renwei2024/nemo-github-issues huggingface dataset:
Configure no restart validation loop in nl.Trainer
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name: skip-docs

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Cherrypick Fix pip install (#11026)
State: closed | Pull request: yes
Labels: name: Run CICD

* Move AutoTokenizer inline



* Move einops to common requirements



* Move AutoTokenizer import to top-level again in fine_tuning



* Move megatron init inside nemo.lightning



* Make megatron_lazy_init_context work when transformer-engine is not installed



* Only import get_nmt_tokenizer when needed



* Apply isort and black reformatting



---------

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CI passed: https://github.com/NVIDIA/NeMo/actions/runs/11521807470
Pip install
State: closed | Pull request: yes
Labels: name: core

name: TTS

name: stale

name: ASR

name: NLP

name: Speaker Tasks

name: CI

name: common

name: Multi Modal

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Fix pip install
State: closed | Pull request: yes
Labels: name: Run CICD

name: r2.0.0

# What does this PR do ?

This PR makes sure that we can import nemo.collections.common when nemo-toolkit[lightning,common] is installed.

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add deprecation note
State: closed | Pull request: yes
Labels: name: NLP

name: Run CICD

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Cherry pick `Add a build option to load_context (10713)` into `r2.0.0`
State: closed | Pull request: yes
Labels: name: cherry-pick

name: Run CICD

[🤖]: Hi @marcromeyn 👋,<br><br>we've cherry picked #10713 into `r2.0.0` for you! 🚀<br><br>Please review and approve this cherry pick by your convenience\!
Akoumparouli/hf lit module peft ckpt bugfix
State: closed | Pull request: yes
Labels: name: Run CICD

# What does this PR do ?
Handle ckpt saving for `LinearAdapter` which does not have `sharded_state_dict`

Need to confirm both save & restore work correctly wrt to all saving options.

Add a one line overview of what this PR aims to accomplish.

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Performance mode (#10926) and gpt3 175b cli (#10985)
State: closed | Pull request: yes
Labels: name: cherry-pick

name: Run CICD

* llama3 performance mode



* llama3 performance mode tests



* mixtral performance mode



* remove unused



* nemotron perf mode



* 405b, 174b perf mode



* perf mode comment



* Apply isort and black reformatting



---------

# What does this PR do ?

cheery-pick Performance mode (#10926) and gpt3 175b cli (#10985)

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Cherry pick `Change default for always_save_context to True (11014)` into `r2.0.0`
State: closed | Pull request: yes
Labels: name: cherry-pick

name: Run CICD

[🤖]: Hi @athitten 👋,<br><br>we've cherry picked #11014 into `r2.0.0` for you! 🚀<br><br>Please review and approve this cherry pick by your convenience\!
Deploy ASR STT Streaming model
State: closed | Pull request: no
Labels: name: stale

Hi

Any suggestions on how to deploy and scale the STT En FastConformer Hybrid Transducer-CTC Large Streaming Multi model. We have finetuned this model and need to handle 100 users (to start with) using this model.

We will receive the chunks of audio data through a websocket connection from our application. How do we tackle multiple users? Do we create multiple instances of the model? Do we connect multiple users to same model? We are using the following tutorial for doing the inference through the model. (https://github.com/NVIDIA/NeMo/blob/main/tutorials/asr/Online_ASR_Microphone_Demo_Cache_Aware_Streaming.ipynb)
This notebook has a transcribe chunk function which takes an audio chunk and processes it. Can we do batch transcription here for multiple users?

Thank You

@vsl9 can we deploy ASR Nemo checkpoints on Triton ? 

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.
Cleanup MegatronStep inside MegatronParallel
State: closed | Pull request: yes
Labels: name: stale

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Update `BaseMegatronSampler` for compatibility with PTL's `_BatchProgress`
State: closed | Pull request: yes
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name: r2.0.0

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Support exporting Nemotron-340B for TensorRT-LLM
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@oyilmaz-nvidia  Hi Onur, can you help review this PR?
In TRT-LLM 0.14 release, we are working to prepare documentation for multi-node deployment and we want to use Nemotron as an example. Without this fix, we cannot run through Nemotron on multi-node.

