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Fix broken inference pools part2

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This commit is contained in:
henryruhs
2025-02-09 01:43:58 +01:00
parent b438b899e8
commit 1bdc02014c
18 changed files with 92 additions and 65 deletions
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7
facefusion/content_analyser.py
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@@ -42,13 +42,14 @@ def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
def get_inference_pool() -> InferencePool: def get_inference_pool() -> InferencePool:
model_names = [ 'yolo_nsfw' ]
model_sources = get_model_options().get('sources') model_sources = get_model_options().get('sources')
return inference_manager.get_inference_pool(__name__, model_sources) return inference_manager.get_inference_pool(__name__, model_names, model_sources)
def clear_inference_pool() -> None: def clear_inference_pool() -> None:
model_sources = get_model_options().get('sources') model_names = [ 'yolo_nsfw' ]
inference_manager.clear_inference_pool(__name__, model_sources) inference_manager.clear_inference_pool(__name__, model_names)
def get_model_options() -> ModelOptions: def get_model_options() -> ModelOptions:

7
facefusion/face_classifier.py
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@@ -42,13 +42,14 @@ def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
def get_inference_pool() -> InferencePool: def get_inference_pool() -> InferencePool:
model_names = [ 'fairface' ]
model_sources = get_model_options().get('sources') model_sources = get_model_options().get('sources')
return inference_manager.get_inference_pool(__name__, model_sources) return inference_manager.get_inference_pool(__name__, model_names, model_sources)
def clear_inference_pool() -> None: def clear_inference_pool() -> None:
model_sources = get_model_options().get('sources') model_names = [ 'fairface' ]
inference_manager.clear_inference_pool(__name__, model_sources) inference_manager.clear_inference_pool(__name__, model_names)
def get_model_options() -> ModelOptions: def get_model_options() -> ModelOptions:

7
facefusion/face_detector.py
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@@ -78,13 +78,14 @@ def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
def get_inference_pool() -> InferencePool: def get_inference_pool() -> InferencePool:
model_names = [ state_manager.get_item('face_detector_model') ]
_, model_sources = collect_model_downloads() _, model_sources = collect_model_downloads()
return inference_manager.get_inference_pool(__name__, model_sources) return inference_manager.get_inference_pool(__name__, model_names, model_sources)
def clear_inference_pool() -> None: def clear_inference_pool() -> None:
_, model_sources = collect_model_downloads() model_names = [ state_manager.get_item('face_detector_model') ]
inference_manager.clear_inference_pool(__name__, model_sources) inference_manager.clear_inference_pool(__name__, model_names)
def collect_model_downloads() -> Tuple[DownloadSet, DownloadSet]: def collect_model_downloads() -> Tuple[DownloadSet, DownloadSet]:

7
facefusion/face_landmarker.py
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@@ -79,13 +79,14 @@ def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
def get_inference_pool() -> InferencePool: def get_inference_pool() -> InferencePool:
model_names = [ state_manager.get_item('face_landmarker_model'), 'fan_68_5' ]
_, model_sources = collect_model_downloads() _, model_sources = collect_model_downloads()
return inference_manager.get_inference_pool(__name__, model_sources) return inference_manager.get_inference_pool(__name__, model_names, model_sources)
def clear_inference_pool() -> None: def clear_inference_pool() -> None:
_, model_sources = collect_model_downloads() model_names = [ state_manager.get_item('face_landmarker_model'), 'fan_68_5' ]
inference_manager.clear_inference_pool(__name__, model_sources) inference_manager.clear_inference_pool(__name__, model_names)
def collect_model_downloads() -> Tuple[DownloadSet, DownloadSet]: def collect_model_downloads() -> Tuple[DownloadSet, DownloadSet]:

7
facefusion/face_masker.py
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@@ -121,13 +121,14 @@ def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
def get_inference_pool() -> InferencePool: def get_inference_pool() -> InferencePool:
model_names = [state_manager.get_item('face_occluder_model'), state_manager.get_item('face_parser_model')]
_, model_sources = collect_model_downloads() _, model_sources = collect_model_downloads()
return inference_manager.get_inference_pool(__name__, model_sources) return inference_manager.get_inference_pool(__name__, model_names, model_sources)
def clear_inference_pool() -> None: def clear_inference_pool() -> None:
_, model_sources = collect_model_downloads() model_names = [ state_manager.get_item('face_occluder_model'), state_manager.get_item('face_parser_model') ]
inference_manager.clear_inference_pool(__name__, model_sources) inference_manager.clear_inference_pool(__name__, model_names)
def collect_model_downloads() -> Tuple[DownloadSet, DownloadSet]: def collect_model_downloads() -> Tuple[DownloadSet, DownloadSet]:

