class_docstr: ImprovedSR model fine-tunes the pretrained DDPM-based SR model by using adversarial and perceptual losses.
  In specific, the low-resolution sample is iteratively recovered by 6 steps with the frozen pretrained SR model.
  In the following additional one step, a seperate fine-tuned model recovers high-frequency details.
  This approach greatly improves the fidelity of images of 256x256px, even with small number of reverse steps.
code: def load_from_checkpoint(cls, config, ckpt_path, strict: bool = True):
      ckpt = torch.load(ckpt_path, map_location="cpu")["state_dict"]
  
      model = cls(config)
      model.load_state_dict(ckpt, strict=strict)
      return model
  
file_path: stablediffusion/ldm/modules/karlo/kakao/models/sr_64_256.py
imports: import copy
  import torch
  from ldm.modules.karlo.kakao.modules.unet import SuperResUNetModel
  from ldm.modules.karlo.kakao.modules import create_gaussian_diffusion
label_desc: Use image node_id 2 for calling the ImprovedSupRes64to256ProgressiveModel obj's underlying member method code with example usage: obj.load_from_checkpoint(cls, config, ckpt_path, strict) and returns: model