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"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."
] | 2024-10-22T12:16:22 | 2024-11-30T02:01:22 | 2024-11-30T02:01:21 | NONE | {
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} | null | null | null | **Describe the bug**
I am using NeuralDiarizer with the default diar_infer_telephonic.yaml settings (nemo version 1.21.0). I am using it to diarize the real-life phone call recordings.
I have experienced the same issue for almost any shorter audio file (less than 2 minutes duration) I have diarized: the first couple of utterances, pronounced by two different speakers, are merged into the same one, and labeled such that it was spoken by a single speaker.
After the initial glitch, diarizer continues to work with the very precise predictions, so this issue is really only about the very first couple of sentences.
Any recommendation how to improve its precision for that particular problem?
**Steps/Code to reproduce bug**
I am using NeuralDiarizer with the default diar_infer_telephonic.yaml settings file, with this addition:
```python
meta = {
"audio_filepath": os.path.join(output_dir, "mono_file.wav"),
"offset": 0,
"duration": None,
"label": "infer",
"text": "-",
"rttm_filepath": None,
"uem_filepath": None,
}
with open(os.path.join(data_dir, "input_manifest.json"), "w") as fp:
json.dump(meta, fp)
fp.write("\n")
pretrained_vad = "vad_multilingual_marblenet"
pretrained_speaker_model = "titanet_large"
config.num_workers = 0
config.diarizer.manifest_filepath = os.path.join(data_dir, "input_manifest.json")
config.diarizer.out_dir = (
output_dir # Directory to store intermediate files and prediction outputs
)
config.diarizer.speaker_embeddings.model_path = pretrained_speaker_model
config.diarizer.oracle_vad = (
False # compute VAD provided with model_path to vad config
)
config.diarizer.clustering.parameters.oracle_num_speakers = False
config.diarizer.clustering.parameters.enhanced_count_thres = 80
config.diarizer.clustering.parameters.max_speaker_num = 2
# Here, we use our in-house pretrained NeMo VAD model
config.diarizer.vad.model_path = pretrained_vad
config.diarizer.vad.parameters.onset = 0.8
config.diarizer.vad.parameters.offset = 0.6
config.diarizer.vad.parameters.pad_offset = -0.05
config.diarizer.msdd_model.model_path = (
"diar_msdd_telephonic" # Telephonic speaker diarization model
)
```
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} | # 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
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# Usage
* You can potentially add a usage example below
```python
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} | # What does this PR do ?
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**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.
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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**PR Type**:
- [x] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
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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.
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"[๐ค]: Hi @janekl ๐,\n\nWe wanted to let you know that a [CICD pipeline](https://github.com/NVIDIA/NeMo/actions/runs/11891896689) for this PR just finished successfully\n\nSo it might be time to merge this PR or get some approvals\n\nI'm just a bot so I'll leave it you what to do next.\n\n//cc @pablo-garay @ko3n1g"
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} | # What does this PR do ?
Adding support for PTQ in nemo CLI.
Prerequisite: https://github.com/NVIDIA/NeMo/pull/10642.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
```bash
nemo llm ptq nemo_checkpoint=/models/Llama-3-70b \
calib_tp=8 \
export_config.inference_tensor_parallel=2 \
export_config.path=/models/Llama-3-70b-FP8
```
# 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**:
- [x] 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 https://github.com/NVIDIA/NeMo/pull/10642
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} | # What does this PR do ?
Apply the following fixes to llm.generate
- load from context subdir instead of ckpt dir
- disabling initializing optimizer
- add logic to find exact McoreGPTModel
- require user to provide their own trainer for llm.generate
Usage:
```
strategy = nl.MegatronStrategy(tensor_model_parallel_size=tp, init_model_parallel=False)
trainer = nl.Trainer(devices=tp, strategy=strategy)
print(
llm.generate(
output_path,
trainer=trainer,
prompts=["Deep learning is"],
inference_params=CommonInferenceParams(num_tokens_to_generate=20),
)
)
```
Example output:
```
[InferenceRequest(request_id='0', prompt='Deep learning is', inference_parameters=CommonInferenceParams(temperature=1.0, top_k=0, top_p=0.0, return_log_probs=False, num_tokens_to_generate=20), prompt_tokens=[34564, 6975, 374, 128001, 128001, 128001, 128001, 128001, 128001, 128001, 128001, 128001, 128001, 128001, 128001, 128001, 128001, 128001, 128001, 128001, 128001, 128001, 128001], arrival_time=1729579214.2338436, status=<Status.COMPLETED: 4>, encoder_prompt=None, generated_text=' the topic of hot interest nowadays. Thanks to its unique representatives including computer vision, natural language program etc', generated_tokens=tensor([ 279, 8712, 315, 4106, 2802, 46877, 13, 11361, 311, 1202,
5016, 24005, 2737, 6500, 11376, 11, 5933, 4221, 2068, 5099],
device='cuda:0'), generated_log_probs=None, generated_length=20)]
```
**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)
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"@akoumpa : Any chance you have the script to convert phi3-mini-4k from hf to .nemo or megatron format ? Its ok even if it is a test script. I'll use it as a starting point"
] | 2024-10-22T06:24:54 | 2024-12-25T06:18:57 | 2024-10-24T08:46:26 | MEMBER | {
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} | # What does this PR do ?
