Fix/remote inference pool lookups (#848)

* Fix edge case when offline and inference session has no model, Prevent inference session creation

* Fix edge case when offline and inference session has no model, Prevent inference session creation

* Fix edge case when offline and inference session has no model, Prevent inference session creation

* Fix edge case when offline and inference session has no model, Prevent inference session creation

facefusion/inference_manager.py

@@ -6,6 +6,7 @@ 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_execution_providers
+from facefusion.filesystem import is_file
 from facefusion.thread_helper import thread_lock
 from facefusion.typing import DownloadSet, ExecutionProvider, InferencePool, InferencePoolSet
 
@@ -16,6 +17,18 @@ INFERENCE_POOLS : InferencePoolSet =\
 }
 
 
+def has_inference_model(model_context : str, model_name : str) -> bool:
+	while process_manager.is_checking():
+		sleep(0.5)
+	app_context = detect_app_context()
+	inference_context = get_inference_context(model_context)
+	inference_pool = INFERENCE_POOLS.get(app_context).get(inference_context)
+
+	if inference_pool:
+		return model_name in inference_pool
+	return False
+
+
 def get_inference_pool(model_context : str, model_sources : DownloadSet) -> InferencePool:
 	global INFERENCE_POOLS
 
@@ -39,7 +52,10 @@ def create_inference_pool(model_sources : DownloadSet, execution_device_id : str
 	inference_pool : InferencePool = {}
 
 	for model_name in model_sources.keys():
-		inference_pool[model_name] = create_inference_session(model_sources.get(model_name).get('path'), execution_device_id, execution_providers)
+		model_path = model_sources.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
 
 

facefusion/processors/modules/deep_swapper.py

@@ -238,6 +238,10 @@ def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
 	return model_set
 
 
+def has_inference_model(model_name : str) -> bool:
+	return inference_manager.has_inference_model(__name__, model_name)
+
+
 def get_inference_pool() -> InferencePool:
 	model_sources = get_model_options().get('sources')
 	return inference_manager.get_inference_pool(__name__, model_sources)
@@ -357,11 +361,13 @@ def forward(crop_vision_frame : VisionFrame, deep_swapper_morph : DeepSwapperMor
 
 
 def has_morph_input() -> bool:
+	if has_inference_model('deep_swapper'):
 		deep_swapper = get_inference_pool().get('deep_swapper')
 
 		for deep_swapper_input in deep_swapper.get_inputs():
 			if deep_swapper_input.name == 'morph_value:0':
 				return True
+
 	return False
 
 

facefusion/processors/modules/face_enhancer.py

@@ -221,6 +221,10 @@ def create_static_model_set(download_scope : DownloadScope) -> ModelSet:
 	}
 
 
+def has_inference_model(model_name : str) -> bool:
+	return inference_manager.has_inference_model(__name__, model_name)
+
+
 def get_inference_pool() -> InferencePool:
 	model_sources = get_model_options().get('sources')
 	return inference_manager.get_inference_pool(__name__, model_sources)
@@ -324,11 +328,13 @@ def forward(crop_vision_frame : VisionFrame, face_enhancer_weight : FaceEnhancer
 
 
 def has_weight_input() -> bool:
+	if has_inference_model('face_enhancer'):
 		face_enhancer = get_inference_pool().get('face_enhancer')
 
 		for deep_swapper_input in face_enhancer.get_inputs():
 			if deep_swapper_input.name == 'weight':
 				return True
+
 	return False
 
 

facefusion/uis/components/deep_swapper_options.py

@@ -31,7 +31,7 @@ def render() -> None:
 		step = calc_int_step(processors_choices.deep_swapper_morph_range),
 		minimum = processors_choices.deep_swapper_morph_range[0],
 		maximum = processors_choices.deep_swapper_morph_range[-1],
-		visible = has_deep_swapper and has_morph_input()
+		visible = has_morph_input()
 	)
 	register_ui_component('deep_swapper_model_dropdown', DEEP_SWAPPER_MODEL_DROPDOWN)
 	register_ui_component('deep_swapper_morph_slider', DEEP_SWAPPER_MORPH_SLIDER)
@@ -48,7 +48,7 @@ def listen() -> None:
 
 def remote_update(processors : List[str]) -> Tuple[gradio.Dropdown, gradio.Slider]:
 	has_deep_swapper = 'deep_swapper' in processors
-	return gradio.Dropdown(visible = has_deep_swapper), gradio.Slider(visible = has_deep_swapper and has_morph_input())
+	return gradio.Dropdown(visible = has_deep_swapper), gradio.Slider(visible = has_morph_input())
 
 
 def update_deep_swapper_model(deep_swapper_model : DeepSwapperModel) -> Tuple[gradio.Dropdown, gradio.Slider]: