renwei2024/nemo-github-issues huggingface dataset:
Enable cudagraphs for Peft and Pretraining
State: closed | Pull request: yes
Labels: name: NLP

name: Run CICD

name: skip-docs

# What does this PR do ?

Adds padding support for packed sequences, enables mcore cudagraph knobs. This depends on an mcore PR that has not been merged.


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ci: Fix release workflow
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Draft: Add bert Model to NeMo 2.0
State: closed | Pull request: yes

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chore: Add changelog
State: closed | Pull request: yes

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Create phi3mini.py
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Adding multimodal examples
State: closed | Pull request: yes
Labels: name: Run CICD

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chore(beep boop 🤖): Bump `MCORE_TAG=64cbae5...` (2024-11-14)
State: closed | Pull request: yes
Labels: name: stale

name: Run CICD

🚀 PR to bump `NVIDIA/Megatron-LM` in `Dockerfile.ci` to `MCORE_TAG=64cbae55ac85cd73fbadbc3c0d715c8123c5e13b`.  

📝 Please remember the following to-do's before merge: 
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add inference
State: closed | Pull request: yes
Labels: name: stale

name: NLP

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Use MegatronDataSampler in HfDatasetDataModule
State: closed | Pull request: yes
Labels: name: Run CICD

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using skip_nan_grad with gradient accumulation for ASR
State: closed | Pull request: no
Labels: name: stale

Hi, I notice that while training the ASR fastconformer model on my data, some after a few epochs there can be a batch that cause NaN error. So, I tried setting skip_nan_grad = True, which allow the train_loss curve to look normal (without spiking to NaN), but I notice in the error log that after the message "detected inf or nan values in gradients! Setting gradients to zero.", the all prediction in the following validation rounds are "??" and the validation wer increased to 1. I set accumulate_grad_batches to 4 for the training so I wonder whether this might be the culprit. Does setting skip_nan_grad = True can still work with gradient accumulation. I'd really appreciate any comment you can give on the issue!

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chore: Add `devN` to semver
State: closed | Pull request: yes
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Adding alinger export
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Fix Finetune Recipe
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We wanted to let you know that a [CICD pipeline](https://github.com/NVIDIA/NeMo/actions/runs/11819198597) for this PR just finished successfully

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************* Module nemo.collections.llm.recipes.gemma_2b
nemo/collections/llm/recipes/gemma_2b.py:256:0: C0301: Line too long (121/119) (line-too-long)
nemo/collections/llm/recipes/gemma_2b.py:257:0: C0301: Line too long (158/119) (line-too-long)
************* Module nemo.collections.llm.recipes.starcoder_15b
nemo/collections/llm/recipes/starcoder_15b.py:283:0: C0301: Line too long (121/119) (line-too-long)

-----------------------------------
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```

---

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Introducing TensorRT lazy export and caching option with trt_compile() 
State: closed | Pull request: yes
Labels: name: Run CICD

# What does this PR do ?
Introducing TensorRT lazy export and caching option with trt_compile(): 
- TRT engine build happens on first forward() call, using either ONNX->TRT or Torch-TensorRT and the inputs passed to forward() 
- Dynamic dimensions can be specified either via 'input_profiles' argument (full-blowt TRT optimization profile values) or 'dynamic_batchsize' argument (batch dimension min/opt/max only). 
- The engine is serialized to the disk for reuse

See inline documentation in the source for more details.

# Usage

```
            args = {"method": "torch_trt"}
            model = trt_compile(
                model,
                "path_to_save_engine",
                args=args,
            )



@borisfom could you resolve the alert from CodeQL? If it's intended, you can dismiss it.

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Add checklist for config validations
State: closed | Pull request: yes
Labels: name: stale

name: CI

# What does this PR do ?

Change PR template for config validation
**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)
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**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)


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.

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.
ci: Run secrets detector on `pull_request_target`
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.

**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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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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perf summary on homepage
State: closed | Pull request: yes
Labels: 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 
```

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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.

@ericharper could you help review and merge this? With this PR, we will have only one source of truth (NeMo docs) for perf numbers.
chore(beep boop 🤖): Bump `MCORE_TAG=aded519...` (2024-11-12)
State: closed | Pull request: yes
Labels: name: Run CICD

🚀 PR to bump `NVIDIA/Megatron-LM` in `Dockerfile.ci` to `MCORE_TAG=aded519cfb1de2abf96f36ca059f992294b7876f`.  

