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convert model_merging and video_model nodes to V3 schema

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bigcat88
2026-02-06 15:58:30 +02:00
parent a1c101f861
commit ac1073be99
3 changed files with 709 additions and 481 deletions
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comfy_extras/nodes_model_merging_model_specific.py
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@@ -1,356 +1,455 @@
import comfy_extras.nodes_model_merging
from comfy_api.latest import io, ComfyExtension
from typing_extensions import override
class ModelMergeSD1(comfy_extras.nodes_model_merging.ModelMergeBlocks):
CATEGORY = "advanced/model_merging/model_specific"
@classmethod
def INPUT_TYPES(s):
arg_dict = { "model1": ("MODEL",),
"model2": ("MODEL",)}
def define_schema(cls):
inputs = [
io.Model.Input("model1"),
io.Model.Input("model2"),
]
argument = ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01})
argument = dict(default=1.0, min=0.0, max=1.0, step=0.01)
arg_dict["time_embed."] = argument
arg_dict["label_emb."] = argument
inputs.append(io.Float.Input("time_embed.", **argument))
inputs.append(io.Float.Input("label_emb.", **argument))
for i in range(12):
arg_dict["input_blocks.{}.".format(i)] = argument
inputs.append(io.Float.Input("input_blocks.{}.".format(i), **argument))
for i in range(3):
arg_dict["middle_block.{}.".format(i)] = argument
inputs.append(io.Float.Input("middle_block.{}.".format(i), **argument))
for i in range(12):
arg_dict["output_blocks.{}.".format(i)] = argument
inputs.append(io.Float.Input("output_blocks.{}.".format(i), **argument))
arg_dict["out."] = argument
inputs.append(io.Float.Input("out.", **argument))
return {"required": arg_dict}
return io.Schema(
node_id="ModelMergeSD1",
category="advanced/model_merging/model_specific",
inputs=inputs,
outputs=[io.Model.Output()],
)
class ModelMergeSD2(ModelMergeSD1):
# SD1 and SD2 have the same blocks
@classmethod
def define_schema(cls):
schema = ModelMergeSD1.define_schema()
schema.node_id = "ModelMergeSD2"
return schema
class ModelMergeSDXL(comfy_extras.nodes_model_merging.ModelMergeBlocks):
CATEGORY = "advanced/model_merging/model_specific"
@classmethod
def INPUT_TYPES(s):
arg_dict = { "model1": ("MODEL",),
"model2": ("MODEL",)}
def define_schema(cls):
inputs = [
io.Model.Input("model1"),
io.Model.Input("model2"),
]
argument = ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01})
argument = dict(default=1.0, min=0.0, max=1.0, step=0.01)
arg_dict["time_embed."] = argument
arg_dict["label_emb."] = argument
inputs.append(io.Float.Input("time_embed.", **argument))
inputs.append(io.Float.Input("label_emb.", **argument))
for i in range(9):
arg_dict["input_blocks.{}".format(i)] = argument
inputs.append(io.Float.Input("input_blocks.{}".format(i), **argument))
for i in range(3):
arg_dict["middle_block.{}".format(i)] = argument
inputs.append(io.Float.Input("middle_block.{}".format(i), **argument))
for i in range(9):
arg_dict["output_blocks.{}".format(i)] = argument
inputs.append(io.Float.Input("output_blocks.{}".format(i), **argument))
arg_dict["out."] = argument
inputs.append(io.Float.Input("out.", **argument))
return io.Schema(
node_id="ModelMergeSDXL",
category="advanced/model_merging/model_specific",
inputs=inputs,
outputs=[io.Model.Output()],
)
return {"required": arg_dict}
class ModelMergeSD3_2B(comfy_extras.nodes_model_merging.ModelMergeBlocks):
CATEGORY = "advanced/model_merging/model_specific"
@classmethod
def INPUT_TYPES(s):
arg_dict = { "model1": ("MODEL",),
"model2": ("MODEL",)}
def define_schema(cls):
