code: def __call__(self, n_samples, rand=None):
      log_sigma = self.p_mean + self.p_std * default(
          rand, torch.randn((n_samples,))
      )
      return log_sigma.exp()
  
file_path: generative-models/sgm/modules/diffusionmodules/sigma_sampling.py
imports: import torch
  from ...util import default, instantiate_from_config
label_desc: Use image node_id 2 for calling the EDMSampling obj's underlying member method code with example usage: obj.__call__(n_samples, rand) and returns: log_sigma