renwei2024/nemo-github-issues huggingface dataset:
typo fix
State: closed | Pull request: yes

Signed-off-by: arendu <adithya.r@gmail.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]

# 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)
[TTS] update organization of model checkpoints and their pointers.
State: closed | Pull request: yes

* added a column pointing correct checkpoint url.
* revised `#Spk` to real numbers.

Signed-off-by: Xuesong Yang <1646669+XuesongYang@users.noreply.github.com>

# What does this PR do ?

After the PR, it looks like,

[screenshot](https://drive.google.com/file/d/1ZbRCAZbf7vzuNsjfR5hHnZHHO8Eo373K/view?usp=sharing)

**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)
[DOC] add sphinx-copybutton requirement to copy button on code snippets.
State: closed | Pull request: yes

Signed-off-by: Xuesong Yang <1646669+XuesongYang@users.noreply.github.com>

# What does this PR do ?

![demo](https://user-images.githubusercontent.com/1839645/150200219-73663c59-08fd-4185-b157-62f3769c02ac.gif)

**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)
small bugfix for r1.13.0
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**: ASR

# Changelog 
- typo fix
- transcribe_partial_audio. https://github.com/NVIDIA/NeMo/pull/5253

# 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)
- [x] Did you write any new necessary tests?
- [x] 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)
Training interruption
State: closed | Pull request: no
Labels: name: bug

Learning starts and then stops at a certain point.

![Screenshot_6](https://user-images.githubusercontent.com/82889232/199955482-b740d545-31a3-425b-ae63-709661b01e5f.png)

Termination of training without explanation, without logs.

![Screenshot_4](https://user-images.githubusercontent.com/82889232/199954667-d4cff613-d231-43c1-afe6-ac2ebeb7b6ef.png)

 Termination of training without explanation, without logs.

![Screenshot_5](https://user-images.githubusercontent.com/82889232/199954678-44718f78-4851-4a8d-8613-b22ecc47c08c.png)

> import nemo
import nemo.collections.asr as nemo_asr
import pytorch_lightning as pl
from nemo.utils.exp_manager import exp_manager
from omegaconf import DictConfig, OmegaConf

> params = OmegaConf.load(model_conf_path)

> min_duration = 0.5
epochs = 15
gpus = 1
lr_optim = 0.001

> params.trainer.devices = gpus
params.trainer.max_epochs = epochs
params.model.optim.lr = lr_optim
params.model.train_ds.manifest_filepath = train_manifest_path
params.model.train_ds.min_duration = min_duration
params.model.validation_ds.manifest_filepath = validation_manifest_path
params.model.test_ds.manifest_filepath = test_manifest_path
params.exp_manager.exp_dir = "/path/to/save_tr_nemo/"

> trainer = pl.Trainer(**params.trainer)
model = nemo_asr.models.EncDecCTCModel(cfg=params.model, trainer=trainer)
exp_manager(trainer=trainer, cfg=params.exp_manager)

> trainer.fit(model)
trainer.test(model)

There is yaml config:
https://github.com/Project-fil/Project-fil/blob/ee79825609cca9e8b01a9c4eb43b564bb5c2b35d/quartznet_ru.yaml

Cuda version: 11.6
Python version: 3.9.12
Torch version: 1.13.0a0+git35563f4
Nemo version: 1.11.0rc0
OS - Ubuntu 20.04.5 LTS
Graphic card - Nvidia A40

What could be wrong?



https://github.com/NVIDIA/NeMo/issues/5324#tasklist-block-cccbe04f-c2c1-4b01-a878-bd03a164bbc4
tutorials/nlp/Information_Retrieval_MSMARCO.ipynb not found
State: closed | Pull request: no
Labels: name: bug

name: stale

**Describe the bug**

I'm trying to follow [Information Retrieval document](https://docs.nvidia.com/deeplearning/nemo/user-guide/docs/en/v1.12.0/nlp/information_retrieval.html), however, the link for its notebook cannot be found.
Fixing de-autocast
State: closed | Pull request: yes

