code: def subsample(X, y, ml_task, train_size):
      shuffle = True
      stratify = None
  
      if ml_task != REGRESSION:
          stratify = y
  
      X_train, X_test, y_train, y_test = train_test_split(
          X,
          y,
          train_size=train_size,
          shuffle=shuffle,
          stratify=stratify,
      )
  
      return X_train, X_test, y_train, y_test
  
imports: import numpy
  import pandas
  from sklearn.model_selection import train_test_split
  from supervised.algorithms.registry import REGRESSION
label_desc: Use image node_id 1 for calling a global function with example usage: subsample(X, y, ml_task, train_size) and returns: X_train,  X_test,  y_train,  y_test