renwei2024/nemo-github-issues huggingface dataset:
update TDT blog with new RTF numbers collected on different machines.
State: closed | Pull request: yes

# What does this PR do ?

update TDT blog with new RTF numbers collected on different machines.

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Tdt blog
State: closed | Pull request: yes
Labels: name: stale

# What does this PR do ?

update TDT blog with new RTF numbers collected on different machines.

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- Add specific line by line info of high level changes in this PR.

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enable nmt to use beam search
State: closed | Pull request: yes
Labels: name: stale

name: NLP

# What does this PR do ?

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"Loop labels" greedy decoding: faster implementation
State: closed | Pull request: yes
Labels: name: ASR

# What does this PR do ?

Improves "loop labels" greedy decoding implementation, introduced in #7926, with using non-blocking operations (avoiding device-to-host synchronization).

On my local machine, the time for decoding unsorted `test-other` (LibriSpeech) with `stt_en_fastconformer_transducer_large` (2 repeated measurements, in seconds; after warmup the results are better):

 bs | precision  | RNN-T, loop_labels v1 (main) | RNN-T, loop_labels v2 (this)
-- | -- | -- | --
16 | fp32 | 50s / 50s | 37s / 36s
128 | fp32 | 34s / 33s | 30s / 29s
16 | bf16 | 48s / 46s | 34s / 32s
128 | bf16 | 25s / 24s | 21s / 20s

This algorithm is planned for further improvements with torch.jit.script in #8203

**Collection**: [ASR]

# Changelog 
- Add specific line by line info of high level changes in this PR.

# Usage

```shell
python examples/asr/speech_to_text_eval.py \
   model_path=<nemo_model.nemo> \
   dataset_manifest=<manifest> \
   batch_size=128 \
   output_filename=<output_mainfest_path> \
   rnnt_decoding.greedy.loop_labels=true
```

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Huvu/mcore retro
State: closed | Pull request: yes
Labels: name: core

name: TTS

name: ASR

name: NLP

name: Speaker Tasks

name: CI

name: common

name: Multi Modal

# What does this PR do ?
Implementing RETRO's mcore model, dataloader's wrapper, training script.

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This PR is stale because it has been open for 14 days with no activity. Remove stale label or comment or update or this will be closed in 7 days.
mcore ds fix
State: closed | Pull request: yes
Labels: name: core

name: NLP

name: CI

name: common

# What does this PR do ?

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Create causal mask on MCore/TE side
State: closed | Pull request: yes
Labels: name: NLP

# What does this PR do ?

Currently Megatron-LM creates causal attention mask for a local-layer spec model on its own -- see https://github.com/NVIDIA/Megatron-LM/commit/a45805a3ee0645b85b48d14b0a8077fa5b1216b2 -- and hence `attention_mask=None` can be specified in Nemo. In this MR, I'm using this new M-LM functionality when creating `fwd_output_only_func` function.

Broader functional tests for `fwd_output_only_func` will follow in subsequent MRs.

**Collection**: NLP

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@titu1994 could you help to land it? Prerequisite is mcore=0.5.0 https://github.com/NVIDIA/NeMo/pull/8465
fix bert mcore for tp, pp and sp
State: closed | Pull request: yes
Labels: name: stale

name: NLP

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WandB project for tp,pp, sp both nemo legacy bert model and mcore bert model. The curves match https://wandb.ai/shanmugamr/mcore_test?workspace=user-shanmugamr

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add deallocate pipeline output optimization
State: closed | Pull request: yes
Labels: name: NLP

# What does this PR do ?

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fix peft mixin arguments to follow mcore 0.5
State: closed | Pull request: yes
Labels: name: NLP

# What does this PR do ?
- mcore TransformerLayer introduced packed_seq_params, adding it to `MCoreTransformerLayerMixin`
- mcore renamed `bias_gelu_fusion` to `bias_activation_fusion`, changing it in adapter mcore_mixins

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jenkins

closing as this is now addressed in #7988
Pretraining + Instruction Tuning + Inference Config Recipes [Video-NeVA]
State: closed | Pull request: yes
Labels: name: stale

# What does this PR do ?

This PR adds config recipes for pretraining, instruction tuning, and inference for VideoNeVA derived from Video-LLaVA

**Collection**: Multimodal

# Changelog 
- Adds `video_llava_config.yaml` config recipe derived from authors pretraining configuration in Video-LLaVA
- Adds `video_neva_config.yaml` config recipe adapted from `video_llava_config.yaml` for NeMo (similar to `neva_config.yaml` vs `video_neva_config.yaml`)
- Adds `video_neva_finetune.yaml` config recipe derived from authors finetuning configuration in Video-LLaVA
- Adds `video_neva_inference.yaml` config recipe derived from authors inference configuration in Video-LLaVA


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fused_adam + mcore fix
State: closed | Pull request: yes
Labels: name: NLP

# What does this PR do ?

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Converter script fixes for mixtral/mistral
State: closed | Pull request: yes
Labels: name: NLP

# What does this PR do ?

Fixes mistral & mixtral conversion scripts(renamed variable `num_experts` to `num_moe_experts` in mixtral converter).

