renwei2024/nemo-github-issues huggingface dataset:
MegaMolBART compatibility
State: closed | Pull request: yes

# What does this PR do ?

1. Fixes RegExTokenizer missing attributes.
2. Fixes broken Megatron encoder-decoder LM model ability to receive directly encoder hiddens.

```
    MegatronLMEncoderDecoderModel.forward(
        self,
        encoder_input_ids,
        decoder_input_ids,
        encoder_attn_mask,
        decoder_attn_mask,
        token_type_ids=None,
        lm_labels=None,
        # NEW API
        enc_output=None,
        enc_output_attn_mask=None,
        # NEW API
        output_enc_hidden_only=False,
        enc_input=None,
    ):
```

3. Added MegatronLMEncoderDecoderModel.encode method.
4. Improved decoding speed.

**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 write any new necessary tests?
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- [ ] 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)
Tacotron2 1.9.0 bugfixes
State: closed | Pull request: yes

# What does this PR do ?

Update Tacotron2 training tutorial and config to work with r.1.9.0

**Collection**: TTS

# Changelog 
- Updated 44kHz config to use TTSDataset (now matches with 22kHz config)
- Added file downloads necessary for training to the Tacotron2 notebook
- Minor bugfix to avoid device mismatch during training for the notebook

**PR Type**:
- [ ] New Feature
- [x] Bugfix
- [ ] Documentation
Updated to Prompt Learning Model to Use Distributed Sampler
State: closed | Pull request: yes

Signed-off-by: Virginia Adams <vadams@nvidia.com>

# What does this PR do ?

Updates the prompt learning model to use pytorch's DistributedSampler and fixes an issue with trailing spaces at the end of some prompts during inference. 

**Collection**: BigNLP

# Changelog 
Updated PromptLearningDataset class
Updated PromptLearningModel class

# Usage
Same as before

# Before your PR is "Ready for review"
**Pre checks**:
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# Additional Information
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Support larger datasets for question answering 
State: closed | Pull request: yes

# What does this PR do ?

Support larger datasets for question answering 

**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**:
- [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**:
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- [ ] Bugfix
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# Additional Information
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Add special tokens to existing (trained) SentencePiece models
State: closed | Pull request: yes

Signed-off-by: Abhinav Khattar <aklife97@gmail.com>

# What does this PR do ?

Script to add special tokens to existing SentencePiece model. This can help in moving away from the legacy way of handling special tokens.

**Collection**: None

# Usage
`python edit_spt_model.py --input_file <input_model_dir> --output_file <output_model_dir> --tokens <space separated special tokens> `

# 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
Patch Hydra
State: closed | Pull request: yes

Signed-off-by: smajumdar <smajumdar@nvidia.com>

# What does this PR do ?

Fix Hydra issue with hydra_runner

**Collection**: [Core]

# Changelog 
- Update signature and lower bound to latest hydra

**PR Type**:
- [ ] New Feature
- [x] Bugfix
- [ ] Documentation
added conformer mandarin model.
State: closed | Pull request: yes

Signed-off-by: Vahid <vnoroozi@nvidia.com>

# What does this PR do ?

Adding the checkpoint of a Mandarin ASR model trained with Conformer-Transducer to the pretrained model's list. It is trained on AIShell-2 dataset.

# Changelog 
Added a Mandarin ASR model trained with Conformer-Transducer on AIShell-2.

**PR Type**:
- [x] New Feature
- [ ] Bugfix
- [ ] Documentation
Update Dialogue tutorial
State: closed | Pull request: yes

# What does this PR do ?

Update typos in Dialogue 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?
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# Additional Information
* Related to # (issue)
Fix/punctuation/trainer required for setting test data
State: closed | Pull request: yes
Labels: name: bug

# What does this PR do ?

1. Previously `PunctuationCapitalizationModel.set_trainer()` was required before calling `PunctuationCapitalizatoinModel.set_{training,test,validation}_data()`. This is unexpected for users. Now `set_trainer()` call is not required and warnings are shown.
2. Training random seed for batching is now `current_epoch` instead of `global_step`.
3. Typo fix
4. Fix last cell in punctuation notebook tutorial.

