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**Collection**: [NLP]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
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Adds apex import guards.
Please have one of the following:
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# What does this PR do?
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# Changelog
- Improves the PR template to include meta info + help reviewers in detailed review
# Before your PR is "Ready for review"
**Pre checks**:
- [x] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
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# What does this PR do?
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* Fixes # (issue) ITN whitelist issues
* New feature: (short feature description): support for IP address, card num, country code
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Upgrade to 22.01 container
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Hi,
Thank you very much for the great Speech Data Explorer (SDE) tool. I have faced a problem when connecting a simple lexicon (or vocab as the --vocab argument) to the SDE. My vocab file has just one word in each line and I have followed the SDE code and it can load it correctly. But the OOV words doesn't sh... | {
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Please have one of the following:
* New feature: (short feature description) FastPitch training tutorial.
This PR adds FastPitch tutorial to the same notebook as MixerTTS as both generate spectrogram. This tutorial goes through the data download, preprocess, FastPitch im... | {
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I am trying to train a TTS model with NeMo implementations of **Tacotron2** and **WaveGlow** architectures. The dataset is my own and includes 15 hours of speech in Slovenian language (sample rate 22050, 16-bit, mono). Label set has 83 symbols, all within 0-255 ASCII.
The dataset has been tested and shou... | {
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[Unigram is better than BPE.](https://arxiv.org/pdf/2004.03720.pdf)
[SpeechBrain supports Unigram.](https://colab.research.google.com/drive/12yE3myHSH-eUxzNM0-FLtEOhzdQoLYWe?usp=sharing) | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/3564 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/3564/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/3564/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/3564/events | https://github.com/NVIDIA/NeMo/pull/3564 | 1,118,569,753 | PR_kwDOC_bI7s4xyxqR | 3,564 | [TTS] Fix bugs in HiFi-GAN (scheduler, optimizers) and add input_example() in Mixer-TTS/Mixer-TTS-X | {
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} | # What does this PR do?
* Fixes:
* https://github.com/NVIDIA/NeMo/issues/3557
* https://github.com/NVIDIA/NeMo/issues/3549
* Use `self.optimizers` in HiFi-GAN
* Fix typo in FastPitch's `input_example()`
Signed-off-by: Oktai Tatanov <oktai.tatanov@gmail.com> | {
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Used instructions from notebooks:
https://github.com/NVIDIA/NeMo/blob/main/tutorials/asr/Streaming_ASR.ipynb
https://github.com/NVIDIA/NeMo/blob/main/tutorials/asr/Online_ASR_Microphone_Demo.ipynb
For some reason, the recognized text differs from what the model produces by the boxed method ... | {
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} | # What does this PR do?
Please have one of the following:
* Fixes #3561
## Before your PR is "Ready for review"
- [x] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [x] Did you write any new necessary tests?
- [x] Did you add or updated a... | {
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} | null | null | null | **Describe the bug**
If model is being restored from checkpoint path from a config field `model.common_dataset_parameters.label_vocab_dir` should not be prepended to config fields `model.class_labels.punct_labels_file` and `model.class_labels.punct_labels_file`. This because in a checkpoint these labels files are in... | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/3560 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/3560/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/3560/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/3560/events | https://github.com/NVIDIA/NeMo/issues/3560 | 1,118,333,618 | I_kwDOC_bI7s5CqGqy | 3,560 | Total crap and not accurate | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/3559 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/3559/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/3559/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/3559/events | https://github.com/NVIDIA/NeMo/issues/3559 | 1,118,193,113 | I_kwDOC_bI7s5CpkXZ | 3,559 | No module named 'apex' in colab notebook 00_NeMo_Primer.ipynb | {
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When running `00_NeMo_Primer.ipynb` notebook during `import nemo.collections.nlp as nemo_nlp` raises an error:
`ModuleNotFoundError: No module named 'apex'`
**Steps/Code to reproduce bug**
Opened in colab tutorial notebook [![Open In Colab](https://colab.research.google.com/assets/colab-b... | {
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```
[NeMo W 2022... | {
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I got this error when exporting mixer_tts model to onnx model:
AttributeError: 'MixerTTSModel' object has no attribute 'input_example'
**Steps/Code to reproduce bug**
```
from nemo.collections.tts.models import MixerTTSModel
spec_generator = MixerTTSModel.from_pretrained("tts_en_lj_mixe... | {
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} | # What does this PR do?