https://github.com/NVIDIA/NeMo/pull/10962 + lora
Running the example:
```
$ python3 NeMo/examples/llm/peft/hf.py --model /mnt/4tb/nemo_lite/phi3-mini-4k/
...
| Name | Type | Params | Mode
--------------------------------------------------
0 | model | Phi3ForCausalLM | 3.9 B | train
--------------------------------------------------
50.3 M Trainable params
3.8 B Non-trainable params
3.9 B Total params
15,485.645Total estimated model params size (MB)
679 Modules in train mode
0 Modules in eval mode
Epoch 0: 0%|โ 126/43800 [00:18<1:45:46, 6.88it/s, v_num=4-36, lr=1e-5, train_log_step=1.400]
```
TODO + add nemorun recipe example output
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"I tested the changes on my local branch, didn't face any problems"
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This PR is fixing two issues
1) Currently, `process_audio.py` tries to override `sampler` even if `cfg.sampler` is an empty dict (so nothing to override)
2) Currently, `transcribe_speech.py` is crashing if using `audio_key != "audio_filepath"`
**Collection**: audio, ASR
# Changelog
1) Skip sampler override if `cfg.sampler` is an empty dict
2) In `transcribe_utils`, assign the resolved audio path to `item["audio_filepath"]`
# Usage
N/A
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If you haven't finished some of the above items you can still open "Draft" PR.
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cherrypick for https://github.com/NVIDIA/NeMo/pull/10887
**Collection**: [Note which collection this PR will affect]
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} | * Add __repr__ to Artifact
* nemo.lightning.io.artifact: represent strings as fdl.Config to avoid path adjustment during restoration
* t5 test minification
* Apply isort and black reformatting
---------
# What does this PR do ?
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"Hi @rogerwelo . Can you specify which Nemo container you are using?\n\nI've been using this one (`nvcr.io/nvidia/nemo:23.08`) for inference with this model. If you are using a different container, can you try it out?\n\nShuoyang",
"I ended up using Riva and followed the steps described [here](https://docs.nvidia.com/deeplearning/riva/user-guide/docs/quick-start-guide.html#local-deployment-using-quick-start-scripts). This worked fine."
] | 2024-10-21T17:31:23 | 2024-10-29T10:40:31 | 2024-10-29T10:40:29 | NONE | {
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} | null | null | null | Hi!
I'm using the [Megatron Multilingual En Any 500M model](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/nemo/models/megatronnmt_en_any_500m) with [this example script](https://github.com/NVIDIA/NeMo/blob/main/examples/nlp/machine_translation/nmt_transformer_infer_megatron.py).
I got the script to work in a [Nemo Docker container](https://github.com/NVIDIA/NeMo/blob/main/examples/nlp/machine_translation/nmt_transformer_infer_megatron.py) in the sense that the script runs without error. However, the output file only contains empty lines indicating that the translation doesn't work properly.
The model seems to be loaded fine and there is no hint in the logs.
Any idea what is going wrong? Is this model still supported?
Thanks!
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} | # 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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If you haven't finished some of the above items you can still open "Draft" PR.
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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
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```python
# Add a code snippet demonstrating how to use this
```
# GitHub Actions CI
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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?
- [ ] 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
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Update T5 tokenizer: adding additional tokens to tokenizer config, so these additional special tokens will be saved inside the checkpoint, which can be loaded and used without manually adding additional tokens.
**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)
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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.
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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)
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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
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**:
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**PR Type**:
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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
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} | * 175b gpt3 recipe
* Apply isort and black reformatting
* dist opt params
* 405b dist opt params
* perf recipes and dist opt params
* Apply isort and black reformatting
* MoE dist opt params
* Apply isort and black reformatting
* gpt bias fusion params
* 175b recipe
* Apply isort and black reformatting
* perf params comments
* Apply isort and black reformatting
* MoE perf params comments
* Apply isort and black reformatting
* perf recipes suffix
* specific models fusion params
* Apply isort and black reformatting
---------
# 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**:
- [x] 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)
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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)
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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)
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"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."
] | 2024-10-21T07:18:59 | 2024-11-30T02:01:24 | 2024-11-30T02:01:23 | NONE | {
"total": 0,
"completed": 0,
"percent_completed": 0
} | null | null | null | **Describe the bug**
I am trying to convert the default `mamba.nemo` file (I converted [form huggingface](https://huggingface.co/nvidia/mamba2-8b-3t-4k/tree/main) .pt to .nemo) to have `tensor_parallel=4`. I have been following the [documentation here](https://docs.nvidia.com/nemo-framework/user-guide/latest/llms/mamba/checkpointconversion.html), but I got the following error.
