TypeError: _get_batch_preds() takes 1 positional argument but 2 were given

[Atefeh197]

Hello

I want to do "Automatic Speech Recognition with Speaker Diarization" based on the link: this but I got error in this line:

word_hyp, word_ts_hyp = asr_decoder_ts.run_ASR(asr_model)

it is : TypeError: _get_batch_preds() takes 1 positional argument but 2 were given

it is my run:

╭───────────────────── Traceback (most recent call last) ──────────────────────╮
│ /home/a/PycharmProjects/Speaker_identification/speaker_identify.py:110 │
│ in │
│ │
│ 107 from nemo.collections.asr.parts.utils.decoder_timestamps_utils import │
│ 108 asr_decoder_ts = ASRDecoderTimeStamps(cfg.diarizer) │
│ 109 asr_model = asr_decoder_ts.set_asr_model() │
│ ❱ 110 asr_decoder_ts.run_ASR(asr_model) │
│ 111 │
│ 112 print("Decoded word output dictionary: \n", word_hyp['an4_diarize_test │
│ 113 print("Word-level timestamps dictionary: \n", word_ts_hyp['an4_diarize │
│ │
│ /home/a/NeMo/nemo/collections/asr/parts/utils/decoder_timestamps_utils. │
│ py:656 in run_ASR_BPE_CTC │
│ │
│ 653 │ │ │ │ logging.info(f"[{idx+1}/{len(self.audio_file_list)}] F │
│ 654 │ │ │ │ frame_asr.clear_buffer() │
│ 655 │ │ │ │ │
│ ❱ 656 │ │ │ │ hyp, greedy_predictions_list, log_prob = get_wer_feat_ │
│ 657 │ │ │ │ │ audio_file_path, │
│ 658 │ │ │ │ │ frame_asr, │
│ 659 │ │ │ │ │ self.chunk_len_in_sec, │
│ │
│ /home/a/NeMo/nemo/collections/asr/parts/utils/decoder_timestamps_utils. │
│ py:231 in get_wer_feat_logit │
│ │
│ 228 │ """ │
│ 229 │ asr.reset() │
│ 230 │ asr.read_audio_file_and_return(audio_file_path, delay, model_strid │
│ ❱ 231 │ hyp, tokens, log_prob = asr.transcribe_with_ts(tokens_per_chunk, d │
│ 232 │ return hyp, tokens, log_prob │
│ 233 │
│ 234 │
│ │
│ /home/a/NeMo/nemo/collections/asr/parts/utils/decoder_timestamps_utils. │
│ py:284 in transcribe_with_ts │
│ │
│ 281 │ def transcribe_with_ts( │
│ 282 │ │ self, tokens_per_chunk: int, delay: int, │
│ 283 │ ): │
│ ❱ 284 │ │ self.infer_logits() │
│ 285 │ │ self.unmerged = [] │
│ 286 │ │ self.part_logprobs = [] │
│ 287 │ │ for idx, pred in enumerate(self.all_preds): │
│ │
│ /home/a/.local/lib/python3.8/site-packages/torch/utils/_contextlib.py:1 │
│ 15 in decorate_context │
│ │
│ 112 │ @functools.wraps(func) │
│ 113 │ def decorate_context(*args, **kwargs): │
│ 114 │ │ with ctx_factory(): │
│ ❱ 115 │ │ │ return func(*args, **kwargs) │
│ 116 │ │
│ 117 │ return decorate_context │
│ 118 │
│ │
│ /home/a/NeMo/nemo/collections/asr/parts/utils/streaming_utils.py:762 in │
│ infer_logits │
│ │
│ 759 │ │ while len(frame_buffers) > 0: │
│ 760 │ │ │ self.frame_buffers += frame_buffers[:] │
│ 761 │ │ │ self.data_layer.set_signal(frame_buffers[:]) │
│ ❱ 762 │ │ │ self._get_batch_preds(keep_logits) │
│ 763 │ │ │ frame_buffers = self.frame_bufferer.get_buffers_batch() │
│ 764 │ │
│ 765 │ @torch.no_grad() │
│ │
│ /home/a/.local/lib/python3.8/site-packages/torch/utils/_contextlib.py:1 │
│ 15 in decorate_context │
│ │
│ 112 │ @functools.wraps(func) │
│ 113 │ def decorate_context(*args, **kwargs): │
│ 114 │ │ with ctx_factory(): │
│ ❱ 115 │ │ │ return func(*args, **kwargs) │
│ 116 │ │
│ 117 │ return decorate_context │
│ 118 │
╰──────────────────────────────────────────────────────────────────────────────╯

How I can fix it?