Consolidate loader logic

utils/loader.py

@@ -0,0 +1,35 @@
+import logging
+import comfy.utils
+import comfy.model_patcher
+from comfy import model_management
+
+def load_state_dict_from_config(model_config, sd, model_options={}):
+    parameters = comfy.utils.calculate_parameters(sd)
+    load_device = model_management.get_torch_device()
+    offload_device = comfy.model_management.unet_offload_device()
+
+    dtype = model_options.get("dtype", None)
+    weight_dtype = comfy.utils.weight_dtype(sd)
+    unet_weight_dtype = list(model_config.supported_inference_dtypes)
+
+    if weight_dtype is not None and model_config.scaled_fp8 is None:
+        unet_weight_dtype.append(weight_dtype)
+
+    if dtype is None:
+        unet_dtype = model_management.unet_dtype(model_params=parameters, supported_dtypes=unet_weight_dtype)
+    else:
+        unet_dtype = 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)
+    model_config.custom_operations = model_options.get("custom_operations", model_config.custom_operations)
+    if model_options.get("fp8_optimizations", False):
+        model_config.optimizations["fp8"] = True
+
+    model = model_config.get_model(sd, "")
+    model = model.to(offload_device).eval()
+    model.load_model_weights(sd, "")
+    left_over = sd.keys()
+    if len(left_over) > 0:
+        logging.info("left over keys in unet: {}".format(left_over))
+    return comfy.model_patcher.ModelPatcher(model, load_device=load_device, offload_device=offload_device)