code: def forward(
      self,
      network: nn.Module,
      input: torch.Tensor,
      sigma: torch.Tensor,
      cond: Dict,
      **additional_model_inputs,
  ) -> torch.Tensor:
      sigma = self.possibly_quantize_sigma(sigma)
      sigma_shape = sigma.shape
      sigma = append_dims(sigma, input.ndim)
      c_skip, c_out, c_in, c_noise = self.scaling(sigma)
      c_noise = self.possibly_quantize_c_noise(
          c_noise.reshape(sigma_shape)
      )
      return (
          network(
              input * c_in, c_noise, cond, **additional_model_inputs
          )
          * c_out
          + input * c_skip
      )
  
file_path: generative-models/sgm/modules/diffusionmodules/denoiser.py
imports: from typing import Dict, Union
  import torch
  import torch.nn
  from ...util import append_dims, instantiate_from_config
  from .denoiser_scaling import DenoiserScaling
  from .discretizer import Discretization
label_desc: Use image node_id 4 for calling the Denoiser obj's underlying member method code with example usage: obj.forward(network, input, sigma, cond) and returns: unknown