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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 train(self, mode=True):
 r""" Sets the module in training mode. This has any effect only on certain modules. See documentations of particular modules for details of their behaviors in training/evaluation mode, if they are affected, e.g. :class:`Dropout`, :class:`BatchNorm`, etc. Returns: Module: self """

        super().train(mode)

        if mode:
            mu.apply_leaf(self, mu.set_train_mode)

        return self