**Collection**: nlp
Prompt tokenization bugfix
State: closed | Pull request: yes

# What does this PR do ?

1. adds <> around virtual prompt token string
2. Removes pseudo token configurability from the config file in favor of using a consistent pseudo token set by us
3. Makes PROMPT lowercase

**Collection**: BigNLP

# Changelog 
Updated megatron_gpt_prompt_learning_model
Updated prompt learning dataset unit tests
Added Enum for virtual prompt token string

# Usage
Same as before

# 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?
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**PR Type**:
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- [x] Bugfix
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# Additional Information
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Pin omegaconf for r1.9.0
State: closed | Pull request: yes

Signed-off-by: ericharper <complex451@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

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# Additional Information
* Related to # (issue)
training with horovod
State: closed | Pull request: no
Labels: name: bug

Hi, I am trying to use horovod for accelerator. Training steps:

1. cd NeMo/examples/nlp/text_classification
2. python text_classification_with_bert.py

This steps works without any problem. However when I try to use horovod:

1. cd NeMo/examples/nlp/text_classification
2.change pl Trainer:
pl.Trainer(plugins=[NLPDDPPlugin()], **cfg.trainer) to trainer = pl.Trainer(strategy="horovod", accelerator="gpu", devices=1, plugins=[NLPDDPPlugin()], **cfg.trainer) in `text_classification_with_bert.py`
3. horovodrun -np 1 -H server1:1 --verbose --start-timeout 300 python text_classification_with_bert.py

I got this error:

```
(nemo)$ horovodrun -np 1 -H server1:1 --verbose --start-timeout 300 python text_classification_with_bert.py
Filtering local host names.
Remote host found: server1
Checking ssh on all remote hosts.
SSH was successful into all the remote hosts.
Testing interfaces on all the hosts.
Launched horovod server.
Launching horovod task function: ssh -o PasswordAuthentication=no -o StrictHostKeyChecking=no server1 path/to/miniconda3/envs/nemo/bin/python -m horovod.runner.task_fn ...
Attempted to launch horovod task servers.
Waiting for the hosts to acknowledge.
Launching horovod task function was not successful:
bash: path/to/miniconda3/envs/nemo/bin/python: No such file or directory
```

**Environment overview**
PyTorch version: 1.11.0
CUDA used to build PyTorch: 10.2

OS: Ubuntu 18.04.3

Python version: 3.8.13
Is CUDA available: True
CUDA runtime version: 11.3.58

Versions of relevant libraries:
[pip3] numpy==1.21.5
[pip3] pytorch-lightning==1.6.1
[pip3] torch==1.11.0
[pip3] torch-stft==0.1.4
[pip3] torchaudio==0.11.0
[pip3] torchmetrics==0.8.0
[pip3] torchvision==0.12.0
[conda] pytorch                   1.11.0          py3.8_cuda10.2_cudnn7.6.5_0    pytorch
[conda] pytorch-lightning         1.6.1                    pypi_0    pypi
[conda] pytorch-mutex             1.0                        cuda    pytorch
[conda] torch-stft                0.1.4                    pypi_0    pypi
[conda] torchaudio                0.11.0               py38_cu102    pytorch
[conda] torchmetrics              0.8.0                    pypi_0    pypi
[conda] torchvision               0.12.0               py38_cu102    pytorch


Note: I run an [mnist example with Horovod](https://github.com/horovod/horovod/blob/master/examples/pytorch/pytorch_mnist.py) itself directly without a problem.
error running offline_diarization.py
State: closed | Pull request: no
Labels: name: bug

**Describe the bug**

Hi, I have previously run the code as stated in Usage description of the script. However, now I get this error by running the exact same code. This is the error messege.
Global seed set to 42
Traceback (most recent call last):
  File "/content/NeMo/examples/speaker_tasks/diarization/offline_diarization.py", line 46, in <module>
    main()
  File "/usr/local/lib/python3.7/dist-packages/nemo/core/config/hydra_runner.py", line 108, in wrapper
    config_name=config_name,
TypeError: _run_hydra() missing 1 required positional argument: 'args'


**Steps/Code to reproduce bug**

!python3 /content/NeMo/examples/speaker_tasks/diarization/offline_diarization.py \
diarizer.manifest_filepath='/content/input_manifest.json' \
diarizer.out_dir='demo_output' \
diarizer.speaker_embeddings.model_path='titanet_large' \
diarizer.oracle_vad=True


**Environment overview (please complete the following information)**

On Google colab

**Environment details**
Upperbound OmegaConf
State: closed | Pull request: yes

Signed-off-by: smajumdar <smajumdar@nvidia.com>

# What does this PR do ?

Fix omegaconf incompatibility.

**Collection**: [Core]

**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?
@ericharper
Add support for Decoder + Joint Adapters for ASR
State: closed | Pull request: yes

# What does this PR do ?

Add support for decoder + joint adapters, alongside encoder adapters. Supports CTC + RNNT decoders, RNNT Joint, RNNT Decoder + Joint adapter.