Please have one of the following:
- Update pytorch_lightning deprecated variables, namely:
> - accelerator to the trainer now takes the type of accelerator device than distributed type
> - distributed type is handled by strategy flag
> - previously: accelerator='ddp' now accelerator=... | {
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} | Current progress on tn for spanish. Throwing up here as a draft to finish on personal account as community contribution. At the moment, fractions, decimals, cardinals, dates, and ordinals are functioning and part of main normalization flow for tn_es. Also all pytests are valid. Need to adjust copyright headers. | {
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I am able to load a pretrained version of Quartznet, and when I explore the encodings, I can't figure out a way to convert them into something I can analyze, like a list, np.ndarray or pandas Series. This is for a voice analysis project and I am looking to access the encodings directly. thanks s... | {
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} | # Bugfix
- Fixes an issue where Wandb will not plot the updated configs even after calling model.cfg = new_cfg.
Closes #3372
Signed-off-by: smajumdar <titu1994@gmail.com> | {
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} | # Changelog
- Add support for `clamp` kwarg in rnnt loss numba.
- Update configs to support this argument.
# Note
- This is different from using Pytorch Lightning `gradient_clip_val>0` as that will clip all gradients of the entire network by the limits of the clamp, this will only clip the gradient of the joint ... | {
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Checking out the docs https://docs.nvidia.co... | {
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} | null | null | null | **Describe the bug**
I am trying to do Ptuning with Nemo with my custom Megtraon gpt2 and tokenizers that were trained using huggingface tokenizers. But when I provide all the configs and run, I get a vocabulary error.
```
root@ptuning-7d8497bf49-r8spb:/workspace/sean/ptuning# PYTHONPATH=NeMo-feature_ptune pytho... | {
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} | null | null | null | **Is your feature request related to a problem? Please describe.**
Can I use NeMo on a gpu without cudas in it?
A clear and concise description of what the problem is. Ex. I'm always frustrated when [...]
As a guy who does not have access to a Nvidia gpu I always find it hard to work with ai related projects,
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} | This PR refactor Megatron T5 to a modular base encoder-decoder class hierarchy, and a T5 class which customizes the base class. The goal of the refactor is to support multiple encoder-decoder models with minimal code redundancy.
# Refactor High Level Description
Hierarchy tree is expressed below via list alignme... | {
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I am unable to use nemo models due to some issue with the tokenizer:
```
from nemo.collections.asr.models import EncDecCTCModel
File "/home/linux/miniconda3/envs/env/lib/python3.9/site-packages/nemo/collections/asr/__init__.py", line 15, in <module>
from nemo.collections.asr ... | {
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- Build a raw changelog automatically for every new NeMo release based on a comparison from PRs between newest version and previous version.
- Raw changelog is then tidied to display on final page.
# Usage
Call the builder and visit the GitHub Action that builds the changelog. It's "Print Changelo... | {
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} | Signed-off-by: Zhilin Wang <zhilinw@nvidia.com>
Design based on attached diagram
[UML proposed dialogue1.pdf](https://github.com/NVIDIA/NeMo/files/7946212/UML.proposed.dialogue1.pdf)
Currently supports SGD-QA (Bert-based) and Huggingface GPT2 models, and planning to support other models. | {
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Fixed Bugs 3509889 and 3509839:
https://nvbugswb.nvidia.com/NVBugs5/redir.aspx?url=/3509889 [ML-NeMo][Tesla A30] Token_Classification-BioMegatron.ipynb contains a typo
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} | # Bugfix
- Enforce UTF-8 on all file reading and writing. Fixes a bug with some locales not enforcing utf 8.
- If you are still facing Unicode errors, you have to pass `LC_ALL=en_US.UTF-8` before launching your python command.
Fixes https://github.com/NVIDIA/NeMo/issues/3452 | {
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- Enforce utf-8 on all file reading and writing inside nemo. | {
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} | Fixes Duplicate cells in entity linking notebook bug
Bug 3509934 (https://nvbugswb.nvidia.com/NVBugs5/redir.aspx?url=/3509934 [ML-NeMo][Quadro GV100] Entity_Linking_Medical.ipynb tutorial notebook contains duplicate cells)
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Bug 3509934 (https://nvbugswb.nvidia.com/NVBugs5/redir.aspx?url=/3509934 [ML-NeMo][Quadro GV100] Entity_Linking_Medical.ipynb tutorial notebook contains duplicate cells)
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} | # Changelog
- Add script to convert HuggingFace ASR datasets to preprocessed NeMo compatible datasets.
- These datasets can then be converted to tarred datasets as always.
# NOTE:
- The converted datasets DO NOT PERFORM TEXT PREPROCESING. That should be handled by the user at manifest level.
- The offline mode d... | {
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```
W0125 21:12:08.102883 140527509010240 schema.py:118] Validation schema not found for nemo.collections.tts.models.Tacotron2Model.
That means Riva does not yet support a pipeline for this network and likel... | {
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} | Several fixes to get the FastSpeech2-HiFiGAN training to work (#3360). The normal training command should work now.