inputs = [
io.Model.Input("model1"),
io.Model.Input("model2"),
]
argument = ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01})
argument = dict(default=1.0, min=0.0, max=1.0, step=0.01)
arg_dict["pos_embed."] = argument
arg_dict["x_embedder."] = argument
arg_dict["context_embedder."] = argument
arg_dict["y_embedder."] = argument
arg_dict["t_embedder."] = argument
inputs.append(io.Float.Input("pos_embed.", **argument))
inputs.append(io.Float.Input("x_embedder.", **argument))
inputs.append(io.Float.Input("context_embedder.", **argument))
inputs.append(io.Float.Input("y_embedder.", **argument))
inputs.append(io.Float.Input("t_embedder.", **argument))
for i in range(24):
arg_dict["joint_blocks.{}.".format(i)] = argument
inputs.append(io.Float.Input("joint_blocks.{}.".format(i), **argument))
arg_dict["final_layer."] = argument
inputs.append(io.Float.Input("final_layer.", **argument))
return {"required": arg_dict}
return io.Schema(
node_id="ModelMergeSD3_2B",
category="advanced/model_merging/model_specific",
inputs=inputs,
outputs=[io.Model.Output()],
)
class ModelMergeAuraflow(comfy_extras.nodes_model_merging.ModelMergeBlocks):
CATEGORY = "advanced/model_merging/model_specific"
@classmethod
def INPUT_TYPES(s):
arg_dict = { "model1": ("MODEL",),
"model2": ("MODEL",)}
def define_schema(cls):
inputs = [
io.Model.Input("model1"),
io.Model.Input("model2"),
]
argument = ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01})
argument = dict(default=1.0, min=0.0, max=1.0, step=0.01)
arg_dict["init_x_linear."] = argument
arg_dict["positional_encoding"] = argument
arg_dict["cond_seq_linear."] = argument
arg_dict["register_tokens"] = argument
arg_dict["t_embedder."] = argument
inputs.append(io.Float.Input("init_x_linear.", **argument))
inputs.append(io.Float.Input("positional_encoding", **argument))
inputs.append(io.Float.Input("cond_seq_linear.", **argument))
inputs.append(io.Float.Input("register_tokens", **argument))
inputs.append(io.Float.Input("t_embedder.", **argument))
for i in range(4):
arg_dict["double_layers.{}.".format(i)] = argument
inputs.append(io.Float.Input("double_layers.{}.".format(i), **argument))
for i in range(32):
arg_dict["single_layers.{}.".format(i)] = argument
inputs.append(io.Float.Input("single_layers.{}.".format(i), **argument))
arg_dict["modF."] = argument
arg_dict["final_linear."] = argument
inputs.append(io.Float.Input("modF.", **argument))
inputs.append(io.Float.Input("final_linear.", **argument))
return io.Schema(
node_id="ModelMergeAuraflow",
category="advanced/model_merging/model_specific",
inputs=inputs,
outputs=[io.Model.Output()],
)
return {"required": arg_dict}
class ModelMergeFlux1(comfy_extras.nodes_model_merging.ModelMergeBlocks):
CATEGORY = "advanced/model_merging/model_specific"
@classmethod
def INPUT_TYPES(s):
arg_dict = { "model1": ("MODEL",),
"model2": ("MODEL",)}
def define_schema(cls):
inputs = [
io.Model.Input("model1"),
io.Model.Input("model2"),
]
argument = ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01})
argument = dict(default=1.0, min=0.0, max=1.0, step=0.01)
arg_dict["img_in."] = argument
arg_dict["time_in."] = argument
arg_dict["guidance_in"] = argument
arg_dict["vector_in."] = argument
arg_dict["txt_in."] = argument
inputs.append(io.Float.Input("img_in.", **argument))
inputs.append(io.Float.Input("time_in.", **argument))
inputs.append(io.Float.Input("guidance_in", **argument))
inputs.append(io.Float.Input("vector_in.", **argument))
inputs.append(io.Float.Input("txt_in.", **argument))
for i in range(19):
arg_dict["double_blocks.{}.".format(i)] = argument