Signed-off-by: Boris Fomitchev <bfomitchev@nvidia.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]

# 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)
ValueError: NeMo ASR collection is not installed. when run ./normalize_with_audio.py
State: closed | Pull request: no
Labels: name: bug

name: stale

When I run the following command

python ./normalize_with_audio.py  --text=" Hold on one second. 429-020"  --language=en --n_tagged=10 --cache_dir="cache_dir" --audio_data="./0001_00002.wav" --model="QuartzNet15x5Base-En" --verbose

I always get the error:
Traceback (most recent call last):
  File "./normalize_with_audio.py",  in <module>
    raise ValueError("NeMo ASR collection is not installed.")
ValueError: NeMo ASR collection is not installed.


I have install  nemo all
pip install nemo_toolkit[all]

**Environment details**

- OS version     CentOS 7
- PyTorch version      1.10.2+cu113
- Python version       Python 3.8.0


Thanks
Mark
Add italian model checkpoints
State: closed | Pull request: yes

Signed-off-by: Igor Gitman <igitman@nvidia.com>

# What does this PR do ?

The same as #5315  but based on the release branch.

**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)
Add italian model checkpoints
State: closed | Pull request: yes

Signed-off-by: Igor Gitman <igitman@nvidia.com>

# What does this PR do ?

Add italian model checkpoints to be available for download from NGC.

**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)
[STT] add Ru ASR conformers to models collections
State: closed | Pull request: yes

Signed-off-by: Aleksandr Meister [ameister@nvidia.com](mailto:ameister@nvidia.com)

# What does this PR do ?

Add Ru ASR Conformer-CTC Large and Conformer-Transducer Large to NeMo models collections

**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)
Pcla tutorial fixes
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
- [ ] 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)
add RNN-T loss implemented by PyTorch and test code
State: closed | Pull request: yes
Labels: name: ASR

# What does this PR do ?

Add support for RNN-T loss implemented with PyTorch only that relies on PyTorch auto-grad for gradient computation.

**Collection**: [ASR]



# 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)
- [x] 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

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)
small bugfix for r1.13.0
State: closed | Pull request: yes

# What does this PR do ?

Add a one line overview of what this PR aims to accomplish.

**Collection**: ASR

# Changelog 
- typo fix
- transcribe_partial_audio. https://github.com/NVIDIA/NeMo/pull/5253

# 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)
- [x] Did you write any new necessary tests?
- [x] 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)
Fixes for Conformer-xl export
State: closed | Pull request: yes

# What does this PR do ?
Fixes for Conformer-xl model export:
1) Fixes ONNXRT error: Type parameter (Tind) of Optype (Slice) bound to different types (tensor(int32) and tensor(int64) in node (Slice_63).
2) Fixes 'runtime-check' crash on ONNX > 2GB

**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)
[TTS] replace obsolete torch_tts unit test marker with run_only_on('CPU')
State: closed | Pull request: yes


Signed-off-by: Xuesong Yang <1646669+XuesongYang@users.noreply.github.com>

# What does this PR do ?
* we should remove the legacy unit test marker `torch_tts` and use the common `run_only_on('CPU')` marker. `torch_tts` marker was only used for testing `TTSDataset` on CPU.

**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)
Add speaker clustering arguments to forward function
State: closed | Pull request: yes

Signed-off-by: Taejin Park <tango4j@gmail.com>

# What does this PR do ?

Move speaker clustering arguments to forward function
Also added scripting option.
Fixed type issues for torch scripting.

