Closed zyc573823770 closed 2 years ago
apologies for late reply. The response_seq_class_m
is used for the input sequence (the stuff that transformer decoder sees), the label/target sequence (the stuff that transformer decoder is asked to predict) is from response_seq
which is either real tokens or fake class token. hope that clarifies it.
apologies for late reply. The
response_seq_class_m
is used for the input sequence (the stuff that transformer decoder sees), the label/target sequence (the stuff that transformer decoder is asked to predict) is fromresponse_seq
which is either real tokens or fake class token. hope that clarifies it.
Why do I randomly change the label of the Input Sequence? I don't really understand.
It seems that the labels in output target are either rand or fake, without any ground truth in it which is different from the paper in the end of section 2.3 that After noise objects are synthesised and discretized, we then append them in the end of the original input sequence.
https://github.com/google-research/pix2seq/blob/6d45f77fcbb1905aca3e42678a2a079907ad17d0/tasks/object_detection.py#L399![image](https://user-images.githubusercontent.com/42412854/167727337-70035f7c-9a8f-4558-8be5-a171980c0f5c.png)