code: def __init__(self, model, **kwargs):
      super().__init__(model, sampler=Sampler.DPM, **kwargs)
  
      def to_torch(x, model):
          x_copy = x.clone()
          x_detached = x_copy.detach()
          x_float32 = x_detached.to(torch.float32)
          x_device = x_float32.to(model.betas.device)
          return x_device
  
      self.register_buffer(
          "alphas_cumprod", to_torch(model.alphas_cumprod, model)
      )
  
file_path: NeMo/nemo/collections/multimodal/models/text_to_image/stable_diffusion/samplers/sampler_dpm.py
imports: import torch
  from nemo.collections.multimodal.models.text_to_image.stable_diffusion.samplers import Sampler
  from nemo.collections.multimodal.models.text_to_image.stable_diffusion.samplers.base_sampler import AbstractBaseSampler
  from .dpmsolver import DPMSolver, NoiseScheduleVP, model_wrapper
label_desc: Use image node_id 1 to create a new DPMSolverSampler object from inherited base classes: AbstractBaseSampler with example: obj = DPMSolverSampler(model)