mirror of
https://github.com/facefusion/facefusion.git
synced 2026-08-05 00:28:38 +02:00
Compare commits
1
Commits
| Author | SHA1 | Date | |
|---|---|---|---|
|
|
218b78a1c9 |
+2
-1
@@ -5,7 +5,7 @@ import signal
|
||||
import sys
|
||||
from time import time
|
||||
|
||||
from facefusion import benchmarker, cli_helper, content_analyser, hash_helper, logger, state_manager, translator
|
||||
from facefusion import benchmarker, cli_helper, content_analyser, hash_helper, logger, memory_manager, state_manager, translator
|
||||
from facefusion.args import apply_args, collect_job_args, reduce_job_args, reduce_step_args
|
||||
from facefusion.download import conditional_download_hashes, conditional_download_sources
|
||||
from facefusion.exit_helper import hard_exit, signal_exit
|
||||
@@ -305,6 +305,7 @@ def process_step(job_id : str, step_index : int, step_args : Args) -> bool:
|
||||
logger.info(translator.get('processing_step').format(step_current = step_index + 1, step_total = step_total), __name__)
|
||||
if common_pre_check() and processors_pre_check():
|
||||
error_code = conditional_process()
|
||||
memory_manager.release_memory()
|
||||
return error_code == 0
|
||||
return False
|
||||
|
||||
|
||||
+1
-11
@@ -3,7 +3,7 @@ import shutil
|
||||
import subprocess
|
||||
import xml.etree.ElementTree as ElementTree
|
||||
from functools import lru_cache
|
||||
from typing import List, Optional, Tuple
|
||||
from typing import List, Optional
|
||||
|
||||
import onnxruntime
|
||||
|
||||
@@ -18,16 +18,6 @@ def has_execution_provider(execution_provider : ExecutionProvider) -> bool:
|
||||
return execution_provider in get_available_execution_providers()
|
||||
|
||||
|
||||
@lru_cache()
|
||||
def get_onnxruntime_version() -> Tuple[int, int, int]:
|
||||
version_split = onnxruntime.__version__.split('.')
|
||||
major_version = int(version_split[0])
|
||||
minor_version = int(version_split[1])
|
||||
patch_version = int(version_split[2].split('+')[0])
|
||||
|
||||
return major_version, minor_version, patch_version
|
||||
|
||||
|
||||
def get_available_execution_providers() -> List[ExecutionProvider]:
|
||||
inference_session_providers = onnxruntime.get_available_providers()
|
||||
available_execution_providers : List[ExecutionProvider] = []
|
||||
|
||||
@@ -9,7 +9,7 @@ from onnxruntime import InferenceSession
|
||||
from facefusion import logger, process_manager, state_manager, translator
|
||||
from facefusion.app_context import detect_app_context
|
||||
from facefusion.common_helper import is_windows
|
||||
from facefusion.execution import create_inference_providers, get_onnxruntime_version, has_execution_provider
|
||||
from facefusion.execution import create_inference_providers, has_execution_provider
|
||||
from facefusion.exit_helper import fatal_exit
|
||||
from facefusion.filesystem import get_file_name, is_file
|
||||
from facefusion.time_helper import calculate_end_time
|
||||
@@ -25,21 +25,17 @@ INFERENCE_POOL_SET : InferencePoolSet =\
|
||||
def get_inference_pool(module_name : str, model_names : List[str], model_source_set : DownloadSet) -> InferencePool:
|
||||
while process_manager.is_checking():
|
||||
sleep(0.5)
|
||||
|
||||
execution_device_ids = state_manager.get_item('execution_device_ids')
|
||||
execution_providers = state_manager.get_item('execution_providers')
|
||||
has_arena_leak = has_execution_provider('cuda') and get_onnxruntime_version() > (1, 24, 4)
|
||||
app_context = detect_app_context()
|
||||
|
||||
for execution_device_id in execution_device_ids:
|
||||
inference_context = get_inference_context(module_name, model_names, execution_device_id, execution_providers)
|
||||
|
||||
if not has_arena_leak:
|
||||
if app_context == 'cli' and INFERENCE_POOL_SET.get('ui').get(inference_context):
|
||||
INFERENCE_POOL_SET['cli'][inference_context] = INFERENCE_POOL_SET.get('ui').get(inference_context)
|
||||
if app_context == 'ui' and INFERENCE_POOL_SET.get('cli').get(inference_context):
|
||||
INFERENCE_POOL_SET['ui'][inference_context] = INFERENCE_POOL_SET.get('cli').get(inference_context)
|
||||
|
||||
if not INFERENCE_POOL_SET.get(app_context).get(inference_context):
|
||||
inference_providers = resolve_static_inference_providers(module_name, execution_device_id)
|
||||
INFERENCE_POOL_SET[app_context][inference_context] = create_inference_pool(model_source_set, inference_providers)
|
||||
@@ -53,7 +49,6 @@ def create_inference_pool(model_source_set : DownloadSet, inference_providers :
|
||||
|
||||
for model_name in model_source_set.keys():
|
||||
model_path = model_source_set.get(model_name).get('path')
|
||||
|
||||
if is_file(model_path):
|
||||
inference_pool[model_name] = create_inference_session(model_path, inference_providers)
|
||||
|
||||
@@ -70,7 +65,6 @@ def clear_inference_pool(module_name : str, model_names : List[str]) -> None:
|
||||
|
||||
for execution_device_id in execution_device_ids:
|
||||
inference_context = get_inference_context(module_name, model_names, execution_device_id, execution_providers)
|
||||
|
||||
if INFERENCE_POOL_SET.get(app_context).get(inference_context):
|
||||
del INFERENCE_POOL_SET[app_context][inference_context]
|
||||
|
||||
|
||||
@@ -19,17 +19,16 @@ LOCALES =\
|
||||
}
|
||||
ONNXRUNTIME_SET =\
|
||||
{
|
||||
'default': ('onnxruntime', '1.28.0')
|
||||
'default': ('onnxruntime', '1.26.0')
|
||||
}
|
||||
if is_windows() or is_linux():
|
||||
ONNXRUNTIME_SET['cuda@12'] = ('onnxruntime-gpu', '1.24.4')
|
||||
ONNXRUNTIME_SET['cuda@13'] = ('onnxruntime-gpu', '1.28.0')
|
||||
ONNXRUNTIME_SET['cuda'] = ('onnxruntime-gpu', '1.26.0')
|
||||
ONNXRUNTIME_SET['openvino'] = ('onnxruntime-openvino', '1.24.1')
|
||||
if is_windows():
|
||||
ONNXRUNTIME_SET['directml'] = ('onnxruntime-directml', '1.24.4')
|
||||
ONNXRUNTIME_SET['qnn'] = ('onnxruntime-qnn', '2.4.0')
|
||||
ONNXRUNTIME_SET['qnn'] = ('onnxruntime-qnn', '1.24.4')
|
||||
if is_linux():
|
||||
ONNXRUNTIME_SET['migraphx'] = ('onnxruntime-migraphx', '1.27.1')
|
||||
ONNXRUNTIME_SET['migraphx'] = ('onnxruntime-migraphx', '1.26.0')
|
||||
ONNXRUNTIME_SET['rocm'] = ('onnxruntime-rocm', '1.22.2.post3')
|
||||
|
||||
|
||||
@@ -55,9 +54,6 @@ def run(program : ArgumentParser) -> None:
|
||||
sys.stdout.write(LOCALES.get('conda_not_activated') + os.linesep)
|
||||
sys.exit(1)
|
||||
|
||||
for onnxruntime_package, _ in ONNXRUNTIME_SET.values():
|
||||
subprocess.call([ shutil.which('pip'), 'uninstall', onnxruntime_package, '-y', '-q' ], stderr = subprocess.DEVNULL)
|
||||
|
||||
commands = [ shutil.which('pip'), 'install' ]
|
||||
|
||||
if args.force_reinstall:
|
||||
@@ -67,10 +63,12 @@ def run(program : ArgumentParser) -> None:
|
||||
|
||||
for line in file.readlines():
|
||||
__line__ = line.strip()
|
||||
|
||||
if not __line__.startswith('onnxruntime'):
|
||||
commands.append(__line__)
|
||||
|
||||
onnxruntime_name, onnxruntime_version = ONNXRUNTIME_SET.get(args.onnxruntime)
|
||||
commands.append(onnxruntime_name + '==' + onnxruntime_version)
|
||||
|
||||
subprocess.call([ shutil.which('pip'), 'uninstall', 'onnxruntime', onnxruntime_name, '-y', '-q' ])
|
||||
|
||||
subprocess.call(commands)
|
||||
|
||||
@@ -0,0 +1,28 @@
|
||||
import ctypes
|
||||
import ctypes.util
|
||||
from functools import lru_cache
|
||||
from typing import Optional
|
||||
|
||||
|
||||
def pre_check() -> bool:
|
||||
return create_static_library() is not None
|
||||
