024 * 1024), b""):
digest.update(chunk)
return digest.hexdigest()
def download_sdk(release, archive):
while True:
if archive.exists() and sha256sum(archive) == release["sha256"]:
logger.info("Using existing archive %s", archive)
return
offset = archive.stat().st_size if archive.exists() else 0
headers = {"User-Agent": "llama.cpp"}
if offset:
headers["Range"] = f"bytes={offset}-"
logger.info("Resuming download of %s at %d MiB", release["name"], offset // (1024 * 1024))
else:
logger.info("Downloading %s", release["name"])
try:
with urlopen(Request(release["url"], headers=headers), timeout=30) as response:
mode = "ab" if offset and response.status == 206 else "wb"
with open(archive, mode) as file:
shutil.copyfileobj(response, file)
except HTTPError as err:
if err.code != 416:
raise RuntimeError(f"Cannot download {release['name']}: {err}") from err
archive.unlink(missing_ok=True)
continue
except (URLError, TimeoutError) as err:
raise RuntimeError(f"Cannot download {release['name']}: {err}") from err
if sha256sum(archive) == release["sha256"]:
return
raise RuntimeError(f"SHA-256 mismatch for {archive}. Re-run the command to resume the download.")
def extract_sdk(config, archive, target_dir):
if not hasattr(tarfile, "data_filter"):
raise RuntimeError("SDK extraction requires Python 3.10.12 or later")
with tempfile.TemporaryDirectory(prefix=f".{target_dir.name}.tmp-", dir=target_dir.parent) as staging_path:
staging_dir = Path(staging_path)
with tarfile.open(archive, "r:xz") as tar:
tar.extractall(staging_dir, filter=tarfile.data_filter)
candidates = [staging_dir] + [path for path in staging_dir.iterdir() if path.is_dir()]
extracted_dirs = [path for path in candidates if is_valid_sdk(config, path)]
if len(extracted_dirs) != 1:
raise RuntimeError(f"{config['name']} archive does not contain the expected files")
extracted_dir = extracted_dirs[0]
backup_dir = None
if target_dir.exists():
backup_dir = target_dir.parent / f".{target_dir.name}.backup"
if backup_dir.exists():
raise RuntimeError(f"Cannot replace {target_dir}: backup directory {backup_dir} already exists")
target_dir.replace(backup_dir)
try:
extracted_dir.replace(target_dir)
except Exception:
if backup_dir:
backup_dir.replace(target_dir)
raise
if backup_dir:
shutil.rmtree(backup_dir)
def install_sdk(config, version, base_dir, force):
version = (version or config["default_version"]).removeprefix("v")
target_dir = base_dir / config["parent_dir"] / version
if is_valid_sdk(config, target_dir) and not force:
logger.info("Using existing %s at %s", config["name"], target_dir)
return target_dir
release = get_sdk_release(config, version)
target_dir.parent.mkdir(parents=True, exist_ok=True)
archive = target_dir.parent / release["name"]
download_sdk(release, archive)
logger.info("Extracting %s to %s", config["name"], target_dir)
extract_sdk(config, archive, target_dir)
archive.unlink(missing_ok=True)
return target_dir
def set_user_environment(values):
if os.name != "nt":
raise RuntimeError("SDK setup must run on Windows")
import winreg
with winreg.CreateKey(winreg.HKEY_CURRENT_USER, "Environment") as key:
for name, value in values.items():
winreg.SetValueEx(key, name, 0, winreg.REG_SZ, str(value))
os.environ[name] = str(value)
import ctypes
result = ctypes.c_ulong()
ctypes.windll.user32.SendMessageTimeoutW(0xffff, 0x001a, 0, "Environment", 0x0002, 5000, ctypes.byref(result))
def setup_sdks(args):
base_dir = Path(args.sdk_base_dir).expanduser().resolve()
hexagon_config, opencl_config = SDK_CONFIGS
environment = {}
if args.hexagon is not None:
hexagon_dir = install_sdk(hexagon_config, args.hexagon, base_dir, args.force)
environment["HEXAGON_SDK_ROOT"] = hexagon_dir
environment["HEXAGON_TOOLS_ROOT"] = get_hexagon_tools_dir(hexagon_dir)
if args.opencl is not None:
opencl_dir = install_sdk(opencl_config, args.opencl, base_dir, args.force)
environment["OPENCL_SDK_ROOT"] = opencl_dir
set_user_environment(environment)
logger.info("SDK environment variables were updated. Start a new terminal before building.")
def main():
logging.basicConfig(level=logging.INFO, format="%(message)s")
parser = argparse.ArgumentParser(description="Install Windows on Snapdragon SDKs for llama.cpp.")
