code: def data_loader(
      path="./dataset/",
  ):
      name = INFO["name"]
      full_path = os.path.join(path, name)
      if os.path.exists(full_path):
          print(f"Existing dataset: {name}")
      else:
          print(f"Dataset not exist. Start downloading: {name}")
          download(
              INFO["url"], path=full_path, sha1_hash=INFO["sha1sum"]
          )
      df = pd.read_csv(full_path, sep="\t")
      return df
  
file_path: autogluon/examples/automm/TCGA_cancer_survival/example_cancer_survival.py
imports: import pandas
  import numpy
  import argparse
  import os
  import random
  from autogluon.tabular import TabularPredictor, TabularDataset
  from autogluon.tabular.configs.hyperparameter_configs import get_hyperparameter_config
  import torch
  from sklearn.model_selection import train_test_split
  from autogluon.multimodal.utils import download
  import warnings
label_desc: Use image node_id 2 for calling a global function with example usage: data_loader(path) and returns: df