|
||||
|
||||
@lru_cache
|
||||
def create_static_library() -> Optional[ctypes.CDLL]:
|
||||
library_path = ctypes.util.find_library('c')
|
||||
|
||||
if library_path:
|
||||
library = ctypes.CDLL(library_path)
|
||||
|
||||
if hasattr(library, 'malloc_trim'):
|
||||
return init_ctypes(library)
|
||||
|
||||
return None
|
||||
|
||||
|
||||
def init_ctypes(library : ctypes.CDLL) -> ctypes.CDLL:
|
||||
library.malloc_trim.argtypes = [ ctypes.c_size_t ]
|
||||
library.malloc_trim.restype = ctypes.c_int
|
||||
|
||||
return library
|
||||
@@ -4,7 +4,7 @@ METADATA =\
|
||||
{
|
||||
'name': 'FaceFusion',
|
||||
'description': 'Industry leading face manipulation platform',
|
||||
'version': '3.8.1',
|
||||
'version': '3.8.0',
|
||||
'license': 'OpenRAIL-AS',
|
||||
'author': 'Henry Ruhs',
|
||||
'url': 'https://facefusion.io'
|
||||
|
||||
@@ -504,15 +504,15 @@ def clear_inference_pool() -> None:
|
||||
|
||||
def adjust_inference_providers() -> List[InferenceProvider]:
|
||||
model_precision = get_model_options().get('precision')
|
||||
model_type = get_model_options().get('type')
|
||||
|
||||
if is_macos() and has_execution_provider('coreml') and model_precision == 'fp16':
|
||||
if state_manager.get_item('workflow_mode') == 'image-to-video':
|
||||
if is_macos() and has_execution_provider('coreml'):
|
||||
if model_type in [ 'ghost', 'uniface' ] or model_precision == 'fp16':
|
||||
return\
|
||||
[
|
||||
(facefusion.choices.execution_provider_set.get('coreml'),
|
||||
{
|
||||
'ModelFormat': 'MLProgram',
|
||||
'MLComputeUnits': 'CPUAndGPU'
|
||||
'ModelFormat': 'MLProgram'
|
||||
})
|
||||
]
|
||||
|
||||
|
||||
+1
-1
@@ -2,7 +2,7 @@ gradio-rangeslider==0.0.8
|
||||
gradio==5.50.0
|
||||
numpy==2.4.6
|
||||
onnx==1.22.0
|
||||
onnxruntime==1.28.0
|
||||
onnxruntime==1.26.0
|
||||
opencv-python-headless==5.0.0.93
|
||||
tqdm==4.70.0
|
||||
scipy==1.18.0
|
||||
|
||||
@@ -36,21 +36,9 @@ def before_each() -> None:
|
||||
init_jobs(get_test_jobs_directory())
|
||||
|
||||
|
||||
@pytest.mark.skip()
|
||||
def test_job_list() -> None:
|
||||
commands = [ sys.executable, 'facefusion.py', 'job-list', 'drafted', '--jobs-path', get_test_jobs_directory() ]
|
||||
|
||||
assert subprocess.run(commands).returncode == 1
|
||||
|
||||
commands = [ sys.executable, 'facefusion.py', 'job-create', 'test-job-list', '--jobs-path', get_test_jobs_directory() ]
|
||||
subprocess.run(commands)
|
||||
|
||||
commands = [ sys.executable, 'facefusion.py', 'job-list', 'drafted', '--jobs-path', get_test_jobs_directory() ]
|
||||
|
||||
assert subprocess.run(commands).returncode == 0
|
||||
|
||||
commands = [ sys.executable, 'facefusion.py', 'job-list', 'queued', '--jobs-path', get_test_jobs_directory() ]
|
||||
|
||||
assert subprocess.run(commands).returncode == 1
|
||||
pass
|
||||
|
||||
|
||||
def test_job_create() -> None:
|
||||
|
||||
@@ -6,7 +6,7 @@ from onnxruntime import InferenceSession
|
||||
|
||||
from facefusion import content_analyser, state_manager
|
||||
from facefusion.execution import resolve_cache_path
|
||||
from facefusion.inference_manager import get_inference_pool, resolve_static_inference_providers
|
||||
from facefusion.inference_manager import INFERENCE_POOL_SET, get_inference_pool, resolve_static_inference_providers
|
||||
|
||||
|
||||
@pytest.fixture(scope = 'module', autouse = True)
|
||||
@@ -20,29 +20,17 @@ def test_get_inference_pool() -> None:
|
||||
model_names = [ 'nsfw_1', 'nsfw_2', 'nsfw_3' ]
|
||||
_, model_source_set = content_analyser.collect_model_downloads()
|
||||
|
||||
with patch('facefusion.inference_manager.has_execution_provider', return_value = True):
|
||||
with patch('facefusion.inference_manager.get_onnxruntime_version', return_value = (1, 26, 0)):