**Collection**: [Note which collection this PR will affect]
ASR

# Changelog 
- Moved tunable parameters to forward function
- removed unnecessary class varialbes
- Moved clustering instance creation to the outside of for loop in speaker_utils.py
# Usage

If you want to export clustering script module, add the following line 

`+diarizer.clustering.parameters.export_script_module=True`


```python
  python clustering_diarizer/offline_diar_infer.py \
    +diarizer.clustering.parameters.export_script_module=True \
    diarizer.manifest_filepath=<path to manifest file> \
    diarizer.out_dir='demo_output' \
    diarizer.speaker_embeddings.parameters.save_embeddings=False \
    diarizer.vad.model_path=<pretrained model name or path to .nemo> \
    diarizer.speaker_embeddings.model_path=<pretrained speaker embedding model 
'name or path to .nemo> 
```

# 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)
- [x] Did you write any new necessary tests?
- [x] 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

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)
Distributed optimizer support for BERT
State: closed | Pull request: yes

# What does this PR do ?

Add support for the distributed Adam optimizer to BERT.

**Collection**: NLP

# Changelog 
- Add support for the Apex distributed Adam optimizer to BERT

# Usage

Set the optimizer to `distributed_fused_adam` in the config file:

https://github.com/NVIDIA/NeMo/blob/79a22eaee0813d5a0e4dc82ebd4a43071399c899/examples/nlp/language_modeling/conf/megatron_bert_config.yaml#L118

# 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

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.

Pinging @shanmugamr1992.

# Additional Information
* Depends on https://github.com/NVIDIA/NeMo/pull/5293.
* BERT distopt support in this PR is basically identical to GPT and T5 distopt support in https://github.com/NVIDIA/NeMo/pull/5236.
[TTS] bugfix IPAG2P and refactor to remove duplicate process.
State: closed | Pull request: yes

Signed-off-by: Xuesong Yang <1646669+XuesongYang@users.noreply.github.com>

# What does this PR do ?

1. fixed a bug for IPAG2P: the returned self.phoneme_dict mismatches between the one obtained from [self.parse_as_cmu_dict](https://github.com/NVIDIA/NeMo/blob/44de3950f0bf2f3e85d7df1a962eb24674f4fa4e/nemo_text_processing/g2p/modules.py#L320) and the one directly updated from a [dict obj](https://github.com/NVIDIA/NeMo/blob/44de3950f0bf2f3e85d7df1a962eb24674f4fa4e/nemo_text_processing/g2p/modules.py#L351). The former will return something like `{..., "WIRE": [["ˈ", "w", "a", "ɪ", "ɚ"], ["ˈ", "w", "a", "ɪ", "ɹ"]], ...}`, while the latter will return like `{..., "WIRE": ["ˈ", "w", "a", "ɪ", "ɚ"], ...}`.
2. refactored to remove duplicate processes for the case when the phoneme dict input is a dict object and for the case when the phoneme dict is a file.
3. added type hints and docstrings for the whole class `IPAG2P`.

**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)
Fix dialogue tutorial bug
State: closed | Pull request: yes
Labels: name: cherry-pick

# What does this PR do ?

Set default value of num_prompt_tokens to 0 for huggingface GPT model (where virtual prompts do not exist). 

**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?

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)
Add ASR Blossoms test
State: closed | Pull request: yes

Signed-off-by: smajumdar <titu1994@gmail.com>

# What does this PR do ?

Starts port of ASR tests to Blossom

**Collection**: [ASR]

# Changelog 
- Add asr test
- Add some checks to blossom ci main tests

# Usage

- `/blossom-ci`

# 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**:
- [x] New Feature
- [ ] Bugfix
- [ ] Documentation
[TTS] Replace IPA lambda arguments with locale string
State: closed | Pull request: yes

# What does this PR do ?

Currently you cannot configure the IPATokenizer in .yaml config because there is no way to modify the lambda arguments. This PR replaces the lambda arguments with a locale string that maps to the correct behavior, which now just maps to English vs Non-English.

An alternative approach would be to replace the lambda arguments with a new class/interface, but we thought that was too complicated for now. And that having default configurations available that someone can control with just a language/locale string would be nice to have regardless.

