renwei2024/nemo-github-issues huggingface dataset:
[Bug fix] EP initialize in megatron fake initialize bug fix
State: closed | Pull request: yes
Labels: name: stale

name: NLP

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[NeMo-UX] Adding GPTModel & MockDataModule
State: closed | Pull request: yes

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Temporarily remove mcore dep
State: closed | Pull request: yes

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neva eval script minor fixes
State: closed | Pull request: yes
Labels: name: stale

name: Multi Modal

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Fix docs errors and most warnings
State: closed | Pull request: yes
Labels: name: core

name: ASR

name: NLP

name: common

name: Multi Modal

name: Run CICD

# What does this PR do ?

Fix all current doc-building errors and most warnings. I have not fixed all warnings in the interest of making the PR not too large, and have tried to avoid making some changes that might conflict with @yaoyu-33 's current work on improving the doc structure.


FAO @titu1994 : please look over the changes to `docs/source/conf.py`. I removed the duplicate "sphinxcontrib.bibtex" extension. I have also commented out the "sphinx.ext.autosectionlabel" extension as that was causing a lot of "duplicate label" warnings. 


**Collection**: Docs

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Microbatch Calculator merge into MCore
State: closed | Pull request: yes
Labels: name: stale

# What does this PR do ?

Change microbatch calculator implementation into mcore. Related to MCore # 24

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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.

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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.

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unfused lora
State: closed | Pull request: yes
Labels: name: NLP

name: CI

name: Run CICD

# What does this PR do ?

make nemo lora compatible with HF ("canonical") lora.

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Update megatron_core requirements to greater or equal
State: closed | Pull request: yes

# What does this PR do ?

Update requirements file

**Collection**: [nlp]

# Changelog 
- Change mcore version to greater or equal

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updated here: https://github.com/NVIDIA/NeMo/pull/9010
Improved random seed configuration for Lhotse dataloaders with docs
State: closed | Pull request: yes
Labels: name: ASR

name: common

# What does this PR do ?

* Comprehensive documentation about random seed configuration, behavior, and effects on dataloading.
* Backward-compatible changes to random seed configuration in training.
* Allows more precise control over randomness; this work was triggered by the need to support mixed data-parallel (DP) and tensor-parallel (TP) training. Before this PR, it wasn't possible to configure the dataloader to yield identical data on identical DP ranks but different TP ranks, causing deadlocks. Now it's possible but the user has to be careful about manually setting different random seeds on training continuations (this is documented).
* Unit tests to ensure the desired behavior in DDP setups.

**Collection**: ASR

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Thanks @erastorgueva-nv, for some reason I thought it's required by sphinx. It should look much better indeed!

Docs LGTM
is Forced Alignment available on prebuilt Docker images?
State: closed | Pull request: no
Labels: name: stale

Hello!

I'm working with the Forced aligner and so far everything has been positive! 

Now I wanted to use the prebuilt docker images provided by Nvidia, but when exploring the images I don't see any reference to the Forced Aligner script I used on the Google Colab example you provide.

Is this expected? Do I have to use the pytorch:23.10-py3 Docker image and install NeMo from GitHub?

Thanks in advance.

Hi! If you want use NeMo, you can either use the PyTorch container and install NeMo on it, or use a NeMo speech container. There are instructions for both in the README, e.g. [here](https://github.com/NVIDIA/NeMo/tree/main?tab=readme-ov-file#docker-containers). AFAIK, neither type of container contains any of the [tools from this directory](https://github.com/NVIDIA/NeMo/tree/main/tools). However, all of those tools are essentially relatively lightweight Python scripts that use NeMo (and maybe some other dependencies that are mentioned in their requirements files).

So if I were you, I would set up one of the Docker containers and make sure NeMo is installed, then git clone the NeMo repository so that you have access to the NFA scripts here: https://github.com/NVIDIA/NeMo/tree/main/tools/nemo_forced_aligner.

