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lllyasviel
@@ -1,351 +0,0 @@
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"""
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Hypertile module for splitting attention layers in SD-1.5 U-Net and SD-1.5 VAE
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Warn: The patch works well only if the input image has a width and height that are multiples of 128
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Original author: @tfernd Github: https://github.com/tfernd/HyperTile
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"""
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from __future__ import annotations
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from dataclasses import dataclass
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from typing import Callable
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from functools import wraps, cache
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import math
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import torch.nn as nn
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import random
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from einops import rearrange
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@dataclass
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class HypertileParams:
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depth = 0
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layer_name = ""
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tile_size: int = 0
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swap_size: int = 0
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aspect_ratio: float = 1.0
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forward = None
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enabled = False
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# TODO add SD-XL layers
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DEPTH_LAYERS = {
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0: [
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# SD 1.5 U-Net (diffusers)
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"down_blocks.0.attentions.0.transformer_blocks.0.attn1",
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"down_blocks.0.attentions.1.transformer_blocks.0.attn1",
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"up_blocks.3.attentions.0.transformer_blocks.0.attn1",
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"up_blocks.3.attentions.1.transformer_blocks.0.attn1",
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"up_blocks.3.attentions.2.transformer_blocks.0.attn1",
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# SD 1.5 U-Net (ldm)
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"input_blocks.1.1.transformer_blocks.0.attn1",
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"input_blocks.2.1.transformer_blocks.0.attn1",
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"output_blocks.9.1.transformer_blocks.0.attn1",
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"output_blocks.10.1.transformer_blocks.0.attn1",
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"output_blocks.11.1.transformer_blocks.0.attn1",
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# SD 1.5 VAE
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"decoder.mid_block.attentions.0",
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"decoder.mid.attn_1",
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],
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1: [
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# SD 1.5 U-Net (diffusers)
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"down_blocks.1.attentions.0.transformer_blocks.0.attn1",
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"down_blocks.1.attentions.1.transformer_blocks.0.attn1",
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"up_blocks.2.attentions.0.transformer_blocks.0.attn1",
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"up_blocks.2.attentions.1.transformer_blocks.0.attn1",
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"up_blocks.2.attentions.2.transformer_blocks.0.attn1",
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# SD 1.5 U-Net (ldm)
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"input_blocks.4.1.transformer_blocks.0.attn1",
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"input_blocks.5.1.transformer_blocks.0.attn1",
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"output_blocks.6.1.transformer_blocks.0.attn1",
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"output_blocks.7.1.transformer_blocks.0.attn1",
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"output_blocks.8.1.transformer_blocks.0.attn1",
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],
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2: [
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# SD 1.5 U-Net (diffusers)
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"down_blocks.2.attentions.0.transformer_blocks.0.attn1",
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"down_blocks.2.attentions.1.transformer_blocks.0.attn1",
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"up_blocks.1.attentions.0.transformer_blocks.0.attn1",
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"up_blocks.1.attentions.1.transformer_blocks.0.attn1",
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"up_blocks.1.attentions.2.transformer_blocks.0.attn1",
