renwei2024/nemo-github-issues huggingface dataset:
fix ssl models ptl monitor val through logging
State: closed | Pull request: yes
Labels: name: ASR

# What does this PR do ?

Add logging of loss by adding to validation_outputs (self.log) for ssl_models

**Collection**: ASR

# Changelog 
- Add to self.log by setting to validation_step_outputs

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Fix validation in G2PModel and ThutmoseTaggerModel
State: closed | Pull request: yes
Labels: name: TTS

name: cherry-pick

name: NLP

# What does this PR do ?

Append output of val step to `self.validation_step_outputs` in `ThutmoseTaggerModel` and `T5G2PModel` as required by lightning 2.0. Also removes `outputs` arg from `on_validation_epoch_end` and `on_test_epoch_end` in `ThutmoseTaggerModel`

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- Add specific line by line info of high level changes in this PR.

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# Additional Information
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Use native mkdocs-material plugin
State: closed | Pull request: yes

# What does this PR do ?

Add a one line overview of what this PR aims to accomplish.

**Collection**: NeMo's Github io webpage

# Changelog 
- Move from using mkdocs-material nav functionality to built-in blog plug-in for hosting blog posts
- Move 'posts' and 'technical blog' into the same place.

# Usage
N/A

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# Additional Information
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Fix metrics for SE tutorial
State: closed | Pull request: yes
Labels: name: ASR

# What does this PR do ?

This PR fixes a bug in SE tutorial caused by initialization of metrics for audio-to-audio models.

**Collection**: ASR, Tutorials

# Changelog 
- Updated metric initialization
- Small fixes in the tutorial notebook

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# Additional Information
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Export to mlmodel/mlpackage?
State: closed | Pull request: no
Labels: name: stale

**Is your feature request related to a problem? Please describe.**
No

**Describe the solution you'd like**
A way to export to models like ECAPA-TDNN to an mlmodel/mlpackage so we can add it easily to our iOS applications

Provide a code snippet on how new APIs/changes would be used by others.

**Describe alternatives you've considered**
I already traced the model and used Libtorch, it works well, but I believe having a mlpackage will reduce the size of the model and the performance will be better. Without forgetting how easy the implementation is.
[TTS] Fix FastPitch data prep tutorial
State: closed | Pull request: yes
Labels: name: TTS

# What does this PR do ?

Update TTS tutorial to be consistent with recent code changes.

Merge to r1.21.0 branch.

**Collection**: [TTS]

# Changelog 
- Update lower_case and batch_size arguments examples for preprocess_text.py
- Add dataset name to path of logged audio.

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French g2p with pronunciation dictionary
State: closed | Pull request: yes
Labels: name: TTS

name: common

# What does this PR do ?

Add a one line overview of what this PR aims to accomplish.

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```python
# Add a code snippet demonstrating how to use this 
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# Additional Information
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defaults changed
State: closed | Pull request: yes

# What does this PR do ?

minor change to defaults.. 

**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

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# Add a code snippet demonstrating how to use this 
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# Additional Information
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SDE Tutorial minor fix 
State: closed | Pull request: yes

specifies the branch

# What does this PR do?

Specified a branch in the tutorial




**Collection**: [Note which collection this PR will affect]

# Changelog 

replaced "!git clone https://github.com/NVIDIA/NeMo"

with

"BRANCH = 'main'
!git clone -b $BRANCH https://github.com/NVIDIA/NeMo"

# 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**:
- [ ] New Feature
- [+] Bugfix
- [+] Documentation

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# Additional Information
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Fix validation in G2PModel and ThutmoseTaggerModel
State: closed | Pull request: yes
Labels: name: TTS

name: NLP

# What does this PR do ?

Append output of val step to `self.validation_step_outputs` in `ThutmoseTaggerModel` and `T5G2PModel` as required by lightning 2.0. Also removes `outputs` arg from `on_validation_epoch_end` and `on_test_epoch_end` in `ThutmoseTaggerModel`

**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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# Additional Information
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After running install_beamsearch_decoders.sh, testing script starts endless loop.
State: closed | Pull request: no
Labels: name: bug

After running install_beamsearch_decoders.sh, testing script starts endless loop. I am using Ubuntu 22.04 with Python 3.10. 
The loop is somewhere in this code:


       `with self.autocast():
            with torch.no_grad():
                if isinstance(self.asr_model, EncDecHybridRNNTCTCModel):
                    self.asr_model.cur_decoder = 'ctc'
                all_logits = self.asr_model.transcribe([audio_file], logprobs=True, verbose = 0)

        preds = np.argmax(all_logits[0], axis=1)
        preds_tensor = torch.tensor(preds, device=self._device).unsqueeze(0)
        if isinstance(self.asr_model, EncDecHybridRNNTCTCModel):
            pred_text = self.asr_model.ctc_decoding.ctc_decoder_predictions_tensor(preds_tensor)[0][0]
        else:
            pred_text = self.asr_model._wer.decoding.ctc_decoder_predictions_tensor(preds_tensor)[0][0]