```
[NeMo I 2024-10-21 06:50:54 megatron_init:314] Rank 0 has data parallel group : [0]
[NeMo I 2024-10-21 06:50:54 megatron_init:320] Rank 0 has combined group of data parallel and context parallel : [0]
[NeMo I 2024-10-21 06:50:54 megatron_init:325] All data parallel group ranks with context parallel combined: [[0], [1], [2], [3]]
[NeMo I 2024-10-21 06:50:54 megatron_init:328] Ranks 0 has data parallel rank: 0
[NeMo I 2024-10-21 06:50:54 megatron_init:336] Rank 0 has context parallel group: [0]
[NeMo I 2024-10-21 06:50:54 megatron_init:339] All context parallel group ranks: [[0], [1], [2], [3]]
[NeMo I 2024-10-21 06:50:54 megatron_init:340] Ranks 0 has context parallel rank: 0
[NeMo I 2024-10-21 06:50:54 megatron_init:347] Rank 0 has model parallel group: [0, 1, 2, 3]
[NeMo I 2024-10-21 06:50:54 megatron_init:348] All model parallel group ranks: [[0, 1, 2, 3]]
[NeMo I 2024-10-21 06:50:54 megatron_init:357] Rank 0 has tensor model parallel group: [0, 1, 2, 3]
[NeMo I 2024-10-21 06:50:54 megatron_init:361] All tensor model parallel group ranks: [[0, 1, 2, 3]]
[NeMo I 2024-10-21 06:50:54 megatron_init:362] Rank 0 has tensor model parallel rank: 0
[NeMo I 2024-10-21 06:50:54 megatron_init:382] Rank 0 has pipeline model parallel group: [0]
[NeMo I 2024-10-21 06:50:54 megatron_init:394] Rank 0 has embedding group: [0]
[NeMo I 2024-10-21 06:50:54 megatron_init:400] All pipeline model parallel group ranks: [[0], [1], [2], [3]]
[NeMo I 2024-10-21 06:50:54 megatron_init:401] Rank 0 has pipeline model parallel rank 0
[NeMo I 2024-10-21 06:50:54 megatron_init:402] All embedding group ranks: [[0], [1], [2], [3]]
[NeMo I 2024-10-21 06:50:54 megatron_init:403] Rank 0 has embedding rank: 0
[NeMo W 2024-10-21 06:50:54 megatron_base_model:1189] The model: MegatronMambaModel() does not have field.name: context_parallel_size in its cfg. Add this key to cfg or config_mapping to make to m
ake it configurable.
[NeMo W 2024-10-21 06:50:54 megatron_base_model:1189] The model: MegatronMambaModel() does not have field.name: moe_extended_tp in its cfg. Add this key to cfg or config_mapping to make to make it
configurable.
[NeMo W 2024-10-21 06:50:54 megatron_base_model:1189] The model: MegatronMambaModel() does not have field.name: finalize_model_grads_func in its cfg. Add this key to cfg or config_mapping to make
to make it configurable.
[NeMo W 2024-10-21 06:50:54 megatron_base_model:1189] The model: MegatronMambaModel() does not have field.name: deterministic_mode in its cfg. Add this key to cfg or config_mapping to make to make
it configurable.
[NeMo W 2024-10-21 06:50:54 megatron_base_model:1189] The model: MegatronMambaModel() does not have field.name: use_te_rng_tracker in its cfg. Add this key to cfg or config_mapping to make to make
it configurable.
[NeMo W 2024-10-21 06:50:54 megatron_base_model:1189] The model: MegatronMambaModel() does not have field.name: tp_comm_bulk_wgrad in its cfg. Add this key to cfg or config_mapping to make to make
it configurable.
[NeMo W 2024-10-21 06:50:54 megatron_base_model:1189] The model: MegatronMambaModel() does not have field.name: tp_comm_bulk_dgrad in its cfg. Add this key to cfg or config_mapping to make to make
it configurable.
[NeMo W 2024-10-21 06:50:54 megatron_base_model:1189] The model: MegatronMambaModel() does not have field.name: tp_comm_overlap_ag in its cfg. Add this key to cfg or config_mapping to make to make
it configurable.
[NeMo W 2024-10-21 06:50:54 megatron_base_model:1189] The model: MegatronMambaModel() does not have field.name: tp_comm_overlap_rs in its cfg. Add this key to cfg or config_mapping to make to make
it configurable.
[NeMo W 2024-10-21 06:50:54 megatron_base_model:1189] The model: MegatronMambaModel() does not have field.name: tp_comm_overlap_rs_dgrad in its cfg. Add this key to cfg or config_mapping to make t
o make it configurable.
