code: def __init__(
      self,
      model,
      optimizer,
      train_loader,
      valid_loader,
      eval_loader,
      grad_clip,
      device,
      *,
      debug,
  ):
      self.model = model
      self.optimizer = optimizer
      self.train_loader = train_loader
      self.valid_loader = valid_loader
      self.eval_loader = eval_loader
      self.grad_clip = grad_clip
      self.device = device
      self.debug = debug
  
file_path: audio/examples/source_separation/conv_tasnet/trainer.py
imports: import time
  from collections import namedtuple
  from typing import Tuple
  import torch
  import torch.distributed
  from utils import dist_utils, metrics
label_desc: Use image node_id 1 to create a new Trainer object  with example: obj = Trainer(model, optimizer, train_loader, valid_loader, eval_loader, grad_clip, device)