It seems the changes in [nemo/export/trt_llm/converter/model_converter.py](https://github.com/NVIDIA/NeMo/pull/11015/files/83299cc74d63a9f9868f94a6990c30c3e25ba546#diff-4a09132034fd9a231315e092fa057c1ad7a7db379985c97d776a8dd1ea995b25) is not necessary. I tested parallel_embedding still works without the changes. Could we remove the change on this file?
Change default for always_save_context to True
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name: r2.0.0

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use __dict__ in check
State: closed | Pull request: yes

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Add new args from mcore to Gemma 2 dot product attention
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# Additional Information
* Related to # (issue)


absorbed in #10959
Ashors/peft async ckpt
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 
```

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* Related to # (issue)
Log_props output in TRT-LLM
State: closed | Pull request: yes
Labels: name: Run CICD

# What does this PR do ?

Adds the functionality to return log_props from TRT-LLM using PyTriton.

@athitten If this PR works for you, I'll do some cleanup and start the CI.

> @athitten If this PR works for you, I'll do some cleanup and start the CI.

@oyilmaz-nvidia sorry I dint get a chance to test it out yet. I will test it tomorrow. But the PR looks good otherwise. Thank you!

Closing this since it'll be included here: https://github.com/NVIDIA/NeMo/pull/11233
Cherry pick `llm.generate fixes (10983)` into `r2.0.0`
State: closed | Pull request: yes
Labels: name: cherry-pick

name: Run CICD

[🤖]: Hi @HuiyingLi 👋,<br><br>we've cherry picked #10983 into `r2.0.0` for you! 🚀<br><br>Please review and approve this cherry pick by your convenience\!
Expose packed seq in finetuning recipes
State: closed | Pull request: yes
Labels: name: Run CICD

name: r2.0.0

# What does this PR do ?

Add a one line overview of what this PR aims to accomplish.

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# Add a code snippet demonstrating how to use this 
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[🤖]: Hi @cuichenx 👋,

We wanted to let you know that a [CICD pipeline](https://github.com/NVIDIA/NeMo/actions/runs/11521928915) for this PR just finished successfully

So it might be time to merge this PR or get some approvals

I'm just a bot so I'll leave it you what to do next.

//cc @pablo-garay @ko3n1g
Cherry pick `Fix for crash with LoRA + tp_overlap_comm=false + sequence_parallel=true (10920)` into `r2.0.0`
State: closed | Pull request: yes
Labels: name: cherry-pick

name: NLP

name: Run CICD

[🤖]: Hi @vysarge 👋,<br><br>we've cherry picked #10920 into `r2.0.0` for you! 🚀<br><br>Please review and approve this cherry pick by your convenience\!
canary-1b is not exportable
State: closed | Pull request: no
Labels: name: bug

name: stale

**Describe the bug**

The Canary model is not exportable to onnx. It seems like it was not configured to be exportable.

**Steps/Code to reproduce bug**
```
import nemo.collections.asr as nemo_asr

def main():
    # Load Canary model
    model_name = "nvidia/canary-1b"
    print(f"Loading model: {model_name}")
    model = nemo_asr.models.ASRModel.from_pretrained(model_name=model_name)
    
    # Prepare for export
    model.eval()
    
    # Try to export - this will raise the error
    output_path = "canary.onnx"
    print("Attempting ONNX export...")
    model.export(
        output_path,
        onnx_opset_version=17,
        verbose=True
    )

