def predict(self, params, exog=None, exposure=None, offset=None,
                linear=False):
        #TODO: add offset tp
        if exog is None:
            exog = self.exog
            offset = getattr(self, 'offset', 0)
            exposure = getattr(self, 'exposure', 0)

        else:
            if exposure is None:
                exposure = 0
            else:
                exposure = np.log(exposure)
            if offset is None:
                offset = 0

        if not linear:
            return np.exp(np.dot(exog, params[:exog.shape[1]]) + exposure + offset) # not cdf
        else:
            return np.dot(exog, params[:exog.shape[1]]) + exposure + offset
Suggest next checksum query batch size in rows.
dataset/ETHPy150Open statsmodels/statsmodels/statsmodels/discrete/discrete_model.py/CountModel.predict--crossover with--dataset/ETHPy150Open google/mysql-tools/drift_lib/drift_policies.py/FixedQuerySizePolicy.GetNextBatchSize