inputs.append(io.Float.Input("double_blocks.{}.".format(i), **argument))
for i in range(38):
arg_dict["single_blocks.{}.".format(i)] = argument
inputs.append(io.Float.Input("single_blocks.{}.".format(i), **argument))
arg_dict["final_layer."] = argument
inputs.append(io.Float.Input("final_layer.", **argument))
return io.Schema(
node_id="ModelMergeFlux1",
category="advanced/model_merging/model_specific",
inputs=inputs,
outputs=[io.Model.Output()],
)
return {"required": arg_dict}
class ModelMergeSD35_Large(comfy_extras.nodes_model_merging.ModelMergeBlocks):
CATEGORY = "advanced/model_merging/model_specific"
@classmethod
def INPUT_TYPES(s):
arg_dict = { "model1": ("MODEL",),
"model2": ("MODEL",)}
def define_schema(cls):
inputs = [
io.Model.Input("model1"),
io.Model.Input("model2"),
]
argument = ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01})
argument = dict(default=1.0, min=0.0, max=1.0, step=0.01)
arg_dict["pos_embed."] = argument
arg_dict["x_embedder."] = argument
arg_dict["context_embedder."] = argument
arg_dict["y_embedder."] = argument
arg_dict["t_embedder."] = argument
inputs.append(io.Float.Input("pos_embed.", **argument))
inputs.append(io.Float.Input("x_embedder.", **argument))
inputs.append(io.Float.Input("context_embedder.", **argument))
inputs.append(io.Float.Input("y_embedder.", **argument))
inputs.append(io.Float.Input("t_embedder.", **argument))
for i in range(38):
arg_dict["joint_blocks.{}.".format(i)] = argument
inputs.append(io.Float.Input("joint_blocks.{}.".format(i), **argument))
arg_dict["final_layer."] = argument
inputs.append(io.Float.Input("final_layer.", **argument))
return io.Schema(
node_id="ModelMergeSD35_Large",
category="advanced/model_merging/model_specific",
inputs=inputs,
outputs=[io.Model.Output()],
)
return {"required": arg_dict}
class ModelMergeMochiPreview(comfy_extras.nodes_model_merging.ModelMergeBlocks):
CATEGORY = "advanced/model_merging/model_specific"
@classmethod
def INPUT_TYPES(s):
arg_dict = { "model1": ("MODEL",),
"model2": ("MODEL",)}
def define_schema(cls):
inputs = [
io.Model.Input("model1"),
io.Model.Input("model2"),
]
argument = ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01})
argument = dict(default=1.0, min=0.0, max=1.0, step=0.01)
arg_dict["pos_frequencies."] = argument
arg_dict["t_embedder."] = argument
arg_dict["t5_y_embedder."] = argument
arg_dict["t5_yproj."] = argument
inputs.append(io.Float.Input("pos_frequencies.", **argument))
inputs.append(io.Float.Input("t_embedder.", **argument))
inputs.append(io.Float.Input("t5_y_embedder.", **argument))
inputs.append(io.Float.Input("t5_yproj.", **argument))
for i in range(48):
arg_dict["blocks.{}.".format(i)] = argument
inputs.append(io.Float.Input("blocks.{}.".format(i), **argument))
arg_dict["final_layer."] = argument
inputs.append(io.Float.Input("final_layer.", **argument))
return io.Schema(
node_id="ModelMergeMochiPreview",
category="advanced/model_merging/model_specific",
inputs=inputs,
outputs=[io.Model.Output()],
)
return {"required": arg_dict}
class ModelMergeLTXV(comfy_extras.nodes_model_merging.ModelMergeBlocks):
CATEGORY = "advanced/model_merging/model_specific"
@classmethod
def INPUT_TYPES(s):
arg_dict = { "model1": ("MODEL",),
"model2": ("MODEL",)}
def define_schema(cls):
inputs = [
io.Model.Input("model1"),
io.Model.Input("model2"),
]
argument = ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01})
argument = dict(default=1.0, min=0.0, max=1.0, step=0.01)
arg_dict["patchify_proj."] = argument
arg_dict["adaln_single."] = argument
arg_dict["caption_projection."] = argument