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# SD 1.5 U-Net (ldm)
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"input_blocks.7.1.transformer_blocks.0.attn1",
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"input_blocks.8.1.transformer_blocks.0.attn1",
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"output_blocks.3.1.transformer_blocks.0.attn1",
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"output_blocks.4.1.transformer_blocks.0.attn1",
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"output_blocks.5.1.transformer_blocks.0.attn1",
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],
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3: [
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# SD 1.5 U-Net (diffusers)
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"mid_block.attentions.0.transformer_blocks.0.attn1",
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# SD 1.5 U-Net (ldm)
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"middle_block.1.transformer_blocks.0.attn1",
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],
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}
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# XL layers, thanks for GitHub@gel-crabs for the help
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DEPTH_LAYERS_XL = {
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0: [
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# SD 1.5 U-Net (diffusers)
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"down_blocks.0.attentions.0.transformer_blocks.0.attn1",
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"down_blocks.0.attentions.1.transformer_blocks.0.attn1",
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"up_blocks.3.attentions.0.transformer_blocks.0.attn1",
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"up_blocks.3.attentions.1.transformer_blocks.0.attn1",
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"up_blocks.3.attentions.2.transformer_blocks.0.attn1",
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# SD 1.5 U-Net (ldm)
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"input_blocks.4.1.transformer_blocks.0.attn1",
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"input_blocks.5.1.transformer_blocks.0.attn1",
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"output_blocks.3.1.transformer_blocks.0.attn1",
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"output_blocks.4.1.transformer_blocks.0.attn1",
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"output_blocks.5.1.transformer_blocks.0.attn1",
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# SD 1.5 VAE
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"decoder.mid_block.attentions.0",
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"decoder.mid.attn_1",
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],
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1: [
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# SD 1.5 U-Net (diffusers)
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#"down_blocks.1.attentions.0.transformer_blocks.0.attn1",
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#"down_blocks.1.attentions.1.transformer_blocks.0.attn1",
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#"up_blocks.2.attentions.0.transformer_blocks.0.attn1",
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#"up_blocks.2.attentions.1.transformer_blocks.0.attn1",
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#"up_blocks.2.attentions.2.transformer_blocks.0.attn1",
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# SD 1.5 U-Net (ldm)
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"input_blocks.4.1.transformer_blocks.1.attn1",
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"input_blocks.5.1.transformer_blocks.1.attn1",
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"output_blocks.3.1.transformer_blocks.1.attn1",
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"output_blocks.4.1.transformer_blocks.1.attn1",
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"output_blocks.5.1.transformer_blocks.1.attn1",
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"input_blocks.7.1.transformer_blocks.0.attn1",
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"input_blocks.8.1.transformer_blocks.0.attn1",
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"output_blocks.0.1.transformer_blocks.0.attn1",
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"output_blocks.1.1.transformer_blocks.0.attn1",
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"output_blocks.2.1.transformer_blocks.0.attn1",
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"input_blocks.7.1.transformer_blocks.1.attn1",
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"input_blocks.8.1.transformer_blocks.1.attn1",
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"output_blocks.0.1.transformer_blocks.1.attn1",
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"output_blocks.1.1.transformer_blocks.1.attn1",
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"output_blocks.2.1.transformer_blocks.1.attn1",
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"input_blocks.7.1.transformer_blocks.2.attn1",
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"input_blocks.8.1.transformer_blocks.2.attn1",
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"output_blocks.0.1.transformer_blocks.2.attn1",