        #self.asr_model = self.asr_model.to('cpu')

        decoding = self.toggle_decoder("beam")

        probs_lens = torch.tensor([all_logits[0].shape[0]])

        with torch.no_grad():
            packed_batch = torch.cat([torch.tensor(all_logits[0], device=self._device, dtype=torch.float32).unsqueeze(0)], dim=1)
       hypotheses = decoding.ctc_decoder_predictions_tensor(packed_batch, decoder_lengths=probs_lens, return_hypotheses=True)`

I also tried to setup environment on Python 3.8, 3.9 and 3.11, either gives "install_beamsearch_decoders.sh not installed " error, or starts endless loop.
Fix ptuning crash for llama 2 ckpt
State: closed | Pull request: yes
Labels: name: NLP

# 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
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replace json with ujson?
State: closed | Pull request: no
Labels: name: feature

**Is your feature request related to a problem? Please describe.**

Recently facing too many warning message during model training like `NOTE! Installing ujson may make loading annotations faster.`. Went over a little on `ujson` vs `json`, it seems a worth to switch mostly because `ujson` is faster, 

ref: https://github.com/ultrajson/ultrajson
PEFT needs mp config propagated for dist ckpt
State: closed | Pull request: yes
Labels: name: cherry-pick

name: NLP

# What does this PR do ?

Updates the base model config so it will use the right mp config.

**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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Typo fixes
State: closed | Pull request: yes
Labels: name: ASR

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Add a one line overview of what this PR aims to accomplish.

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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
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generate tokens_to_generate for all items in a batch
State: closed | Pull request: yes
Labels: name: stale

name: NLP

# What does this PR do ?

ensure that all examples in a batch generate only `tokens_to_generate` number of tokens.

**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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- [x] Bugfix
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# Additional Information
* Related to # (issue)
PEFT needs mp config propagated for dist ckpt
State: closed | Pull request: yes
Labels: name: NLP

# What does this PR do ?

Updates the base model config so it will use the right mp config.