inputs.append(io.Float.Input("patchify_proj.", **argument))
inputs.append(io.Float.Input("adaln_single.", **argument))
inputs.append(io.Float.Input("caption_projection.", **argument))
for i in range(28):
arg_dict["transformer_blocks.{}.".format(i)] = argument
inputs.append(io.Float.Input("transformer_blocks.{}.".format(i), **argument))
arg_dict["scale_shift_table"] = argument
arg_dict["proj_out."] = argument
inputs.append(io.Float.Input("scale_shift_table", **argument))
inputs.append(io.Float.Input("proj_out.", **argument))
return io.Schema(
node_id="ModelMergeLTXV",
category="advanced/model_merging/model_specific",
inputs=inputs,
outputs=[io.Model.Output()],
)
return {"required": arg_dict}
class ModelMergeCosmos7B(comfy_extras.nodes_model_merging.ModelMergeBlocks):
CATEGORY = "advanced/model_merging/model_specific"
@classmethod
def INPUT_TYPES(s):
arg_dict = { "model1": ("MODEL",),
"model2": ("MODEL",)}
def define_schema(cls):
inputs = [
io.Model.Input("model1"),
io.Model.Input("model2"),
]
argument = ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01})
arg_dict["pos_embedder."] = argument
arg_dict["extra_pos_embedder."] = argument
arg_dict["x_embedder."] = argument
arg_dict["t_embedder."] = argument
arg_dict["affline_norm."] = argument
argument = dict(default=1.0, min=0.0, max=1.0, step=0.01)
inputs.append(io.Float.Input("pos_embedder.", **argument))
inputs.append(io.Float.Input("extra_pos_embedder.", **argument))
inputs.append(io.Float.Input("x_embedder.", **argument))
inputs.append(io.Float.Input("t_embedder.", **argument))
inputs.append(io.Float.Input("affline_norm.", **argument))
for i in range(28):
arg_dict["blocks.block{}.".format(i)] = argument
inputs.append(io.Float.Input("blocks.block{}.".format(i), **argument))
arg_dict["final_layer."] = argument
inputs.append(io.Float.Input("final_layer.", **argument))
return io.Schema(
node_id="ModelMergeCosmos7B",
category="advanced/model_merging/model_specific",
inputs=inputs,
outputs=[io.Model.Output()],
)
return {"required": arg_dict}
class ModelMergeCosmos14B(comfy_extras.nodes_model_merging.ModelMergeBlocks):
CATEGORY = "advanced/model_merging/model_specific"
@classmethod
def INPUT_TYPES(s):
arg_dict = { "model1": ("MODEL",),
"model2": ("MODEL",)}
def define_schema(cls):
inputs = [
io.Model.Input("model1"),
io.Model.Input("model2"),
]
argument = ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01})
arg_dict["pos_embedder."] = argument
arg_dict["extra_pos_embedder."] = argument
arg_dict["x_embedder."] = argument
arg_dict["t_embedder."] = argument
arg_dict["affline_norm."] = argument
argument = dict(default=1.0, min=0.0, max=1.0, step=0.01)
inputs.append(io.Float.Input("pos_embedder.", **argument))
inputs.append(io.Float.Input("extra_pos_embedder.", **argument))
inputs.append(io.Float.Input("x_embedder.", **argument))
inputs.append(io.Float.Input("t_embedder.", **argument))
inputs.append(io.Float.Input("affline_norm.", **argument))
for i in range(36):
arg_dict["blocks.block{}.".format(i)] = argument
inputs.append(io.Float.Input("blocks.block{}.".format(i), **argument))
arg_dict["final_layer."] = argument
inputs.append(io.Float.Input("final_layer.", **argument))
return io.Schema(
node_id="ModelMergeCosmos14B",
category="advanced/model_merging/model_specific",
inputs=inputs,
outputs=[io.Model.Output()],
)
return {"required": arg_dict}
class ModelMergeWAN2_1(comfy_extras.nodes_model_merging.ModelMergeBlocks):
CATEGORY = "advanced/model_merging/model_specific"
DESCRIPTION = "1.3B model has 30 blocks, 14B model has 40 blocks. Image to video model has the extra img_emb."