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"output_blocks.1.1.transformer_blocks.2.attn1",
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"output_blocks.2.1.transformer_blocks.2.attn1",
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"input_blocks.7.1.transformer_blocks.3.attn1",
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"input_blocks.8.1.transformer_blocks.3.attn1",
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"output_blocks.0.1.transformer_blocks.3.attn1",
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"output_blocks.1.1.transformer_blocks.3.attn1",
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"output_blocks.2.1.transformer_blocks.3.attn1",
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"input_blocks.7.1.transformer_blocks.4.attn1",
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"input_blocks.8.1.transformer_blocks.4.attn1",
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"output_blocks.0.1.transformer_blocks.4.attn1",
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"output_blocks.1.1.transformer_blocks.4.attn1",
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"output_blocks.2.1.transformer_blocks.4.attn1",
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"input_blocks.7.1.transformer_blocks.5.attn1",
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"input_blocks.8.1.transformer_blocks.5.attn1",
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"output_blocks.0.1.transformer_blocks.5.attn1",
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"output_blocks.1.1.transformer_blocks.5.attn1",
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"output_blocks.2.1.transformer_blocks.5.attn1",
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"input_blocks.7.1.transformer_blocks.6.attn1",
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"input_blocks.8.1.transformer_blocks.6.attn1",
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"output_blocks.0.1.transformer_blocks.6.attn1",
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"output_blocks.1.1.transformer_blocks.6.attn1",
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"output_blocks.2.1.transformer_blocks.6.attn1",
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"input_blocks.7.1.transformer_blocks.7.attn1",
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"input_blocks.8.1.transformer_blocks.7.attn1",
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"output_blocks.0.1.transformer_blocks.7.attn1",
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"output_blocks.1.1.transformer_blocks.7.attn1",
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"output_blocks.2.1.transformer_blocks.7.attn1",
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"input_blocks.7.1.transformer_blocks.8.attn1",
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"input_blocks.8.1.transformer_blocks.8.attn1",
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"output_blocks.0.1.transformer_blocks.8.attn1",
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"output_blocks.1.1.transformer_blocks.8.attn1",
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"output_blocks.2.1.transformer_blocks.8.attn1",
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"input_blocks.7.1.transformer_blocks.9.attn1",
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"input_blocks.8.1.transformer_blocks.9.attn1",
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"output_blocks.0.1.transformer_blocks.9.attn1",
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"output_blocks.1.1.transformer_blocks.9.attn1",
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"output_blocks.2.1.transformer_blocks.9.attn1",
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],
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2: [
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# SD 1.5 U-Net (diffusers)
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"mid_block.attentions.0.transformer_blocks.0.attn1",
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# SD 1.5 U-Net (ldm)
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"middle_block.1.transformer_blocks.0.attn1",
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"middle_block.1.transformer_blocks.1.attn1",
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"middle_block.1.transformer_blocks.2.attn1",
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"middle_block.1.transformer_blocks.3.attn1",
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"middle_block.1.transformer_blocks.4.attn1",
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"middle_block.1.transformer_blocks.5.attn1",
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"middle_block.1.transformer_blocks.6.attn1",
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"middle_block.1.transformer_blocks.7.attn1",
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"middle_block.1.transformer_blocks.8.attn1",
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"middle_block.1.transformer_blocks.9.attn1",
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],
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3 : [] # TODO - separate layers for SD-XL
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}
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RNG_INSTANCE = random.Random()
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@cache
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def get_divisors(value: int, min_value: int, /, max_options: int = 1) -> list[int]:
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"""
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Returns divisors of value that
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x * min_value <= value
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in big -> small order, amount of divisors is limited by max_options
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"""
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max_options = max(1, max_options) # at least 1 option should be returned
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min_value = min(min_value, value)
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divisors = [i for i in range(min_value, value + 1) if value % i == 0] # divisors in small -> big order
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ns = [value // i for i in divisors[:max_options]] # has at least 1 element # big -> small order
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return ns
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def random_divisor(value: int, min_value: int, /, max_options: int = 1) -> int:
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"""
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Returns a random divisor of value that
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x * min_value <= value
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if max_options is 1, the behavior is deterministic
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"""
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ns = get_divisors(value, min_value, max_options=max_options) # get cached divisors
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idx = RNG_INSTANCE.randint(0, len(ns) - 1)
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return ns[idx]
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def set_hypertile_seed(seed: int) -> None:
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RNG_INSTANCE.seed(seed)
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@cache
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def largest_tile_size_available(width: int, height: int) -> int:
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"""
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Calculates the largest tile size available for a given width and height
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Tile size is always a power of 2
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"""
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gcd = math.gcd(width, height)
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largest_tile_size_available = 1
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while gcd % (largest_tile_size_available * 2) == 0:
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largest_tile_size_available *= 2
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return largest_tile_size_available
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def iterative_closest_divisors(hw:int, aspect_ratio:float) -> tuple[int, int]:
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"""
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Finds h and w such that h*w = hw and h/w = aspect_ratio
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We check all possible divisors of hw and return the closest to the aspect ratio
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"""
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divisors = [i for i in range(2, hw + 1) if hw % i == 0] # all divisors of hw
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pairs = [(i, hw // i) for i in divisors] # all pairs of divisors of hw
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ratios = [w/h for h, w in pairs] # all ratios of pairs of divisors of hw
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closest_ratio = min(ratios, key=lambda x: abs(x - aspect_ratio)) # closest ratio to aspect_ratio
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closest_pair = pairs[ratios.index(closest_ratio)] # closest pair of divisors to aspect_ratio
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return closest_pair
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@cache
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def find_hw_candidates(hw:int, aspect_ratio:float) -> tuple[int, int]:
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"""
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Finds h and w such that h*w = hw and h/w = aspect_ratio
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"""
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h, w = round(math.sqrt(hw * aspect_ratio)), round(math.sqrt(hw / aspect_ratio))
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# find h and w such that h*w = hw and h/w = aspect_ratio
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if h * w != hw:
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w_candidate = hw / h
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# check if w is an integer
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if not w_candidate.is_integer():
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h_candidate = hw / w
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# check if h is an integer
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if not h_candidate.is_integer():
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return iterative_closest_divisors(hw, aspect_ratio)
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else:
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h = int(h_candidate)
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else:
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w = int(w_candidate)
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return h, w
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def self_attn_forward(params: HypertileParams, scale_depth=True) -> Callable:
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@wraps(params.forward)
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def wrapper(*args, **kwargs):
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if not params.enabled:
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return params.forward(*args, **kwargs)
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latent_tile_size = max(128, params.tile_size) // 8
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x = args[0]
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# VAE
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if x.ndim == 4:
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b, c, h, w = x.shape
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nh = random_divisor(h, latent_tile_size, params.swap_size)
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nw = random_divisor(w, latent_tile_size, params.swap_size)
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if nh * nw > 1:
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x = rearrange(x, "b c (nh h) (nw w) -> (b nh nw) c h w", nh=nh, nw=nw) # split into nh * nw tiles
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out = params.forward(x, *args[1:], **kwargs)
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if nh * nw > 1:
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out = rearrange(out, "(b nh nw) c h w -> b c (nh h) (nw w)", nh=nh, nw=nw)
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# U-Net
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else:
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hw: int = x.size(1)
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h, w = find_hw_candidates(hw, params.aspect_ratio)
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assert h * w == hw, f"Invalid aspect ratio {params.aspect_ratio} for input of shape {x.shape}, hw={hw}, h={h}, w={w}"
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factor = 2 ** params.depth if scale_depth else 1
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nh = random_divisor(h, latent_tile_size * factor, params.swap_size)
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nw = random_divisor(w, latent_tile_size * factor, params.swap_size)
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if nh * nw > 1:
|
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x = rearrange(x, "b (nh h nw w) c -> (b nh nw) (h w) c", h=h // nh, w=w // nw, nh=nh, nw=nw)
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out = params.forward(x, *args[1:], **kwargs)
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|
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if nh * nw > 1:
|
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out = rearrange(out, "(b nh nw) hw c -> b nh nw hw c", nh=nh, nw=nw)
|
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out = rearrange(out, "b nh nw (h w) c -> b (nh h nw w) c", h=h // nh, w=w // nw)
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return out
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||||
|
||||
return wrapper
|
||||
|
||||
|
||||
def hypertile_hook_model(model: nn.Module, width, height, *, enable=False, tile_size_max=128, swap_size=1, max_depth=3, is_sdxl=False):
|
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hypertile_layers = getattr(model, "__webui_hypertile_layers", None)
|
||||
if hypertile_layers is None:
|
||||
if not enable:
|
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return
|
||||
|
||||
hypertile_layers = {}
|
||||
layers = DEPTH_LAYERS_XL if is_sdxl else DEPTH_LAYERS
|
||||
|
||||
for depth in range(4):
|
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for layer_name, module in model.named_modules():
|
||||
if any(layer_name.endswith(try_name) for try_name in layers[depth]):
|
||||
params = HypertileParams()
|
||||
module.__webui_hypertile_params = params
|
||||
params.forward = module.forward
|
||||
params.depth = depth
|
||||
params.layer_name = layer_name
|
||||
module.forward = self_attn_forward(params)
|
||||
|
||||
hypertile_layers[layer_name] = 1
|
||||
|
||||
model.__webui_hypertile_layers = hypertile_layers
|
||||
|
||||
aspect_ratio = width / height
|
||||
tile_size = min(largest_tile_size_available(width, height), tile_size_max)
|
||||
|
||||
for layer_name, module in model.named_modules():
|
||||
if layer_name in hypertile_layers:
|
||||
params = module.__webui_hypertile_params
|
||||
|
||||
params.tile_size = tile_size
|
||||
params.swap_size = swap_size
|
||||
params.aspect_ratio = aspect_ratio
|
||||
params.enabled = enable and params.depth <= max_depth
|
||||
@@ -1,109 +0,0 @@
|
||||
import hypertile
|
||||
from modules import scripts, script_callbacks, shared
|
||||
from scripts.hypertile_xyz import add_axis_options
|
||||
|
||||
|
||||
class ScriptHypertile(scripts.Script):
|
||||
name = "Hypertile"
|
||||
|
||||
def title(self):
|
||||
return self.name
|
||||
|
||||
def show(self, is_img2img):
|
||||
return scripts.AlwaysVisible
|
||||
|
||||
def process(self, p, *args):
|
||||
hypertile.set_hypertile_seed(p.all_seeds[0])
|
||||
|
||||
