mirror of
https://github.com/comfyanonymous/ComfyUI.git
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69 lines
2.7 KiB
Python
69 lines
2.7 KiB
Python
from __future__ import annotations
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import comfy.utils
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from comfy_api.latest import io
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class PatchModelAddDownscale(io.ComfyNode):
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UPSCALE_METHODS = ["bicubic", "nearest-exact", "bilinear", "area", "bislerp"]
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@classmethod
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def define_schema(cls):
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return io.Schema(
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node_id="PatchModelAddDownscale_V3",
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display_name="PatchModelAddDownscale (Kohya Deep Shrink) _V3",
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category="model_patches/unet",
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inputs=[
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io.Model.Input("model"),
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io.Int.Input("block_number", default=3, min=1, max=32, step=1),
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io.Float.Input("downscale_factor", default=2.0, min=0.1, max=9.0, step=0.001),
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io.Float.Input("start_percent", default=0.0, min=0.0, max=1.0, step=0.001),
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io.Float.Input("end_percent", default=0.35, min=0.0, max=1.0, step=0.001),
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io.Boolean.Input("downscale_after_skip", default=True),
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io.Combo.Input("downscale_method", options=cls.UPSCALE_METHODS),
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io.Combo.Input("upscale_method", options=cls.UPSCALE_METHODS),
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],
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outputs=[
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io.Model.Output(),
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],
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)
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@classmethod
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def execute(
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cls, model, block_number, downscale_factor, start_percent, end_percent, downscale_after_skip, downscale_method, upscale_method
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):
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model_sampling = model.get_model_object("model_sampling")
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sigma_start = model_sampling.percent_to_sigma(start_percent)
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sigma_end = model_sampling.percent_to_sigma(end_percent)
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def input_block_patch(h, transformer_options):
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if transformer_options["block"][1] == block_number:
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sigma = transformer_options["sigmas"][0].item()
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if sigma <= sigma_start and sigma >= sigma_end:
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h = comfy.utils.common_upscale(
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h,
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round(h.shape[-1] * (1.0 / downscale_factor)),
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round(h.shape[-2] * (1.0 / downscale_factor)),
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downscale_method,
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"disabled",
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)
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return h
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def output_block_patch(h, hsp, transformer_options):
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if h.shape[2] != hsp.shape[2]:
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h = comfy.utils.common_upscale(h, hsp.shape[-1], hsp.shape[-2], upscale_method, "disabled")
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return h, hsp
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m = model.clone()
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if downscale_after_skip:
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m.set_model_input_block_patch_after_skip(input_block_patch)
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else:
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m.set_model_input_block_patch(input_block_patch)
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m.set_model_output_block_patch(output_block_patch)
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return io.NodeOutput(m)
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NODES_LIST = [
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PatchModelAddDownscale,
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]
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