code: def load_data(fpath):
      """
      Simple helper function for loading data to be used by CPU/GPU models.
  
      :param fpath: Path to the data to be ingested
      :return: DataFrame wrapping the data at [fpath]. Data will be in either a Pandas or RAPIDS (cuDF) DataFrame
      """
      import cudf
  
      df = cudf.read_csv(fpath)
      X = df.drop(["target"], axis=1)
      y = df["target"].astype("int32")
  
      return train_test_split(X, y, test_size=0.2)
  
file_path: mlflow/examples/rapids/mlflow_project/src/rf_test/train.py
imports: import argparse
  from functools import partial
  from cuml.ensemble import RandomForestClassifier
  from cuml.metrics.accuracy import accuracy_score
  from cuml.preprocessing.model_selection import train_test_split
  from hyperopt import STATUS_OK, Trials, fmin, hp, tpe
  import mlflow
  import mlflow.sklearn
  from mlflow.models import infer_signature
label_desc: Use image node_id 1 for calling a global function with example usage: load_data(fpath) and returns: train_test_split