code: def load_machine_hack_product_sentiment(train_path, test_path):
      train_df = pd.read_csv(train_path)
      test_df = pd.read_csv(test_path)
      feature_columns = ["Product_Description", "Product_Type"]
      label_column = "Sentiment"
      train_df = train_df[feature_columns + [label_column]]
      test_df = test_df[feature_columns]
      return train_df, test_df, label_column
  
file_path: autogluon/examples/automm/text_prediction/run_competition.py
imports: import os
  import json
  import argparse
  import pandas
  import numpy
  import random
  from autogluon.tabular import TabularPredictor
  from autogluon.multimodal import MultiModalPredictor
  from autogluon.tabular.configs.hyperparameter_configs import get_hyperparameter_config
label_desc: Use image node_id 2 for calling a global function with example usage: load_machine_hack_product_sentiment(train_path, test_path) and returns: train_df,  test_df,  label_column