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Variables `hidden_steps` (line 306) and `_SUPPORTED_ARCH` (line 337) in https://github.com/NVIDIA/NeMo/blob/main/nemo/collections/nlp/modules/common/transformer/transformer_bottleneck.py are not defined.
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2. Add amp precision casting decorator (use input precision as is) | {
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- Update script to generalize transcript to all ASR models (CTC/RNNT Char/Subword) | {
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I am trying to run the script self_alignment_pretraining.py (location - https://github.com/NVIDIA/NeMo/blob/main/examples/nlp/entity_linking/self_alignment_pretraining.py)
I keep getting the error: ModuleNotFoundError: No module named 'nemo'
I have tried installing the nemo toolkit using the following:
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I've encountered this using the [example config provided ](https://github.com/NVIDIA/NeMo/blob/ed2005eda9470cb2c7c42e7ca1bd6b2e5b7a8479/examples/nlp/token_classification/conf/punctuation_capitalization_config.yaml#L28)for the PunctuationCapitalizationModel. Currently, the default trainer params ... | {
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Need help with some moments:
1. How to perform GPU batched inference with trained model?
2. Is it possible to make MatchboxNet architecture more heavy? Encountered problem that https://github.com/NVIDIA/NeMo/blob/main/examples/asr/conf/matchboxnet/matchboxnet_3x1x64_v2.yaml was stucked on ~50% accuracy on cle... | {
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} | * Fix DALI log default floor and normalization formula
Signed-off-by: Joaquin Anton <janton@nvidia.com>
* Fix style
Signed-off-by: Joaquin Anton <janton@nvidia.com>
(cherry picked from commit ad75db34c816bff23f64de7a875d89c50c319c85) | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2873 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2873/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2873/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2873/events | https://github.com/NVIDIA/NeMo/issues/2873 | 1,004,602,342 | I_kwDOC_bI7s474QPm | 2,873 | "ASR_with_NeMo.ipynb" TypeError: TypeError: NeuralTypeComparisonResult.INCOMPATIBLE : Input type expected : axes: (batch, time); elements_type: AudioSignal input param_0 : freq: 16000 Input type found : axes: (batch, time); elements_type: VoidType | {
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I'm trying to run "ASR_with_NeMo.ipynb" in tutorials directory. In the section `Using an Out-of-the-Box Model`, I can successfully load `QuartzNet15x5Base-En`, but when I run `quartznet.transcribe(paths2audio_files=files)`, I get the following error:
```
TypeError: NeuralTypeComparisonResult.INCOMPAT... | {
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} | # Chanelog
- Upperbound PTL until https://github.com/PyTorchLightning/pytorch-lightning/pull/9642 is available in PTL 1.4.8
Signed-off-by: smajumdar <titu1994@gmail.com> | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2870 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2870/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2870/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2870/events | https://github.com/NVIDIA/NeMo/issues/2870 | 1,004,233,113 | I_kwDOC_bI7s4722GZ | 2,870 | How to create nemo_text_processing/text_normalization/en/data/numbers/cardinal_number_name.far? | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2869 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2869/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2869/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2869/events | https://github.com/NVIDIA/NeMo/pull/2869 | 1,004,171,243 | PR_kwDOC_bI7s4sIQ5G | 2,869 | Fix DALI log default floor and normalization formula | {
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} | Fixes the default floor value used for DALI log calculation, to match the one used in the torch based implementation (features.py). Sets the ddof and eps for normalization step, to match what is used in other implementations
Signed-off-by: Joaquin Anton <janton@nvidia.com> | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2867 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2867/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2867/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2867/events | https://github.com/NVIDIA/NeMo/pull/2867 | 1,003,366,148 | PR_kwDOC_bI7s4sFmvJ | 2,867 | bug fix for update to match sde | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2865 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2865/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2865/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2865/events | https://github.com/NVIDIA/NeMo/pull/2865 | 1,003,336,994 | PR_kwDOC_bI7s4sFgUh | 2,865 | Linear warmup cosine anneal schedule | {
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} | …n (#2858)
Signed-off-by: Joaquin Anton <janton@nvidia.com>
Co-authored-by: Somshubra Majumdar <titu1994@gmail.com>
