| | |
|---|
| | | ocr, ocr_lens, _ = self.text_encoder(ocr, ocr_lengths) |
|---|
| | | fusion_out, _, _, _ = self.fusion_encoder(encoder_out,None, ocr, None) |
|---|
| | | encoder_out = encoder_out + fusion_out |
|---|
| | | |
|---|
| | | pdb.set_trace() |
|---|
| | | # c. Passed the encoder result and the beam search |
|---|
| | | nbest_hyps = self.beam_search( |
|---|
| | | x=encoder_out[0], maxlenratio=kwargs.get("maxlenratio", 0.0), minlenratio=kwargs.get("minlenratio", 0.0) |
|---|
| | |
|---|
| | | pdb.set_trace() |
|---|
| | | text = tokenizer.tokens2text(token) |
|---|
| | | pdb.set_trace() |
|---|
| | | |
|---|
| | | |
|---|
| | | text_postprocessed, _ = postprocess_utils.sentence_postprocess(token) |
|---|
| | | result_i = {"key": key[i], "token": token, "text": text_postprocessed} |
|---|
| | | results.append(result_i) |
|---|
