import numpy as np


def compute_subgradient_mae(y, tx, w):
    """Compute a subgradient of the MAE at w.

    Args:
        y: shape=(N, )
        tx: shape=(N,2)
        w: shape=(2, ). The vector of model parameters.

    Returns:
        An array of shape (2, ) (same shape as w), containing the subgradient of the MAE at w.
    """
    ### SOLUTION
    err = y - tx.dot(w)
    grad = -np.dot(tx.T, np.sign(err)) / len(err)
    return grad, err
    ### TEMPLATE
    # # ***************************************************
    # # INSERT YOUR CODE HERE
    # # TODO: compute subgradient gradient vector for MAE
    # # ***************************************************
    # raise NotImplementedError
    ### END SOLUTION