[NeMo W 2024-10-21 06:50:54 megatron_base_model:1189] The model: MegatronMambaModel() does not have field.name: tp_comm_split_ag in its cfg. Add this key to cfg or config_mapping to make to make i
t configurable.
[NeMo W 2024-10-21 06:50:54 megatron_base_model:1189] The model: MegatronMambaModel() does not have field.name: tp_comm_atomic_ag in its cfg. Add this key to cfg or config_mapping to make to make
it configurable.
[NeMo W 2024-10-21 06:50:54 megatron_base_model:1189] The model: MegatronMambaModel() does not have field.name: tp_comm_split_rs in its cfg. Add this key to cfg or config_mapping to make to make i
t configurable.
[NeMo W 2024-10-21 06:50:54 megatron_base_model:1189] The model: MegatronMambaModel() does not have field.name: tp_comm_atomic_rs in its cfg. Add this key to cfg or config_mapping to make to make
it configurable.
[NeMo W 2024-10-21 06:50:54 megatron_base_model:1189] The model: MegatronMambaModel() does not have field.name: cross_entropy_loss_fusion in its cfg. Add this key to cfg or config_mapping to make
to make it configurable.
[NeMo W 2024-10-21 06:50:54 megatron_base_model:1189] The model: MegatronMambaModel() does not have field.name: tp_comm_overlap_disable_qkv in its cfg. Add this key to cfg or config_mapping to mak
e to make it configurable.
[NeMo W 2024-10-21 06:50:54 megatron_base_model:1189] The model: MegatronMambaModel() does not have field.name: tp_comm_overlap_disable_fc1 in its cfg. Add this key to cfg or config_mapping to mak
e to make it configurable.
[NeMo W 2024-10-21 06:50:54 megatron_base_model:1189] The model: MegatronMambaModel() does not have field.name: tp_comm_bootstrap_backend in its cfg. Add this key to cfg or config_mapping to make
to make it configurable.
[NeMo W 2024-10-21 06:50:54 megatron_base_model:1189] The model: MegatronMambaModel() does not have field.name: overlap_p2p_comm in its cfg. Add this key to cfg or config_mapping to make to make i
t configurable.
[NeMo W 2024-10-21 06:50:54 megatron_base_model:1189] The model: MegatronMambaModel() does not have field.name: batch_p2p_comm in its cfg. Add this key to cfg or config_mapping to make to make it
configurable.
[NeMo W 2024-10-21 06:50:54 megatron_base_model:1189] The model: MegatronMambaModel() does not have field.name: defer_embedding_wgrad_compute in its cfg. Add this key to cfg or config_mapping to m
ake to make it configurable.
[NeMo W 2024-10-21 06:50:54 megatron_base_model:1189] The model: MegatronMambaModel() does not have field.name: wgrad_deferral_limit in its cfg. Add this key to cfg or config_mapping to make to ma
ke it configurable.
[NeMo W 2024-10-21 06:50:54 megatron_base_model:1189] The model: MegatronMambaModel() does not have field.name: pipeline_model_parallel_split_rank in its cfg. Add this key to cfg or config_mapping
to make to make it configurable.
[NeMo W 2024-10-21 06:50:54 megatron_base_model:1189] The model: MegatronMambaModel() does not have field.name: cpu_offloading in its cfg. Add this key to cfg or config_mapping to make to make it
configurable.
[NeMo W 2024-10-21 06:50:54 megatron_base_model:1189] The model: MegatronMambaModel() does not have field.name: cpu_offloading_num_layers in its cfg. Add this key to cfg or config_mapping to make
to make it configurable.
[NeMo W 2024-10-21 06:50:54 megatron_base_model:1189] The model: MegatronMambaModel() does not have field.name: _cpu_offloading_context in its cfg. Add this key to cfg or config_mapping to make to
make it configurable.
[NeMo W 2024-10-21 06:50:54 megatron_base_model:1189] The model: MegatronMambaModel() does not have field.name: cpu_offloading_activations in its cfg. Add this key to cfg or config_mapping to make
to make it configurable.
[NeMo W 2024-10-21 06:50:54 megatron_base_model:1189] The model: MegatronMambaModel() does not have field.name: cpu_offloading_weights in its cfg. Add this key to cfg or config_mapping to make to
make it configurable.
[NeMo W 2024-10-21 06:50:54 megatron_base_model:1189] The model: MegatronMambaModel() does not have field.name: barrier_with_L1_time in its cfg. Add this key to cfg or config_mapping to make to ma
ke it configurable.