if __name__ == "__main__":
    main()
```

This gives the error:
```
AttributeError: 'EncDecMultiTaskModel' object has no attribute 'output_names'
Traceback:
File "venv/lib/python3.11/site-packages/streamlit/runtime/scriptrunner/exec_code.py", line 88, in exec_func_with_error_handling
    result = func()
             ^^^^^^
File "venv/lib/python3.11/site-packages/streamlit/runtime/scriptrunner/script_runner.py", line 579, in code_to_exec
    exec(code, module.__dict__)
File "app.py", line 22, in <module>
    main()
File "app.py", line 15, in main
    model.export(
File "nemo/core/classes/exportable.py", line 117, in export
    out, descr, out_example = model._export(
                              ^^^^^^^^^^^^^^
File "nemo/core/classes/exportable.py", line 196, in _export
    output_names = self.output_names
                   ^^^^^^^^^^^^^^^^^
File "venv/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1931, in __getattr__
    raise AttributeError(
```


**Expected behavior**

I would expect to be able to export this model.

**Environment overview (please complete the following information)**

 - Environment location: Mac
 - Method of NeMo install: pip install

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 just commenting since GH marked this as stale.

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.
Cherry pick 51e9b7c 2.0.0
State: closed | Pull request: yes
Labels: name: CI

name: Run CICD

# 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 
```

# GitHub Actions CI

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The GitHub Actions CI will run automatically when the "Run CICD" label is added to the PR.
To re-run CI remove and add the label again.
To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".

# 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
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NeMo 1.0: upcycle dense to moe
State: closed | Pull request: yes
Labels: name: NLP

name: Run CICD

# What does this PR do ?

```
python3 upcycle_dense_to_moe.py --model ../mistral_2l_extracted/ --num-experts 8 --output-path what-moe
```
**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 
```

# GitHub Actions CI

The Jenkins CI system has been replaced by GitHub Actions self-hosted runners.

The GitHub Actions CI will run automatically when the "Run CICD" label is added to the PR.
To re-run CI remove and add the label again.
To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".

# 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)


[🤖]: Hi @akoumpa 👋,

We wanted to let you know that a [CICD pipeline](https://github.com/NVIDIA/NeMo/actions/runs/11578189409) for this PR just finished successfully

So it might be time to merge this PR or get some approvals

I'm just a bot so I'll leave it you what to do next.

//cc @pablo-garay @ko3n1g
Bump `Dockerfile.ci` (2024-10-23)
State: closed | Pull request: yes
Labels: name: Run CICD

🚀 PR to Bump `Dockerfile.ci`.  

📝 Please remember the following to-do's before merge: 
- [ ] Verify the presubmit CI  

🙏 Please merge this PR only if the CI workflow completed successfully.

[🤖]: Hi @ko3n1g 👋,

We wanted to let you know that a [CICD pipeline](https://github.com/NVIDIA/NeMo/actions/runs/11470661097) for this PR just finished successfully

So it might be time to merge this PR or get some approvals

I'm just a bot so I'll leave it you what to do next.

//cc @pablo-garay @ko3n1g
Cherrypick Change recipes #10915
State: closed | Pull request: yes
Labels: name: Run CICD

# What does this PR do ?

Cherrypick #10915 into r2.0.0

**Collection**: [Note which collection this PR will affect]

# Changelog 
- Add specific line by line info of high level changes in this PR.

# Usage
* You can potentially add a usage example below