configure_hypertile(p.width, p.height, enable_unet=shared.opts.hypertile_enable_unet)
|
||||
|
||||
self.add_infotext(p)
|
||||
|
||||
def before_hr(self, p, *args):
|
||||
|
||||
enable = shared.opts.hypertile_enable_unet_secondpass or shared.opts.hypertile_enable_unet
|
||||
|
||||
# exclusive hypertile seed for the second pass
|
||||
if enable:
|
||||
hypertile.set_hypertile_seed(p.all_seeds[0])
|
||||
|
||||
configure_hypertile(p.hr_upscale_to_x, p.hr_upscale_to_y, enable_unet=enable)
|
||||
|
||||
if enable and not shared.opts.hypertile_enable_unet:
|
||||
p.extra_generation_params["Hypertile U-Net second pass"] = True
|
||||
|
||||
self.add_infotext(p, add_unet_params=True)
|
||||
|
||||
def add_infotext(self, p, add_unet_params=False):
|
||||
def option(name):
|
||||
value = getattr(shared.opts, name)
|
||||
default_value = shared.opts.get_default(name)
|
||||
return None if value == default_value else value
|
||||
|
||||
if shared.opts.hypertile_enable_unet:
|
||||
p.extra_generation_params["Hypertile U-Net"] = True
|
||||
|
||||
if shared.opts.hypertile_enable_unet or add_unet_params:
|
||||
p.extra_generation_params["Hypertile U-Net max depth"] = option('hypertile_max_depth_unet')
|
||||
p.extra_generation_params["Hypertile U-Net max tile size"] = option('hypertile_max_tile_unet')
|
||||
p.extra_generation_params["Hypertile U-Net swap size"] = option('hypertile_swap_size_unet')
|
||||
|
||||
if shared.opts.hypertile_enable_vae:
|
||||
p.extra_generation_params["Hypertile VAE"] = True
|
||||
p.extra_generation_params["Hypertile VAE max depth"] = option('hypertile_max_depth_vae')
|
||||
p.extra_generation_params["Hypertile VAE max tile size"] = option('hypertile_max_tile_vae')
|
||||
p.extra_generation_params["Hypertile VAE swap size"] = option('hypertile_swap_size_vae')
|
||||
|
||||
|
||||
def configure_hypertile(width, height, enable_unet=True):
|
||||
hypertile.hypertile_hook_model(
|
||||
shared.sd_model.first_stage_model,
|
||||
width,
|
||||
height,
|
||||
swap_size=shared.opts.hypertile_swap_size_vae,
|
||||
max_depth=shared.opts.hypertile_max_depth_vae,
|
||||
tile_size_max=shared.opts.hypertile_max_tile_vae,
|
||||
enable=shared.opts.hypertile_enable_vae,
|
||||
)
|
||||
|
||||
hypertile.hypertile_hook_model(
|
||||
shared.sd_model.model,
|
||||
width,
|
||||
height,
|
||||
swap_size=shared.opts.hypertile_swap_size_unet,
|
||||
max_depth=shared.opts.hypertile_max_depth_unet,
|
||||
tile_size_max=shared.opts.hypertile_max_tile_unet,
|
||||
enable=enable_unet,
|
||||
is_sdxl=shared.sd_model.is_sdxl
|
||||
)
|
||||
|
||||
|
||||
def on_ui_settings():
|
||||
import gradio as gr
|
||||
|
||||
options = {
|
||||
"hypertile_explanation": shared.OptionHTML("""
|
||||
<a href='https://github.com/tfernd/HyperTile'>Hypertile</a> optimizes the self-attention layer within U-Net and VAE models,
|
||||
resulting in a reduction in computation time ranging from 1 to 4 times. The larger the generated image is, the greater the
|
||||
benefit.
|
||||
"""),
|
||||
|
||||
"hypertile_enable_unet": shared.OptionInfo(False, "Enable Hypertile U-Net", infotext="Hypertile U-Net").info("enables hypertile for all modes, including hires fix second pass; noticeable change in details of the generated picture"),
|
||||
"hypertile_enable_unet_secondpass": shared.OptionInfo(False, "Enable Hypertile U-Net for hires fix second pass", infotext="Hypertile U-Net second pass").info("enables hypertile just for hires fix second pass - regardless of whether the above setting is enabled"),
|
||||
"hypertile_max_depth_unet": shared.OptionInfo(3, "Hypertile U-Net max depth", gr.Slider, {"minimum": 0, "maximum": 3, "step": 1}, infotext="Hypertile U-Net max depth").info("larger = more neural network layers affected; minor effect on performance"),
|
||||
"hypertile_max_tile_unet": shared.OptionInfo(256, "Hypertile U-Net max tile size", gr.Slider, {"minimum": 0, "maximum": 512, "step": 16}, infotext="Hypertile U-Net max tile size").info("larger = worse performance"),
|
||||
"hypertile_swap_size_unet": shared.OptionInfo(3, "Hypertile U-Net swap size", gr.Slider, {"minimum": 0, "maximum": 64, "step": 1}, infotext="Hypertile U-Net swap size"),
|
||||
|
||||
"hypertile_enable_vae": shared.OptionInfo(False, "Enable Hypertile VAE", infotext="Hypertile VAE").info("minimal change in the generated picture"),
|
||||
"hypertile_max_depth_vae": shared.OptionInfo(3, "Hypertile VAE max depth", gr.Slider, {"minimum": 0, "maximum": 3, "step": 1}, infotext="Hypertile VAE max depth"),
|
||||
"hypertile_max_tile_vae": shared.OptionInfo(128, "Hypertile VAE max tile size", gr.Slider, {"minimum": 0, "maximum": 512, "step": 16}, infotext="Hypertile VAE max tile size"),
|
||||
"hypertile_swap_size_vae": shared.OptionInfo(3, "Hypertile VAE swap size ", gr.Slider, {"minimum": 0, "maximum": 64, "step": 1}, infotext="Hypertile VAE swap size"),
|
||||
}
|
||||
|
||||
for name, opt in options.items():
|
||||
opt.section = ('hypertile', "Hypertile")
|
||||
shared.opts.add_option(name, opt)
|
||||
|
||||
|
||||
script_callbacks.on_ui_settings(on_ui_settings)
|
||||
script_callbacks.on_before_ui(add_axis_options)
|
||||
@@ -1,51 +0,0 @@
|
||||
from modules import scripts
|
||||
from modules.shared import opts
|
||||
|
||||
xyz_grid = [x for x in scripts.scripts_data if x.script_class.__module__ == "xyz_grid.py"][0].module
|
||||
|
||||
def int_applier(value_name:str, min_range:int = -1, max_range:int = -1):
|
||||
"""
|
||||
Returns a function that applies the given value to the given value_name in opts.data.