(cherry picked from commit 6987b6cfc9c9769f61116d0ac5a49088798266f8) | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2863 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2863/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2863/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2863/events | https://github.com/NVIDIA/NeMo/pull/2863 | 1,003,126,596 | PR_kwDOC_bI7s4sEyDu | 2,863 | Fix abs_pos of Conformer | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2862 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2862/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2862/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2862/events | https://github.com/NVIDIA/NeMo/issues/2862 | 1,003,088,480 | I_kwDOC_bI7s47yepg | 2,862 | Speaker Verification | {
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```
verification_model = nemo_asr.models.ExtractSpeakerEmbeddingsModel.restore_from(... | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2861 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2861/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2861/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2861/events | https://github.com/NVIDIA/NeMo/pull/2861 | 1,002,849,150 | PR_kwDOC_bI7s4sD05B | 2,861 | add zero shot intent model | {
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} | - New model class ZeroShotIntentModel is a subclass of TextClassificationModel
- Allows training/inference with either three classes ("entailment", "contradiction", and "neutral") or two classes ("entailment" and "not_entailment")
- ZeroShotIntentDataset and ZeroShotIntentInferenceDataset are subclasses of GLUEDatase... | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2860 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2860/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2860/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2860/events | https://github.com/NVIDIA/NeMo/pull/2860 | 1,002,699,050 | PR_kwDOC_bI7s4sDTzK | 2,860 | Fix loading and resample audio in get_samples | {
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} | There are several bugs in this file:
1. librosa library is not imported.
2. librosa.core.resample is expecting float32 array and not int.
3. librosa.core.resample returns float32 array, so no need to re-convert it. | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2859 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2859/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2859/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2859/events | https://github.com/NVIDIA/NeMo/pull/2859 | 1,002,531,076 | PR_kwDOC_bI7s4sCu96 | 2,859 | MixerTTS, MixerTTSDataset and small updates in tts tokenizers | {
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} | * Mixer-TTS (with extended version, Mixer-TTS-X): https://arxiv.org/abs/2110.03584
* MixerTTSDataset
* Small updates in nemo/collections/tts/torch/tts_tokenizers.py | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2858 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2858/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2858/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2858/events | https://github.com/NVIDIA/NeMo/pull/2858 | 1,002,401,601 | PR_kwDOC_bI7s4sCSsA | 2,858 | Fix window_stride calculation in DALI pipeline & Fix dither generation | {
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} | Fixes a bug in the calculation of the window stride uses for spectrogram calculation in the DALI implementation.
Fixes a bug in the generation of gaussian noise (dither). Generate noise with the shape of the audio, instead of a single sample (bug)
Signed-off-by: Joaquin Anton <janton@nvidia.com> | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2857 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2857/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2857/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2857/events | https://github.com/NVIDIA/NeMo/issues/2857 | 1,001,599,190 | I_kwDOC_bI7s47szDW | 2,857 | BPE timestamp extraction example | {
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} | null | null | null | **Is your feature request related to a problem? Please describe.**
Not a problem, just seeking some guidance on how to replicate the timestamp extraction code featured within the [Offline_ASR](https://github.com/NVIDIA/NeMo/blob/main/tutorials/asr/Offline_ASR.ipynb) notebook. Currently experiencing difficulties adap... | {
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} | 1. Enabled encoder/decoder with different size in bottleneck architecture.
2. Validating encoder/decoder are with the same hidden_size in non-bottleneck parent class. | {
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} | - inference from a raw text file without labels added
- post-processing added to neural TN/ITN and WFST TN
- deleted redundant entries from Ru data | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2853 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2853/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2853/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2853/events | https://github.com/NVIDIA/NeMo/issues/2853 | 1,000,818,517 | I_kwDOC_bI7s47p0dV | 2,853 | [BUG] DALI result is worse than normal pytorch data loader | {
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When running the same training or even the same validation script without DALI, we get the expected WER.
