fix(lora): clarify Lodestone controls
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silveroxides
+16
-14
@@ -236,14 +236,14 @@ def merge_lodestone_loras(lora_paths, method, device, save_dtype, output_filenam
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def _controls(default_filename):
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return [
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io.Combo.Input("calc_mode", options=list(LODESTONE_METHODS), default="sum", tooltip="Dense delta-space Lodestone calculation."),
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io.Combo.Input("mismatch_mode", options=["skip", "zeros", "error"], default="skip", tooltip="Preserve LoRA 1, insert zero deltas, or abort for missing layers."),
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io.String.Input("output_filename", default=default_filename, tooltip="Filename without extension under ComfyUI's LoRA directory."),
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io.Combo.Input("save_dtype", options=["fp32", "fp16", "bf16"], default="bf16", tooltip="Saved full-delta tensor dtype."),
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io.Combo.Input("process_device", options=["cuda", "cpu"], default="cuda", tooltip="Dense processing device; CUDA OOM retries the layer on CPU."),
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io.String.Input("exclude_patterns", default="", multiline=True, tooltip="Preserve matching logical layers from LoRA 1."),
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io.String.Input("discard_patterns", default="", multiline=True, tooltip="Omit matching logical layers."),
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io.Boolean.Input("glob_patterns", default=False, tooltip="Interpret filters as globs instead of regular expressions."),
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io.Combo.Input("calc_mode", options=list(LODESTONE_METHODS), default="sum", tooltip="How full LoRA weight changes are combined per layer. sum adds them; mean averages them; slotnorm equalizes each input's Frobenius magnitude before averaging; normmatch adds them and scales the result to a typical input magnitude; slotnorm-normmatch performs both normalization steps."),
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io.Combo.Input("mismatch_mode", options=["skip", "zeros", "error"], default="skip", tooltip="What to do when a layer exists in LoRA 1 but is absent from another input. skip copies LoRA 1's layer unchanged; zeros treats each missing input as a zero update; error stops without replacing an existing output file."),
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io.String.Input("output_filename", default=default_filename, tooltip="Name of the new .safetensors file. It is saved in ComfyUI's loras folder; omit the extension."),
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io.Combo.Input("save_dtype", options=["fp32", "fp16", "bf16"], default="bf16", tooltip="Precision used to save the expanded full-weight difference tensors. FP32 is largest and most precise; FP16 is smallest; BF16 has wider numeric range than FP16."),
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io.Combo.Input("process_device", options=["cuda", "cpu"], default="cuda", tooltip="Where each full layer is expanded and merged. CUDA is faster; if a layer runs out of VRAM, that layer is automatically retried on CPU."),
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io.String.Input("exclude_patterns", default="", multiline=True, tooltip="Optional layer-name patterns to copy from LoRA 1 instead of merging. Enter one pattern per line; useful for protecting specific blocks."),
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io.String.Input("discard_patterns", default="", multiline=True, tooltip="Optional layer-name patterns to leave out of the saved LoRA completely. Enter one pattern per line; discarded layers cannot affect the model."),
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io.Boolean.Input("glob_patterns", default=False, tooltip="Choose filter syntax. Off uses regular expressions; on uses shell-style globs where * matches any text and ? matches one character."),
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]
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@@ -262,7 +262,8 @@ class LodestoneLoRATwoMerger(io.ComfyNode):
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options = folder_paths.get_filename_list("loras")
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return io.Schema(node_id="LodestoneLoRATwoMerger", display_name="Lodestone Merge LoRAs (2)",
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category="ModelUtils/LoRA/Merge/Lodestone",
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inputs=[io.Combo.Input("lora_1", options=options, tooltip="First equal-prior LoRA and anchor."), io.Combo.Input("lora_2", options=options, tooltip="Second equal-prior LoRA."), *_controls("lodestone_merged_2_lora")],
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description="Expand two LoRAs into full per-layer weight changes, combine them with the selected Frobenius-norm method, and save a full-difference LoRA.",