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Multimodal r1.23.0 fixes
State: closed | Pull request: yes
Labels: name: core

name: TTS

name: ASR

name: NLP

name: Speaker Tasks

name: CI

# What does this PR do ?

Fix r1.23.0 issues for multimodal collection

**Collection**: [Multimodal]

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training bug fix and adding launch script for speech_multitask
State: closed | Pull request: yes
Labels: name: ASR

# What does this PR do ?
Fixes some bugs related to training after canary-2 refactor
Adds a launch script for AED multitask models in `examples/asr/speech_multitask` folder

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blogpost for Parakeet-TDT model
State: closed | Pull request: yes

# What does this PR do ?

blogpost for Parakeet-TDT model

**Collection**: [Note which collection this PR will affect]

# Changelog 
blogpost for Parakeet-TDT model
# Usage

N/A

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Neftune
State: closed | Pull request: yes
Labels: name: stale

name: NLP

# What does this PR do ?

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**Pre checks**:
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# Additional Information
* Related to # (issue)


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create_alignment_manifest.py conf ValueError
State: closed | Pull request: no
Labels: name: bug

name: stale

Run the Speaker_Diarization_Training.ipynb notebook.
Run this cell:

!python NeMo/scripts/speaker_tasks/create_alignment_manifest.py \
  --input_manifest_filepath LibriSpeech/dev_clean.json \
  --base_alignment_path LibriSpeech_Alignments \
  --output_manifest_filepath ./dev-clean-align.json \
  --ctm_output_directory ./ctm_out \
  --libri_dataset_split dev-clean

This cell produces the following error:

File "/home/acampbellblack/dev/py/nemo-training/.venv/lib/python3.10/site-packages/nemo/collections/asr/parts/utils/manifest_utils.py", line 110, in get_ctm_line
    raise ValueError(f"`conf` must be a float or str containing float, but got {type(conf)}")
ValueError: `conf` must be a float or str containing float, but got <class 'int'>

Running locally (bare-metal), installed NeMo via install script in the notebook:
! python -m pip install git+https://github.com/NVIDIA/NeMo.git@$BRANCH#egg=nemo_toolkit[all]

Running on WSL on Windows 11,
Ubuntu 22.04.3 LTS
Python 3.10.12
torch==2.1.2+cu118

GPU: NVidia RTX 4080 Laptop

This issue is stale because it has been open for 30 days with no activity. Remove stale label or comment or this will be closed in 7 days.

This issue was closed because it has been inactive for 7 days since being marked as stale.
Support uploading NeMo models to HF via `push_to_hf_hub()`
State: closed | Pull request: yes
Labels: name: core

name: NLP

# What does this PR do ?

Adds the ability to upload NeMo models to Huggingface, and restore NeMo models from unpacked HF directory.

**Collection**: [Core]

# Changelog 
- Support upload to HF via `push_to_hf_hub()` in Model/ModelPT
- Support uploading single .nemo file or full folder of unpacked nemo file. Full folder is useful for LLMs where the single nemo file is larger than HF upload limit of 10 GB per uploaded object.
- Support restoring unpacked NeMo file when downloading from Huggingface hub

# Usage

## Upload loaded model
```python

token = "<HF TOKEN>" or None
pack_nemo_file = True  # False uploads multiple files that comprise the NeMo file onto HF Hub; Easier for LLMs 

model.push_to_hf_hub(
   repo_id=repo_id, pack_nemo_file=True, token=token,
)
```

## Supports most HF Upload arguments such as private upload

```python
model.push_to_hf_hub(
    repo_id=repo_id, pack_nemo_file=False, token=token, private=True
)
```

## Modify model card with helpers
```python

template = """ <Your own custom template> 
# {model_name}
"""
kwargs = {"model_name": "ABC", "repo_id": "nvidia/ABC_XYZ"}
model_card = model.generate_model_card(template=template, template_kwargs=kwargs, type="hf")

model.push_to_hf_hub(
    repo_id=repo_id, token=token, model_card=model_card
)
```

## Modify model card with custom class
```python
class MyModelCard:
  def __init__(self, model_name):
    self.model_name = model_name

  def __repr__(self):
    template = """
This is the {model_name} model
""".format(model_name=self.model_name)
    return template

model.push_to_hf_hub(
    repo_id=repo_id, token=token, model_card=MyModelCard("ABC")
)
```

# Jenkins CI
To run Jenkins, a NeMo User with write access must comment `jenkins` on the PR.

# 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.



jenkins

jenkins

jenkins
Update PEFT Doc
State: closed | Pull request: yes
Labels: name: NLP

# What does this PR do ?

Update models names in supported models
Remove old prompt learning doc and notebook

# Jenkins CI
To run Jenkins, a NeMo User with write access must comment `jenkins` on the PR.

# 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
- [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. 
[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 to accomendate mcore changes
State: closed | Pull request: yes
Labels: name: NLP

# What does this PR do ?

- Remove FalconTransformerLayer's sharded_state_dict() to use the mcore 0.5's TransformerLayer's sharded_state_dict() because it supports sharded_dict according to submodules now.
- add packed_seq_params (introduced in mcore 0.5) args for layer forward.