[NeMo I 2024-10-21 06:50:54 tokenizer_utils:217] tokenizer_model:
[NeMo I 2024-10-21 06:50:54 tokenizer_utils:218] /tmp/tmpozie5_vl/a649c6bb46eb404fac64c5ee8f43c407_mt_nlg_plus_multilingual_ja_zh_the_stack_frac_015_256k.model
[NeMo I 2024-10-21 06:50:55 megatron_base_model:604] Padded vocab_size: 256000, original vocab_size: 256000, dummy tokens: 0.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:1189] The model: MegatronMambaModel() does not have field.name: context_parallel_size in its cfg. Add this key to cfg or config_mapping to make to m
ake it configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:1189] The model: MegatronMambaModel() does not have field.name: moe_extended_tp in its cfg. Add this key to cfg or config_mapping to make to make it
configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:1189] The model: MegatronMambaModel() does not have field.name: finalize_model_grads_func in its cfg. Add this key to cfg or config_mapping to make
to make it configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:1189] The model: MegatronMambaModel() does not have field.name: deterministic_mode in its cfg. Add this key to cfg or config_mapping to make to make
it configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:1189] The model: MegatronMambaModel() does not have field.name: use_te_rng_tracker in its cfg. Add this key to cfg or config_mapping to make to make
it configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:1189] The model: MegatronMambaModel() does not have field.name: tp_comm_bulk_wgrad in its cfg. Add this key to cfg or config_mapping to make to make
it configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:1189] The model: MegatronMambaModel() does not have field.name: tp_comm_bulk_dgrad in its cfg. Add this key to cfg or config_mapping to make to make
it configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:1189] The model: MegatronMambaModel() does not have field.name: tp_comm_overlap_ag in its cfg. Add this key to cfg or config_mapping to make to make
it configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:1189] The model: MegatronMambaModel() does not have field.name: tp_comm_overlap_rs in its cfg. Add this key to cfg or config_mapping to make to make
it configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:1189] The model: MegatronMambaModel() does not have field.name: tp_comm_overlap_rs_dgrad in its cfg. Add this key to cfg or config_mapping to make t
o make it configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:1189] The model: MegatronMambaModel() does not have field.name: tp_comm_split_ag in its cfg. Add this key to cfg or config_mapping to make to make i
t configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:1189] The model: MegatronMambaModel() does not have field.name: tp_comm_atomic_ag in its cfg. Add this key to cfg or config_mapping to make to make
it configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:1189] The model: MegatronMambaModel() does not have field.name: tp_comm_split_rs in its cfg. Add this key to cfg or config_mapping to make to make i
t configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:1189] The model: MegatronMambaModel() does not have field.name: tp_comm_atomic_rs in its cfg. Add this key to cfg or config_mapping to make to make
it configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:1189] The model: MegatronMambaModel() does not have field.name: cross_entropy_loss_fusion in its cfg. Add this key to cfg or config_mapping to make
to make it configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:1189] The model: MegatronMambaModel() does not have field.name: defer_embedding_wgrad_compute in its cfg. Add this key to cfg or config_mapping to m
ake to make it configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:1189] The model: MegatronMambaModel() does not have field.name: wgrad_deferral_limit in its cfg. Add this key to cfg or config_mapping to make to ma
ke it configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:1189] The model: MegatronMambaModel() does not have field.name: pipeline_model_parallel_split_rank in its cfg. Add this key to cfg or config_mapping
to make to make it configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:1189] The model: MegatronMambaModel() does not have field.name: cpu_offloading in its cfg. Add this key to cfg or config_mapping to make to make it
configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:1189] The model: MegatronMambaModel() does not have field.name: cpu_offloading_num_layers in its cfg. Add this key to cfg or config_mapping to make
to make it configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:1189] The model: MegatronMambaModel() does not have field.name: _cpu_offloading_context in its cfg. Add this key to cfg or config_mapping to make to
make it configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:1189] The model: MegatronMambaModel() does not have field.name: cpu_offloading_activations in its cfg. Add this key to cfg or config_mapping to make
to make it configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:1189] The model: MegatronMambaModel() does not have field.name: cpu_offloading_weights in its cfg. Add this key to cfg or config_mapping to make to
make it configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:1189] The model: MegatronMambaModel() does not have field.name: barrier_with_L1_time in its cfg. Add this key to cfg or config_mapping to make to ma
ke it configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:516] apply_query_key_layer_scaling is only enabled when using FP16, setting it to False and setting NVTE_APPLY_QK_LAYER_SCALING=0
[NeMo W 2024-10-21 06:50:55 megatron_base_model:577] The model: MegatronMambaModel() does not have field.name: first_pipeline_num_layers in its cfg. Add this key to cfg or config_mapping to make t
o make it configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:577] The model: MegatronMambaModel() does not have field.name: last_pipeline_num_layers in its cfg. Add this key to cfg or config_mapping to make to
make it configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:577] The model: MegatronMambaModel() does not have field.name: activation_func_fp8_input_store in its cfg. Add this key to cfg or config_mapping to
make to make it configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:577] The model: MegatronMambaModel() does not have field.name: num_moe_experts in its cfg. Add this key to cfg or config_mapping to make to make it
configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:577] The model: MegatronMambaModel() does not have field.name: window_size in its cfg. Add this key to cfg or config_mapping to make to make it conf
igurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:577] The model: MegatronMambaModel() does not have field.name: qk_layernorm in its cfg. Add this key to cfg or config_mapping to make to make it con
figurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:577] The model: MegatronMambaModel() does not have field.name: test_mode in its cfg. Add this key to cfg or config_mapping to make to make it config
urable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:577] The model: MegatronMambaModel() does not have field.name: calculate_per_token_loss in its cfg. Add this key to cfg or config_mapping to make to
make it configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:577] The model: MegatronMambaModel() does not have field.name: multi_latent_attention in its cfg. Add this key to cfg or config_mapping to make to m
ake it configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:577] The model: MegatronMambaModel() does not have field.name: memory_efficient_layer_norm in its cfg. Add this key to cfg or config_mapping to make
to make it configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:577] The model: MegatronMambaModel() does not have field.name: fp8_margin in its cfg. Add this key to cfg or config_mapping to make to make it confi
gurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:577] The model: MegatronMambaModel() does not have field.name: fp8_interval in its cfg. Add this key to cfg or config_mapping to make to make it con
figurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:577] The model: MegatronMambaModel() does not have field.name: fp8_amax_history_len in its cfg. Add this key to cfg or config_mapping to make to mak
e it configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:577] The model: MegatronMambaModel() does not have field.name: fp8_amax_compute_algo in its cfg. Add this key to cfg or config_mapping to make to ma
ke it configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:577] The model: MegatronMambaModel() does not have field.name: fp8_wgrad in its cfg. Add this key to cfg or config_mapping to make to make it config
urable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:577] The model: MegatronMambaModel() does not have field.name: fp8_dot_product_attention in its cfg. Add this key to cfg or config_mapping to make t
o make it configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:577] The model: MegatronMambaModel() does not have field.name: fp8_multi_head_attention in its cfg. Add this key to cfg or config_mapping to make to
make it configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:577] The model: MegatronMambaModel() does not have field.name: moe_shared_expert_intermediate_size in its cfg. Add this key to cfg or config_mapping
to make to make it configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:577] The model: MegatronMambaModel() does not have field.name: moe_shared_expert_overlap in its cfg. Add this key to cfg or config_mapping to make t
o make it configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:577] The model: MegatronMambaModel() does not have field.name: moe_router_load_balancing_type in its cfg. Add this key to cfg or config_mapping to m
ake to make it configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:577] The model: MegatronMambaModel() does not have field.name: moe_router_topk in its cfg. Add this key to cfg or config_mapping to make to make it
configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:577] The model: MegatronMambaModel() does not have field.name: moe_router_pre_softmax in its cfg. Add this key to cfg or config_mapping to make to m
ake it configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:577] The model: MegatronMambaModel() does not have field.name: moe_grouped_gemm in its cfg. Add this key to cfg or config_mapping to make to make it
configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:577] The model: MegatronMambaModel() does not have field.name: moe_aux_loss_coeff in its cfg. Add this key to cfg or config_mapping to make to make
it configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:577] The model: MegatronMambaModel() does not have field.name: moe_z_loss_coeff in its cfg. Add this key to cfg or config_mapping to make to make it
configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:577] The model: MegatronMambaModel() does not have field.name: moe_input_jitter_eps in its cfg. Add this key to cfg or config_mapping to make to mak
e it configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:577] The model: MegatronMambaModel() does not have field.name: moe_token_dropping in its cfg. Add this key to cfg or config_mapping to make to make
it configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:577] The model: MegatronMambaModel() does not have field.name: moe_token_dispatcher_type in its cfg. Add this key to cfg or config_mapping to make t
o make it configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:577] The model: MegatronMambaModel() does not have field.name: moe_per_layer_logging in its cfg. Add this key to cfg or config_mapping to make to ma
ke it configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:577] The model: MegatronMambaModel() does not have field.name: moe_expert_capacity_factor in its cfg. Add this key to cfg or config_mapping to make
to make it configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:577] The model: MegatronMambaModel() does not have field.name: moe_pad_expert_input_to_capacity in its cfg. Add this key to cfg or config_mapping to
make to make it configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:577] The model: MegatronMambaModel() does not have field.name: moe_token_drop_policy in its cfg. Add this key to cfg or config_mapping to make to ma
ke it configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:577] The model: MegatronMambaModel() does not have field.name: moe_layer_recompute in its cfg. Add this key to cfg or config_mapping to make to make
it configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:577] The model: MegatronMambaModel() does not have field.name: clone_scatter_output_in_embedding in its cfg. Add this key to cfg or config_mapping t
o make to make it configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:577] The model: MegatronMambaModel() does not have field.name: disable_parameter_transpose_cache in its cfg. Add this key to cfg or config_mapping t
o make to make it configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:577] The model: MegatronMambaModel() does not have field.name: enable_cuda_graph in its cfg. Add this key to cfg or config_mapping to make to make i
t configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:577] The model: MegatronMambaModel() does not have field.name: external_cuda_graph in its cfg. Add this key to cfg or config_mapping to make to make
it configurable.
