scale.py

import torch

import modules.scripts as scripts
import gradio as gr
from modules.processing import StableDiffusionProcessing, process_images

class Script(scripts.Script):

    def __init__(self):
        pass

    def title(self):
        return "scale"

    def ui(self, is_img2img):
        with gr.Group():
            with gr.Row():
                scale = gr.Textbox(label="scale factor:number or list of 4 numbers(a,b,c,d)",value=1)
        return [scale]

    def run(
        self, 
        p: StableDiffusionProcessing, 
        scale:str,
        ):
        
        pre_scale_factor = p.sd_model.scale_factor
        scale = [pre_scale_factor / float(s) for s in scale.split(",")]
        
        #(batch_size, channel, height, width)
        p.sd_model.scale_factor = torch.tensor(scale).unsqueeze(0).unsqueeze(-1).unsqueeze(-1).to("cuda", dtype=p.sd_model.first_stage_model.dtype)
        
        result = process_images(p)
        p.sd_model.scale_factor = pre_scale_factor
        return result