@classmethod
def INPUT_TYPES(s):
arg_dict = { "model1": ("MODEL",),
"model2": ("MODEL",)}
def define_schema(cls):
inputs = [
io.Model.Input("model1"),
io.Model.Input("model2"),
]
argument = ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01})
argument = dict(default=1.0, min=0.0, max=1.0, step=0.01)
arg_dict["patch_embedding."] = argument
arg_dict["time_embedding."] = argument
arg_dict["time_projection."] = argument
arg_dict["text_embedding."] = argument
arg_dict["img_emb."] = argument
inputs.append(io.Float.Input("patch_embedding.", **argument))
inputs.append(io.Float.Input("time_embedding.", **argument))
inputs.append(io.Float.Input("time_projection.", **argument))
inputs.append(io.Float.Input("text_embedding.", **argument))
inputs.append(io.Float.Input("img_emb.", **argument))
for i in range(40):
arg_dict["blocks.{}.".format(i)] = argument
inputs.append(io.Float.Input("blocks.{}.".format(i), **argument))
arg_dict["head."] = argument
inputs.append(io.Float.Input("head.", **argument))
return io.Schema(
node_id="ModelMergeWAN2_1",
category="advanced/model_merging/model_specific",
description="1.3B model has 30 blocks, 14B model has 40 blocks. Image to video model has the extra img_emb.",
inputs=inputs,
outputs=[io.Model.Output()],
)
return {"required": arg_dict}
class ModelMergeCosmosPredict2_2B(comfy_extras.nodes_model_merging.ModelMergeBlocks):
CATEGORY = "advanced/model_merging/model_specific"
@classmethod
def INPUT_TYPES(s):
arg_dict = { "model1": ("MODEL",),
"model2": ("MODEL",)}
def define_schema(cls):
inputs = [
io.Model.Input("model1"),
io.Model.Input("model2"),
]
argument = ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01})
arg_dict["pos_embedder."] = argument
arg_dict["x_embedder."] = argument
arg_dict["t_embedder."] = argument
arg_dict["t_embedding_norm."] = argument
argument = dict(default=1.0, min=0.0, max=1.0, step=0.01)
inputs.append(io.Float.Input("pos_embedder.", **argument))
inputs.append(io.Float.Input("x_embedder.", **argument))
inputs.append(io.Float.Input("t_embedder.", **argument))
inputs.append(io.Float.Input("t_embedding_norm.", **argument))
for i in range(28):
arg_dict["blocks.{}.".format(i)] = argument
inputs.append(io.Float.Input("blocks.{}.".format(i), **argument))
arg_dict["final_layer."] = argument
inputs.append(io.Float.Input("final_layer.", **argument))
return io.Schema(
node_id="ModelMergeCosmosPredict2_2B",
category="advanced/model_merging/model_specific",
inputs=inputs,
outputs=[io.Model.Output()],
)
return {"required": arg_dict}
class ModelMergeCosmosPredict2_14B(comfy_extras.nodes_model_merging.ModelMergeBlocks):
CATEGORY = "advanced/model_merging/model_specific"
@classmethod
def INPUT_TYPES(s):
arg_dict = { "model1": ("MODEL",),
"model2": ("MODEL",)}
def define_schema(cls):
inputs = [
io.Model.Input("model1"),
io.Model.Input("model2"),
]
argument = ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01})
arg_dict["pos_embedder."] = argument
arg_dict["x_embedder."] = argument
arg_dict["t_embedder."] = argument
arg_dict["t_embedding_norm."] = argument
argument = dict(default=1.0, min=0.0, max=1.0, step=0.01)
inputs.append(io.Float.Input("pos_embedder.", **argument))
