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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def _preprocess_inputs(x, weights):
 """ Coerce inputs into compatible format """

    if weights is None:
        w_arr = np.ones(len(x))
    else:
        w_arr = np.array(weights)
    x_arr = np.array(x)
    if x_arr.ndim == 2:
        if w_arr.ndim == 1:
            w_arr = w_arr[:, np.newaxis]
    return x_arr, w_arr