**Collection**: [TTS]

# Changelog 
- Replace IPA tokenizer lambda arguments with locale string that maps to English vs non-English IPA functions.

# 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)
- [x] 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
Fix dialogue tutorial bug
State: closed | Pull request: yes

# What does this PR do ?

Set default value of num_prompt_tokens to 0 for huggingface GPT model (where virtual prompts do not exist). 

**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?

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)
diarization: add configurable parameters for clustering
State: closed | Pull request: yes

Signed-off-by: Viraj Karandikar <vkarandikar@nvidia.com>

Changes some of the clustering parameters from init time to run time.

**asr**

# Changelog 
- Moves parameters like max_num_speaker, multiscale_weights, sparse_search_volume from init-time to run-time

# Usage
* Used when clustering is exported as torchscript model and some parameters need to be changed runtime. 


# 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? - NA
- [*] Did you add or update any necessary documentation? - NA
- [*] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc) - No
  - [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
  
**PR Type**:
- [*] New Feature (minor enhancement actually)

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)
Pipeline paralleism in Bert
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
- [ ] 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)
[Bugfix] Added rm -f / wget- nc command to avoid bash error in multispeaker sim notebook
State: closed | Pull request: yes

Signed-off-by: Taejin Park <tango4j@gmail.com>

# What does this PR do ?

Fix minor bugs in multispeaker simulation tutorial notebook
https://github.com/NVIDIA/NeMo/blob/main/tutorials/tools/Multispeaker_Simulator.ipynb

Bugfix for 
https://nvbugswb.nvidia.com/NvBugs5/SWBug.aspx?bugid=3848353

- rm throws out an error if there is no such file

**Collection**: [Note which collection this PR will affect]

# Changelog 


added rm -f (try deleting only if file exists)
added wget -nc  (no duplication)


# Usage

Please run the tutorial notebook

# 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)
- [x] Did you write any new necessary tests?
- [x] 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?

any one in ASR

# Additional Information
* Related to # (issue)
PCLA tutorial typo fix
State: closed | Pull request: yes
Labels: name: cherry-pick

Signed-off-by: Matvei Novikov <mattyson.so@gmail.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]

# 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)
AttributeError: 'dict' object has no attribute '_get_node_flag'
State: closed | Pull request: no

root/abc/venv/lib/python3.8/site-packages/omegaconf/omegaconf.py", line 670, in open_dict
    prev_state = config._get_node_flag("struct")
AttributeError: 'dict' object has no attribute '_get_node_flag'

Thanks.
transcribe() outputting different results than validate()
State: closed | Pull request: no

Hello,

I have fine-tuned the German Conformer Transducer on a subset of Mozilla Common Voice. The WER on the validation set decreases throughout the 20 training epochs. However, when I load the checkpoint and use the `transcribe` method, the model outputs weird predictions containing `??`. For example: 

```
' ⁇ un müssen meines  ⁇ rachtens konkrete und erkennbare  ⁇ aßnahmen ergriffen werden ⁇ '
```

This does not occur when I use the pre-trained model offered by Nvidia. Only when I use the one I have fine-tuned myself. I have run another validation loop with the same checkpoint, and the WER is lower than for the model that is not fine-tuned. 

I assume that there must be a difference between these two methods (`validate` and `transcribe`) that makes one work but not the other. Do you have any clue as to why this is?
PCLA tutorial typo fix
State: closed | Pull request: yes

Signed-off-by: Matvei Novikov <mattyson.so@gmail.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]

# 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)
How to get asr result of audio with offset and duration
State: closed | Pull request: no

Hello!
I want to test an audio file that has a specific offset and duraion, how can I do this?
For example, I want to test from 20s to 40s. The below scripts can only give me the result of the whole audio.
```
import nemo
import nemo.collections.asr as nemo_asr
quartznet = nemo_asr.models.EncDecCTCModel.from_pretrained(model_name="QuartzNet15x5Base-En")
files = [os.path.join(data_dir, 'an4/wav/an4_clstk/mgah/cen2-mgah-b.wav')]
for fname, transcription in zip(files, quartznet.transcribe(paths2audio_files=files)):
  print(f"Audio in {fname} was recognized as: {transcription}")
```
Question about RAM consumption increasing.
State: closed | Pull request: no

Hello everybody.

