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698abf5481 convert nodes_lt_upsampler nodes to V3 schema 2026-02-12 15:47:20 +02:00
14 changed files with 53 additions and 348 deletions

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@ -227,7 +227,7 @@ Put your VAE in: models/vae
AMD users can install rocm and pytorch with pip if you don't have it already installed, this is the command to install the stable version:
```pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/rocm7.1```
```pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/rocm6.4```
This is the command to install the nightly with ROCm 7.1 which might have some performance improvements:

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@ -1,105 +0,0 @@
from __future__ import annotations
from aiohttp import web
from typing import TYPE_CHECKING, TypedDict
if TYPE_CHECKING:
from comfy_api.latest._node_replace import NodeReplace
from nodes import NODE_CLASS_MAPPINGS
class NodeStruct(TypedDict):
inputs: dict[str, str | int | float | bool | tuple[str, int]]
class_type: str
_meta: dict[str, str]
def copy_node_struct(node_struct: NodeStruct, empty_inputs: bool = False) -> NodeStruct:
new_node_struct = node_struct.copy()
if empty_inputs:
new_node_struct["inputs"] = {}
else:
new_node_struct["inputs"] = node_struct["inputs"].copy()
new_node_struct["_meta"] = node_struct["_meta"].copy()
return new_node_struct
class NodeReplaceManager:
"""Manages node replacement registrations."""
def __init__(self):
self._replacements: dict[str, list[NodeReplace]] = {}
def register(self, node_replace: NodeReplace):
"""Register a node replacement mapping."""
self._replacements.setdefault(node_replace.old_node_id, []).append(node_replace)
def get_replacement(self, old_node_id: str) -> list[NodeReplace] | None:
"""Get replacements for an old node ID."""
return self._replacements.get(old_node_id)
def has_replacement(self, old_node_id: str) -> bool:
"""Check if a replacement exists for an old node ID."""
return old_node_id in self._replacements
def apply_replacements(self, prompt: dict[str, NodeStruct]):
connections: dict[str, list[tuple[str, str, int]]] = {}
need_replacement: set[str] = set()
for node_number, node_struct in prompt.items():
class_type = node_struct["class_type"]
# need replacement if not in NODE_CLASS_MAPPINGS and has replacement
if class_type not in NODE_CLASS_MAPPINGS.keys() and self.has_replacement(class_type):
need_replacement.add(node_number)
# keep track of connections
for input_id, input_value in node_struct["inputs"].items():
if isinstance(input_value, list):
conn_number = input_value[0]
connections.setdefault(conn_number, []).append((node_number, input_id, input_value[1]))
if len(need_replacement) > 0:
for node_number in need_replacement:
node_struct = prompt[node_number]
class_type = node_struct["class_type"]
replacements = self.get_replacement(class_type)
if replacements is None:
continue
# just use the first replacement
replacement = replacements[0]
new_node_id = replacement.new_node_id
# if replacement is not a valid node, skip trying to replace it as will only cause confusion
if new_node_id not in NODE_CLASS_MAPPINGS.keys():
continue
# first, replace node id (class_type)
new_node_struct = copy_node_struct(node_struct, empty_inputs=True)
new_node_struct["class_type"] = new_node_id
# TODO: consider replacing display_name in _meta as well for error reporting purposes; would need to query node schema
# second, replace inputs
if replacement.input_mapping is not None:
for input_map in replacement.input_mapping:
if "set_value" in input_map:
new_node_struct["inputs"][input_map["new_id"]] = input_map["set_value"]
elif "old_id" in input_map:
new_node_struct["inputs"][input_map["new_id"]] = node_struct["inputs"][input_map["old_id"]]
# finalize input replacement
prompt[node_number] = new_node_struct
# third, replace outputs
if replacement.output_mapping is not None:
# re-mapping outputs requires changing the input values of nodes that receive connections from this one
if node_number in connections:
for conns in connections[node_number]:
conn_node_number, conn_input_id, old_output_idx = conns
for output_map in replacement.output_mapping:
if output_map["old_idx"] == old_output_idx:
new_output_idx = output_map["new_idx"]
previous_input = prompt[conn_node_number]["inputs"][conn_input_id]
previous_input[1] = new_output_idx
def as_dict(self):
"""Serialize all replacements to dict."""
return {
k: [v.as_dict() for v in v_list]
for k, v_list in self._replacements.items()
}
def add_routes(self, routes):
@routes.get("/node_replacements")
async def get_node_replacements(request):
return web.json_response(self.as_dict())