**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
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best ckpt fix
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 
```

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**Pre checks**:
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**PR Type**:
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# Additional Information
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Broadcast loss only when using pipeline parallelism and within the pipeline parallel domain
State: closed | Pull request: yes
Labels: name: cherry-pick

name: NLP

Broadcast train and validation loss only when pipeline parallel size is larger than 1.
Also, the loss broadcasting only within the pipeline parallel domain.

# 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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**Pre checks**:
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**PR Type**:
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- [ ] Bugfix
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# Additional Information
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Update Speaker_Diarization_Training.ipynb
State: closed | Pull request: yes
Labels: name: Speaker Tasks

auto trainer strategy set to "auto"

# What does this PR do ?

Fix a simple bug in a example, config.trainer.strategy = auto changed to config.trainer.strategy = 'auto'
that was interrupting the execution of the code

**Collection**: [Note which collection this PR will affect]
Speaker_Diarization_Training.ipynb
tutorial example

# Changelog 
- Add specific line by line info of high level changes in this PR.
config.trainer.strategy = auto changed to config.trainer.strategy = 'auto'

# 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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- [x ] Did you write any new necessary tests? Ran the notebook
- [ ] Did you add or update any necessary documentation? No need
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**PR Type**:
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- [ x] Bugfix
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# Additional Information
* Related to # (issue)
Change hifigan finetune strategy to ddp_find_unused_parameters_true
State: closed | Pull request: yes
Labels: name: TTS

name: cherry-pick

# What does this PR do ?

Change strategy from ddp to auto because of PL 2.0

**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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  - [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
  
**PR Type**:
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- [x] Bugfix
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# Additional Information
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fix typos in nfa and speech enhancement tutorials
State: closed | Pull request: yes
Labels: name: cherry-pick

# What does this PR do ?

Fix typos

**Collection**: tutorials

# Changelog 
- Fix typos in NFA and Speech Enhancement tutorials

# Usage
N/A

# 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)
- [N/A] Did you write any new necessary tests?
- [N/A] Did you add or update any necessary documentation?
- [N/A] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
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## Who can review?

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# Additional Information
* Related to # (issue)
Fix py3.11 dataclasses issue 
State: closed | Pull request: yes
Labels: name: core

name: TTS

name: ASR

name: NLP

name: common

# What does this PR do ?

Fixes an issue with mutable defaults inside dataclasses across NeMo configs

Fixes #7166 

**Collection**: [Core, ASR, NLP, TTS, Tools]

# Changelog 
- Guard mecab and ipadic
- Remove dependence on mecab and ipadic from sacrebleu
- Fix dataclasses across domains and tools

# 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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  - [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
  
**PR Type**:
- [ ] New Feature
- [x] Bugfix
- [ ] Documentation
Fix typos in confidence tutorial notebooks
State: closed | Pull request: yes
Labels: name: ASR

# 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**:
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  - [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
  
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
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## Who can review?

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# Additional Information
* Related to # (issue)
fix typos in nfa and speech enhancement tutorials
State: closed | Pull request: yes

# What does this PR do ?

Fix typos

**Collection**: tutorials

# Changelog 
- Fix typos in NFA and Speech Enhancement tutorials

# Usage
N/A

# 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)
- [N/A] Did you write any new necessary tests?
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- [N/A] 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)
Change hifigan finetune strategy to ddp_find_unused_parameters_true
State: closed | Pull request: yes
Labels: name: TTS

# What does this PR do ?

Change strategy from ddp to auto because of PL 2.0

**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**:
- [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
- [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)
Broadcast loss only when using pipeline parallelism and within the pipeline parallel domain
State: closed | Pull request: yes
Labels: name: NLP

Broadcast train and validation loss only when pipeline parallel size is larger than 1.
Also, the loss broadcasting only within the pipeline parallel domain.

# 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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- [ ] 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. 
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# Additional Information
* Related to # (issue)
Path to Convert from Dist Ckpt to Legacy
State: closed | Pull request: yes
Labels: name: stale

name: NLP

# 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
- [ ] 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. 
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# Additional Information
* Related to # (issue)
[TTS] fixed trainer's accelerator and strategy.
State: closed | Pull request: yes
Labels: name: TTS

name: cherry-pick

# What does this PR do ?

strategy should be replaced as `ddp_find_unused_parameters_true`.

**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**:
- [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
- [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)
Append val/test output to instance variable in EncDecSpeakerLabelModel
State: closed | Pull request: yes
Labels: name: cherry-pick

name: ASR

# What does this PR do ?

Appends val/test output to self.validation/test_step_outputs in `evaluation_step` method of `EncDecSpeakerLabelModel` and `EncMaskDecAudioToAudioModel`

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
- [ ] Bugfix
- [ ] Documentation

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## Who can review?

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# Additional Information
* Related to # (issue)
Clarify that `length_params.max_length` is not a hard constraint
State: closed | Pull request: yes
Labels: name: NLP

# What does this PR do ?

Update docstring describing `length_params.max_length` to say that generated sequences may actually exceed this length, since this can be surprising.

**Collection**: nlp

# Changelog 
- Clarify that `length_params.max_length` is not a hard constraint

# 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?
- [X] 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**:
- [ ] New Feature
- [ ] Bugfix
- [X] Documentation


## Who can review?

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# Additional Information

I need someone to confirm whether the same doc change should be applied to this `asr` file, that seems to be copied from `nlp`:
https://github.com/NVIDIA/NeMo/blob/82e1f4f9f1a280edb70088bf30bf0a099152e185/nemo/collections/asr/modules/transformer/text_generation.py#L79

@stevehuang52 would you be able to confirm by any chance?
Add two youtube introductory videos to README and Docs.
State: closed | Pull request: yes

# What does this PR do ?

See attached html snippets for the results.

**README**
![readme](https://github.com/NVIDIA/NeMo/assets/1646669/3216a621-b2ba-4d8d-b5f1-599ebbc3d10b)

**Documentation**
![docs](https://github.com/NVIDIA/NeMo/assets/1646669/ef8f3035-f032-4bc3-bbec-fb2f44139b43)


**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**:
- [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
- [ ] Bugfix
- [x] Documentation

If you haven't finished some of the above items you can still open "Draft" PR.


## Who can review?

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[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)
[TTS] fixed trainer's accelerator and strategy.
State: closed | Pull request: yes
Labels: name: TTS

# What does this PR do ?

strategy should be replaced as `ddp_find_unused_parameters_true`.

**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**:
- [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
- [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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[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)
Hotfix: change the order of config overrides
State: closed | Pull request: yes
Labels: name: cherry-pick

name: NLP

# 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
- [ ] 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)
layernorm1p fix
State: closed | Pull request: yes
Labels: name: cherry-pick

name: NLP

# What does this PR do ?

Passes layernorm_zero_centered_gamma param properly which fixes layernorm1p issue.

**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)
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  - [ ] 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)
Avoid duplicated dist checkpoint save 
State: closed | Pull request: yes
Labels: name: cherry-pick

name: NLP

# What does this PR do ?

This is a WAR for the case of saving a checkpoint twice into the same directory.
A proper fix would be avoiding calling the `save_checkpoint` method altogether.

**Collection**: [Note which collection this PR will affect]

# Changelog 
- Avoid duplicated dist checkpoint save

# 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)