However, when we enable DALI using the same configuration, we get much worse WER.
I have created a Google Colab example that replicates this issue, which can be found here:
https://colab.research.goog... | {
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} | null | null | null | Should both functions be something like `fst @ SINGULAR_TO_PLURAL` instead of `SINGULAR_TO_PLURAL @ fst`? Besides, it seems that these functions are not used actually.
https://github.com/NVIDIA/NeMo/blob/main/nemo_text_processing/text_normalization/en/graph_utils.py#L129
https://github.com/NVIDIA/NeMo/blob/main/n... | {
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python nmt_service.py occcur that
config.json
en-zh:"NGC/nmt_en_zh_transformer6x6"
zh-en:"NGC/nmt_zh_en_transformer6x6"
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![MicrosoftTeams-i... | {
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**speaker_reco_infer.py loads the model and manifestfiles and then breaks,
I guess its again a pytorch issue? wanted to use the model from yesterday:**
[NeMo W 2021-09-17 12:18:42 patch_utils:49] torch.stft() signature has been updated for PyTorch 1.7+
Please update PyTorch to remain co... | {
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If you can provide a notebook for finet... | {
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} | # Changelog
- Add pretrained checkpoints of RNNT models
- ContextNet RNNT trained on ASR SET
- ContextNet RNNT trained on MLS
- Conformer RNNT trained on ASR SET
- Conformer RNNT trained on MLS
- Add pretrained model for ECAPA TDNN (Speaker model)
Signed-off-by: smajumdar <titu1994@gmail.com> | {
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I am fine-tuning the conformer model, and I have noticed that the defined LR in the Yaml file is not used and another lower LR is actually used during training.
The defined LR is 0.005, but the actual reported LR on wandb is around 0.00000206 .
The warm-up rate is used correctly. Only the maximum LR is no... | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2832 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2832/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2832/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2832/events | https://github.com/NVIDIA/NeMo/issues/2832 | 998,381,430 | I_kwDOC_bI7s47ghd2 | 2,832 | Add support for `LightningDataModule` | {
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} | null | null | null | One of the [recommended](https://pytorch-lightning.readthedocs.io/en/latest/guides/data.html) ways of dealing with data in pytorch-lightning is using the `LigtningDataModule`. This allows decoupling the model code from the data code. Then the training code would look something like this:
```python
trainer = Trainer... | {
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I was trying to convert the CitriNet-1024-Gamma-0.25 to TensorRT Quantized Model, while following the example workflow given under the quantization section but facing the following issue
**Steps/Code to reproduce bug**
root@nvidia-DGX-Station:/workspace/nemo/NeMo/examples/asr/quantization# p... | {
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Apparently class `CharTokenizer` needs to be rewritten.
1. The tokenizer does not add special tokens such as `<EOS>` and `<CLS>` automatically, so it is not consistent with tokenizers like `yttm`.