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

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

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We wanted to let you know that a [CICD pipeline](https://github.com/NVIDIA/NeMo/actions/runs/11802050066) for this PR just finished successfully

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Remove builder_opt param from trtllm-build for TensorRT-LLM >= 0.14.0
State: closed | Pull request: yes
Labels: name: Run CICD

# What does this PR do ?

Removing deprecated `--builder_opt` param from `trtllm-build` command, see https://github.com/NVIDIA/TensorRT-LLM/releases/tag/v0.14.0.

**Collection**: NLP / LLM

# Changelog 
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* 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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We wanted to let you know that a [CICD pipeline](https://github.com/NVIDIA/NeMo/actions/runs/11800744418) for this PR just finished successfully

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Fail to convert Llama3 Nemo 2.0 checkpoint to HF
State: closed | Pull request: no
Labels: name: bug

name: stale

**Describe the bug**

I use Nemo 2.0 to train my model and get Nemo 2.0 checkpoint like this with .distcp files:
model_name
├── context
│   ├── model_config.yaml
│   ├── io.json
│   └── tokenizer
├── weights
│   ├── distributed checkpointing directories/files in torch_dist format
│   ├── metadata.json
│   └── common.pt


but filed to use NeMo/scripts/checkpoint_converters/convert_llama_nemo_to_hf.py to export it to a HF file

**Expected behavior**

get HF files by Nemo2.0 checkpoint



Is there a way we can now save non .distcp files or huggingface .bin files directly after training?
If not, how to convert nemo2.0 checkpoint to the community common format?

Hi, the scripts/checkpoint_converters/convert_llama_nemo_to_hf.py script is only for NeMo 1.0 checkpoints. To export 2.0 checkpoints, you can use a custom script like

```python
from pathlib import Path

from nemo.collections.llm import export_ckpt

if __name__ == "__main__":
    export_ckpt(
        path=Path("/workspace/input_ckpt"),
        target="hf",
        output_path=Path("/workspace/output_ckpt.hf"),
    )
```

> Hi, the scripts/checkpoint_converters/convert_llama_nemo_to_hf.py script is only for NeMo 1.0 checkpoints. To export 2.0 checkpoints, you can use a custom script like
> 
> from pathlib import Path
> 
> from nemo.collections.llm import export_ckpt
> 
> if __name__ == "__main__":
>     export_ckpt(
>         path=Path("/workspace/input_ckpt"),
>         target="hf",
>         output_path=Path("/workspace/output_ckpt.hf"),
>     )



Here are my fold arch:
```shell
nemo2_llama3
├── context
│ ├── model.yaml
│ ├── io.json
│ └── nemo_tokenizer
├── weights
│ ├── __0_0.distcp
│ ├── __0_1.distcp
│ ├── metadata.json
│ └── common.pt
``` 

and I follow your instruction to use
```python
if __name__ == "__main__":
    export_ckpt(
        path=Path("./nemo2_llama3"),
        target="hf",
        output_path=Path("./nemo2exporthf"),
    )

``` 
but i get failed again, could you help me with this?


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.
fix(export): GPT models w/ bias=False convert properly
State: closed | Pull request: yes
Labels: 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**:
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- [ ] 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?
  
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- [ ] 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)


<!-- pylint-output-strict-mode-false -->

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---

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```
************* Module nemo.export.trt_llm.tensorrt_llm_build
nemo/export/trt_llm/tensorrt_llm_build.py:31:0: C0116: Missing function or method docstring (missing-function-docstring)
nemo/export/trt_llm/tensorrt_llm_build.py:19:0: W0611: Unused Builder imported from tensorrt_llm.builder (unused-import)
nemo/export/trt_llm/tensorrt_llm_build.py:23:0: W0611: Unused add_lora imported from tensorrt_llm.models.modeling_utils (unused-import)

-----------------------------------
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//cc @pablo-garay @ko3n1g
Bump `Dockerfile.ci` (2024-11-12)
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/11788317259) 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
update nemo1->2 conversion according to changes in main
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 
```

# 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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  - [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
  
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- [ ] 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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it's a new path & it wouldnt affect CI
Initialize a Parakeet Cache-Aware Streaming model's encoder from an offline model.
State: closed | Pull request: no

Hello,

Thank you for all your amazing work!

At the moment, nemo only support the fastconformer 120M streaming model, however I would like to also try a bigger model. I was wondering if it is possible to modify the architecture to match de 600M parakeet model and initialize the encoder weights from the offline parakeet model? Otherwise, training a bare 600M streaming model without any SSL pretraining would probably be worse and slower to train than the 120M model.

Best regards,
Gabi

See the following answer: [https://github.com/NVIDIA/NeMo/issues/9615#issuecomment-2264136385](https://github.com/NVIDIA/NeMo/issues/9615#issuecomment-2264136385)

Thanks!