code: def data():
      X, y = load_iris(return_X_y=True)
      X, y = make_imbalance(
          X, y, sampling_strategy={0: 30, 1: 50, 2: 40}
      )
      X = X.astype(np.float32)
      return X, y
  
file_path: imbalanced-learn/imblearn/tensorflow/tests/test_generator.py
imports: from distutils.version import LooseVersion
  import numpy
  import pytest
  from scipy import sparse
  from sklearn.datasets import load_iris
  from imblearn.datasets import make_imbalance
  from imblearn.over_sampling import RandomOverSampler
  from imblearn.tensorflow import balanced_batch_generator
  from imblearn.under_sampling import NearMiss
label_desc: Use image node_id 1 for calling a global function with example usage: data() and returns: X,  y