|
||||
|
||||
with patch('facefusion.inference_manager.detect_app_context', return_value = 'cli'):
|
||||
cli_inference_pool = get_inference_pool('facefusion.content_analyser', model_names, model_source_set)
|
||||
get_inference_pool('facefusion.content_analyser', model_names, model_source_set)
|
||||
|
||||
assert isinstance(cli_inference_pool.get('nsfw_1'), InferenceSession)
|
||||
assert isinstance(INFERENCE_POOL_SET.get('cli').get('facefusion.content_analyser.nsfw_1.nsfw_2.nsfw_3.0.cpu').get('nsfw_1'), InferenceSession)
|
||||
|
||||
with patch('facefusion.inference_manager.detect_app_context', return_value = 'ui'):
|
||||
ui_inference_pool = get_inference_pool('facefusion.content_analyser', model_names, model_source_set)
|
||||
get_inference_pool('facefusion.content_analyser', model_names, model_source_set)
|
||||
|
||||
assert isinstance(ui_inference_pool.get('nsfw_1'), InferenceSession)
|
||||
assert isinstance(INFERENCE_POOL_SET.get('cli').get('facefusion.content_analyser.nsfw_1.nsfw_2.nsfw_3.0.cpu').get('nsfw_1'), InferenceSession)
|
||||
|
||||
assert not (cli_inference_pool.get('nsfw_1') is ui_inference_pool.get('nsfw_1'))
|
||||
|
||||
with patch('facefusion.inference_manager.get_onnxruntime_version', return_value = (1, 24, 4)):
|
||||
|
||||
with patch('facefusion.inference_manager.detect_app_context', return_value = 'ui'):
|
||||
ui_inference_pool = get_inference_pool('facefusion.content_analyser', model_names, model_source_set)
|
||||
|
||||
assert isinstance(ui_inference_pool.get('nsfw_1'), InferenceSession)
|
||||
|
||||
assert cli_inference_pool.get('nsfw_1') is ui_inference_pool.get('nsfw_1')
|
||||
assert INFERENCE_POOL_SET.get('cli').get('facefusion.content_analyser.nsfw_1.nsfw_2.nsfw_3.0.cpu').get('nsfw_1') == INFERENCE_POOL_SET.get('ui').get('facefusion.content_analyser.nsfw_1.nsfw_2.nsfw_3.0.cpu').get('nsfw_1')
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
@@ -60,15 +48,9 @@ def test_resolve_static_inference_providers(override_module : SimpleNamespace, a
|
||||
resolve_static_inference_providers.cache_clear()
|
||||
|
||||
with patch('facefusion.inference_manager.importlib', Mock(import_module = Mock(return_value = override_module))):
|
||||
inference_providers = resolve_static_inference_providers('override_module', 0)
|
||||
|
||||
assert inference_providers == [ ('CoreMLExecutionProvider', { 'ModelFormat': 'MLProgram' }) ]
|
||||
assert resolve_static_inference_providers('override_module', 0) == [ ('CoreMLExecutionProvider', { 'ModelFormat': 'MLProgram' }) ]
|
||||
|
||||
with patch('facefusion.inference_manager.importlib', Mock(import_module = Mock(return_value = adjust_module))):
|
||||
inference_providers = resolve_static_inference_providers('adjust_module', 0)
|
||||
assert resolve_static_inference_providers('adjust_module', 0) == [ ('CoreMLExecutionProvider', { 'SpecializationStrategy': 'FastPrediction', 'ModelCacheDirectory': resolve_cache_path(), 'ModelFormat': 'MLProgram' }) ]
|
||||
|
||||
assert inference_providers == [ ('CoreMLExecutionProvider', { 'SpecializationStrategy': 'FastPrediction', 'ModelCacheDirectory': resolve_cache_path(), 'ModelFormat': 'MLProgram' }) ]
|
||||
|
||||
inference_providers = resolve_static_inference_providers('test', 0)
|
||||
|
||||
assert inference_providers == [ ('CoreMLExecutionProvider', { 'SpecializationStrategy': 'FastPrediction', 'ModelCacheDirectory': resolve_cache_path() }) ]
|
||||
assert resolve_static_inference_providers('test', 0) == [ ('CoreMLExecutionProvider', { 'SpecializationStrategy': 'FastPrediction', 'ModelCacheDirectory': resolve_cache_path() }) ]
|
||||
|
||||
Reference in New Issue
Block a user