Fix some issues with TE being in lowvram mode.

Author: comfyanonymous

comfy/model_management.py

@@ -434,7 +434,7 @@ def free_memory(memory_required, device, keep_loaded=[]):
                 soft_empty_cache()
     return unloaded_models
 
-def load_models_gpu(models, memory_required=0, force_patch_weights=False, minimum_memory_required=None):
+def load_models_gpu(models, memory_required=0, force_patch_weights=False, minimum_memory_required=None, force_full_load=False):
     global vram_state
 
     inference_memory = minimum_inference_memory()
@@ -513,7 +513,7 @@ def load_models_gpu(models, memory_required=0, force_patch_weights=False, minimu
         else:
             vram_set_state = vram_state
         lowvram_model_memory = 0
-        if lowvram_available and (vram_set_state == VRAMState.LOW_VRAM or vram_set_state == VRAMState.NORMAL_VRAM):
+        if lowvram_available and (vram_set_state == VRAMState.LOW_VRAM or vram_set_state == VRAMState.NORMAL_VRAM) and not force_full_load:
             model_size = loaded_model.model_memory_required(torch_dev)
             current_free_mem = get_free_memory(torch_dev)
             lowvram_model_memory = max(64 * (1024 * 1024), (current_free_mem - minimum_memory_required), min(current_free_mem * 0.4, current_free_mem - minimum_inference_memory()))

comfy/model_patcher.py

@@ -411,7 +411,7 @@ def lowvram_load(self, device_to=None, lowvram_model_memory=0, force_patch_weigh
                     logging.debug("lowvram: loaded module regularly {} {}".format(n, m))
 
         if lowvram_counter > 0:
-            logging.info("loaded partially {} {}".format(lowvram_model_memory / (1024 * 1024), patch_counter))
+            logging.info("loaded partially {} {} {}".format(lowvram_model_memory / (1024 * 1024), mem_counter / (1024 * 1024), patch_counter))
             self.model.model_lowvram = True
         else:
             logging.info("loaded completely {} {}".format(lowvram_model_memory / (1024 * 1024), mem_counter / (1024 * 1024)))

comfy/sd.py

@@ -86,7 +86,7 @@ def __init__(self, target=None, embedding_directory=None, no_init=False, tokeniz
         self.tokenizer = tokenizer(embedding_directory=embedding_directory, tokenizer_data=tokenizer_data)
         self.patcher = comfy.model_patcher.ModelPatcher(self.cond_stage_model, load_device=load_device, offload_device=offload_device)
         if params['device'] == load_device:
-            model_management.load_model_gpu(self.patcher)
+            model_management.load_models_gpu([self.patcher], force_full_load=True)
         self.layer_idx = None
         logging.debug("CLIP model load device: {}, offload device: {}, current: {}".format(load_device, offload_device, params['device']))
 
@@ -585,7 +585,7 @@ def load_state_dict_guess_config(sd, output_vae=True, output_clip=True, output_c
         model_patcher = comfy.model_patcher.ModelPatcher(model, load_device=load_device, offload_device=model_management.unet_offload_device())
         if inital_load_device != torch.device("cpu"):
             logging.info("loaded straight to GPU")
-            model_management.load_model_gpu(model_patcher)
+            model_management.load_models_gpu([model_patcher], force_full_load=True)
 
     return (model_patcher, clip, vae, clipvision)