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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 cache_inputs(self):
 """ Runs the Study's repository source node for each of the inputs of the study, thereby caching any data required from remote repositorys. Useful when launching many parallel jobs that will all try to concurrently access the remote repository, and probably lead to timeout errors. """

        workflow = pe.Workflow(name='cache_download',
                               base_dir=self.processor.work_dir)
        subjects = pe.Node(IdentityInterface(['subject_id']), name='subjects',
                           environment=self.environment)
        sessions = pe.Node(IdentityInterface(['subject_id', 'visit_id']),
                           name='sessions', environment=self.environment)
        subjects.iterables = ('subject_id', tuple(self.subject_ids))
        sessions.iterables = ('visit_id', tuple(self.visit_ids))
        source = pe.Node(RepositorySource(
            self.bound_spec(i).collection for i in self.inputs), name='source')
        workflow.connect(subjects, 'subject_id', sessions, 'subject_id')
        workflow.connect(sessions, 'subject_id', source, 'subject_id')
        workflow.connect(sessions, 'visit_id', source, 'visit_id')
        workflow.run()