Then you should be able to use NFA inside the container by calling the `<path to your NeMo location>/tools/nemo_forced_aligner/align.py` script.


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.

Hi, marking as closed since I believe the issue is resolved.
add geglu to mlp swap
State: closed | Pull request: yes
Labels: name: NLP

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Jenkins

Jenkins
add timeout for new_group
State: closed | Pull request: yes
Labels: name: NLP

name: CI

# What does this PR do ?

Based on https://github.com/NVIDIA/Megatron-LM/commit/e69187bc3679ea5841030a165d587bb48b56ee77, this PR aims to make user-set timeout applicable to all ProcessGroups instead of just default ProcessGroups

**Collection**: [Note which collection this PR will affect]

# Changelog 
- During model parallel initialization, it will pass a timeout parameter (which is the existing attribute of `NLPDDPStrategy`) to new ProcessGroup creation. 

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test for update_black [NOT FOR MERGING]
State: closed | Pull request: yes
Labels: name: ASR

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@ipmedenn Thanks, it works now. Closing this PR, but need another one to test changes)
[NeMo-UX] Adding megatron strategy
State: closed | Pull request: yes

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Simplify sharded_state_dict saving
State: closed | Pull request: yes
Labels: name: NLP

# What does this PR do ?

Simplify NLPDDPStrategy.save_checkpoint methods by using native PTL mechanism for state dict construction.

**Collection**: NLP

# Changelog 
- Create optimizer state dict with `optimizer_state` method
- Create model state in `on_save_checkpoint` method

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Add safety checks for 'data' key in MegatronGPTModel cfg
State: closed | Pull request: yes
Labels: name: NLP

# What does this PR do ?

Add safety checks for 'data' key in MegatronGPTModel cfg

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- Add specific line by line info of high level changes in this PR.

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Update dependency install for LLM and MM
State: closed | Pull request: yes

# What does this PR do ?

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# Add a code snippet demonstrating how to use this 
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mixtral evaluation PR
State: closed | Pull request: yes
Labels: name: Multi Modal

name: Run CICD

Please refer to the previous PR:
https://github.com/NVIDIA/NeMo/pull/8988

@ethanhe42   
too messy to fix the signature issue for the previous pr: https://github.com/NVIDIA/NeMo/pull/8988
So restart a new one. LOL..


@Slyne could you move doc to `docs/source/multimodal/mllm/video_neva.rst` ?

@ethanhe42 Done.
Small fix for Mixtral as judge eval pipeline
State: closed | Pull request: yes
Labels: name: stale

name: Multi Modal

# What does this PR do ?

This PR is a fix for https://github.com/NVIDIA/NeMo/pull/8634.

**Collection**: 
No collection would be affected.
We can run the script independently. And nemo dependency is not needed.

# Changelog 
- Fix small bugs
- Add doc

# Usage

For internal usage and evaluate the neva result, you can run the below command. Please check the doc to generate your NGC API for fundation model.
```python
 API_TOKEN=nvapi-xxx  python3 mixtral_eval.py --model-name-list gpt vneva --media-type image  --question-file llava-bench-in-the-wild/questions.jsonl --responses-list responses/gpt4v.jsonl responses/vneva.jsonl  --answers-dir ./   --context-file llava-bench-in-the-wild/context.jsonl --output ./output.json
```
You can also check the document for how to do benchmark on `llava-bench-in-the-wild`.
Please contact @PannuMuthu for the response files. 

# Jenkins CI

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@PannuMuthu  There's one commit not signed off. Please help check.
@PannuMuthu @ethanhe42  Please review.
Thanks!

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.
fix condition
State: closed | Pull request: yes
Labels: name: stale

name: NLP

# What does this PR do ?
With EP enabled mcore_gpt is required (previously was checking megatron_amp_O2 whether it was enabled).