7
facefusion/face_recognizer.py
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@@ -40,13 +40,14 @@ def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
def get_inference_pool() -> InferencePool: def get_inference_pool() -> InferencePool:
model_names = [ 'arcface' ]
model_sources = get_model_options().get('sources') model_sources = get_model_options().get('sources')
return inference_manager.get_inference_pool(__name__, model_sources) return inference_manager.get_inference_pool(__name__, model_names, model_sources)
def clear_inference_pool() -> None: def clear_inference_pool() -> None:
model_sources = get_model_options().get('sources') model_names = [ 'arcface' ]
inference_manager.clear_inference_pool(__name__, model_sources) inference_manager.clear_inference_pool(__name__, model_names)
def get_model_options() -> ModelOptions: def get_model_options() -> ModelOptions:

12
facefusion/inference_manager.py
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@@ -17,7 +17,7 @@ INFERENCE_POOLS : InferencePoolSet =\
} }
def get_inference_pool(module_name : str, model_sources : DownloadSet) -> InferencePool: def get_inference_pool(module_name : str, model_names : List[str], model_sources : DownloadSet) -> InferencePool:
global INFERENCE_POOLS global INFERENCE_POOLS
while process_manager.is_checking(): while process_manager.is_checking():
@@ -25,7 +25,7 @@ def get_inference_pool(module_name : str, model_sources : DownloadSet) -> Infere
execution_device_id = state_manager.get_item('execution_device_id') execution_device_id = state_manager.get_item('execution_device_id')
execution_providers = resolve_execution_providers(module_name) execution_providers = resolve_execution_providers(module_name)
app_context = detect_app_context() app_context = detect_app_context()
inference_context = get_inference_context(module_name, model_sources, execution_device_id, execution_providers) inference_context = get_inference_context(module_name, model_names, execution_device_id, execution_providers)
if app_context == 'cli' and INFERENCE_POOLS.get('ui').get(inference_context): if app_context == 'cli' and INFERENCE_POOLS.get('ui').get(inference_context):
INFERENCE_POOLS['cli'][inference_context] = INFERENCE_POOLS.get('ui').get(inference_context) INFERENCE_POOLS['cli'][inference_context] = INFERENCE_POOLS.get('ui').get(inference_context)
@@ -48,13 +48,13 @@ def create_inference_pool(model_sources : DownloadSet, execution_device_id : str
return inference_pool return inference_pool
def clear_inference_pool(module_name : str, model_sources : DownloadSet) -> None: def clear_inference_pool(module_name : str, model_names : List[str]) -> None:
global INFERENCE_POOLS global INFERENCE_POOLS
execution_device_id = state_manager.get_item('execution_device_id') execution_device_id = state_manager.get_item('execution_device_id')
execution_providers = resolve_execution_providers(module_name) execution_providers = resolve_execution_providers(module_name)
app_context = detect_app_context() app_context = detect_app_context()
inference_context = get_inference_context(module_name, model_sources, execution_device_id, execution_providers) inference_context = get_inference_context(module_name, model_names, execution_device_id, execution_providers)
if INFERENCE_POOLS.get(app_context).get(inference_context): if INFERENCE_POOLS.get(app_context).get(inference_context):
del INFERENCE_POOLS[app_context][inference_context] del INFERENCE_POOLS[app_context][inference_context]
@@ -65,8 +65,8 @@ def create_inference_session(model_path : str, execution_device_id : str, execut
return InferenceSession(model_path, providers = inference_session_providers) return InferenceSession(model_path, providers = inference_session_providers)
def get_inference_context(module_name : str, model_sources : DownloadSet, execution_device_id : str, execution_providers : List[ExecutionProvider]) -> str: 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 ] + list(model_sources.keys()) + [ execution_device_id ] + list(execution_providers)) inference_context = '.'.join([ module_name ] + model_names + [ execution_device_id ] + list(execution_providers))
return inference_context return inference_context