parser.add_argument("--list-sdk-releases", action="store_true", help="List available Windows on Snapdragon SDK releases")
parser.add_argument("--sdk-base-dir", default=DEFAULT_SDK_BASE_DIR, help=r"SDK installation directory (default: C:\Qualcomm)")
parser.add_argument("--hexagon", nargs="?", const=SDK_CONFIGS[0]["default_version"], metavar="VERSION", help="Install the Hexagon SDK, optionally selecting a version")
parser.add_argument("--opencl", nargs="?", const=SDK_CONFIGS[1]["default_version"], metavar="VERSION", help="Install the OpenCL SDK, optionally selecting a version")
parser.add_argument("--force", action="store_true", help="Reinstall selected SDKs even when they already exist")
args = parser.parse_args()
if args.list_sdk_releases:
if args.sdk_base_dir != DEFAULT_SDK_BASE_DIR or args.hexagon is not None or args.opencl is not None or args.force:
parser.error("Installation options cannot be combined with --list-sdk-releases")
list_sdk_releases()
return
if args.hexagon is None and args.opencl is None:
parser.error("Select at least one SDK with --hexagon or --opencl")
if os.name != "nt":
parser.error("SDK setup must run on Windows")
setup_sdks(args)
if __name__ == "__main__":
try:
main()
except KeyboardInterrupt:
logger.info("\nInterrupted by user.")
sys.exit(130)
except RuntimeError as err:
logger.error("Error: %s", err)
sys.exit(1)
+2 -2
View File
@@ -1287,10 +1287,10 @@ struct ggml_tensor * llama_model_loader::create_tensor(
return NULL;
}
if ((flags & TENSOR_READ_LAZY) && use_mmap && tensor_read_lazy != LLAMA_TENSOR_READ_LAZY_OFF) {
if ((flags & TENSOR_READ_LAZY) && use_mmap && lazy_mode != LLAMA_LAZY_MODE_OFF) {
// in auto mode, small tensors are cheap enough to keep resident
constexpr size_t auto_lazy_min_size = 4ull * 1024 * 1024 * 1024;
if (tensor_read_lazy == LLAMA_TENSOR_READ_LAZY_ON || ggml_nbytes(cur) > auto_lazy_min_size) {
if (lazy_mode == LLAMA_LAZY_MODE_ON || ggml_nbytes(cur) > auto_lazy_min_size) {
const auto & w = require_weight(tn.str().c_str());
lazy_tensor_ranges[w.idx].emplace_back(w.offs, w.offs + ggml_nbytes(cur));
+1 -1
View File
@@ -84,7 +84,7 @@ struct llama_model_loader {
bool load_mtp;
// set by the caller before the create_tensor() calls
enum llama_tensor_read_lazy tensor_read_lazy = LLAMA_TENSOR_READ_LAZY_OFF;
enum llama_lazy_mode lazy_mode = LLAMA_LAZY_MODE_OFF;
llama_files files;
llama_ftype ftype;
+1 -1
View File
@@ -2681,7 +2681,7 @@ llama_model_params llama_model_default_params() {
/*.n_gpu_layers =*/ -1,
/*.split_mode =*/ LLAMA_SPLIT_MODE_LAYER,
/*.load_mode =*/ LLAMA_LOAD_MODE_AUTO,
/*.tensor_read_lazy =*/ LLAMA_TENSOR_READ_LAZY_AUTO,
/*.lazy_mode =*/ LLAMA_LAZY_MODE_AUTO,
/*.main_gpu =*/ 0,
/*.tensor_split =*/ nullptr,
/*.progress_callback =*/ nullptr,
+1 -1
View File
@@ -318,7 +318,7 @@ static std::pair<int, llama_model *> llama_model_load(struct gguf_context * meta
llama_model_loader ml(metadata, set_tensor_data, set_tensor_data_ud, fname, splits, file, params.load_mode,
params.check_tensors, params.no_alloc, params.load_mtp, params.kv_overrides, params.tensor_buft_overrides);
ml.tensor_read_lazy = params.tensor_read_lazy;
ml.lazy_mode = params.lazy_mode;
ml.print_info();
std::unique_ptr<llama_model> model_ptr(llama_model_create(ml, params));
+1
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@@ -67,6 +67,7 @@ test parameters:
-nkvo, --no-kv-offload <0|1> (default: 0)
-fa, --flash-attn <on|off|auto> (default: auto)
-dev, --device <dev0/dev1/...> (default: auto)
--tensor-read-lazy <on|auto|off> (default: auto)
-mmp, --mmap <0|1> (DEPRECATED IN FAVOUR OF --load-mode)
-dio, --direct-io <0|1> (DEPRECATED IN FAVOUR OF --load-mode)
