If I change
_, preds_index = preds.topk(1, dim=-1, largest=True, sorted=True)
to
_, preds_index = preds.topk(k=5, dim=-1, largest=True, sorted=True),
the program raise error
dataset_root: data_lmdb_release/evaluation/CUTE80 dataset: /
sub-directory: /. num samples: 288
Traceback (most recent call last):
File "test.py", line 318, in <module>
test(opt)
File "test.py", line 271, in test
benchmark_all_eval(model, criterion, converter, opt)
File "test.py", line 57, in benchmark_all_eval
_, accuracy_by_best_model, norm_ED_by_best_model, _, _, _, infer_time, length_of_data = validation(
File "test.py", line 151, in validation
preds_str = converter.decode(preds_index[:,1], length_for_pred)
File "/home/WeiHongxi/PengHusile/Server/ViTSTR/utils.py", line 197, in decode
text = ''.join([self.character[i] for i in text_index[index, :]])
IndexError: too many indices for tensor of dimension 1```
or the accuracy turn to 0%
If I change
_, preds_index = preds.topk(1, dim=-1, largest=True, sorted=True)to_, preds_index = preds.topk(k=5, dim=-1, largest=True, sorted=True), the program raise error