code: def generate_regression_data(
      mode: int = 1, p: int = 8, sigma: float = 0.1
  ):
      generated = False
  
      def _generate_data(
          mode: int = mode, p: int = p, sigma: float = sigma
      ):
          if not generated:
              np.random.seed(RANDOM_SEED)
              data = synthetic_data(
                  mode=mode, n=N_SAMPLE, p=p, sigma=sigma
              )
  
          return data
  
      yield _generate_data
  
file_path: causalml/tests/conftest.py
imports: import numpy
  import pytest
  from causalml.dataset import synthetic_data
  from causalml.dataset import make_uplift_classification
  from .const import RANDOM_SEED, N_SAMPLE, TREATMENT_NAMES, CONVERSION, DELTA_UPLIFT_INCREASE_DICT, N_UPLIFT_INCREASE_DICT
label_desc: Use image node_id 1 for calling a global function with example usage: generate_regression_data(mode, p, sigma) and returns: data