text: from sklearn.datasets import load_iris
  import numpy as np
  from sklearn.model_selection import train_test_split
  from autoprototype.sklearnopt import HyperparamOpt
  X, y = load_iris(return_X_y=True)
  X_train, X_valid, y_train, y_valid = train_test_split(X, y)
  classes = np.unique(y)
  trials = 50
  hpo = HyperparamOpt(X_train,y_train)
  trial , params , accuracy = hpo.get_best_params(n_trials=trials)
  
  print("\n")
  print("This is the best trial",trial)
  print("\n")
  print("This is the best params",params)
  print("\n")
  print("This is the accuracy",accuracy)
  