class_docstr: Solver for compression task.
  
  The diffusion task allows for MultiBand diffusion model training.
  
  Args:
      cfg (DictConfig): Configuration.
class_docstr_tok: ["Solver","for","compression","task",".","The","diffusion","task","allows","for","MultiBand","diffusion","model","training",".","Args",":","cfg","(","DictConfig",")",":","Configuration","."]
code: def run_epoch(self):
      # reset random seed at the beginning of the epoch
      self.rng = torch.Generator()
      self.rng.manual_seed(1234 + self.epoch)
      self.per_stage = PerStageMetrics(
          self.schedule.num_steps, self.cfg.metrics.num_stage
      )
      # run epoch
      super().run_epoch()
  
imports: import typing
  import flashy
  import julius
  import omegaconf
  import torch
  import torch.nn.functional
  from .None import builders
  from .None import base
  from ..None import models
  from ..modules.diffusion_schedule import NoiseSchedule
  from ..metrics import RelativeVolumeMel
  from ..models.builders import get_processor
  from ..utils.samples.manager import SampleManager
  from ..solvers.compression import CompressionSolver
label_desc: Use image node_id 8 for calling the DiffusionSolver obj's underlying member method code with example usage: obj.run_epoch() without return types