2. To add special tokens, it is not enough to insert something like `"<EOS>"` into input text becau... | {
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} | Closes https://github.com/NVIDIA/NeMo/issues/2817
Signed-off-by: smajumdar <titu1994@gmail.com> | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2824 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2824/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2824/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2824/events | https://github.com/NVIDIA/NeMo/pull/2824 | 997,524,195 | PR_kwDOC_bI7s4rzhjt | 2,824 | Tn punct train | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2823 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2823/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2823/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2823/events | https://github.com/NVIDIA/NeMo/pull/2823 | 997,359,996 | PR_kwDOC_bI7s4rzAbU | 2,823 | Enforce numba compat | {
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} | # TODO
- Revert this patch after CI update
Signed-off-by: smajumdar <titu1994@gmail.com> | {
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} | null | null | null | I am facing issue when I train a tansformer LM, its giving attribute error 'NoneType' object has no attribute 'get. Please help me to resolve this
I have update the tansformer config file as given below
train_ds = "dummydata.txt"
vocab="vocab.txt"
config.model.train_ds.file_name = train_ds
config.model.validat... | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2820 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2820/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2820/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2820/events | https://github.com/NVIDIA/NeMo/pull/2820 | 996,341,810 | PR_kwDOC_bI7s4rvy3R | 2,820 | Temporarily disable numba cuda tests from running | {
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- Temporarily disable numba tests from running unti CI updates
Signed-off-by: smajumdar <titu1994@gmail.com> | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2819 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2819/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2819/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2819/events | https://github.com/NVIDIA/NeMo/pull/2819 | 996,288,688 | PR_kwDOC_bI7s4rvn95 | 2,819 | Update ContextNet RNNT configs | {
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- Add char based ContextNet config
- Update subword based ContextNet config
- Fix Mandarin Citrinet pretrained model info | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2818 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2818/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2818/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2818/events | https://github.com/NVIDIA/NeMo/pull/2818 | 996,276,604 | PR_kwDOC_bI7s4rvlvJ | 2,818 | Megatron GPT training with NeMo tokenizers | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2817 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2817/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2817/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2817/events | https://github.com/NVIDIA/NeMo/issues/2817 | 996,096,939 | I_kwDOC_bI7s47Xzur | 2,817 | DALI Audio To Text Fails | {
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I am trying to train the conformer model with the DALI input pipeline, but it crash at the very early start.
Here is the logs:
```
[NeMo I 2021-09-14 16:32:36 mixins:147] Tokenizer SentencePieceTokenizer initialized with 128 tokens
[NeMo I 2021-09-14 16:32:36 ctc_bpe_models:172]
Replacing placehold... | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2814 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2814/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2814/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2814/events | https://github.com/NVIDIA/NeMo/pull/2814 | 995,555,854 | PR_kwDOC_bI7s4rtSM1 | 2,814 | remove test | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2813 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2813/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2813/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2813/events | https://github.com/NVIDIA/NeMo/pull/2813 | 995,363,616 | MDExOlB1bGxSZXF1ZXN0NzMzMTM4MjYz | 2,813 | Tarred dataset for text normalization model | {
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} | Currently we save the value of the validation metric into the name of the checkpoints upto 2 numbers after the decimal point. For some models like ASR where we have WER and numbers are less than 1, it can cause an issue. The experiment manager cannot find the right topk checkpoints. | {
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The validation step is not running when training a [mt_enc_dec](https://github.com/NVIDIA/NeMo/blob/r1.2.0/nemo/collections/nlp/models/machine_translation/mt_enc_dec_model.py) model using `TarredTranslationDataset`. As a result, the checkpoint call back is not invoked and no validation metrics a... | {
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trainer.fit(first_asr_model)
ValueError: Cannot resolve schedulerDictConfig'. Available optimizers are : dict_keys(['WarmupPolicy', 'WarmupHoldPolicy', 'SquareAnnealing', 'CosineAnnealing', 'NoamAnnealing', 'WarmupAnne... | {
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I need to take the exact time each word was said to build a transcription "timeline".
I saw that this script exemplifies how to accomplish this task
https://colab.research.google.com/github/NVIDIA/NeMo/blob/stable/tutorials/asr/Offline_ASR.ipynb#scrollTo=a-LSg9dSL_O1
However, as it was done, I only have the in... | {
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The cut-audio.py script fails if using models other than QuartzNet15x5Base-En, e.g. stt_en_quartznet15x5 or stt_en_jasper10x5dr.
Traceback (most recent call last):
File "tools/ctc_segmentation/scripts/cut_audio.py", line 299, in <module>
stats = process_alignment(alignment_file, ... | {
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} | # Bugfix
- Fix maes num steps < 2, force to be >= 2 for now until auto tuning is ready
- Fix lr scheduler division by 0 error if num_workers is 0
- Fix dataloader injection when provided base dictionary and not DictConfig
- Fix DALI on CPU
Signed-off-by: smajumdar <titu1994@gmail.com> | {
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} | Updating ASR_with_SpeakerDiarization.ipynb.
