code: def train(model, train_dataloader, valid_dataloader, args):
      model.train()
      optimizer = torch.optim.Adam(model.parameters())
  
      for epoch in range(args.epochs):
          train_epoch(model, train_dataloader, optimizer, epoch)
          evaluate_model(model, valid_dataloader)
  
file_path: textlesslib/examples/speaker_probing/train.py
imports: import torch
  import argparse
  from textless.data.quantized_datasets import QuantizedLibriSpeech
  from torch.utils.data import DataLoader
  import torch.nn.functional
  from probes import ContinuousClassifier, DiscreteClassifier, ConstantBaseline
  from textless.data.speech_encoder import SpeechEncoder
  from textless import dispatch_dense_model, dispatch_quantizer
label_desc: Use image node_id 4 for calling a global function with example usage: train(model, train_dataloader, valid_dataloader, args) without return types