Forgive me for the stupid question but: 
Is expected the RAM consumption to increase or have high usage values?

I've been using a `stt_en_conformer_ctc_large.nemo` in GPU without any problem, to be more specific I'm running two models in two child processes. After every transcription, `torch.cuda.empty_cache()` solve my problems with the GPU cache and so on.

But I noticed when these processes start, the RAM had a significantly increased consumption (basically starting from model size + other things) and increase transcription after transcription.

That is the way I'm loading the models:
```python
 asr_model = nemo_asr.models.EncDecCTCModel.restore_from(_model_path)
 asr_model.eval()
 asr_model = asr_model.to(asr_model.device)
```

Is this normal behavior? Is there anything that I can do to solve it?

Thank you!
Fix bug into Dialogue tutorial
State: closed | Pull request: yes
Labels: name: cherry-pick

# What does this PR do ?

set find_unused_parameters=True to overcome RuntimeError of unused pooler layer for BERT model.

**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)
Add cpWER for evaluation of ASR with diarization
State: closed | Pull request: yes

# What does this PR do ?

This PR adds `cpWER` calculation feature to diarization-ASR pipeline. 
`WDER` features are removed from `diarization_utils.py` to keep the code simple.
Additionally, docstrings are added to the functions in `diarization_utils.py`

From this PR on, NeMo multispeaker ASR or ASR-with-diarization will be evaluated by cpWER. 
To evaluate cpWER value, corresponding CTM files are needed.

All diarization related evaluation (DER, cpWER) is now included in collections/utils/metric/der.py.
This is for reusability of the diarization evaluation code

**Collection**: [Note which collection this PR will affect]
ASR

# Changelog 

- Added functions regarding `cpWER` calculation
- Added docstings in `diarization_utils.py`
- Changed variable names:
 `total_riva_dict` -> `trans_info_dict`,
 `riva_dict` -> `session_trans_dict`,

- Removed functions and imports regarding `WDER` and word-timestamp calculation.
- DER, cpWER are  now included in collections/utils/metric/der.py.
# Usage
* You can potentially add a usage example below

```python
python offline_diar_with_asr_infer.py \
    diarizer.manifest_filepath=<path to manifest file> \
    diarizer.out_dir='demo_asr_output' \
    diarizer.speaker_embeddings.model_path=<pretrained model name or path to .nemo> \
    diarizer.asr.model_path=<pretrained model name or path to .nemo> \
    diarizer.speaker_embeddings.parameters.save_embeddings=False \
    diarizer.asr.parameters.asr_based_vad=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)
- [x] Did you write any new necessary tests?
- [x] 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

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)
add label inference support to EncDecSpeakerLabel class
State: closed | Pull request: yes

Signed-off-by: nithinraok <nithinrao.koluguri@gmail.com>

# What does this PR do ?

Add label inference support for EncDecSpeakerLabel models

**Collection**: ASR

# Changelog 
- Add new `infer_file` function which returns both logits and embeddings
- update existing `get_embedding` function to use `infer_file`
- add new `get_label` function that returns label automatically (based on trained model labels)
- update existing speaker inference scripts to use these functions

# Usage

* For getting label (for eg: langid)
```python
from nemo.collections.asr.models import EncDecSpeakerLabelModel 
model = EncDecSpeakerLabelModel.from_pretrained('langid_ambernet')
lang = model.get_label(<path_to_audio_file>)
```

# 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)
- [x] 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