renwei2024/nemo-github-issues huggingface dataset:
Release SOTA Lang ID model 
State: closed | Pull request: yes

# What does this PR do ?

Release SOTA lang id model AmberNet which achieves 5.22% error rate on the official evaluation set of [voxlingua107](http://bark.phon.ioc.ee/voxlingua107/) and update doc.

**Collection**: ASR

# Changelog 
# Usage

```python
langidmodel = nemo_asr.models.EncDecSpeakerLabelModel.from_pretrained(model_name="langid_ambernet")

```

# Before your PR is "Ready for review"
**Pre checks**:
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# Additional Information
* Related to # (issue)
probabilites -> probabilities
State: closed | Pull request: yes
Labels: name: cherry-pick

Signed-off-by: nithinraok <nithinrao.koluguri@gmail.com>

# What does this PR do ?

typo fix

**Collection**: ASR

# Changelog 
- probabilites -> probabilities

**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [x] Documentation
Fix and refactor consumed samples save/restore for Megatron models.
State: closed | Pull request: yes

Signed-off-by: MaximumEntropy <sandeep.subramanian.1@umontreal.ca>

# What does this PR do ?

Fixes and refactors things related to loading of consumed samples.

**Collection**: NLP

# Changelog 
- Add specific line by line info of high level changes in this PR.

# Usage
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```python
# Add a code snippet demonstrating how to use this 
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# Additional Information
* Related to # (issue)
rename to match prompt learning
State: closed | Pull request: yes

Signed-off-by: arendu <adithya.r@gmail.com>

# What does this PR do ?

renames the `output_file` for adapter and ia3 training to `pred_file_path`
**Collection**: [nlp]

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- Add specific line by line info of high level changes in this PR.

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# Add a code snippet demonstrating how to use this 
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# Additional Information
* Related to # (issue)
T5 prompt learning fixes missing from r.11.0 merge
State: closed | Pull request: yes

# What does this PR do ?

Adds fixes that were missing from r1.11.0 merge to main.

**Collection**: NLP

# Changelog 
- Add specific line by line info of high level changes in this PR.

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* You can potentially add a usage example below

```python
# Add a code snippet demonstrating how to use this 
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# Additional Information
* Related to # (issue)
[TTS] added missing German phoneme tokenizer
State: closed | Pull request: yes
Labels: name: cherry-pick

Signed-off-by: Xuesong Yang <1646669+XuesongYang@users.noreply.github.com>

# What does this PR do ?

This was added in r1.11.0, but not sure why it disappears for r1.12.0. See previous PR:https://github.com/NVIDIA/NeMo/pull/4756

**Collection**: [Note which collection this PR will affect]

# Changelog 
- Add specific line by line info of high level changes in this PR.

# Usage
* You can potentially add a usage example below

```python
# Add a code snippet demonstrating how to use this 
```

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# Additional Information
* Related to # (issue)
increase PR and Issue sweep quantity and active close PRs.
State: closed | Pull request: yes

Signed-off-by: Xuesong Yang <1646669+XuesongYang@users.noreply.github.com>

# What does this PR do ?
* refine the workflow name, and close stale messages;
* increase sweep quantity for PR and Issues at each cycle;
* activate close for inactive PRs in 30 days.


**Collection**: [Note which collection this PR will affect]

# Changelog 
- Add specific line by line info of high level changes in this PR.

# Usage
* You can potentially add a usage example below

```python
# Add a code snippet demonstrating how to use this 
```

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# Additional Information
* Related to # (issue)
Add spe_split_by_unicode_script arg
State: closed | Pull request: yes

# What does this PR do ?

Expose the `spe_split_by_unicode_script` SentencePiece cmd line flag to the tokenizer generation script.

Arabic text contains diacritics that can influence the meaning of a word, therefore, they must be considered part of a character when generating a tokenizer vocabulary.
The `sentencepiece` library however does not consider diacritics as part of the word and generally considers it as a separate token altogether.
As a result, the diacritics are generally stripped as separate tokens from the word and the generated vocabulary does not properly represent the words in the dataset.

By adding this flag, we allow the SPE library to consider multiple unicode scripts as a single "piece".
See the comments on the flag [here](https://github.com/google/sentencepiece/blob/9f3ed99f5c68609fc94ac83a5c0aea9eb163f6d9/src/sentencepiece_model.proto#L135).

**Collection**: ASR

# Changelog 
- Expose the `spe_split_by_unicode_script` SentencePiece command line flag to the tokenizer generation script.

# Usage

