Prediction uses select column from the ground truth about sqlova HOT 3 CLOSED

Hi @farsmile

To predict SQL from the plane text, you need to tokenize questions first by using StandforeCoreNLP, for example, by using following function.

After that, to generate SQL, the ground truth is not required. It is used in test function only to calculate loss and accuracies of dev set or test set. See below.

Thanks.

Wonseok

from sqlova.

Hi Wonseok:
it works again.
so much thanks!

from sqlova.

您好Wonseok：
感谢您在这里的漂亮工作，问题如下：
https：//github.com/naver/sqlova/blob/master/train.py#L406
g_wvi_corenlp = get_g_wvi_corenlp(t)
这是在开发中使用“conds”，如果想要的话从英语的计划句中预测，他找不到像“{”conds“：[[0,0，”1998“]]，”sel“：1，”agg“：0}这样的方法。 。

以下url告诉SQLnet xiaojunxu / SQLNet＃12上的类似问题

have i miss something or do you have a similar snippet of codes.

非常感谢

Hi Wonseok:
thanks for your pretty work here and the issue is as following:
https://github.com/naver/sqlova/blob/master/train.py#L406
g_wvi_corenlp = get_g_wvi_corenlp(t)
this is using the "conds" in dev and if one want to predict from a plan sentence of english, he would not find the way to get something like "{"conds":[[0,0,"1998"]], "sel":1, "agg":0}".

the following url tells a similar problem on SQLnet
xiaojunxu/SQLNet#12

have i miss something or do you have a similar snippet of codes.

thank a lot

same question, How did you change it?

from sqlova.