Add support for weighted LoRAs in the LoRA merge script.

src/invoke_training/scripts/_experimental/lora_merge/merge_lora_into_sd_model.py

@@ -89,7 +89,7 @@ def merge_lora_into_sd_model(
     base_model: str,
     base_model_variant: str | None,
     base_model_type: PipelineVersionEnum,
-    lora_models: list[str],
+    lora_models: list[tuple[str, float]],
     output: str,
     save_dtype: str,
 ):
@@ -113,16 +113,18 @@ def merge_lora_into_sd_model(
     else:
         raise ValueError(f"Unexpected pipeline type: {type(pipeline)}")
 
-    for lora_model_path in lora_models:
+    for lora_model_path, lora_model_weight in lora_models:
         lora_model = LoRAModelRaw.from_checkpoint(
             file_path=lora_model_path,
             device=pipeline.device,
             dtype=save_dtype,
             base_model=to_invokeai_base_model_type(base_model_type),
         )
         for model, lora_prefix in zip(models, lora_prefixes, strict=True):
-            # TODO(ryand): Parameterize the weight.
-            apply_lora_model_to_base_model(base_model=model, lora=lora_model, lora_weight=1.0, prefix=lora_prefix)
+            apply_lora_model_to_base_model(
+                base_model=model, lora=lora_model, lora_weight=lora_model_weight, prefix=lora_prefix
+            )
+        logger.info(f"Applied LoRA model '{lora_model_path}' with weight {lora_model_weight}.")
 
     output_path = Path(output)
     output_path.mkdir(parents=True)
@@ -132,6 +134,17 @@ def merge_lora_into_sd_model(
     logger.info(f"Saved merged model to '{output_path}'.")
 
 
+def parse_lora_model_arg(lora_model_arg: str) -> tuple[str, float]:
+    """Parse a --lora-model argument into a tuple of the model path and weight."""
+    parts = lora_model_arg.split(":")
+    if len(parts) == 1:
+        return parts[0], 1.0
+    elif len(parts) == 2:
+        return parts[0], float(parts[1])
+    else:
+        raise ValueError(f"Unexpected format for --lora-model arg: '{lora_model_arg}'.")
+
+
 def main():
     parser = argparse.ArgumentParser()
     parser.add_argument(
@@ -157,7 +170,9 @@ def main():
         "--lora-model",
         type=str,
         nargs="+",
-        help="The path(s) to one or more LoRA models to merge into the base model.",
+        help="The path(s) to one or more LoRA models to merge into the base model. Model weights can be appended to "
+        "the path, separated by a colon (':'). E.g. 'path/to/lora_model:0.5'. The weight is optional and defaults to "
+        "1.0.",
         required=True,
     )
     parser.add_argument(
@@ -182,7 +197,7 @@ def main():
         base_model=args.base_model,
         base_model_variant=args.base_model_variant,
         base_model_type=PipelineVersionEnum(args.base_model_type),
-        lora_models=args.lora_model,
+        lora_models=[parse_lora_model_arg(arg) for arg in args.lora_model],
         output=args.output,
         save_dtype=args.save_dtype,
     )