```sh
python process_asr_text_tokenizer.py --manifest=/path/to/dataset_manifest.json \
        --data_root=tokenizers/datatset \
        --vocab_size=1024 \
        --tokenizer=spe \
        --spe_no_spe_split_by_unicode_script \
        --log
```

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[TTS] remove phonemizer.py
State: closed | Pull request: yes

Signed-off-by: Xuesong Yang <1646669+XuesongYang@users.noreply.github.com>

# What does this PR do ?

we decided to remove phonemizer python script. We decided to add an instruction about how to transliterate graphemes into phonemes using phonemizer + espeak in the tutorial.

**Collection**: [Note which collection this PR will affect]

# Changelog 
- Add specific line by line info of high level changes in this PR.

# Usage
* You can potentially add a usage example below

```python
# Add a code snippet demonstrating how to use this 
```

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# Additional Information
* Related to # (issue)
[TTS] added missing German phoneme tokenizer
State: closed | Pull request: yes

Signed-off-by: Xuesong Yang <1646669+XuesongYang@users.noreply.github.com>

# What does this PR do ?

This was added in r1.11.0, but not sure why it disappears for r1.12.0. See previous PR:https://github.com/NVIDIA/NeMo/pull/4756

**Collection**: [Note which collection this PR will affect]

# Changelog 
- Add specific line by line info of high level changes in this PR.

# Usage
* You can potentially add a usage example below

```python
# Add a code snippet demonstrating how to use this 
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# Additional Information
* Related to # (issue)
P&C docs
State: closed | Pull request: yes
Labels: name: cherry-pick

Signed-off-by: Matvei Novikov <mattyson.so@gmail.com>

# What does this PR do ?

Documentation for P&C model update

**Collection**: [Note which collection this PR will affect]

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- Add specific line by line info of high level changes in this PR.

# Usage
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```python
# Add a code snippet demonstrating how to use this 
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# Additional Information
* Related to # (issue)
P&C docs
State: closed | Pull request: yes

Signed-off-by: Matvei Novikov <mattyson.so@gmail.com>

# What does this PR do ?

Documentation for P&C model update

**Collection**: [Note which collection this PR will affect]

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- Add specific line by line info of high level changes in this PR.

# Usage
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```python
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# Additional Information
* Related to # (issue)
Add ability to configure drop last batch for validation datasets with MegatronGPT
State: closed | Pull request: yes

Signed-off-by: Shanmugam Ramasamy <111910568+shanmugamr1992@users.noreply.github.com>

# What does this PR do ?

Add a one line overview of what this PR aims to accomplish.

**Collection**: [Note which collection this PR will affect]

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# Usage
* You can potentially add a usage example below

```python
# Add a code snippet demonstrating how to use this 
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# Additional Information
* Related to # (issue)
[bug_fix] kv_channels is used when available
State: closed | Pull request: yes

Signed-off-by: arendu <adithya.r@gmail.com>

# What does this PR do ?

IA3 logic should look at `kv_channels * num_attention_heads` to get the true `hidden_size` for k,v,q in `ParallelAttention`.

**Collection**: [nlp]

# Changelog 
- checks if `kv_channels` is available in the config of a T5 model, if available it will use it and ignore `hidden_size`.

# Usage
* You can potentially add a usage example below

```python
# Add a code snippet demonstrating how to use this 
```

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**Pre checks**:
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**PR Type**:
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# Additional Information
* Related to # (issue)
Remove unsupported arguments from MegatronNMT
State: closed | Pull request: yes

Signed-off-by: MaximumEntropy <sandeep.subramanian.1@umontreal.ca>

# What does this PR do ?

Removes unsupported args from MegatronNMT.

Specifically removes

1. MTDataPreproc (needed for tarred datasets)
2. Tarred and text datasets as options for train_ds.
3. Removes distributed sampler option. Only possible to use megatron batch samplers.
4. Removes associated code in the model like GlobalBatchDataFetcher, train step reconfiguring of MBS etc.

**Collection**: NLP

# Changelog 
- Add specific line by line info of high level changes in this PR.

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* You can potentially add a usage example below

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# Add a code snippet demonstrating how to use this 
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# Additional Information
* Related to # (issue)
[pre-commit.ci] pre-commit suggestions
State: closed | Pull request: yes
Labels: name: stale

<!--pre-commit.ci start-->
updates:
- [github.com/PyCQA/isort: 4.3.21 → 5.10.1](https://github.com/PyCQA/isort/compare/4.3.21...5.10.1)
- [github.com/psf/black: 19.10b0 → 22.8.0](https://github.com/psf/black/compare/19.10b0...22.8.0)
<!--pre-commit.ci end-->
Updating Megatron LM conversion according to PTL 1.7
State: closed | Pull request: yes
Labels: name: cherry-pick

# What does this PR do ?

Updating Megatron LM conversion according to PTL 1.7

**Collection**: [Note which collection this PR will affect]

# Changelog 
- Updated megatron_lm_ckpt_to_nemo.py

# Usage
* You can potentially add a usage example below