-embd, --embeddings <0|1> (default: 0)
+62 -3
View File
@@ -271,6 +271,19 @@ static const char * split_mode_str(llama_split_mode mode) {
}
}
static const char * lazy_mode_str(llama_lazy_mode mode) {
switch (mode) {
case LLAMA_LAZY_MODE_OFF:
return "off";
case LLAMA_LAZY_MODE_AUTO:
return "auto";
case LLAMA_LAZY_MODE_ON:
return "on";
default:
GGML_ABORT("invalid tensor read lazy mode");
}
}
static std::string pair_str(const std::pair<int, int> & p) {
static char buf[32];
snprintf(buf, sizeof(buf), "%d,%d", p.first, p.second);
@@ -341,6 +354,7 @@ struct cmd_params {
std::vector<int> n_cpu_moe;
std::vector<llama_split_mode> split_mode;
std::vector<llama_load_mode> load_mode;
std::vector<llama_lazy_mode> lazy_mode;
std::vector<int> main_gpu;
std::vector<bool> no_kv_offload;
std::vector<llama_flash_attn_type> flash_attn;
@@ -385,6 +399,7 @@ static const cmd_params cmd_params_defaults = {
/* n_cpu_moe */ { 0 },
/* split_mode */ { LLAMA_SPLIT_MODE_LAYER },
/* load_mode */ { LLAMA_LOAD_MODE_AUTO },
/* lazy_mode */ { LLAMA_LAZY_MODE_AUTO },
/* main_gpu */ { 0 },
/* no_kv_offload */ { false },
/* flash_attn */ { LLAMA_FLASH_ATTN_TYPE_AUTO },
@@ -460,6 +475,7 @@ static void print_usage(int /* argc */, char ** argv) {
printf(" -fa, --flash-attn <on|off|auto> (default: %s)\n", join(transform_to_str(cmd_params_defaults.flash_attn, llama_flash_attn_type_name), ",").c_str());
printf(" -dev, --device <dev0/dev1/...> (default: auto)\n");
printf(" -lm, --load-mode <auto|none|mmap|mlock|mmap+mlock|dio> (default: %s)\n", join(transform_to_str(cmd_params_defaults.load_mode, llama_load_mode_name), ",").c_str());
printf(" --tensor-read-lazy <on|auto|off> (default: %s)\n", join(transform_to_str(cmd_params_defaults.lazy_mode, lazy_mode_str), ",").c_str());
printf(" -mmp, --mmap <0|1> (DEPRECATED IN FAVOUR OF --load-mode)\n");
printf(" -dio, --direct-io <0|1> (DEPRECATED IN FAVOUR OF --load-mode)\n");
printf(" -embd, --embeddings <0|1> (default: %s)\n", join(cmd_params_defaults.embeddings, ",").c_str());
@@ -786,6 +802,32 @@ static cmd_params parse_cmd_params(int argc, char ** argv) {
break;
}
params.load_mode.insert(params.load_mode.end(), modes.begin(), modes.end());
} else if (arg == "--tensor-read-lazy") {
if (++i >= argc) {
invalid_param = true;
break;
}
auto p = string_split<std::string>(argv[i], split_delim);
std::vector<llama_lazy_mode> modes;
for (const auto & m : p) {
llama_lazy_mode mode;
if (m == "on") {
mode = LLAMA_LAZY_MODE_ON;
} else if (m == "auto") {
mode = LLAMA_LAZY_MODE_AUTO;
} else if (m == "off") {
mode = LLAMA_LAZY_MODE_OFF;
} else {
invalid_param = true;
break;
}
modes.push_back(mode);
}
if (invalid_param) {
break;
}
params.lazy_mode.insert(params.lazy_mode.end(), modes.begin(), modes.end());
} else if (arg == "-mg" || arg == "--main-gpu") {
if (++i >= argc) {
invalid_param = true;
@@ -1137,6 +1179,9 @@ static cmd_params parse_cmd_params(int argc, char ** argv) {
if (params.load_mode.empty()) {
params.load_mode = cmd_params_defaults.load_mode;
}
if (params.lazy_mode.empty()) {
params.lazy_mode = cmd_params_defaults.lazy_mode;
}
if (params.main_gpu.empty()) {
params.main_gpu = cmd_params_defaults.main_gpu;
}
@@ -1203,6 +1248,7 @@ struct cmd_params_instance {
int n_cpu_moe;
llama_split_mode split_mode;
llama_load_mode load_mode;
llama_lazy_mode lazy_mode;
int main_gpu;
bool no_kv_offload;
llama_flash_attn_type flash_attn;
@@ -1224,6 +1270,7 @@ struct cmd_params_instance {
}
mparams.split_mode = split_mode;
mparams.load_mode = load_mode;
mparams.lazy_mode = lazy_mode;
mparams.main_gpu = main_gpu;
mparams.tensor_split = tensor_split.data();
