input: Write a python function to load a dataset from a text file and split it into training and test sets.
  assert X_data.shape == (1000, 10) and y_data.shape == (1000,)
  assert X_train.shape == (800, 10) and y_train.shape == (800,)
  assert X_test.shape == (200, 10) and y_test.shape == (200,)
output: import numpy as np
  from sklearn.model_selection import train_test_split
  
  def load_and_split_dataset(file_path):
      data = np.loadtxt(file_path)
      X_data = data[:, :-1]
      y_data = data[:, -1]
      X_train, X_test, y_train, y_test = train_test_split(X_data, y_data, test_size=0.2, random_state=42)
      return X_data, y_data, X_train, y_train, X_test, y_test