Sunny-Island commented on issue #12009: URL: https://github.com/apache/tvm/issues/12009#issuecomment-1180114920
> Thanks for submitting the first PR! I just sent a couple comments, let me know if you have any questions! I am working on upgrading the callback function in AutoScheduler XGBoost Cost Model. I noticed some codes are related with crossfold(cv), but I'm not clear when will the crossfold function be called? When the env.cvfolds will become true? In latest xgboost code, it seems that crossfold is a dependent function. And deprecated `train` method will set `cvfold=None`. https://github.com/dmlc/xgboost/blob/e7decb9775dae440fd829fd37d1f56c5bcedb138/python-package/xgboost/training.py#L74 Ignore this reply if you are not familiar with this part. ```python def callback(env): """internal function""" if not state: init(env) bst = env.model i = env.iteration cvfolds = env.cvfolds res_dict = {} if i % skip_every == 1: return ##### evaluation ##### if cvfolds is not None: for feval in fevals: tmp = aggcv([f.eval(i, feval) for f in cvfolds]) for k, mean, std in tmp: res_dict[k] = [mean, std] else: for feval in fevals: bst_eval = bst.eval_set(evals, i, feval) res = [x.split(":") for x in bst_eval.split()] for kv in res[1:]: res_dict[kv[0]] = [float(kv[1])] ``` -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