mparams.no_host = no_host;
@@ -1271,7 +1318,8 @@ struct cmd_params_instance {
return model == other.model && n_gpu_layers == other.n_gpu_layers && n_cpu_moe == other.n_cpu_moe &&
split_mode == other.split_mode &&
main_gpu == other.main_gpu && tensor_split == other.tensor_split &&
load_mode == other.load_mode && devices == other.devices && no_host == other.no_host &&
load_mode == other.load_mode && lazy_mode == other.lazy_mode &&
devices == other.devices && no_host == other.no_host &&
vec_tensor_buft_override_equal(tensor_buft_overrides, other.tensor_buft_overrides);
}
@@ -1305,6 +1353,7 @@ static std::vector<cmd_params_instance> get_cmd_params_instances(const cmd_param
for (const auto & ncmoe : params.n_cpu_moe)
for (const auto & sm : params.split_mode)
for (const auto & lm : params.load_mode)
for (const auto & lzm : params.lazy_mode)
for (const auto & mg : params.main_gpu)
for (const auto & devs : params.devices)
for (const auto & ts : params.tensor_split)
@@ -1344,6 +1393,7 @@ static std::vector<cmd_params_instance> get_cmd_params_instances(const cmd_param
/* .n_cpu_moe = */ ncmoe,
/* .split_mode = */ sm,
/* .load_mode = */ lm,
/* .lazy_mode = */ lzm,
/* .main_gpu = */ mg,
/* .no_kv_offload = */ nkvo,
/* .flash_attn = */ fa,
@@ -1380,6 +1430,7 @@ static std::vector<cmd_params_instance> get_cmd_params_instances(const cmd_param
/* .n_cpu_moe = */ ncmoe,
/* .split_mode = */ sm,
/* .load_mode = */ lm,
/* .lazy_mode = */ lzm,
/* .main_gpu = */ mg,
/* .no_kv_offload = */ nkvo,
/* .flash_attn = */ fa,
@@ -1416,6 +1467,7 @@ static std::vector<cmd_params_instance> get_cmd_params_instances(const cmd_param
/* .n_cpu_moe = */ ncmoe,
/* .split_mode = */ sm,
/* .load_mode = */ lm,
/* .lazy_mode = */ lzm,
/* .main_gpu = */ mg,
/* .no_kv_offload = */ nkvo,
/* .flash_attn = */ fa,
@@ -1457,6 +1509,7 @@ struct test {
int n_cpu_moe;
llama_split_mode split_mode;
llama_load_mode load_mode;
llama_lazy_mode lazy_mode;
int main_gpu;
bool no_kv_offload;
llama_flash_attn_type flash_attn;
@@ -1496,6 +1549,7 @@ struct test {
n_cpu_moe = inst.n_cpu_moe;
split_mode = inst.split_mode;
load_mode = inst.load_mode;
lazy_mode = inst.lazy_mode;
main_gpu = inst.main_gpu;
no_kv_offload = inst.no_kv_offload;
flash_attn = inst.flash_attn;
@@ -1563,7 +1617,8 @@ struct test {
"n_ubatch", "n_threads", "cpu_mask", "cpu_strict", "poll",
"type_k", "type_v", "n_gpu_layers", "n_cpu_moe", "split_mode",
"main_gpu", "no_kv_offload", "flash_attn", "devices", "tensor_split",
"tensor_buft_overrides", "load_mode", "embeddings",
"tensor_buft_overrides", "load_mode", "lazy_mode",
"embeddings",
"no_op_offload", "no_host", "fit_target", "fit_min_ctx",
"n_prompt", "n_gen", "n_depth",
"test_time", "avg_ns", "stddev_ns", "avg_ts", "stddev_ts"
@@ -1588,7 +1643,7 @@ struct test {
if (field == "avg_ts" || field == "stddev_ts") {
return FLOAT;
}
if (field == "load_mode") {
if (field == "load_mode" || field == "lazy_mode") {
return STRING;
}
return STRING;
@@ -1658,6 +1713,7 @@ struct test {
tensor_split_str,
tensor_buft_overrides_str,
llama_load_mode_name(load_mode),
lazy_mode_str(lazy_mode),
std::to_string(embeddings),
std::to_string(no_op_offload),
std::to_string(no_host),
@@ -1972,6 +2028,9 @@ struct markdown_printer : public printer {
if (params.load_mode.size() > 1 || params.load_mode != cmd_params_defaults.load_mode) {
fields.emplace_back("load_mode");
}
if (params.lazy_mode.size() > 1 || params.lazy_mode != cmd_params_defaults.lazy_mode) {
fields.emplace_back("lazy_mode");
}
if (params.embeddings.size() > 1 || params.embeddings != cmd_params_defaults.embeddings) {
fields.emplace_back("embeddings");
}