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7 changed files with 21 additions and 44 deletions
+1 -2
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@@ -5,7 +5,7 @@ import signal
import sys
from time import time
from facefusion import benchmarker, cli_helper, content_analyser, hash_helper, logger, memory_manager, state_manager, translator
from facefusion import benchmarker, cli_helper, content_analyser, hash_helper, logger, 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
@@ -305,7 +305,6 @@ 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
+8 -4
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@@ -32,10 +32,12 @@ def get_inference_pool(module_name : str, model_names : List[str], model_source_
for execution_device_id in execution_device_ids:
inference_context = get_inference_context(module_name, model_names, execution_device_id, execution_providers)
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 state_manager.get_item('video_memory_strategy') == 'tolerant':
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)
@@ -49,6 +51,7 @@ 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)
@@ -65,6 +68,7 @@ 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]
+6 -4
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@@ -19,16 +19,17 @@ LOCALES =\
}
ONNXRUNTIME_SET =\
{
'default': ('onnxruntime', '1.26.0')
'default': ('onnxruntime', '1.28.0')
}
if is_windows() or is_linux():
ONNXRUNTIME_SET['cuda'] = ('onnxruntime-gpu', '1.26.0')
ONNXRUNTIME_SET['cuda@12'] = ('onnxruntime-gpu', '1.26.0')
ONNXRUNTIME_SET['cuda@13'] = ('onnxruntime-gpu', '1.28.0')
ONNXRUNTIME_SET['openvino'] = ('onnxruntime-openvino', '1.24.1')
if is_windows():
ONNXRUNTIME_SET['directml'] = ('onnxruntime-directml', '1.24.4')
ONNXRUNTIME_SET['qnn'] = ('onnxruntime-qnn', '1.24.4')
ONNXRUNTIME_SET['qnn'] = ('onnxruntime-qnn', '2.4.0')
if is_linux():
ONNXRUNTIME_SET['migraphx'] = ('onnxruntime-migraphx', '1.26.0')
ONNXRUNTIME_SET['migraphx'] = ('onnxruntime-migraphx', '1.27.1')
ONNXRUNTIME_SET['rocm'] = ('onnxruntime-rocm', '1.22.2.post3')
@@ -63,6 +64,7 @@ def run(program : ArgumentParser) -> None:
for line in file.readlines():
__line__ = line.strip()
if not __line__.startswith('onnxruntime'):
commands.append(__line__)
-28
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@@ -1,28 +0,0 @@
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
+1 -1
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@@ -4,7 +4,7 @@ METADATA =\
{
'name': 'FaceFusion',
'description': 'Industry leading face manipulation platform',
'version': '3.8.0',
'version': '3.8.1',
'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'):
if model_type in [ 'ghost', 'uniface' ] or model_precision == 'fp16':
if is_macos() and has_execution_provider('coreml') and model_precision == 'fp16':
if state_manager.get_item('workflow_mode') == 'image-to-video':
return\
[
(facefusion.choices.execution_provider_set.get('coreml'),
{
'ModelFormat': 'MLProgram'
'ModelFormat': 'MLProgram',
'MLComputeUnits': 'CPUAndGPU'
})
]
+1 -1
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@@ -2,7 +2,7 @@ gradio-rangeslider==0.0.8
gradio==5.50.0
numpy==2.4.6
onnx==1.22.0
onnxruntime==1.26.0
onnxruntime==1.28.0
opencv-python-headless==5.0.0.93
tqdm==4.70.0
scipy==1.18.0