code: def train_fn(df):
      def p(new_df):
          return new_df.assign(prediction=0)
  
      log = {
          "xgb_classification_learner": {
              "features": ["f1"],
              "target": "target",
              "prediction_column": "prediction",
              "package": "xgboost",
              "package_version": "3",
              "parameters": {"a": 3},
              "feature_importance": {"f1": 1},
              "running_time": "3 ms",
              "training_samples": len(df),
          }
      }
  
      return p, p(df), log
  
file_path: fklearn/tests/validation/test_validator.py
imports: import warnings
  from datetime import datetime, timedelta
  import pandas
  from toolz.functoolz import identity
  from fklearn.training.classification import lgbm_classification_learner
  from fklearn.validation import splitters, evaluators
  from fklearn.validation.validator import validator_iteration, validator, parallel_validator
  from fklearn.validation.perturbators import perturbator, nullify
  import pytest
label_desc: Use image node_id 1 for calling a global function with example usage: train_fn(df) and returns: p,  p,  log, new_df