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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 kron_with_controls(*matrices: np.ndarray) -> np.ndarray: """Computes the kronecker product of a sequence of matrices and controls. Use linalg.CONTROL_TAG to represent controls. Any entry of the output matrix corresponding to a situation where the control is not satisfied will be overwritten by identity matrix elements. The control logic works by imbuing NaN with the meaning "failed to meet one or more controls". The normal kronecker product then spreads the per-item NaNs to all the entries in the product that need to be replaced by identity matrix elements. This method rewrites those NaNs. Thus CONTROL_TAG can be the matrix [[NaN, 0], [0, 1]] or equivalently [[NaN, NaN], [NaN, 1]]. Because this method re-interprets NaNs as control-failed elements, it won't propagate error-indicating NaNs from its input to its output in the way you'd otherwise expect. Args: *matrices: The matrices and controls to combine with the kronecker product. Returns: The resulting matrix. """


    product = kron(*matrices)

    # The NaN from CONTROL_TAG spreads to everywhere identity belongs.
    for i in range(product.shape[0]):
        for j in range(product.shape[1]):
            if np.isnan(product[i, j]):
                product[i, j] = 1 if i == j else 0

    return product