**Collection**: [ASR]

# Changelog 
- Support CTC Decoder, RNNT Decoder, RNNT Joint adapter support (module level).
- Update tests to check new modules
- Add support for property that defines list of valid modules that support adapters.

# Usage


```python
# Add a code snippet demonstrating how to use this 
model.add_adapter("decoder:<adapter_name>", cfg=...)  # decoder only adapter; CTC/RNNT
model.add_adapter("joint:<adapter_name>", cfg=...)  # joint only adapter; RNNT only
model.add_adapter("decoder+joint:<adapter_name>", cfg=...)  # decoder + joint adapter; RNNT only
```

# 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
SSL Multi-loss Update
State: closed | Pull request: yes

# What does this PR do ?

- adds multi-loss training to ssl, with corresponding list of decoders and losses defined through the ssl model config
- adds option to use pseudo-labels from quantization module of contrastive loss as targets for other losses
- adds option for ssl decoders to use outputs of non-final layer of encoder as input
- default ssl config is updated to use contrastive + mlm loss combination
- adds tests for ssl and maskedpatchaugmentation
- fixes sampling for tarred datasets with multiple utterances per file

**Collection**: ASR

**PR Type**:
- [x] New Feature
- [ ] Bugfix
- [ ] Documentation

If you haven't finished some of the above items you can still open "Draft" PR.
Implements the UL2 Dataset and config
State: closed | Pull request: yes

# What does this PR do ?

1. Implements the UL2 Dataset from https://arxiv.org/abs/2205.05131.
2. Adds a `megatron_ul2_config.yaml` to train an encoder-decoder model on this data using t5 pretraining script.

**Collection**: NLP

# Changelog 
- UL2 dataset class that inherits from T5Dataset
- UL2 yaml config
- Minor refactor of LMAdaptedT5Dataset

# Usage

`python megatron_t5_pretraining.py -cn megatron_ul2_config`

# 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
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# Additional Information
* Related to # (issue)
Conformer Model Training Details.
State: closed | Pull request: no

Hi I am training a Conformer Model  and need to know if thing about the training process. 

My Training params :  
- learning rate : 0.1,   
- batch_size = 128 
- max_epochs : 100
- warmup steps : 10000

The questions I had were. 
1.   What hardware was used to train the `ctc_conformer_large` and `ctc_conformers_medium` models. gpus and how long were they trained (hrs). 
2. If my learning rate has reduced to 1e-6 will the model still continue learning or should I be stopping at this point.
    asking becz  using the noam scheduler the learning rate has decreased quite a bit in the first 2 epochs only and hv another 98 to go.
3. A curious question what happens if my batch size is 4 and a set up a really high grad accum like 16 will his work?    
    
 @titu1994   
 
 
 thanks
[TTS] Fix Hifigan finetune tutorial
State: closed | Pull request: yes

Signed-off-by: Subhankar Ghosh <subhankar2321@gmail.com>

# What does this PR do ?

Fix Hifigan finetune tutorial
Solution to https://github.com/NVIDIA/NeMo/issues/4181

**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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# Additional Information
* Related to #4181
Possible bug in the tutorial for fine-tuning hifi
State: closed | Pull request: no

Hello! I'm trying to fine-tune the HiFi according to your fastpitch_finetuning tutorial. I generated manifests in the same format as in the example. Then I launched the fine-tuning script by simply changing the paths. Despite the small number of changes, I constantly get an error. I tried to study the code to understand what I'm doing wrong. In the process of studying, I found a possible cause of my troubles and would like to ask you on whose side the error occurred. I think it would be more convenient to explain the essence of my question with screenshots.

You use the file path as the model.train_ds parameter:

![image](https://user-images.githubusercontent.com/69087388/168687289-17551431-3b4f-4da5-949b-8b93cee5ba8c.png)

Next, I went through the error traceback and found that at some point the parameter that was specified in the previous step is used. If I didn’t mix up anything, then we also just use the path to the file:

![image](https://user-images.githubusercontent.com/69087388/168687995-b07350aa-13c9-4d55-9bec-ee010552c0d4.png)

In the next traceback step, we send this path to the setup_data_loader_from_config function, where the error occurs. Looking inside the function, I found that our argument is checked for the presence of the word "dataset". It is at this point that the error occurs, since the path to my manifest does not contain this word. Although, apparently, it was assumed that the input of the function would not be a string containing the path to the manifest, but the config itself, which would contain the specified argument. The same thing can be observed in the two lines of code below, where the presence of dataloader_params is checked:

![image](https://user-images.githubusercontent.com/69087388/168688988-38d30379-70d8-42a8-93ad-bc83abd1018a.png)

In this regard, I really hope for your help. Thanks in advance!
small import name fix
State: closed | Pull request: yes

Signed-off-by: fayejf <fayejf07@gmail.com>

# What does this PR do ?

Add a one line overview of what this PR aims to accomplish.

