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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 _operator_norms(L):
 """Get operator norms if needed. Parameters L : sequence of `Operator` or float The operators or the norms of the operators that are used in the `douglas_rachford_pd` method. For `Operator` entries, the norm is computed with ``Operator.norm(estimate=True)``. """

    L_norms = []
    for Li in L:
        if np.isscalar(Li):
            L_norms.append(float(Li))
        elif isinstance(Li, Operator):
            L_norms.append(Li.norm(estimate=True))
        else:
            raise TypeError('invalid entry {!r} in `L`'.format(Li))
    return L_norms