Comments (7)
If you do pip install -e .[all]
, then the main branch version of the scripts are needed.
If you do pip install nemo_toolkit[all]==VERSION
then you need to switch to VERSION branch before going to the example scripts.
The two mismatches you're seeing are
- Traceback (most recent call last):
File "/home/aidos/exp/NeMo/examples/asr/speech_to_text_eval.py", line 71, in
import transcribe_speech
File "/home/aidos/exp/NeMo/examples/asr/transcribe_speech.py", line 34, in
from nemo.collections.asr.parts.utils.transcribe_utils import (
ImportError: cannot import name 'read_and_maybe_sort_manifest' from 'nemo.collections.asr.parts.utils.transcribe_utils' (/home/aidos/nemo_venv/lib/python3.11/site-packages/nemo/collections/asr/parts/utils/transcribe_utils.py)
I tried this on both transcribe speech and speech to text eval just a moment ago - they work.
Most likely you have an older version of main branch (or are using 1.23 branch and attempting to use the latest main script) - you need to pull from main again and install it.
- The dataclass issue - you're using Python 3.11 presumably. Its a bug with the dataclass handling, ill fix that in a PR in some time. If you want you can switch to 3.10 if its easy, or wait until I fix it.
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Can you paste your full stack trace ? Rnnt wer was merged into wer.py in NeMo 1.23.0, and we tested the eval script but might have missed something.
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Traceback (most recent call last):
File "/home/aidos/exp/NeMo/examples/asr/speech_to_text_eval.py", line 71, in <module>
import transcribe_speech
File "/home/aidos/exp/NeMo/examples/asr/transcribe_speech.py", line 34, in <module>
from nemo.collections.asr.parts.utils.transcribe_utils import (
ImportError: cannot import name 'read_and_maybe_sort_manifest' from 'nemo.collections.asr.parts.utils.transcribe_utils' (/home/aidos/nemo_venv/lib/python3.11/site-packages/nemo/collections/asr/parts/utils/transcribe_utils.py)
This exception is being thrown on main branch.
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I tried to switch to r1.23.0 and r1.22.0 etc. Further exceptions were thrown of different branches:
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You can't use the main branch script with the r1.23 branch or lower Nemo installation, you should switch to the correct branch of the installed NeMo version before using the script. So if you have 1.23 pip installed you need the 1.23.0 branch
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As to main, thanks for the trace, well take a look asap. Fyi @stevehuang52 @tbartley94
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You can't use the main branch script with the r1.23 branch or lower Nemo installation, you should switch to the correct branch of the installed NeMo version before using the script. So if you have 1.23 pip installed you need the 1.23.0 branch
I'm actually training on main branch. The Nemo toolkit has been install in python venv.
For the inference then, should I create another venv and install r1.23? Is speech_to_text_eval
script is working stable on that version?
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Related Issues (20)
- Issue with pip installing on windows due to youtokentome dependency HOT 1
- Tokenizer suggestion for fine tuning cache aware streaming model HOT 2
- Titanet-L Augmentation HOT 4
- Not found file "convert_mistral_hf_to_nemo.py" in /opt/NeMo/scripts/checkpoint_converters/ for Convert Mistral
- Precision Problem between nemo model and hugging face model HOT 2
- Llama2 70B SFT with FSDP failing HOT 2
- training config used for training stt_en_quartznet15x5 HOT 2
- llama2 training hangs when pp_size > 1 HOT 2
- Integration of Turn-Taking Models into Nemo Framework for Enhanced Realistic Conversations
- FileNotFoundError: Model stt_fa_fastconformer_hybrid_large was not found. HOT 6
- [Feature] Add Support on Multiple Metrics Reporting during Training Progress for Validation
- checkpoints not saved due to wrong loss comparison?
- when "write_predictions_to_file" is true,generate will fail。 HOT 1
- "RuntimeError: start (4) + length (1) exceeds dimension size (4)." when running cache aware streaming inference
- slow validation process HOT 2
- Optimizing Learning Rate Parameters in Model Fine-tuning
- AUDIO FILE SIZE for fine tuning STT En FastConformer Hybrid Transducer-CTC Large Streaming Multi HOT 1
- `EncDecCTCModel.transcribe(audio=...)` changed to `EncDecCTCModel.transcribe(paths2audio_files=...)` HOT 6
- Enormous number of `.nemo` checkpoints produced in training HOT 4
- [Conversion] How to convert Finetuned T5 checkpoint ended with `.ckpt` to `.nemo` checkpoint with NeMo toolkit?
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