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@ -679,19 +679,18 @@ class ModelPatcher:
for key in list(self.pinned):
self.unpin_weight(key)
def _load_list(self, prio_comfy_cast_weights=False, default_device=None):
def _load_list(self, prio_comfy_cast_weights=False):
loading = []
for n, m in self.model.named_modules():
default = False
params = { name: param for name, param in m.named_parameters(recurse=False) }
params = []
skip = False
for name, param in m.named_parameters(recurse=False):
params.append(name)
for name, param in m.named_parameters(recurse=True):
if name not in params:
default = True # default random weights in non leaf modules
skip = True # skip random weights in non leaf modules
break
if default and default_device is not None:
for param in params.values():
param.data = param.data.to(device=default_device)
if not default and (hasattr(m, "comfy_cast_weights") or len(params) > 0):
if not skip and (hasattr(m, "comfy_cast_weights") or len(params) > 0):
module_mem = comfy.model_management.module_size(m)
module_offload_mem = module_mem
if hasattr(m, "comfy_cast_weights"):
@ -1496,7 +1495,7 @@ class ModelPatcherDynamic(ModelPatcher):
#with pin and unpin syncrhonization which can be expensive for small weights
#with a high layer rate (e.g. autoregressive LLMs).
#prioritize the non-comfy weights (note the order reverse).
loading = self._load_list(prio_comfy_cast_weights=True, default_device=device_to)
loading = self._load_list(prio_comfy_cast_weights=True)
loading.sort(reverse=True)
for x in loading:
@ -1580,7 +1579,7 @@ class ModelPatcherDynamic(ModelPatcher):
return 0 if vbar is None else vbar.free_memory(memory_to_free)
def partially_unload_ram(self, ram_to_unload):
loading = self._load_list(prio_comfy_cast_weights=True, default_device=self.offload_device)
loading = self._load_list(prio_comfy_cast_weights=True)
for x in loading:
_, _, _, _, m, _ = x
ram_to_unload -= comfy.pinned_memory.unpin_memory(m)

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@ -355,6 +355,13 @@ class RMSNorm(nn.Module):
def rotate_half(x):
"""Rotates half the hidden dims of the input."""
x1 = x[..., : x.shape[-1] // 2]
x2 = x[..., x.shape[-1] // 2 :]
return torch.cat((-x2, x1), dim=-1)
def precompute_freqs_cis(head_dim, position_ids, theta, rope_scale=None, rope_dims=None, device=None):
if not isinstance(theta, list):
theta = [theta]
@ -383,30 +390,20 @@ def precompute_freqs_cis(head_dim, position_ids, theta, rope_scale=None, rope_di
else:
cos = cos.unsqueeze(1)
sin = sin.unsqueeze(1)
sin_split = sin.shape[-1] // 2
out.append((cos, sin[..., : sin_split], -sin[..., sin_split :]))
out.append((cos, sin))
if len(out) == 1:
return out[0]
return out
def apply_rope(xq, xk, freqs_cis):
org_dtype = xq.dtype
cos = freqs_cis[0]
sin = freqs_cis[1]
nsin = freqs_cis[2]
q_embed = (xq * cos)
q_split = q_embed.shape[-1] // 2
q_embed[..., : q_split].addcmul_(xq[..., q_split :], nsin)
q_embed[..., q_split :].addcmul_(xq[..., : q_split], sin)
k_embed = (xk * cos)
k_split = k_embed.shape[-1] // 2
k_embed[..., : k_split].addcmul_(xk[..., k_split :], nsin)
k_embed[..., k_split :].addcmul_(xk[..., : k_split], sin)
q_embed = (xq * cos) + (rotate_half(xq) * sin)
k_embed = (xk * cos) + (rotate_half(xk) * sin)
return q_embed.to(org_dtype), k_embed.to(org_dtype)

