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import importlib
from time import sleep
from typing import List
from onnxruntime import InferenceSession
from facefusion import process_manager, state_manager
from facefusion.app_context import detect_app_context
from facefusion.execution import create_inference_session_providers
from facefusion.filesystem import is_file
from facefusion.types import DownloadSet, ExecutionProvider, InferencePool, InferencePoolSet
INFERENCE_POOL_SET : InferencePoolSet =\
{
'cli': {},
'ui': {}
}
def get_inference_pool(module_name : str, model_names : List[str], model_source_set : DownloadSet) -> InferencePool:
global INFERENCE_POOL_SET
while process_manager.is_checking():
sleep(0.5)
execution_device_id = state_manager.get_item('execution_device_id')
execution_providers = resolve_execution_providers(module_name)
app_context = detect_app_context()
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 not INFERENCE_POOL_SET.get(app_context).get(inference_context):
INFERENCE_POOL_SET[app_context][inference_context] = create_inference_pool(model_source_set, execution_device_id, execution_providers)
return INFERENCE_POOL_SET.get(app_context).get(inference_context)
def create_inference_pool(model_source_set : DownloadSet, execution_device_id : str, execution_providers : List[ExecutionProvider]) -> InferencePool:
inference_pool : InferencePool = {}
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, execution_device_id, execution_providers)
return inference_pool
def clear_inference_pool(module_name : str, model_names : List[str]) -> None:
global INFERENCE_POOL_SET
execution_device_id = state_manager.get_item('execution_device_id')
execution_providers = resolve_execution_providers(module_name)
app_context = detect_app_context()
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]
def create_inference_session(model_path : str, execution_device_id : str, execution_providers : List[ExecutionProvider]) -> InferenceSession:
inference_session_providers = create_inference_session_providers(execution_device_id, execution_providers)
return InferenceSession(model_path, providers = inference_session_providers)
def get_inference_context(module_name : str, model_names : List[str], execution_device_id : str, execution_providers : List[ExecutionProvider]) -> str:
inference_context = '.'.join([ module_name ] + model_names + [ execution_device_id ] + list(execution_providers))
return inference_context
def resolve_execution_providers(module_name : str) -> List[ExecutionProvider]:
module = importlib.import_module(module_name)
if hasattr(module, 'resolve_execution_providers'):
return getattr(module, 'resolve_execution_providers')()
return state_manager.get_item('execution_providers')
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