[NeMo W 2024-10-21 06:50:55 megatron_base_model:577] The model: MegatronMambaModel() does not have field.name: config_logger_dir in its cfg. Add this key to cfg or config_mapping to make to make i
t configurable.
[rank0]: Traceback (most recent call last):
[rank0]: File "/usr/local/lib/python3.10/dist-packages/megatron/core/transformer/spec_utils.py", line 97, in build_module
[rank0]: return module(
[rank0]: File "/usr/local/lib/python3.10/dist-packages/megatron/core/extensions/transformer_engine.py", line 333, in __init__
[rank0]: _ = _initialize_affine_weight_cpu(
[rank0]: File "/usr/local/lib/python3.10/dist-packages/megatron/core/tensor_parallel/layers.py", line 150, in _initialize_affine_weight_cpu
[rank0]: weight.data.copy_(cpu_weight)
[rank0]: RuntimeError: The size of tensor a (18560) must match the size of tensor b (4640) at non-singleton dimension 0
[rank0]: During handling of the above exception, another exception occurred:
[rank0]: Traceback (most recent call last):
[rank0]: File "/usr/local/lib/python3.10/dist-packages/megatron/core/transformer/spec_utils.py", line 97, in build_module
[rank0]: return module(
[rank0]: File "/usr/local/lib/python3.10/dist-packages/megatron/core/ssm/mamba_mixer.py", line 168, in __init__
[rank0]: self.in_proj = build_module(
[rank0]: File "/usr/local/lib/python3.10/dist-packages/megatron/core/transformer/spec_utils.py", line 104, in build_module
[rank0]: raise type(e)(f"{str(e)} when instantiating {module.__name__}").with_traceback(
[rank0]: File "/usr/local/lib/python3.10/dist-packages/megatron/core/transformer/spec_utils.py", line 97, in build_module
[rank0]: return module(
[rank0]: File "/usr/local/lib/python3.10/dist-packages/megatron/core/extensions/transformer_engine.py", line 333, in __init__
[rank0]: _ = _initialize_affine_weight_cpu(
[rank0]: File "/usr/local/lib/python3.10/dist-packages/megatron/core/tensor_parallel/layers.py", line 150, in _initialize_affine_weight_cpu
[rank0]: weight.data.copy_(cpu_weight)
[rank0]: RuntimeError: The size of tensor a (18560) must match the size of tensor b (4640) at non-singleton dimension 0 when instantiating TELayerNormColumnParallelLinear
[rank0]: During handling of the above exception, another exception occurred:
[rank0]: Traceback (most recent call last):
[rank0]: File "/usr/local/lib/python3.10/dist-packages/megatron/core/transformer/spec_utils.py", line 97, in build_module
[rank0]: return module(
[rank0]: File "/usr/local/lib/python3.10/dist-packages/megatron/core/ssm/mamba_layer.py", line 45, in __init__
[rank0]: self.mixer = build_module(
[rank0]: File "/usr/local/lib/python3.10/dist-packages/megatron/core/transformer/spec_utils.py", line 104, in build_module
[rank0]: raise type(e)(f"{str(e)} when instantiating {module.__name__}").with_traceback(
[rank0]: File "/usr/local/lib/python3.10/dist-packages/megatron/core/transformer/spec_utils.py", line 97, in build_module
[rank0]: return module(
[rank0]: File "/usr/local/lib/python3.10/dist-packages/megatron/core/ssm/mamba_mixer.py", line 168, in __init__
[rank0]: self.in_proj = build_module(
[rank0]: File "/usr/local/lib/python3.10/dist-packages/megatron/core/transformer/spec_utils.py", line 104, in build_module
[rank0]: raise type(e)(f"{str(e)} when instantiating {module.__name__}").with_traceback(
[rank0]: File "/usr/local/lib/python3.10/dist-packages/megatron/core/transformer/spec_utils.py", line 97, in build_module
[rank0]: return module(
[rank0]: File "/usr/local/lib/python3.10/dist-packages/megatron/core/extensions/transformer_engine.py", line 333, in __init__
[rank0]: _ = _initialize_affine_weight_cpu(
[rank0]: File "/usr/local/lib/python3.10/dist-packages/megatron/core/tensor_parallel/layers.py", line 150, in _initialize_affine_weight_cpu
[rank0]: weight.data.copy_(cpu_weight)
[rank0]: RuntimeError: The size of tensor a (18560) must match the size of tensor b (4640) at non-singleton dimension 0 when instantiating TELayerNormColumnParallelLinear when instantiating MambaM
ixer
[rank0]: During handling of the above exception, another exception occurred:
[rank0]: Traceback (most recent call last):
[rank0]: File "/usr/local/lib/python3.10/dist-packages/megatron/core/transformer/spec_utils.py", line 97, in build_module
[rank0]: return module(
