input: Write a function to train and predict with a linear regression model using scikit-learn.
  assert np.allclose(train_and_predict([[1, 0], [0, 1]], [1, 0]), [1, 0])
  assert np.allclose(train_and_predict([[2, 3], [3, 4]], [3, 5]), [3, 5])
  assert np.allclose(train_and_predict([[1, 1], [2, 2]], [2, 4]), [2, 4])
output: def train_and_predict(X, y):
      from sklearn.linear_model import LinearRegression
      import numpy as np
      
      # Create the model
      model = LinearRegression()
      
      # Train the model
      model.fit(X, y)
      
      # Predict using the same input features
      predictions = model.predict(X)
      
      return predictions