```python
# Add a code snippet demonstrating how to use this 
```

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**Pre checks**:
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# Additional Information
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Try using transformers online so new workers update the cache
State: closed | Pull request: yes

# What does this PR do ?

Add a one line overview of what this PR aims to accomplish.

**Collection**: [Note which collection this PR will affect]

# Changelog 
- Add specific line by line info of high level changes in this PR.

# Usage
* You can potentially add a usage example below

```python
# Add a code snippet demonstrating how to use this 
```

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**Pre checks**:
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# Additional Information
* Related to # (issue)
Missing fixes from r1.11.0 to T5 finetuning eval
State: closed | Pull request: yes
Labels: name: cherry-pick

Signed-off-by: MaximumEntropy <sandeep.subramanian.1@umontreal.ca>

# What does this PR do ?

Adds fixes that were initially a part of the BigNLP cherry-pick but were not merged back to main.

**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
# Add a code snippet demonstrating how to use this 
```

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**Pre checks**:
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# Additional Information
* Related to # (issue)
Question about Diarization inference
State: closed | Pull request: no

Hi guys

I have couple of questions about Diarization inference script

1. https://github.com/NVIDIA/NeMo/blob/f964e1c17c3922d6f35b5e453aa712f2be153e6d/nemo/collections/asr/parts/utils/nmesc_clustering.py#L723 

Here, we are trying to marge clustering outputs together using ```torch.mode```.  But it seems wrong, because at each trial the output class indices are different. So majority voting will not produce any benefits. Can you explain how it works? 


https://github.com/NVIDIA/NeMo/blob/f964e1c17c3922d6f35b5e453aa712f2be153e6d/nemo/collections/asr/parts/utils/nmesc_clustering.py#L895
2. Why are you making graph fully connected after binarization? Are there any corner cases in which fully connected graph is necessary? 


Thanks
Issue in ASR chunk inference
State: closed | Pull request: no
Labels: name: bug

name: stale

Hello, I'm trying to use the ASR chunk Inference script as the video I want too process is too big (2 hours). But getting an error while running the script. 

command I'm using `python .\speech_to_text_buffered_infer_ctc.py --asr_model="stt_en_conformer_ctc_xlarge" --test_manifest="video_2.wav" --model_stride=4`

Issue 
`Traceback (most recent call last):
  File ".\chunk_inference.py", line 169, in <module>
    main()  # noqa pylint: disable=no-value-for-parameter
  File ".\chunk_inference.py", line 132, in main
    hyps, refs, wer = get_wer_feat(
  File ".\chunk_inference.py", line 62, in get_wer_feat
    row = json.loads(l.strip())
  File "C:\Users\dhruv\AppData\Local\Programs\Python\Python38\lib\json\__init__.py", line 343, in loads
    s = s.decode(detect_encoding(s), 'surrogatepass')
UnicodeDecodeError: 'utf-8' codec can't decode byte 0x98 in position 5: invalid start byte`
Logging audio & images during TTS training
State: closed | Pull request: no
Labels: name: feature

**Is your feature request related to a problem? Please describe.**

Whenever I'm training, I cannot conclude the exact performance of a TTS model when training, having to manually stop and resume training.

**Describe the solution you'd like**

A simple parameter in the training config to add audio samples & alignment (if possible) into the tensorboard.

**Describe alternatives you've considered**

N/A

**Additional context**

N/A
Unable to instantiate HuggingFace AUTOTOKENIZER for gpt2 and facebook/bart-base
State: closed | Pull request: no
Labels: name: bug

**Describe the bug**

Get errors 
`Unable to instantiate HuggingFace AUTOTOKENIZER `
for both gpt2 and facebook/bart-base


**Steps/Code to reproduce bug**

Trying to run NeMO tutorial from https://github.com/NVIDIA/NeMo/blob/stable/tutorials/nlp/Question_Answering.ipynb

The notebook fails when trying to create trainer and initialize models gpt2 and facebook/bart-base

**Expected behavior**

I expected to bee able to create a trainer properly just like it happened for "bert-base-uncased" which worked well earlier in the same notebook.