```python
# Add a code snippet demonstrating how to use this 
```

# GitHub Actions CI

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To re-run CI remove and add the label again.
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# 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?
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  - [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
  
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation

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# Additional Information
* Related to # (issue)
Unable to export MSDD model to pt or ONNX
State: closed | Pull request: no
Labels: name: bug

name: stale

**Describe the bug**

`EncDecDiarLabelModel` inherits `ExportableEncDecModel` which inherits `Exportable`. That means it should be exported to pt or ONNX file. When I ran the following code to export it, 
```
model = EncDecDiarLabelModel(cfg=modelConfig)
 msdd_model.export(output="msdd_model.pt", input_example=input_example)
```
I ran into errors:
```
AttributeError: 'EncDecDiarLabelModel' object has no attribute 'input_names'
```
The `input_names` attribute is defined in`Exportable`at [here](https://github.com/NVIDIA/NeMo/blob/1ba8bb1c623c2b7e938549002f5b77ab02fbe4bc/nemo/core/classes/exportable.py#L320). Is this an issue related to Python MRO (method resolution order)? 

**Steps/Code to reproduce bug**

I added some lines after [here](https://github.com/NVIDIA/NeMo/blob/1ba8bb1c623c2b7e938549002f5b77ab02fbe4bc/tests/collections/asr/test_diar_label_models.py#L155).
```
            input_example = (input_signal, input_signal_length, emb_vectors, targets)
            msdd_model.msdd._speaker_model.export(output="speaker_model.onnx")
            msdd_model.export(output="msdd_model.pt", input_example=input_example)
```

**Expected behavior**

Both`speaker_model.py`and`msdd_model.pt` are generated.

**Environment overview (please complete the following information)**

 - Environment location: Bare-metal
 - Method of NeMo install: check out the latest NeMo (commit 9a66eeeac2aa62541476bb4b66ae375b70d2db83) and run `pip install -e ".[asr]"` under the root folder.

**Environment details**

If NVIDIA docker image is used you don't need to specify these.
Otherwise, please provide:
- OS version: Ubuntu 24.04
- PyTorch version: 2.4.1+cu124
- Python version: 3.11.10

**Additional context**

Add any other context about the problem here.
GPU model: Nvidia L4 


Hi. MSDD is not an end-to-end model that performs speaker diarization from audio to label and it does not support ONNX export.
We are less than a month ahead of releasing end-to-end speaker diarizer, so please try using the new model once it gets released. 

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.
Cherry pick llm.generate
State: closed | Pull request: yes
Labels: name: Run CICD

* Add llm.generate



* Remove comment



* Apply isort and black reformatting



* Fix launching with python



* PR feedback



* PR feedback



* Apply isort and black reformatting



* Add assert cp



* Add example script



* Fix



---------

# 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 
```

# GitHub Actions CI

The Jenkins CI system has been replaced by GitHub Actions self-hosted runners.

The GitHub Actions CI will run automatically when the "Run CICD" label is added to the PR.
To re-run CI remove and add the label again.
To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".

# 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)


Related : https://github.com/NVIDIA/NeMo/pull/10471
srun issue with nemorun
State: closed | Pull request: no
Labels: name: stale

I am trying to run a simple pretraining job with nemorun: `nemorun llm pretrain --factory llama3_8b`

However, I see the following error before the training starts:
```
The application appears to have been direct launched using "srun",
but OMPI was not built with SLURM's PMI support and therefore cannot
execute. There are several options for building PMI support under
SLURM, depending upon the SLURM version you are using:

  version 16.05 or later: you can use SLURM's PMIx support. This
  requires that you configure and build SLURM --with-pmix.

  Versions earlier than 16.05: you must use either SLURM's PMI-1 or
  PMI-2 support. SLURM builds PMI-1 by default, or you can manually
  install PMI-2. You must then build Open MPI using --with-pmi pointing
  to the SLURM PMI library location.

Please configure as appropriate and try again.
```

I understand that this is a problem with the way openmpi is configured on my cluster but I can't change it.
An alternate solution that I have been told is to replace the `srun` command with something like `mpirun -np`. I want to try this but I am unable to locate where the `srun` command is being run in the first place? I dug into the [slurm.py file in NeMo-run](https://github.com/NVIDIA/NeMo-Run/blob/main/src/nemo_run/core/execution/slurm.py), but changing the commands there did not yield any difference.

Are there any other potential alternatives to this?

Can you try adding `executor.srun_args = ["--mpi=pmix"]` and see if that works?

@hemildesai 
How do I set that argument? I don't see it in the listed arguments with the command `nemorun llm pretrain --help`:

![Image](https://github.com/user-attachments/assets/d8af7cdf-4c57-4411-889e-859f52e5e581)


In the current version of the repo, the `srun_args` ([here](https://github.com/NVIDIA/NeMo/blob/f27a982ed192f8039d5a30b51208847c9c1b0fc3/nemo/collections/common/parts/run_utils.py#L496)) seem to have the `--mpi=pmix` command by default? However, I still see the same error as before.

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.