[Bart] Question for BartModel Output shape
Hi I’m trying to fine-tune multilingual-Bart with Korean to generate some texts.while I tried to pass my datas into model, I can’t under stand why the output shape of the model is different from what I expected.Settings : I used MBartTokenizer and BartForConditionalGenerationfor batch, I used prepare_translation_batch to make datas as batch, inputs_ids and target_ids.I also need decoder_input_ids(form like [tgt_lang_code, seqence, eos]), so I made it.Here’s the problem.BartForConditionalGeneration’s forward pass needs input_ids necessarily. From the Docs of Bart, If I pass only the ‘input_ids’ to the model(it can include attention_mask), the model’s decoder wouldn’t have it’s own input, so It takes ‘input_ids’ as their input.And the shape of the prediction_scores in returns should be (batch_size, seq_len, vocab_size) and It worked rightBut, When I pass the ‘input_ids’ and ‘decoder_input_ids’ together to the model, the shape of the prediction_scores shows (batch_size, 1 , vocab_size) all the time.I think when I pass the inputs together, The shape of prediction_scores in returns should be like (batch_size, decoder_input_seq_len, vocab_size)I don’t know why this happen. Maybe I totally misunderstood the model at all.The reason I made this topic is I need a clean view of this problem.Any advice would be appreciated.Thank you.q1904×785 15 KB
2020-07-19T21:47:42Z
passuse_cache=Falseto forward. Confusing, I know.
2020-07-20T05:51:14Z
It worked. Thank you very much!