7
facefusion/processors/modules/age_modifier.py
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@@ -64,13 +64,14 @@ def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
def get_inference_pool() -> InferencePool: def get_inference_pool() -> InferencePool:
model_names = [ state_manager.get_item('age_modifier_model') ]
model_sources = get_model_options().get('sources') model_sources = get_model_options().get('sources')
return inference_manager.get_inference_pool(__name__, model_sources) return inference_manager.get_inference_pool(__name__, model_names, model_sources)
def clear_inference_pool() -> None: def clear_inference_pool() -> None:
model_sources = get_model_options().get('sources') model_names = [ state_manager.get_item('age_modifier_model') ]
inference_manager.clear_inference_pool(__name__, model_sources) inference_manager.clear_inference_pool(__name__, model_names)
def get_model_options() -> ModelOptions: def get_model_options() -> ModelOptions:

7
facefusion/processors/modules/deep_swapper.py
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@@ -240,13 +240,14 @@ def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
def get_inference_pool() -> InferencePool: def get_inference_pool() -> InferencePool:
model_names = [ state_manager.get_item('deep_swapper_model') ]
model_sources = get_model_options().get('sources') model_sources = get_model_options().get('sources')
return inference_manager.get_inference_pool(__name__, model_sources) return inference_manager.get_inference_pool(__name__, model_names, model_sources)
def clear_inference_pool() -> None: def clear_inference_pool() -> None:
model_sources = get_model_options().get('sources') model_names = [ state_manager.get_item('deep_swapper_model') ]
inference_manager.clear_inference_pool(__name__, model_sources) inference_manager.clear_inference_pool(__name__, model_names)
def get_model_options() -> ModelOptions: def get_model_options() -> ModelOptions:

7
facefusion/processors/modules/expression_restorer.py
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@@ -75,13 +75,14 @@ def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
def get_inference_pool() -> InferencePool: def get_inference_pool() -> InferencePool:
model_names = [ state_manager.get_item('expression_restorer_model') ]
model_sources = get_model_options().get('sources') model_sources = get_model_options().get('sources')
return inference_manager.get_inference_pool(__name__, model_sources) return inference_manager.get_inference_pool(__name__, model_names, model_sources)
def clear_inference_pool() -> None: def clear_inference_pool() -> None:
model_sources = get_model_options().get('sources') model_names = [ state_manager.get_item('expression_restorer_model') ]
inference_manager.clear_inference_pool(__name__, model_sources) inference_manager.clear_inference_pool(__name__, model_names)
def get_model_options() -> ModelOptions: def get_model_options() -> ModelOptions:

7
facefusion/processors/modules/face_editor.py
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@@ -105,13 +105,14 @@ def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
def get_inference_pool() -> InferencePool: def get_inference_pool() -> InferencePool:
model_names = [ state_manager.get_item('face_editor_model') ]
model_sources = get_model_options().get('sources') model_sources = get_model_options().get('sources')
return inference_manager.get_inference_pool(__name__, model_sources) return inference_manager.get_inference_pool(__name__, model_names, model_sources)
def clear_inference_pool() -> None: def clear_inference_pool() -> None:
model_sources = get_model_options().get('sources') model_names = [ state_manager.get_item('face_editor_model') ]
inference_manager.clear_inference_pool(__name__, model_sources) inference_manager.clear_inference_pool(__name__, model_names)
def get_model_options() -> ModelOptions: def get_model_options() -> ModelOptions:

7
facefusion/processors/modules/face_enhancer.py
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@@ -222,13 +222,14 @@ def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
def get_inference_pool() -> InferencePool: def get_inference_pool() -> InferencePool:
model_names = [ state_manager.get_item('face_enhancer_model') ]
model_sources = get_model_options().get('sources') model_sources = get_model_options().get('sources')
return inference_manager.get_inference_pool(__name__, model_sources) return inference_manager.get_inference_pool(__name__, model_names, model_sources)
def clear_inference_pool() -> None: def clear_inference_pool() -> None:
model_sources = get_model_options().get('sources') model_names = [ state_manager.get_item('face_enhancer_model') ]
inference_manager.clear_inference_pool(__name__, model_sources) inference_manager.clear_inference_pool(__name__, model_names)
def get_model_options() -> ModelOptions: def get_model_options() -> ModelOptions:

16
facefusion/processors/modules/face_swapper.py
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@@ -336,21 +336,27 @@ def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
def get_inference_pool() -> InferencePool: def get_inference_pool() -> InferencePool:
model_names = [ get_face_swapper_model() ]
model_sources = get_model_options().get('sources') model_sources = get_model_options().get('sources')
return inference_manager.get_inference_pool(__name__, model_sources) return inference_manager.get_inference_pool(__name__, model_names, model_sources)
def clear_inference_pool() -> None: def clear_inference_pool() -> None:
model_sources = get_model_options().get('sources') model_names = [ get_face_swapper_model() ]
inference_manager.clear_inference_pool(__name__, model_sources) inference_manager.clear_inference_pool(__name__, model_names)
def get_model_options() -> ModelOptions: def get_model_options() -> ModelOptions:
face_swapper_model = get_face_swapper_model()
return create_static_model_set('full').get(face_swapper_model)
def get_face_swapper_model() -> str:
face_swapper_model = state_manager.get_item('face_swapper_model') face_swapper_model = state_manager.get_item('face_swapper_model')
if has_execution_provider('coreml') and face_swapper_model == 'inswapper_128_fp16': if has_execution_provider('coreml') and face_swapper_model == 'inswapper_128_fp16':
return create_static_model_set('full').get('inswapper_128') return 'inswapper_128'
return create_static_model_set('full').get(face_swapper_model) return face_swapper_model
def register_args(program : ArgumentParser) -> None: def register_args(program : ArgumentParser) -> None:

7
facefusion/processors/modules/frame_colorizer.py
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@@ -129,13 +129,14 @@ def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
def get_inference_pool() -> InferencePool: def get_inference_pool() -> InferencePool:
model_names = [ state_manager.get_item('frame_colorizer_model') ]
model_sources = get_model_options().get('sources') model_sources = get_model_options().get('sources')
return inference_manager.get_inference_pool(__name__, model_sources) return inference_manager.get_inference_pool(__name__, model_names, model_sources)
def clear_inference_pool() -> None: def clear_inference_pool() -> None:
model_sources = get_model_options().get('sources') model_names = [ state_manager.get_item('frame_colorizer_model') ]
inference_manager.clear_inference_pool(__name__, model_sources) inference_manager.clear_inference_pool(__name__, model_names)
def resolve_execution_providers() -> List[ExecutionProvider]: def resolve_execution_providers() -> List[ExecutionProvider]:

20
facefusion/processors/modules/frame_enhancer.py
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@@ -386,26 +386,32 @@ def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
def get_inference_pool() -> InferencePool: def get_inference_pool() -> InferencePool:
model_names = [ get_frame_enhancer_model() ]
model_sources = get_model_options().get('sources') model_sources = get_model_options().get('sources')
return inference_manager.get_inference_pool(__name__, model_sources) return inference_manager.get_inference_pool(__name__, model_names, model_sources)
def clear_inference_pool() -> None: def clear_inference_pool() -> None:
model_sources = get_model_options().get('sources') model_names = [ get_frame_enhancer_model() ]
inference_manager.clear_inference_pool(__name__, model_sources) inference_manager.clear_inference_pool(__name__, model_names)
def get_model_options() -> ModelOptions: def get_model_options() -> ModelOptions:
frame_enhancer_model = get_frame_enhancer_model()
return create_static_model_set('full').get(frame_enhancer_model)
def get_frame_enhancer_model() -> str:
frame_enhancer_model = state_manager.get_item('frame_enhancer_model') frame_enhancer_model = state_manager.get_item('frame_enhancer_model')
if has_execution_provider('coreml'): if has_execution_provider('coreml'):
if frame_enhancer_model == 'real_esrgan_x2_fp16': if frame_enhancer_model == 'real_esrgan_x2_fp16':
return create_static_model_set('full').get('real_esrgan_x2') return 'real_esrgan_x2'
if frame_enhancer_model == 'real_esrgan_x4_fp16': if frame_enhancer_model == 'real_esrgan_x4_fp16':
return create_static_model_set('full').get('real_esrgan_x4') return 'real_esrgan_x4'
if frame_enhancer_model == 'real_esrgan_x8_fp16': if frame_enhancer_model == 'real_esrgan_x8_fp16':
return create_static_model_set('full').get('real_esrgan_x8') return 'real_esrgan_x8'
return create_static_model_set('full').get(frame_enhancer_model) return frame_enhancer_model
def register_args(program : ArgumentParser) -> None: def register_args(program : ArgumentParser) -> None:

7
facefusion/processors/modules/lip_syncer.py
View File

@@ -74,13 +74,14 @@ def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
def get_inference_pool() -> InferencePool: def get_inference_pool() -> InferencePool:
model_names = [ state_manager.get_item('lip_syncer_model') ]
model_sources = get_model_options().get('sources') model_sources = get_model_options().get('sources')
return inference_manager.get_inference_pool(__name__, model_sources) return inference_manager.get_inference_pool(__name__, model_names, model_sources)
def clear_inference_pool() -> None: def clear_inference_pool() -> None:
model_sources = get_model_options().get('sources') model_names = [ state_manager.get_item('lip_syncer_model') ]
inference_manager.clear_inference_pool(__name__, model_sources) inference_manager.clear_inference_pool(__name__, model_names)
def get_model_options() -> ModelOptions: def get_model_options() -> ModelOptions:

7
facefusion/voice_extractor.py
View File

@@ -38,13 +38,14 @@ def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
def get_inference_pool() -> InferencePool: def get_inference_pool() -> InferencePool:
model_names = [ 'kim_vocal_2' ]
model_sources = get_model_options().get('sources') model_sources = get_model_options().get('sources')
return inference_manager.get_inference_pool(__name__, model_sources) return inference_manager.get_inference_pool(__name__, model_names, model_sources)
def clear_inference_pool() -> None: def clear_inference_pool() -> None:
model_sources = get_model_options().get('sources') model_names = [ 'kim_vocal_2' ]
inference_manager.clear_inference_pool(__name__, model_sources) inference_manager.clear_inference_pool(__name__, model_names)
def get_model_options() -> ModelOptions: def get_model_options() -> ModelOptions:

11
tests/test_inference_manager.py
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@@ -16,16 +16,17 @@ def before_all() -> None:
def test_get_inference_pool() -> None: def test_get_inference_pool() -> None:
model_names = [ 'yolo_nsfw' ]
model_sources = content_analyser.get_model_options().get('sources') model_sources = content_analyser.get_model_options().get('sources')
with patch('facefusion.inference_manager.detect_app_context', return_value = 'cli'): with patch('facefusion.inference_manager.detect_app_context', return_value = 'cli'):
get_inference_pool('test', model_sources) get_inference_pool('facefusion.content_analyser', model_names, model_sources)
assert isinstance(INFERENCE_POOLS.get('cli').get('test.content_analyser.0.cpu').get('content_analyser'), InferenceSession) assert isinstance(INFERENCE_POOLS.get('cli').get('facefusion.content_analyser.yolo_nsfw.0.cpu').get('content_analyser'), InferenceSession)
with patch('facefusion.inference_manager.detect_app_context', return_value = 'ui'): with patch('facefusion.inference_manager.detect_app_context', return_value = 'ui'):
get_inference_pool('test', model_sources) get_inference_pool('facefusion.content_analyser', model_names, model_sources)
assert isinstance(INFERENCE_POOLS.get('ui').get('test.content_analyser.0.cpu').get('content_analyser'), InferenceSession) assert isinstance(INFERENCE_POOLS.get('ui').get('facefusion.content_analyser.yolo_nsfw.0.cpu').get('content_analyser'), InferenceSession)
assert INFERENCE_POOLS.get('cli').get('test.content_analyser.0.cpu').get('content_analyser') == INFERENCE_POOLS.get('ui').get('test.content_analyser.0.cpu').get('content_analyser') assert INFERENCE_POOLS.get('cli').get('facefusion.content_analyser.yolo_nsfw.0.cpu').get('content_analyser') == INFERENCE_POOLS.get('ui').get('facefusion.content_analyser.yolo_nsfw.0.cpu').get('content_analyser')