Fix some issues.

comfy/model_management.py

@@ -450,8 +450,7 @@ def load_models_gpu(models, memory_required=0, force_patch_weights=False, minimu
         if lowvram_available and (vram_set_state == VRAMState.LOW_VRAM or vram_set_state == VRAMState.NORMAL_VRAM):
             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))
-            lowvram_model_memory = int(min(current_free_mem * 0.5, lowvram_model_memory))
+            lowvram_model_memory = max(64 * (1024 * 1024), (current_free_mem - minimum_memory_required), current_free_mem * 0.5)
             if model_size <= lowvram_model_memory: #only switch to lowvram if really necessary
                 lowvram_model_memory = 0
 

comfy/sd.py

@@ -517,7 +517,11 @@ def load_checkpoint_guess_config(ckpt_path, output_vae=True, output_clip=True, o
     if model_config is None:
         raise RuntimeError("ERROR: Could not detect model type of: {}".format(ckpt_path))
 
-    unet_dtype = model_management.unet_dtype(model_params=parameters, supported_dtypes=[weight_dtype] + model_config.supported_inference_dtypes)
+    unet_weight_dtype = list(model_config.supported_inference_dtypes)
+    if weight_dtype is not None:
+        unet_weight_dtype.append(weight_dtype)
+
+    unet_dtype = model_management.unet_dtype(model_params=parameters, supported_dtypes=unet_weight_dtype)
     manual_cast_dtype = model_management.unet_manual_cast(unet_dtype, load_device, model_config.supported_inference_dtypes)
     model_config.set_inference_dtype(unet_dtype, manual_cast_dtype)
 

comfy/utils.py

@@ -51,6 +51,9 @@ def weight_dtype(sd, prefix=""):
             w = sd[k]
             dtypes[w.dtype] = dtypes.get(w.dtype, 0) + 1
 
+    if len(dtypes) == 0:
+        return None
+
     return max(dtypes, key=dtypes.get)
 
 def state_dict_key_replace(state_dict, keys_to_replace):