code: def train(
      self, manager, train_data_loader, val_data_loader, **train_kwargs
  ):
      self.train_data_loader = train_data_loader
      self.val_data_loader = val_data_loader
      self._setup_training(**train_kwargs)
      self.optimizer = manager.modify(
          self.model,
          self.optimizer,
          steps_per_epoch=len(self.train_data_loader),
      )
      self.model.train()
      # Run model pruning
      epoch = manager.min_epochs
      while epoch < manager.max_epochs:
          # run training loop
          epoch_name = "{}/{}".format(epoch + 1, manager.max_epochs)
          logger.info("Running Training Epoch {}".format(epoch_name))
          train_loss = self._run_model_one_epoch(train=True)
          logger.info(
              ("Training Epoch: {}\nTraining Loss: {}\n").format(
                  epoch_name, train_loss
              )
          )
  
          # run validation loop
          logger.info("Running Validation Epoch {}".format(epoch_name))
          val_loss = self._run_model_one_epoch()
          logger.info(
              "Validation Epoch: {}\nVal Loss: {}\n".format(
                  epoch_name, val_loss
              )
          )
  
          epoch += 1
  
      manager.finalize(self.model)
  
      return self.model
  
imports: import json
  import logging
  import os.path
  from pathlib import Path
  from tempfile import TemporaryDirectory
  from typing import Tuple, List, Any, Dict
  import torch
  from sparseml.onnx.optim import ModelAnalyzer, pruning_loss_sens_magnitude
  from sparseml.pytorch.optim import ScheduledModifierManager
  from sparseml.pytorch.sparsification import EpochRangeModifier, GMPruningModifier
  from sparseml.pytorch.utils import ModuleExporter
  from sparsify.blueprints.utils import default_epochs_distribution, PruningModelEvaluator, default_pruning_settings
  from sparsify.schemas import ProjectModelAnalysisSchema
  from torch.nn import CrossEntropyLoss, MSELoss
  from torch.optim import SGD
  from tqdm.auto import tqdm
label_desc: Use image node_id 4 for calling the PruningTrainer obj's underlying member method code with example usage: obj.train(manager, train_data_loader, val_data_loader) and returns: self