**Collection**: ASR

# 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)
Tiny import func name fix
State: closed | Pull request: yes

# What does this PR do ?

import function name fix 

**Collection**: ASE

# 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
- [ ] 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)
[bugfix] consistent highfreq to both fastpitch and hifigan in their 44100 configs.
State: closed | Pull request: yes

# What does this PR do ?

make highfreq consistent to both fastpitch and hifigan in their 44100 configs.

**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)
SpeakerDecoder weight normalization
State: closed | Pull request: no
Labels: name: bug

Hi!

When reading SpeakerDecoder code I bumped into [this](https://github.com/NVIDIA/NeMo/blob/1d3eb3d0d045f7f57316217320b8d265bf3256ce/nemo/collections/asr/modules/conv_asr.py#L848) line. Looks like it is weight normalization for AAS loss. But why should it work?

```
>>> import torch.nn as nn
>>> import torch.nn.functional as F
>>> layer = nn.Linear(128, 100, bias=False)
>>> weight1 = layer.weight.data.clone()
>>> for W in layer.parameters():
...     W = F.normalize(W, p=2, dim=1)
...
>>> weight2 = layer.weight.data.clone()
>>> weight1 == weight2
tensor([[True, True, True,  ..., True, True, True],
        [True, True, True,  ..., True, True, True],
        [True, True, True,  ..., True, True, True],
        ...,
        [True, True, True,  ..., True, True, True],
        [True, True, True,  ..., True, True, True],
        [True, True, True,  ..., True, True, True]])
>>>
```
let sox find wav duration when it is missing (None).
State: closed | Pull request: yes
Labels: name: stale

# What does this PR do ?

bug-fix.  sox must find the wav duration when dur is None.

**Collection**:  speaker_tasks

# Changelog 
L135: this condition should be true when 'dur is None' because it allows sox to get the duration from the wav_file.

# Usage
* You can potentially add a usage example below

```python
# Add a code snippet demonstrating how to use this 
python ../../../scripts/speaker_tasks/scp_to_manifest.py --scp voxceleb12.scp  --id 8 --out TMP 
```

# 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

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## Who can review?

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# Additional Information
* Related to # (issue)
Add docs for Thutmose Tagger
State: closed | Pull request: yes

Signed-off-by: Alexandra Antonova <aleksandraa@nvidia.com>

# What does this PR do ?

Add docs for Thutmose Tagger model (ITN)

**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)
Thutmose tagger docs
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 docs for Thutmose Tagger model (ITN)

# 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)
set plugin to None when no apex
State: closed | Pull request: yes

Signed-off-by: ekmb <ebakhturina@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
- [ X] Bugfix
- [ ] 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)
k2 package conflict with NeMo
State: closed | Pull request: no
Labels: name: bug

Hi,

I was examining `examples/asr/experimental/k2/align_speech_parallel.py` script as I wish to get speech alignments from my trained CTC-based ASR model. Somewhere, I was told that I have to install k2 package to use this script and its recommended method is by using `scripts/speech_recognition/k2/setup.sh`. However, when I executed the `setup.sh` script, its output is like this:
`ImportError: k2 was built using PyTorch 1.7.1+cu101
But you are using PyTorch 1.11.0+cu102 to run it
k2 installed with errors! Please check installation manually.`
As far as I know, NeMo needs Pytorch 1.10.0 or above to function but it seems that k2 has been built by PyTorch 1.7.1.
I know the k2 based scripts in NeMo are experimental for now, but is there any chance to bypass this?
TTS removed models 
State: closed | Pull request: no

Hi,
Why Some TTS model (MelGAN, TalkNet) are removed from main branch, while they are exist in 1.8.2 ? 
Do you want to stop maintaining them ?

https://github.com/NVIDIA/NeMo/commit/c37786a9acb443b1d55d56636f00d3826ffc76d5
TTS Tacotron training
State: closed | Pull request: no

Hi,

I followed the [tacotron notebook](https://colab.research.google.com/github/NVIDIA/NeMo/blob/r1.0.0rc1/tutorials/tts/2_TTS_Tacotron2_Training.ipynb#scrollTo=Upv_LxBIsC51) and tried to train the nemo model. I end up getting stuck with this error. Can you please help?

