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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 committor_sensitivity(T, A, B, i, forward=True):
 r"""Sensitivity matrix of a specified committor entry. Parameters T : (M, M) ndarray Transition matrix A : array_like List of integer state labels for set A B : array_like List of integer state labels for set B i : int Compute the sensitivity for committor entry `i` forward : bool (optional) Compute the forward committor. If forward is False compute the backward committor. Returns ------- S : (M, M) ndarray Sensitivity matrix of the specified committor entry. """

    # check inputs
    T = _types.ensure_ndarray_or_sparse(T, ndim=2, uniform=True, kind='numeric')
    A = _types.ensure_int_vector(A)
    B = _types.ensure_int_vector(B)
    if _issparse(T):
        _showSparseConversionWarning()
        committor_sensitivity(T.todense(), A, B, i, forward)
    else:
        if forward:
            return dense.sensitivity.forward_committor_sensitivity(T, A, B, i)
        else:
            return dense.sensitivity.backward_committor_sensitivity(T, A, B, i)