**Environment overview (please complete the following information)**

 - Environment location: VMware vSphere VM
 - Method of NeMo install: 
```
conda create --name nemo python==3.8
conda activate nemo
conda install pytorch torchvision torchaudio cudatoolkit=11.3 -c pytorch
apt-get update && apt-get install -y libsndfile1 ffmpeg
pip install Cython
pip install nemo_toolkit['all']
```

**Environment details**

If NVIDIA docker image is used you don't need to specify these.
Otherwise, please provide:
- OS version Ubuntu 20.04.5 LTS
- PyTorch version 1.12.1
- Python version 3.8.0
- nemo-toolkit                  1.11.0

**Additional context**

Add any other context about the problem here.
**GPU model V100**
Text memmap dataset index memory efficiency
State: closed | Pull request: yes

# What does this PR do ?

1. Loading index file into memmap object.
2. Deallocates indexed dataset memory after samples mapping has been computed.
3. Blendable dataset supports index computation

**Collection**: [Note which collection this PR will affect]

# Changelog 
- Add specific line by line info of high level changes in this PR.

# Usage
* You can potentially add a usage example below

```python
# Add a code snippet demonstrating how to use this 
```

# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
  - [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
  
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation

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## Who can review?

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# Additional Information
* Related to # (issue)
Added save inference ready .nemo file with every checkpoint
State: closed | Pull request: yes

Signed-off-by: Virginia Adams <vadams@nvidia.com>

# What does this PR do ?

Saves inference ready .nemo checkpoint every time a training checkpoint is saved. 

**Collection**: NLP

# Changelog 
- Updates Base Prompt Learning Model Class
- Updates GPT Prompt Learning Model Class
- Updates T5 Prompt Learning Model Class

# Usage
Now, when a .ckpt file is saved at the end of validation, an inference ready .nemo file is also saved at the path given in `models.nemo_path`

# 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)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
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- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
  
**PR Type**:
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- [ ] Bugfix
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# Additional Information
* Related to # (issue)
Missing fixes from r1.11.0 to T5 finetuning eval
State: closed | Pull request: yes

Signed-off-by: MaximumEntropy <sandeep.subramanian.1@umontreal.ca>

# What does this PR do ?

Adds fixes that were initially a part of the BigNLP cherry-pick but were not merged back to main.

**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
# Add a code snippet demonstrating how to use this 
```

# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
  - [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
  
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation

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## Who can review?

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# Additional Information
* Related to # (issue)
Bug fixes for parallel mp3 to wav conversion, PC notebook, update Readme for TN requirements
State: closed | Pull request: yes
Labels: name: cherry-pick

# What does this PR do ?

Add a one line overview of what this PR aims to accomplish.

**Collection**: [Note which collection this PR will affect]

# Changelog 
- Add specific line by line info of high level changes in this PR.

# Usage
* You can potentially add a usage example below

```python
# Add a code snippet demonstrating how to use this 
```

# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
  - [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
  
**PR Type**:
- [ ] New Feature
- [X ] Bugfix
- [ ] Documentation

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## Who can review?

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# Additional Information
* Related to # (issue)
Expose keep_initializers_as_inputs to Exportable class
State: closed | Pull request: yes

# What does this PR do ?

[`torch.onnx.export`](https://pytorch.org/docs/stable/onnx.html#torch.onnx.export) has the parameter `keep_initializers_as_inputs` which allows to conveniently override parameters when running a graph.

**Collection**: Every collection that is exportable.

# Changelog 
- Allow to use `keep_initializers_as_inputs` parameter when exporting a model to ONNX

# Usage
* You can potentially add a usage example below

```python
model.export(..., keep_initializers_as_inputs=True)
```

# 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)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
  - [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
  
**PR Type**:
- [x] New Feature
- [ ] Bugfix
- [ ] Documentation


## Who can review?

@ericharper, @titu1994, @blisc, or @okuchaiev

# Additional Information
don't use bfloat16 when in jit
State: closed | Pull request: yes
Labels: name: bug

name: core

Signed-off-by: Dima Rekesh <drekesh@nvidia.com>

# What does this PR do ?
Prevents the use of bfloat16 autocast when jit() is used

Add a one line overview of what this PR aims to accomplish.
Prevents the use of bfloat16 autocast when jit() is used

**Collection**: [Note which collection this PR will affect]
general
# Changelog 
- Add specific line by line info of high level changes in this PR.
- [training_utils.py](https://github.com/NVIDIA/NeMo/compare/main...no_bfloat16_in_jit#diff-09d6a5be8cc6d798800c50fa7cb0d7bd34e89ad5a71c872c87f6e07c4f4ea38f)

# Usage
* You can potentially add a usage example below
* No change