`TypeError: Error instantiating 'nemo.collections.asr.data.audio_to_text.AudioToCharDataset' : __init__() got an unexpected keyword argument 'load_audio'
`
update speaker docs
State: closed | Pull request: yes

Signed-off-by: nithinraok <nithinrao.koluguri@gmail.com>

# What does this PR do ?

Update speaker docs related to recent script name change from scp_to_manifest.py to filelist_to_manifest.py

# Changelog 
- Update docs

# 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?
- [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
- [ ] Bugfix
- [x] Documentation
rename folder VAD -> vad
State: closed | Pull request: yes

Signed-off-by: fayejf <fayejf07@gmail.com>

# What does this PR do ?

rename VAD folder in examples/asr/conf/ to vad and update files accordingly. 

**Collection**:ASR

# 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)
Thutmose tagger bug fixes
State: closed | Pull request: yes

# What does this PR do ?

Bug fixes. Update tutorial. Add pretrained model to list_available_models

**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. 
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# Additional Information
* Related to # (issue)
Add 44KHz yaml file for Fastpitch training
State: closed | Pull request: yes

Signed-off-by: Subhankar Ghosh <subhankar2321@gmail.com>

# What does this PR do ?

Add 44KHz yaml file for Fastpitch training

**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)
transcribe: scan directories recursively
State: closed | Pull request: yes

# What does this PR do ?

Update transcribe script to scan directories recursively.

**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)
notebooks' link, typo and import  fix 
State: closed | Pull request: yes

# What does this PR do ?

bug fix for notebook

**Collection**:ASR
# 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)
Speaker Diarization
State: closed | Pull request: no
Labels: name: bug

I am trying to implement speaker diarization using __vad_marblenet__ and __titanet_large__ models.

# Issue
When I am trying to run on server/local machine .... the process either gets stuck or terminates due to CPU memory allocation error during clustering.
- __memory allocation issue__
![Screenshot from 2022-05-11 17-34-38](https://user-images.githubusercontent.com/29993931/168004643-afd81bdc-d018-422a-9a7c-1788f733d4e0.png)
- __execution halted__
![Screenshot from 2022-05-12 12-01-30](https://user-images.githubusercontent.com/29993931/168006552-788685e5-be35-4ee2-8035-9b4e11517c51.png)
![Screenshot from 2022-05-12 12-03-23](https://user-images.githubusercontent.com/29993931/168006635-73c1b165-4e95-43f8-90c2-c38fd1edcd64.png)

## Environment:
- OS : Ubuntu 18.04.6 LTS (GNU/Linux 4.18.0-25-generic x86_64)
- Memory: 
![Screenshot from 2022-05-12 11-52-18](https://user-images.githubusercontent.com/29993931/168005126-f3197681-38c3-4b6a-834d-d5fe5df053a5.png)
- Python: 3.7.13
- Installation : from source i.e. __(git clone ... & cd NeMo & ./reinstall.sh)__
# Reference
When executing on collab, it's working properly. It's giving proper diarization results.
 - Link to notebook: https://colab.research.google.com/drive/1UgzoPHV1aByDDhygCUAiEaEIRGldrocK?usp=sharing
 - Test audio file: https://drive.google.com/file/d/1ChLsVHTgH4SUgvqLP7ymtrbao-L0KKsj/view?usp=sharing
 - Manifest file: https://drive.google.com/file/d/1SAeLmMIHGk-rc7ydHfYLywCkbMx7SbH6/view?usp=sharing
 - Diarization yaml config file: https://drive.google.com/file/d/1lvYYg5Pd8hUceS2a-raO76huu-p0p39V/view?usp=sharing
 - Test audio file result: https://drive.google.com/drive/folders/1FCH_UOFUFJZUQdxMHQfzXQII-bg6auaO?usp=sharing

## Environment:
- Installation on collab: from source i.e. __(git clone ... & cd NeMo & ./reinstall.sh)__
- Python: 3.7.13
Freesound fixes
State: closed | Pull request: yes

# What does this PR do ?

Fixes freesound-python git path and updates filename cleanup

**Collection**: [Note which collection this PR will affect]

# Changelog 
- Update requirements.txt to use https instead of git to fix "The unauthenticated git protocol on port 9418 is no longer supported."
- Remove additional characters from filename

# 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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# Additional Information
* Related to # (issue)
Fix Docs CSS: align docs left and increase width for large screens
State: closed | Pull request: yes

# What does this PR do ?

Align docs left and increase width for screens > 1200px

**Collection**: All

# Changelog 
- Align docs left and increase width for screens > 1200px

# 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
- [ ] Bugfix
- [x] 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)