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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 infer(self, expl_dims, inf_dims, x):
 """ Use the sensorimotor model to compute the expected value on inf_dims given that the value on expl_dims is x. .. note:: This corresponds to a prediction if expl_dims=self.conf.m_dims and inf_dims=self.conf.s_dims and to inverse prediction if expl_dims=self.conf.s_dims and inf_dims=self.conf.m_dims. """

        try:
            if self.n_bootstrap > 0:
                self.n_bootstrap -= 1
                raise ExplautoBootstrapError
            y = self.sensorimotor_model.infer(expl_dims,
                                              inf_dims,
                                              x.flatten())
        except ExplautoBootstrapError:
            logger.warning('Sensorimotor model not bootstrapped yet')
            y = rand_bounds(self.conf.bounds[:, inf_dims]).flatten()
        return y