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inputs=[io.Combo.Input("lora_1", options=options, tooltip="First LoRA to merge. It also supplies metadata and is the layer kept when Missing Layer Handling is set to skip."), io.Combo.Input("lora_2", options=options, tooltip="Second LoRA to merge. It contributes equally with LoRA 1 wherever both contain the same layer."), *_controls("lodestone_merged_2_lora")],
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outputs=[io.AnyType.Output(display_name="output_filename")], is_output_node=True)
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@classmethod
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@@ -276,7 +277,8 @@ class LodestoneLoRAThreeMerger(io.ComfyNode):
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options = folder_paths.get_filename_list("loras")
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return io.Schema(node_id="LodestoneLoRAThreeMerger", display_name="Lodestone Merge LoRAs (3)",
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category="ModelUtils/LoRA/Merge/Lodestone",
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inputs=[io.Combo.Input("lora_1", options=options, tooltip="First equal-prior LoRA and anchor."), io.Combo.Input("lora_2", options=options, tooltip="Second equal-prior LoRA."), io.Combo.Input("lora_3", options=options, tooltip="Third equal-prior LoRA."), *_controls("lodestone_merged_3_lora")],
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description="Expand three LoRAs into full per-layer weight changes, combine them with the selected Frobenius-norm method, and save a full-difference LoRA.",
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inputs=[io.Combo.Input("lora_1", options=options, tooltip="First LoRA to merge. It supplies metadata, defines the output layer set, and is kept when Missing Layer Handling is skip."), io.Combo.Input("lora_2", options=options, tooltip="Second equal-strength LoRA contribution for every matching layer."), io.Combo.Input("lora_3", options=options, tooltip="Third equal-strength LoRA contribution for every matching layer."), *_controls("lodestone_merged_3_lora")],
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outputs=[io.AnyType.Output(display_name="output_filename")], is_output_node=True)
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@classmethod
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@@ -289,12 +291,12 @@ class LodestoneLoRAMultiMerger(io.ComfyNode):
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def define_schema(cls):
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options = folder_paths.get_filename_list("loras")
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optional = ["None", *options]
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inputs = [io.Combo.Input("lora_count", options=[str(index) for index in range(2, 9)], default="2", tooltip="Number of consecutive equal-prior LoRAs."),
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io.Combo.Input("lora_1", options=options, tooltip="First equal-prior LoRA and anchor."), io.Combo.Input("lora_2", options=options, tooltip="Second equal-prior LoRA.")]
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inputs.extend(io.Combo.Input(f"lora_{index}", options=optional, default="None", tooltip="Optional equal-prior LoRA used when included by LoRA Count.") for index in range(3, 9))
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inputs = [io.Combo.Input("lora_count", options=[str(index) for index in range(2, 9)], default="2", tooltip="Number of consecutive LoRA selectors to merge, starting at LoRA 1. Every included LoRA has equal influence before the selected normalization method."),
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io.Combo.Input("lora_1", options=options, tooltip="First LoRA to merge. It supplies metadata, defines the output layer set, and anchors missing-layer handling."), io.Combo.Input("lora_2", options=options, tooltip="Second equal-strength LoRA contribution. LoRA Count always includes this input.")]
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inputs.extend(io.Combo.Input(f"lora_{index}", options=optional, default="None", tooltip="Additional equal-strength LoRA contribution. Select a file for every input included by LoRA Count.") for index in range(3, 9))
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inputs.extend(_controls("lodestone_merged_multi_lora"))
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return io.Schema(node_id="LodestoneLoRAMultiMerger", display_name="Lodestone LoRA Multi-Merge",
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category="ModelUtils/LoRA/Merge/Lodestone", inputs=inputs,
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category="ModelUtils/LoRA/Merge/Lodestone", description="Expand 2-8 equal-strength LoRAs into full per-layer weight changes, combine them with Frobenius-norm-aware math, and save a full-difference LoRA.", inputs=inputs,
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outputs=[io.AnyType.Output(display_name="output_filename")], is_output_node=True)
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@classmethod
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