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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 load_from_config(cp, model, **kwargs):
 """Loads a sampler from the given config file. This looks for a name in the section ``[sampler]`` to determine which sampler class to load. That sampler's ``from_config`` is then called. Parameters cp : WorkflowConfigParser Config parser to read from. model : pycbc.inference.model Which model to pass to the sampler. \**kwargs : All other keyword arguments are passed directly to the sampler's ``from_config`` file. Returns ------- sampler : The initialized sampler. """

    name = cp.get('sampler', 'name')
    return samplers[name].from_config(cp, model, **kwargs)