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@ -14,7 +14,6 @@ SERVER_FEATURE_FLAGS: dict[str, Any] = {
"supports_preview_metadata": True,
"max_upload_size": args.max_upload_size * 1024 * 1024, # Convert MB to bytes
"extension": {"manager": {"supports_v4": True}},
"node_replacements": True,
}

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@ -10,7 +10,6 @@ from ._input_impl import VideoFromFile, VideoFromComponents
from ._util import VideoCodec, VideoContainer, VideoComponents, MESH, VOXEL, File3D
from . import _io_public as io
from . import _ui_public as ui
from . import _node_replace_public as node_replace
from comfy_execution.utils import get_executing_context
from comfy_execution.progress import get_progress_state, PreviewImageTuple
from PIL import Image
@ -22,14 +21,6 @@ class ComfyAPI_latest(ComfyAPIBase):
VERSION = "latest"
STABLE = False
class NodeReplacement(ProxiedSingleton):
async def register(self, node_replace: 'node_replace.NodeReplace') -> None:
"""Register a node replacement mapping."""
from server import PromptServer
PromptServer.instance.node_replace_manager.register(node_replace)
node_replacement: NodeReplacement
class Execution(ProxiedSingleton):
async def set_progress(
self,
@ -140,5 +131,4 @@ __all__ = [
"IO",
"ui",
"UI",
"node_replace",
]

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@ -1,69 +0,0 @@
from __future__ import annotations
from typing import Any, TypedDict
class InputMapOldId(TypedDict):
"""Map an old node input to a new node input by ID."""
new_id: str
old_id: str
class InputMapSetValue(TypedDict):
"""Set a specific value for a new node input."""
new_id: str
set_value: Any
InputMap = InputMapOldId | InputMapSetValue
"""
Input mapping for node replacement. Type is inferred by dictionary keys:
- {"new_id": str, "old_id": str} - maps old input to new input
- {"new_id": str, "set_value": Any} - sets a specific value for new input
"""
class OutputMap(TypedDict):
"""Map outputs of node replacement via indexes."""
new_idx: int
old_idx: int
class NodeReplace:
"""
Defines a possible node replacement, mapping inputs and outputs of the old node to the new node.
Also supports assigning specific values to the input widgets of the new node.
Args:
new_node_id: The class name of the new replacement node.
old_node_id: The class name of the deprecated node.
old_widget_ids: Ordered list of input IDs for widgets that may not have an input slot
connected. The workflow JSON stores widget values by their relative position index,
not by ID. This list maps those positional indexes to input IDs, enabling the
replacement system to correctly identify widget values during node migration.
input_mapping: List of input mappings from old node to new node.
output_mapping: List of output mappings from old node to new node.
"""
def __init__(self,
new_node_id: str,
old_node_id: str,
old_widget_ids: list[str] | None=None,
input_mapping: list[InputMap] | None=None,
output_mapping: list[OutputMap] | None=None,
):
self.new_node_id = new_node_id
self.old_node_id = old_node_id
self.old_widget_ids = old_widget_ids
self.input_mapping = input_mapping
self.output_mapping = output_mapping
def as_dict(self):
"""Create serializable representation of the node replacement."""
return {
"new_node_id": self.new_node_id,
"old_node_id": self.old_node_id,
"old_widget_ids": self.old_widget_ids,
"input_mapping": list(self.input_mapping) if self.input_mapping else None,
"output_mapping": list(self.output_mapping) if self.output_mapping else None,
}

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@ -1 +0,0 @@
from ._node_replace import * # noqa: F403

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@ -6,7 +6,7 @@ from comfy_api.latest import (
)
from typing import Type, TYPE_CHECKING
from comfy_api.internal.async_to_sync import create_sync_class
from comfy_api.latest import io, ui, IO, UI, ComfyExtension, node_replace #noqa: F401
from comfy_api.latest import io, ui, IO, UI, ComfyExtension #noqa: F401
class ComfyAPIAdapter_v0_0_2(ComfyAPI_latest):
@ -46,5 +46,4 @@ __all__ = [
"IO",
"ui",
"UI",
"node_replace",
]

