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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 view(A, offset=0):
 """ Get a view on the diagonal elements of a 2D array. This is actually a view (!) on the diagonal of the array, so you can in-place adjust the view. :param :class:`ndarray` A: 2 dimensional numpy array :param int offset: view offset to give back (negative entries allowed) :rtype: :class:`ndarray` view of diag(A) array([0, 4, 8]) array([ 2, 6, 10]) array([3, 7]) array([[ 2, 1, 2], [ 0, 6, 5], [ 6, 4, 10]]) """

    from numpy.lib.stride_tricks import as_strided
    assert A.ndim == 2, "only implemented for 2 dimensions"
    assert A.shape[0] == A.shape[1], "attempting to get the view of non-square matrix?!"
    if offset > 0:
        return as_strided(A[0, offset:], shape=(A.shape[0] - offset, ), strides=((A.shape[0]+1)*A.itemsize, ))
    elif offset < 0:
        return as_strided(A[-offset:, 0], shape=(A.shape[0] + offset, ), strides=((A.shape[0]+1)*A.itemsize, ))
    else:
        return as_strided(A, shape=(A.shape[0], ), strides=((A.shape[0]+1)*A.itemsize, ))