code: def load_tradesy(dataset_folder="dataset/"):
      raw_data = dict()
      raw_data["total_users"] = 19243
      raw_data["total_items"] = 165906
  
      raw_data["train_data"] = np.load(
          dataset_folder + "tradesy/user_data_train.npy"
      )
      raw_data["val_data"] = np.load(
          dataset_folder + "tradesy/user_data_val.npy"
      )
      raw_data["test_data"] = np.load(
          dataset_folder + "tradesy/user_data_test.npy"
      )
  
      raw_data["item_features"] = (
          np.load(dataset_folder + "tradesy/item_features.npy")
          / 32.671101
      )
      return raw_data
  
imports: import tensorflow
  import numpy
label_desc: Use image node_id 3 for calling a global function with example usage: load_tradesy(dataset_folder) and returns: raw_data