本文整理匯總了Python中opts.translate_opts方法的典型用法代碼示例。如果您正苦於以下問題：Python opts.translate_opts方法的具體用法？Python opts.translate_opts怎麽用？Python opts.translate_opts使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類opts的用法示例。
在下文中一共展示了opts.translate_opts方法的1個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: main
# 需要導入模塊: import opts [as 別名]
# 或者: from opts import translate_opts [as 別名]
def main(anno_file_name, col_headers, raw_args=None):
parser = argparse.ArgumentParser(description='evaluate.py')
opts.translate_opts(parser)
opt = parser.parse_args(raw_args)
torch.cuda.set_device(opt.gpu)
opt.db_file = os.path.join(opt.data_path, '{}.db'.format(opt.split))
opt.pre_word_vecs = os.path.join(opt.data_path, 'embedding')
dummy_parser = argparse.ArgumentParser(description='train.py')
opts.model_opts(dummy_parser)
opts.train_opts(dummy_parser)
dummy_opt = dummy_parser.parse_known_args([])[0]
opt.anno = anno_file_name
engine = DBEngine(opt.db_file)
js_list = table.IO.read_anno_json(opt.anno)
prev_best = (None, None)
sql_query = []
for fn_model in glob.glob(opt.model_path):
opt.model = fn_model
translator = Translator(opt, dummy_opt.__dict__)
data = table.IO.TableDataset(js_list, translator.fields, None, False)
test_data = table.IO.OrderedIterator(
dataset=data, device=opt.gpu, batch_size=opt.batch_size, train=False, sort=True, sort_within_batch=False)
# inference
r_list = []
for batch in test_data:
r_list += translator.translate(batch)
r_list.sort(key=lambda x: x.idx)
pred = r_list[-1]
sql_pred = {'agg':pred.agg, 'sel':pred.sel, 'conds': pred.recover_cond_to_gloss(js_list[-1])}
sql_query = Query(sql_pred['sel'], sql_pred['agg'], sql_pred['conds'])
try:
ans_pred = engine.execute_query(
js_list[-1]['table_id'], Query.from_dict(sql_pred), lower=True)
except Exception as e:
ans_pred = None
return sql_query.get_complete_query(col_headers), ans_pred