```python
# Add a code snippet demonstrating how to use this 
```

# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
  - [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
  
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation

If you haven't finished some of the above items you can still open "Draft" PR.


## Who can review?

Anyone in the community is free to review the PR once the checks have passed. 
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.

# Additional Information
* Related to # (issue)
Fix bug in question answering tutorial
State: closed | Pull request: yes
Labels: name: cherry-pick

# What does this PR do ?

Fix bug in question answering tutorial

**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
# Add a code snippet demonstrating how to use this 
```

# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
  - [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
  
**PR Type**:
- [ ] New Feature
- [x] Bugfix
- [ ] Documentation

If you haven't finished some of the above items you can still open "Draft" PR.


## Who can review?

Anyone in the community is free to review the PR once the checks have passed. 
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.

# Additional Information
* Related to # (issue)
Fix bug in question answering tutorial
State: closed | Pull request: yes

# What does this PR do ?

Fix bug in question answering tutorial

**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
# Add a code snippet demonstrating how to use this 
```

# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
  - [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
  
**PR Type**:
- [ ] New Feature
- [x] Bugfix
- [ ] Documentation

If you haven't finished some of the above items you can still open "Draft" PR.


## Who can review?

Anyone in the community is free to review the PR once the checks have passed. 
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.

# Additional Information
* Related to # (issue)
Memory efficient text_mammap handling of index files
State: closed | Pull request: yes

# What does this PR do ?

1. Loading index file into memmap object.

**Collection**: [Note which collection this PR will affect]

# Changelog 
- Add specific line by line info of high level changes in this PR.

# Usage
* You can potentially add a usage example below

```python
# Add a code snippet demonstrating how to use this 
```

# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
  - [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
  
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation

If you haven't finished some of the above items you can still open "Draft" PR.


## Who can review?

Anyone in the community is free to review the PR once the checks have passed. 
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.

# Additional Information
* Related to # (issue)
Bug fixes for parallel mp3 to wav conversion, PC notebook, update Readme for TN requirements
State: closed | Pull request: yes

# What does this PR do ?

Add a one line overview of what this PR aims to accomplish.

**Collection**: [Note which collection this PR will affect]

# Changelog 
- Add specific line by line info of high level changes in this PR.

# Usage
* You can potentially add a usage example below

```python
# Add a code snippet demonstrating how to use this 
```

# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
  - [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
  
**PR Type**:
- [ ] New Feature
- [X ] Bugfix
- [ ] Documentation

If you haven't finished some of the above items you can still open "Draft" PR.


## Who can review?

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# Additional Information
* Related to # (issue)
fix undefined constant in code example
State: closed | Pull request: yes

Signed-off-by: Alexandra Antonova <aleksandraa@nvidia.com>

# What does this PR do ?

Fix undefined constant in code example.

**Collection**: [Note which collection this PR will affect]

# Changelog 
- Add specific line by line info of high level changes in this PR.

# Usage
* You can potentially add a usage example below

```python
# Add a code snippet demonstrating how to use this 
```

# Before your PR is "Ready for review"
**Pre checks**:
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- [ ] Did you add or update any necessary documentation?
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  - [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
  
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# Additional Information
* Related to # (issue)
Add black to pre-commit (#5027)
State: closed | Pull request: yes

Signed-off-by: SeanNaren <snarenthiran@nvidia.com>

Signed-off-by: SeanNaren <snarenthiran@nvidia.com>
(cherry picked from commit 986a76612593863a8fa3a8529fb60c620c91bd7b)

# What does this PR do ?

Add a one line overview of what this PR aims to accomplish.

**Collection**: [Note which collection this PR will affect]

# Changelog 
- Add specific line by line info of high level changes in this PR.

# Usage
* You can potentially add a usage example below

```python
# Add a code snippet demonstrating how to use this 
```

# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
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**PR Type**:
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## Who can review?

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# Additional Information
* Related to # (issue)
Refactor output directory for MSDD Inference Notebook
State: closed | Pull request: yes

# What does this PR do ?

The output directory was assumed as apposed to using the variable to track. This ensures we use the variable as apposed to `outputs/`.

# 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)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
  - [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
  
**PR Type**:
- [ ] New Feature
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- [ ] Documentation

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## Who can review?

Anyone in the community is free to review the PR once the checks have passed. 
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# Additional Information
* Related to # (issue)