- Config reference to n_mels corrected
- Fix output type issue when `splices` is None for FS2-HiFiGAN
- Removed `spec` from calls to forward function in FS2-HiFiGAN
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* update TitaNet conf, to reflect what was published in paper | {
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Thanks | {
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When installing nemo[all] via pip from source, some of the data files used to build the french ITN grammar are missing from site-packages (e.g. those in folders electronic, measurements, money, numbers, time). These folders are the only ones that are not packages i.e. missing `__init__.py` files... | {
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} | null | null | null | Hello and so happy to see you use Pytorch-Lightning! :tada:
Just wondering if you already heard about quite the new **Pytorch Lightning (PL) ecosystem CI** where we would like to invite you to... You can check out our blog post about it: [Stay Ahead of Breaking Changes with the New Lightning Ecosystem CI](https://dev... | {
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Below error is thrown while importing `nemo.collections.asr` package
```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/local/miniconda3/envs/nemo1/lib/python3.8/site-packages/nemo/collections/asr/__init__.py", line 15, in <module>
from nemo.co... | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/3495 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/3495/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/3495/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/3495/events | https://github.com/NVIDIA/NeMo/issues/3495 | 1,111,899,503 | I_kwDOC_bI7s5CRj1v | 3,495 | Dependence of the WER on batch size in val set? | {
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Trained the QuartzNet15x5 from scratch on the dataset An4 for 200 epochs. When I try to calculate the WER using the method given in the first tutorial, I noticed a strange dependence of the batch size on the size of the resulting error value. The larger the batch size, the smaller the error, wha... | {
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I can train WaveGlow models, but when I try to load checkpoints or `.nemo` files back, I am not able to.
**Steps/Code to reproduce bug**
Train, in a Google Colab GPU environment with or without Apex, a Waveglow 16khz model for one epoch. When attempting to load it back, either the checkpoi... | {
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I am trying to train a TTS model. I followed the steps of the documentation but still cannot train the model.
I always get RuntimeError: Cuda out of memory. So the program crash.
**Steps/Code to reproduce bug**
The way to reproduce the error is to execute this command from the console in a ... | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/3492 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/3492/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/3492/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/3492/events | https://github.com/NVIDIA/NeMo/pull/3492 | 1,111,638,102 | PR_kwDOC_bI7s4xcjBd | 3,492 | Refactor megatron apex guard | {
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} | Starting of a nemo:1.5.0 container and using `./reinstall.sh` to upgrade to nemo:1.6.0rc0 the `import nemo.collections.nlp` will crash:
```
Python 3.8.12 | packaged by conda-forge | (default, Sep 29 2021, 19:52:28)
[GCC 9.4.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> imp... | {
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} | 1. Since pickled features file is always created, it needs to be removed from tarred dataset. Add removal of pickled features from tarred dataset.
2. Make a path to pickled features file an attribute of `BertPunctuationCapitalizationDataset` class. | {
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} | Remove unstable and not essential link
Fix typo in vad related tutorials. | {
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} | Added P-Tuning method to use Large Megatron GPT model for downstream NLP tasks.
The `PTune_Sentiment_Analysis.ipynb` tutorial notebook shows how to use P-Tuning for financial sentiment analysis. It achieve 92% accuracy using GPT 344M model. | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/3487 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/3487/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/3487/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/3487/events | https://github.com/NVIDIA/NeMo/pull/3487 | 1,110,940,104 | PR_kwDOC_bI7s4xaJor | 3,487 | Properly support -1 for labels in ctc char models | {
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} | # Changelog
- Add support for -1 in num_classes if vocabulary is provided for CTC char models.
Signed-off-by: smajumdar <titu1994@gmail.com> | {
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} | Fixed few issues due to weight key renaming in O2 style
Signed-off-by: Yu Yao <yuya@nvidia.com> | {
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} | # Changelog
- Add support for tarred dataset support for Nvidia DALI 1.11+ | {
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} | - [x] Create unify downloading and processing TTS datasets in `scripts/dataset_proccesing/tts`
- [x] Add `VocoderDataset`
- [x] Fix problem with collision in name (e.g. LibriTTS suffers) for supplementary data in `TTSDataset`
- [x] Other minor updates in `collection.tts.torch`
Signed-off-by: Oktai Tatanov <okt... | {
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I am getting this error when I try to instantiate ASR model (following [this](https://github.com/NVIDIA/NeMo/blob/v1.0.0/tutorials/asr/01_ASR_with_NeMo.ipynb) tutorial):
`ValueError: num_samples should be a positive integer value, but got num_samples=0`
But it's quite strange because I am ... | {
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