Currently, ASR with diarization only supports QuartzNet. We will be adding more models later on. | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2799 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2799/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2799/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2799/events | https://github.com/NVIDIA/NeMo/pull/2799 | 992,646,793 | MDExOlB1bGxSZXF1ZXN0NzMwOTQ5NTY1 | 2,799 | Update container and Dockerfile | {
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} | # Changelog
- bump container to 21.08
Signed-off-by: smajumdar <titu1994@gmail.com> | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2798 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2798/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2798/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2798/events | https://github.com/NVIDIA/NeMo/pull/2798 | 992,508,662 | MDExOlB1bGxSZXF1ZXN0NzMwODMwNDA4 | 2,798 | NMT input ID validity test for negative values | {
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} | This PR extends validity checks of src/tgt input IDs:
1. Added a test for special tokens being valid (i.e., non-negative) for Sentencepiece tokenizer.
2. Extended MTEncDecModel id validity test to include non-negativity.
3. Added `model.validate_input_ids` to `MTEncDecModel` config to allow disabling id validity (... | {
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} | null | null | null | Hi, I installed the nemo 1.3.0 latest version recently and find there is an attribute error as shown below. Although I have reinstall my environment for a few times, it still have this error. Has anyone encounter this recently with NeMo 1.3.0?
my code：
quartznet = nemo_asr.models.EncDecCTCModel.restore_from("./model/... | {
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} | Fixed a spelling mistake.
<img width="979" alt="typo fix" src="https://user-images.githubusercontent.com/29411721/132643791-53cb2ae7-01bf-4357-87ff-72d5e31b89ee.png">
Signed-off-by: kiranscaria <kiranscaria@outlook.com> | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2794 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2794/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2794/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2794/events | https://github.com/NVIDIA/NeMo/issues/2794 | 991,026,715 | MDU6SXNzdWU5OTEwMjY3MTU= | 2,794 | Cannot reproduce environment | {
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} | null | null | null | I can't reproduce the environment to run the code in this tutorial https://docs.nvidia.com/deeplearning/nemo/user-guide/docs/zh/latest/nlp/bert_pretraining.html , I have followed pip installation instructions but I keep getting errors when I import things
AttributeError: module 'nemo.collections.nlp.data' has n... | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2793 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2793/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2793/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2793/events | https://github.com/NVIDIA/NeMo/issues/2793 | 990,828,970 | MDU6SXNzdWU5OTA4Mjg5NzA= | 2,793 | Get features from given input wav using preprocessor of an asr model. | {
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} | null | null | null | **Describe the bug**
For inference, i would like to try the feature extractor part individually using [.get_features()](https://github.com/NVIDIA/NeMo/blob/65bcb68640469d1c77d7882520511546e67fc514/nemo/collections/asr/modules/audio_preprocessing.py) function that's already implemented. As i understood, the inputs fo... | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2792 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2792/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2792/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2792/events | https://github.com/NVIDIA/NeMo/pull/2792 | 990,780,578 | MDExOlB1bGxSZXF1ZXN0NzI5MzM5MjUy | 2,792 | New TTSDataset, tts tokenizers and g2ps | {
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} | This PR adds TTSDataset, english tokenizers (char and phoneme) and g2ps, base tokenizer and g2p classes for any other language.
I have fixed many bugs in [nemo/collections/asr/data/vocabs.py](https://github.com/NVIDIA/NeMo/blob/main/nemo/collections/asr/data/vocabs.py) and decided to put result in TTS code, because ... | {
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} | null | null | null | fastpich_hifigan_e2e.py (just like fastpitch.py) requires some extra processing setup steps and I can't find what generates the missing durations and pitch_char .pt files. Can anyone give me a hint?
There was an earlier defect closed that talked about needing to run tacotron2 training first.
I did that for a coupl... | {
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I have follow your [example](https://github.com/NVIDIA/NeMo/blob/v1.0.0b3/scripts/convasr_to_onnx.py) to convert a single asr model (.nemo) into encoder and decoder. But, it does not allow to export the Preprocessor model as .onnx. When i checked the... | {
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