mirror of
https://github.com/comfyanonymous/ComfyUI.git
synced 2026-02-03 02:00:29 +08:00
ae20354b69
Mark widgets as advanced across core, comfy_extras, and comfy_api_nodes to support the new collapsible advanced inputs section in the frontend. Changes: - 267 advanced markers in comfy_extras/ - 162 advanced markers in comfy_api_nodes/ - All files pass python3 -m py_compile verification Widgets marked advanced (hidden by default): - Scheduler internals: sigma_max, sigma_min, rho, mu, beta, alpha - Sampler internals: eta, s_noise, order, rtol, atol, h_init, pcoeff, etc. - Memory optimization: tile_size, overlap, temporal_size, temporal_overlap - Pipeline controls: add_noise, start_at_step, end_at_step - Timing controls: start_percent, end_percent - Layer selection: stop_at_clip_layer, layers, block_number - Video encoding: codec, crf, format - Device/dtype: device, noise_device, dtype, weight_dtype Widgets kept basic (always visible): - Core params: strength, steps, cfg, denoise, seed, width, height - Model selectors: ckpt_name, lora_name, vae_name, sampler_name - Common controls: upscale_method, crop, batch_size, fps, opacity Related: frontend PR #11939 Amp-Thread-ID: https://ampcode.com/threads/T-019c1734-6b61-702e-b333-f02c399963fc
66 lines
2.9 KiB
Python
66 lines
2.9 KiB
Python
from typing_extensions import override
|
|
import comfy.utils
|
|
from comfy_api.latest import ComfyExtension, io
|
|
|
|
|
|
class PatchModelAddDownscale(io.ComfyNode):
|
|
UPSCALE_METHODS = ["bicubic", "nearest-exact", "bilinear", "area", "bislerp"]
|
|
@classmethod
|
|
def define_schema(cls):
|
|
return io.Schema(
|
|
node_id="PatchModelAddDownscale",
|
|
display_name="PatchModelAddDownscale (Kohya Deep Shrink)",
|
|
category="model_patches/unet",
|
|
inputs=[
|
|
io.Model.Input("model"),
|
|
io.Int.Input("block_number", default=3, min=1, max=32, step=1, advanced=True),
|
|
io.Float.Input("downscale_factor", default=2.0, min=0.1, max=9.0, step=0.001),
|
|
io.Float.Input("start_percent", default=0.0, min=0.0, max=1.0, step=0.001, advanced=True),
|
|
io.Float.Input("end_percent", default=0.35, min=0.0, max=1.0, step=0.001, advanced=True),
|
|
io.Boolean.Input("downscale_after_skip", default=True, advanced=True),
|
|
io.Combo.Input("downscale_method", options=cls.UPSCALE_METHODS),
|
|
io.Combo.Input("upscale_method", options=cls.UPSCALE_METHODS),
|
|
],
|
|
outputs=[
|
|
io.Model.Output(),
|
|
],
|
|
)
|
|
|
|
@classmethod
|
|
def execute(cls, model, block_number, downscale_factor, start_percent, end_percent, downscale_after_skip, downscale_method, upscale_method) -> io.NodeOutput:
|
|
model_sampling = model.get_model_object("model_sampling")
|
|
sigma_start = model_sampling.percent_to_sigma(start_percent)
|
|
sigma_end = model_sampling.percent_to_sigma(end_percent)
|
|
|
|
def input_block_patch(h, transformer_options):
|
|
if transformer_options["block"][1] == block_number:
|
|
sigma = transformer_options["sigmas"][0].item()
|
|
if sigma <= sigma_start and sigma >= sigma_end:
|
|
h = comfy.utils.common_upscale(h, round(h.shape[-1] * (1.0 / downscale_factor)), round(h.shape[-2] * (1.0 / downscale_factor)), downscale_method, "disabled")
|
|
return h
|
|
|
|
def output_block_patch(h, hsp, transformer_options):
|
|
if h.shape[2] != hsp.shape[2]:
|
|
h = comfy.utils.common_upscale(h, hsp.shape[-1], hsp.shape[-2], upscale_method, "disabled")
|
|
return h, hsp
|
|
|
|
m = model.clone()
|
|
if downscale_after_skip:
|
|
m.set_model_input_block_patch_after_skip(input_block_patch)
|
|
else:
|
|
m.set_model_input_block_patch(input_block_patch)
|
|
m.set_model_output_block_patch(output_block_patch)
|
|
return io.NodeOutput(m)
|
|
|
|
|
|
class ModelDownscaleExtension(ComfyExtension):
|
|
@override
|
|
async def get_node_list(self) -> list[type[io.ComfyNode]]:
|
|
return [
|
|
PatchModelAddDownscale,
|
|
]
|
|
|
|
|
|
async def comfy_entrypoint() -> ModelDownscaleExtension:
|
|
return ModelDownscaleExtension()
|