inputs.append(io.Float.Input("x_embedder.", **argument))
inputs.append(io.Float.Input("t_embedder.", **argument))
inputs.append(io.Float.Input("t_embedding_norm.", **argument))
for i in range(36):
arg_dict["blocks.{}.".format(i)] = argument
inputs.append(io.Float.Input("blocks.{}.".format(i), **argument))
arg_dict["final_layer."] = argument
inputs.append(io.Float.Input("final_layer.", **argument))
return io.Schema(
node_id="ModelMergeCosmosPredict2_14B",
category="advanced/model_merging/model_specific",
inputs=inputs,
outputs=[io.Model.Output()],
)
return {"required": arg_dict}
class ModelMergeQwenImage(comfy_extras.nodes_model_merging.ModelMergeBlocks):
CATEGORY = "advanced/model_merging/model_specific"
@classmethod
def INPUT_TYPES(s):
arg_dict = { "model1": ("MODEL",),
"model2": ("MODEL",)}
def define_schema(cls):
inputs = [
io.Model.Input("model1"),
io.Model.Input("model2"),
]
argument = ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01})
argument = dict(default=1.0, min=0.0, max=1.0, step=0.01)
arg_dict["pos_embeds."] = argument
arg_dict["img_in."] = argument
arg_dict["txt_norm."] = argument
arg_dict["txt_in."] = argument
arg_dict["time_text_embed."] = argument
inputs.append(io.Float.Input("pos_embeds.", **argument))
inputs.append(io.Float.Input("img_in.", **argument))
inputs.append(io.Float.Input("txt_norm.", **argument))
inputs.append(io.Float.Input("txt_in.", **argument))
inputs.append(io.Float.Input("time_text_embed.", **argument))
for i in range(60):
arg_dict["transformer_blocks.{}.".format(i)] = argument
inputs.append(io.Float.Input("transformer_blocks.{}.".format(i), **argument))
arg_dict["proj_out."] = argument
inputs.append(io.Float.Input("proj_out.", **argument))
return {"required": arg_dict}
return io.Schema(
node_id="ModelMergeQwenImage",
category="advanced/model_merging/model_specific",
inputs=inputs,
outputs=[io.Model.Output()],
)
NODE_CLASS_MAPPINGS = {
"ModelMergeSD1": ModelMergeSD1,
"ModelMergeSD2": ModelMergeSD1, #SD1 and SD2 have the same blocks
"ModelMergeSDXL": ModelMergeSDXL,
"ModelMergeSD3_2B": ModelMergeSD3_2B,
"ModelMergeAuraflow": ModelMergeAuraflow,
"ModelMergeFlux1": ModelMergeFlux1,
"ModelMergeSD35_Large": ModelMergeSD35_Large,
"ModelMergeMochiPreview": ModelMergeMochiPreview,
"ModelMergeLTXV": ModelMergeLTXV,
"ModelMergeCosmos7B": ModelMergeCosmos7B,
"ModelMergeCosmos14B": ModelMergeCosmos14B,
"ModelMergeWAN2_1": ModelMergeWAN2_1,
"ModelMergeCosmosPredict2_2B": ModelMergeCosmosPredict2_2B,
"ModelMergeCosmosPredict2_14B": ModelMergeCosmosPredict2_14B,
"ModelMergeQwenImage": ModelMergeQwenImage,
}
class ModelMergingModelSpecificExtension(ComfyExtension):
@override
async def get_node_list(self) -> list[type[io.ComfyNode]]:
return [
ModelMergeSD1,
ModelMergeSD2,
ModelMergeSDXL,
ModelMergeSD3_2B,
ModelMergeAuraflow,
ModelMergeFlux1,
ModelMergeSD35_Large,
ModelMergeMochiPreview,
ModelMergeLTXV,
ModelMergeCosmos7B,
ModelMergeCosmos14B,
ModelMergeWAN2_1,
ModelMergeCosmosPredict2_2B,
ModelMergeCosmosPredict2_14B,
ModelMergeQwenImage,
]
async def comfy_entrypoint() -> ModelMergingModelSpecificExtension:
return ModelMergingModelSpecificExtension()