code: def __init__(self):
      self.parser_args = None
      self.ax_client = None
      self.base_model_path = "base_model"
      self.pruning_amount = None
  
imports: import argparse
  import copy
  import os
  import shutil
  import tempfile
  from pathlib import Path
  import lightning
  import torch
  from ax.service.ax_client import AxClient
  from mnist import LightningMNISTClassifier, MNISTDataModule
  from prettytable import PrettyTable
  from torch.nn.utils import prune
  import mlflow.pytorch
  from mlflow.tracking.artifact_utils import _download_artifact_from_uri
label_desc: Use image node_id 1 to create a new IterativePrune object  with example: obj = IterativePrune()