|
||||
"""
|
||||
def validate(value_name:str, value:str):
|
||||
value = int(value)
|
||||
# validate value
|
||||
if not min_range == -1:
|
||||
assert value >= min_range, f"Value {value} for {value_name} must be greater than or equal to {min_range}"
|
||||
if not max_range == -1:
|
||||
assert value <= max_range, f"Value {value} for {value_name} must be less than or equal to {max_range}"
|
||||
def apply_int(p, x, xs):
|
||||
validate(value_name, x)
|
||||
opts.data[value_name] = int(x)
|
||||
return apply_int
|
||||
|
||||
def bool_applier(value_name:str):
|
||||
"""
|
||||
Returns a function that applies the given value to the given value_name in opts.data.
|
||||
"""
|
||||
def validate(value_name:str, value:str):
|
||||
assert value.lower() in ["true", "false"], f"Value {value} for {value_name} must be either true or false"
|
||||
def apply_bool(p, x, xs):
|
||||
validate(value_name, x)
|
||||
value_boolean = x.lower() == "true"
|
||||
opts.data[value_name] = value_boolean
|
||||
return apply_bool
|
||||
|
||||
def add_axis_options():
|
||||
extra_axis_options = [
|
||||
xyz_grid.AxisOption("[Hypertile] Unet First pass Enabled", str, bool_applier("hypertile_enable_unet"), choices=xyz_grid.boolean_choice(reverse=True)),
|
||||
xyz_grid.AxisOption("[Hypertile] Unet Second pass Enabled", str, bool_applier("hypertile_enable_unet_secondpass"), choices=xyz_grid.boolean_choice(reverse=True)),
|
||||
xyz_grid.AxisOption("[Hypertile] Unet Max Depth", int, int_applier("hypertile_max_depth_unet", 0, 3), choices=lambda: [str(x) for x in range(4)]),
|
||||
xyz_grid.AxisOption("[Hypertile] Unet Max Tile Size", int, int_applier("hypertile_max_tile_unet", 0, 512)),
|
||||
xyz_grid.AxisOption("[Hypertile] Unet Swap Size", int, int_applier("hypertile_swap_size_unet", 0, 64)),
|
||||
xyz_grid.AxisOption("[Hypertile] VAE Enabled", str, bool_applier("hypertile_enable_vae"), choices=xyz_grid.boolean_choice(reverse=True)),
|
||||
xyz_grid.AxisOption("[Hypertile] VAE Max Depth", int, int_applier("hypertile_max_depth_vae", 0, 3), choices=lambda: [str(x) for x in range(4)]),
|
||||
xyz_grid.AxisOption("[Hypertile] VAE Max Tile Size", int, int_applier("hypertile_max_tile_vae", 0, 512)),
|
||||
xyz_grid.AxisOption("[Hypertile] VAE Swap Size", int, int_applier("hypertile_swap_size_vae", 0, 64)),
|
||||
]
|
||||
set_a = {opt.label for opt in xyz_grid.axis_options}
|
||||
set_b = {opt.label for opt in extra_axis_options}
|
||||
if set_a.intersection(set_b):
|
||||
return
|
||||
|
||||
xyz_grid.axis_options.extend(extra_axis_options)
|
||||
Reference in New Issue
Block a user