**Collection**: [Note which collection this PR will affect]

# Changelog 
- Add specific line by line info of high level changes in this PR.

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* You can potentially add a usage example below

```python
# Add a code snippet demonstrating how to use this 
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jenkins

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.
Fix checkpoint saving with checkpoint_callback_params.save_weights_only
State: closed | Pull request: yes
Labels: name: stale

name: NLP

# What does this PR do ?

Add a one line overview of what this PR aims to accomplish.

**Collection**: [Note which collection this PR will affect]

# Changelog 
- Add specific line by line info of high level changes in this PR.

# Usage
* You can potentially add a usage example below

```python
# Add a code snippet demonstrating how to use this 
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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.

This PR was closed because it has been inactive for 7 days since being marked as stale.
Is frame marblenet VAD still supported?
State: closed | Pull request: no
Labels: name: bug

Hello,

I have tried downloading and using the frame marblenet vad, but it returns an error.

```
 wget --content-disposition https://api.ngc.nvidia.com/v2/models/nvidia/nemo/vad_multilingual_frame_marblenet/versions/1.20.0/zip -O vad_multilingual_frame_marblenet_1.20.0.zip
--2024-01-23 16:14:29--  https://api.ngc.nvidia.com/v2/models/nvidia/nemo/vad_multilingual_frame_marblenet/versions/1.20.0/zip
Resolving api.ngc.nvidia.com (api.ngc.nvidia.com)... 54.188.231.142, 34.223.159.108
Connecting to api.ngc.nvidia.com (api.ngc.nvidia.com)|54.188.231.142|:443... connected.
HTTP request sent, awaiting response... 404 Not Found
2024-01-23 16:14:30 ERROR 404: Not Found.
```

Is it still supported?

Best regards,
Gabriel
TDT confidence fix
State: closed | Pull request: yes
Labels: name: ASR

# What does this PR do ?

This PR enables confidence scores computing for TDT models.

It introduces a new `ConfidenceConfig` parameter named `tdt_include_duration` which allows caclulating frame-level confidence for the token duration prediction.

**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 
```

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# Additional Information
* Related to  https://github.com/NVIDIA/NeMo/issues/8737


> I found 2 problems with the current implementation:

I think I fixed those problems. Could you please check again?
Implement DistributedCheckpointIO
State: closed | Pull request: yes
Labels: name: NLP

# What does this PR do ?

This PR sets the ground for more advanced distributed checkpointing features, like fully parallel save/load or async save which will be configured and implemented as part of DistributedCheckpointIO plugin. It doesn't introduce any new features, just refactors existing behavior.

Note: the correctness of not applying the "skip if exists" saving logic relies on https://github.com/NVIDIA/NeMo/pull/8980 and is required for async saving

**Collection**: NLP

# Changelog 
- implement DistributedCheckpointIO plugin for save/load of distributed checkpoints
- simplify checkpoint saving NLPDDPStrategy flow

# Usage
* You can potentially add a usage example below

```python
# Add a code snippet demonstrating how to use this 
```

# Jenkins CI

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# Additional Information
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Prevent duplicated checkpoints
State: closed | Pull request: yes
Labels: name: NLP

# What does this PR do ?

This PR fixes the behavior of encountering an existing distributed checkpoint. Previously it caused saving skip, this PR reuses the PTL versioning mechanism to adjust the checkpoint name accordingly

**Collection**: NLP

# Changelog 
- fix the behavior of skipping duplicate checkpoint by reusing PTL versioning mechanism

# Usage
* You can potentially add a usage example below

```python
# Add a code snippet demonstrating how to use this 
```

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docs and simplification of cmd args
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.

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# Changelog 
- Add specific line by line info of high level changes in this PR.

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# Add a code snippet demonstrating how to use this 
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jenkins

Great doc @arendu , just a few typos to fix. Btw, I saw no Jenkins test, is cicd-main.yml the replacement?
Update PR template
State: closed | Pull request: yes
Labels: name: CI

# What does this PR do ?

Add a one line overview of what this PR aims to accomplish.

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# Changelog 
- Add specific line by line info of high level changes in this PR.

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# Add a code snippet demonstrating how to use this 
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