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@ -1,32 +1,32 @@
from comfy import model_management
from comfy_api.latest import ComfyExtension, IO
from typing_extensions import override
import math
class LTXVLatentUpsampler:
class LTXVLatentUpsampler(IO.ComfyNode):
"""
Upsamples a video latent by a factor of 2.
"""
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"samples": ("LATENT",),
"upscale_model": ("LATENT_UPSCALE_MODEL",),
"vae": ("VAE",),
}
}
def define_schema(cls):
return IO.Schema(
node_id="LTXVLatentUpsampler",
category="latent/video",
is_experimental=True,
inputs=[
IO.Latent.Input("samples"),
IO.LatentUpscaleModel.Input("upscale_model"),
IO.Vae.Input("vae"),
],
outputs=[
IO.Latent.Output(),
],
)
RETURN_TYPES = ("LATENT",)
FUNCTION = "upsample_latent"
CATEGORY = "latent/video"
EXPERIMENTAL = True
def upsample_latent(
self,
samples: dict,
upscale_model,
vae,
) -> tuple:
@classmethod
def execute(cls, samples, upscale_model, vae) -> IO.NodeOutput:
"""
Upsample the input latent using the provided model.
@ -34,7 +34,6 @@ class LTXVLatentUpsampler:
samples (dict): Input latent samples
upscale_model (LatentUpsampler): Loaded upscale model
vae: VAE model for normalization
auto_tiling (bool): Whether to automatically tile the input for processing
Returns:
tuple: Tuple containing the upsampled latent
@ -67,9 +66,16 @@ class LTXVLatentUpsampler:
return_dict = samples.copy()
return_dict["samples"] = upsampled_latents
return_dict.pop("noise_mask", None)
return (return_dict,)
return IO.NodeOutput(return_dict)
upsample_latent = execute # TODO: remove
NODE_CLASS_MAPPINGS = {
"LTXVLatentUpsampler": LTXVLatentUpsampler,
}
class LTXVLatentUpsamplerExtension(ComfyExtension):
@override
async def get_node_list(self) -> list[type[IO.ComfyNode]]:
return [LTXVLatentUpsampler]
async def comfy_entrypoint() -> LTXVLatentUpsamplerExtension:
return LTXVLatentUpsamplerExtension()

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@ -655,7 +655,6 @@ class BatchImagesMasksLatentsNode(io.ComfyNode):
batched = batch_masks(values)
return io.NodeOutput(batched)
class PostProcessingExtension(ComfyExtension):
@override
async def get_node_list(self) -> list[type[io.ComfyNode]]:

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@ -1,103 +0,0 @@
from comfy_api.latest import ComfyExtension, io, node_replace
from server import PromptServer
def _register(nr: node_replace.NodeReplace):
"""Helper to register replacements via PromptServer."""
PromptServer.instance.node_replace_manager.register(nr)
async def register_replacements():
"""Register all built-in node replacements."""
register_replacements_longeredge()
register_replacements_batchimages()
register_replacements_upscaleimage()
register_replacements_controlnet()
register_replacements_load3d()
register_replacements_preview3d()
register_replacements_svdimg2vid()
register_replacements_conditioningavg()
def register_replacements_longeredge():
# No dynamic inputs here
_register(node_replace.NodeReplace(
new_node_id="ImageScaleToMaxDimension",
old_node_id="ResizeImagesByLongerEdge",
old_widget_ids=["longer_edge"],
input_mapping=[
{"new_id": "image", "old_id": "images"},
{"new_id": "largest_size", "old_id": "longer_edge"},
{"new_id": "upscale_method", "set_value": "lanczos"},
],
# just to test the frontend output_mapping code, does nothing really here
output_mapping=[{"new_idx": 0, "old_idx": 0}],
))
def register_replacements_batchimages():
# BatchImages node uses Autogrow
_register(node_replace.NodeReplace(
new_node_id="BatchImagesNode",
old_node_id="ImageBatch",
input_mapping=[
{"new_id": "images.image0", "old_id": "image1"},
{"new_id": "images.image1", "old_id": "image2"},
],
))
def register_replacements_upscaleimage():
# ResizeImageMaskNode uses DynamicCombo
_register(node_replace.NodeReplace(
new_node_id="ResizeImageMaskNode",
old_node_id="ImageScaleBy",
old_widget_ids=["upscale_method", "scale_by"],
input_mapping=[
{"new_id": "input", "old_id": "image"},
{"new_id": "resize_type", "set_value": "scale by multiplier"},
{"new_id": "resize_type.multiplier", "old_id": "scale_by"},
{"new_id": "scale_method", "old_id": "upscale_method"},
],
))
def register_replacements_controlnet():
# T2IAdapterLoader → ControlNetLoader
_register(node_replace.NodeReplace(
new_node_id="ControlNetLoader",
old_node_id="T2IAdapterLoader",
input_mapping=[
{"new_id": "control_net_name", "old_id": "t2i_adapter_name"},
],
))
def register_replacements_load3d():
# Load3DAnimation merged into Load3D
_register(node_replace.NodeReplace(
new_node_id="Load3D",
old_node_id="Load3DAnimation",
))
def register_replacements_preview3d():
# Preview3DAnimation merged into Preview3D
_register(node_replace.NodeReplace(
new_node_id="Preview3D",
old_node_id="Preview3DAnimation",
))
def register_replacements_svdimg2vid():
# Typo fix: SDV → SVD
_register(node_replace.NodeReplace(
new_node_id="SVD_img2vid_Conditioning",
old_node_id="SDV_img2vid_Conditioning",
))
def register_replacements_conditioningavg():
# Typo fix: trailing space in node name
_register(node_replace.NodeReplace(
new_node_id="ConditioningAverage",
old_node_id="ConditioningAverage ",
))
class NodeReplacementsExtension(ComfyExtension):
async def get_node_list(self) -> list[type[io.ComfyNode]]:
return []
async def comfy_entrypoint() -> NodeReplacementsExtension:
await register_replacements()
return NodeReplacementsExtension()

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@ -2435,7 +2435,6 @@ async def init_builtin_extra_nodes():
"nodes_lora_debug.py",
"nodes_color.py",
"nodes_toolkit.py",
"nodes_replacements.py",
]
import_failed = []

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@ -40,7 +40,6 @@ from app.user_manager import UserManager
from app.model_manager import ModelFileManager
from app.custom_node_manager import CustomNodeManager
from app.subgraph_manager import SubgraphManager
from app.node_replace_manager import NodeReplaceManager
from typing import Optional, Union
from api_server.routes.internal.internal_routes import InternalRoutes
from protocol import BinaryEventTypes
@ -205,7 +204,6 @@ class PromptServer():
self.model_file_manager = ModelFileManager()
self.custom_node_manager = CustomNodeManager()
self.subgraph_manager = SubgraphManager()
self.node_replace_manager = NodeReplaceManager()
self.internal_routes = InternalRoutes(self)
self.supports = ["custom_nodes_from_web"]
self.prompt_queue = execution.PromptQueue(self)
@ -889,8 +887,6 @@ class PromptServer():
if "partial_execution_targets" in json_data:
partial_execution_targets = json_data["partial_execution_targets"]
self.node_replace_manager.apply_replacements(prompt)
valid = await execution.validate_prompt(prompt_id, prompt, partial_execution_targets)
extra_data = {}
if "extra_data" in json_data:
@ -999,7 +995,6 @@ class PromptServer():
self.model_file_manager.add_routes(self.routes)
self.custom_node_manager.add_routes(self.routes, self.app, nodes.LOADED_MODULE_DIRS.items())
self.subgraph_manager.add_routes(self.routes, nodes.LOADED_MODULE_DIRS.items())
self.node_replace_manager.add_routes(self.routes)
self.app.add_subapp('/internal', self.internal_routes.get_app())
# Prefix every route with /api for easier matching for delegation.