**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 
```

# Jenkins CI
To run Jenkins, a NeMo User with write access must comment `jenkins` on the PR.

# 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)


jenkins
Refactor Canary to follow schema of remaining ASR models
State: closed | Pull request: yes
Labels: name: core

name: ASR

# What does this PR do ?

Refactor Canary to follow Archetype pattern of rest of ASR. Add Decoding Strategy to disentangle decoding with model  architecture.

**Collection**: [ASR]

# Changelog 
- Refactors model class to conform to ASR's archetype pattern
- Add Decoding strategy as a middle layer between model logits and text to allow extending decoding algorithms in the future
- Update configs to new schema

# 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
update webdataset to latest version
State: closed | Pull request: yes
Labels: name: stale

name: ASR

Initial commit. 

> Update version to 0.2.86
> Pipe functionality removed and has been replaced with DataPipeline. 

Draft version, In works 

This PR is stale because it has been open for 14 days with no activity. Remove stale label or comment or update or this will be closed in 7 days.

This PR was closed because it has been inactive for 7 days since being marked as stale.
[tutorial] fixed missing RIR scripts file.
State: closed | Pull request: yes
Labels: name: ASR

# What does this PR do ?

missing get_openslr_rir_data.py file in RIR section.

**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 
```

# Jenkins CI
To run Jenkins, a NeMo User with write access must comment `jenkins` on the PR.

# 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)


jenkins
MoE parameter passing
State: closed | Pull request: yes
Labels: name: NLP

name: CI

# 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 
```

# Jenkins CI
To run Jenkins, a NeMo User with write access must comment `jenkins` on the PR.

# 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)


jenkins

jenkins

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jenkins
Expert parallelism
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 
```

# Jenkins CI
To run Jenkins, a NeMo User with write access must comment `jenkins` on the PR.

# 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)
mcore ds fix
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 
```

# Jenkins CI
To run Jenkins, a NeMo User with write access must comment `jenkins` on the PR.

# 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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[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)


jenkins

 Thanks Dmytro!

Was this able to start training megatron_gpt model successfully? If so, what version of Megatron-LM was used? 
I see the commit in the base Dockerfile is 27cbe46714a50c43ed290f1b1472db8d2780c55c, which is on the core_r0.4.0 branch. 

But the addition of GPTDatasetConfig in megatron.core.datasets.gpt_dataset only exists on main, and for reset_position_ids and etc only after this commit: https://github.com/NVIDIA/Megatron-LM/commit/8d8241a9cfdf5ad6c511c5303a2623185ee18c3c

I'm wondering where eod_id comes from since it's passed as part of all kwargs into GPTDatasetConfig.
But I don't see eod_id existing in gpt_dataset in Megatron-LM https://github.com/NVIDIA/Megatron-LM/blame/4bd4e7426c8def582eb80ae53f296a803643d2f5/megatron/core/datasets/gpt_dataset.py#L33

Currently I'm having issues launching the job:
```
  File "lib/python3.10/site-packages/nemo/collections/nlp/models/language_modeling/megatron_gpt_model.py", line 1223, in build_train_valid_test_datasets
    dataset_config = GPTDatasetConfig(**kwargs)
TypeError: GPTDatasetConfig.__init__() got an unexpected keyword argument 'eod_id'
```

@ryxli I had a similar issue. My WAR was to disable warmup on synthetic data.
[canary] Refactor: move changes in transformer_bpe_models.py to Canar…
State: closed | Pull request: yes
Labels: name: ASR

…yModel

# 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 
```

# Jenkins CI
To run Jenkins, a NeMo User with write access must comment `jenkins` on the PR.

# 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.


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# Additional Information
* Related to # (issue)


After renaming/refactoring + converting old ckpt to use new target model definition it works - merging this to https://github.com/NVIDIA/NeMo/tree/canary-2-dataset-refactor where I'll next rename/refactor the dataset class
Use Pytest with Coverage
State: closed | Pull request: yes
Labels: name: CI

# What does this PR do ?

- PyTest on Jenkins runs with coverage (you can see the coverage report in logs for unit tests GPU/CPU)
- Remove deprecated `pytest-runner` (plugin used earlier to run pytest via setup.py, now useless and unsupported)
- You can see now the failing/skipped/passed tests in Jenkins UI, e.g., http://10.110.40.131:8080/blue/organizations/jenkins/NeMo-multibranch/detail/PR-8250/3/tests

**Collection**: [CI]

# Changelog 
- Add specific line by line info of high level changes in this PR.

# Usage
* You can potentially add a usage example below

```shell
pytest --cov=nemo --cov-report=html test_my_awesome_feature.py
```

# Jenkins CI
To run Jenkins, a NeMo User with write access must comment `jenkins` on the PR.

# Before your PR is "Ready for review"
**Pre checks**:
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jenkins

jenkins

jenkins

Closed since Jenkins will be replaced with Github actions in the near future