[rank0]: File "/usr/local/lib/python3.10/dist-packages/megatron/core/ssm/mamba_block.py", line 155, in __init__
[rank0]: layer = build_module(
[rank0]: File "/usr/local/lib/python3.10/dist-packages/megatron/core/transformer/spec_utils.py", line 104, in build_module
[rank0]: raise type(e)(f"{str(e)} when instantiating {module.__name__}").with_traceback(
[rank0]: File "/usr/local/lib/python3.10/dist-packages/megatron/core/transformer/spec_utils.py", line 97, in build_module
[rank0]: return module(
[rank0]: File "/usr/local/lib/python3.10/dist-packages/megatron/core/ssm/mamba_layer.py", line 45, in __init__
[rank0]: self.mixer = build_module(
[rank0]: File "/usr/local/lib/python3.10/dist-packages/megatron/core/transformer/spec_utils.py", line 104, in build_module
[rank0]: raise type(e)(f"{str(e)} when instantiating {module.__name__}").with_traceback(
[rank0]: File "/usr/local/lib/python3.10/dist-packages/megatron/core/transformer/spec_utils.py", line 97, in build_module
[rank0]: return module(
[rank0]: File "/usr/local/lib/python3.10/dist-packages/megatron/core/ssm/mamba_mixer.py", line 168, in __init__
[rank0]: self.in_proj = build_module(
[rank0]: File "/usr/local/lib/python3.10/dist-packages/megatron/core/transformer/spec_utils.py", line 104, in build_module
[rank0]: raise type(e)(f"{str(e)} when instantiating {module.__name__}").with_traceback(
[rank0]: File "/usr/local/lib/python3.10/dist-packages/megatron/core/transformer/spec_utils.py", line 97, in build_module
[rank0]: return module(
[rank0]: File "/usr/local/lib/python3.10/dist-packages/megatron/core/extensions/transformer_engine.py", line 333, in __init__
[rank0]: _ = _initialize_affine_weight_cpu(
[rank0]: File "/usr/local/lib/python3.10/dist-packages/megatron/core/tensor_parallel/layers.py", line 150, in _initialize_affine_weight_cpu
[rank0]: weight.data.copy_(cpu_weight)
[rank0]: RuntimeError: The size of tensor a (18560) must match the size of tensor b (4640) at non-singleton dimension 0 when instantiating TELayerNormColumnParallelLinear when instantiating MambaM
ixer when instantiating MambaLayer
[rank0]: During handling of the above exception, another exception occurred:
```
**Steps/Code to reproduce bug**
Please list *minimal* steps or code snippet for us to be able to reproduce the bug.
I am using the `main branch`.
load the model huggingface: https://huggingface.co/nvidia/mamba2-8b-3t-4k/tree/main
```
CUDA_VISIBLE_DEVICES="0" python /opt/NeMo/scripts/checkpoint_converters/convert_mamba2_pyt_to_nemo.py \
--input_name_or_path <path to the source pytorch model> \
--output_path <path to target .nemo model> \
--mamba_ssm_ngroups 8 \
--precision bf16 \
--tokenizer_model_dir=<path to tokenizer.model> # Remove this line (or set it to None) for 130m, 370m, 780m, 1.3b, and 2.7b models.
```
```
python /opt/NeMo/examples/nlp/language_modeling/mamba_change_num_partition.py \
--model_file=<path to source .nemo model> \
--target_file=<path to target .nemo model> \
--tensor_model_parallel_size=1 \
--target_tensor_model_parallel_size=4 \
--precision=bf16 \
--tokenizer_path=<path to tokenizer.model>
```
A helpful guide on on how to craft a minimal bug report http://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports.
**Expected behavior**
It should work without any errors by following the documentation.
**Environment overview (please complete the following information)**
- Environment location: `docker.`
- Method of NeMo install: [pip install or from source]. Please specify exact commands you used to install.
running the docker command
- If method of install is [Docker], provide `docker pull` & `docker run` commands used
- https://github.com/NVIDIA/NeMo/blob/main/Dockerfile.ci
```
docker build -f Dockerfile.ci -t nemo:latest .
```
Add any other context about the problem here.
Example: 8-SXM H100
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"[๐ค]: Hi @ko3n1g ๐,\n\nWe wanted to let you know that a [CICD pipeline](https://github.com/NVIDIA/NeMo/actions/runs/11430910557) for this PR just finished successfully\n\nSo it might be time to merge this PR or get some approvals\n\nI'm just a bot so I'll leave it you what to do next.\n\n//cc @pablo-garay @ko3n1g"
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} | ๐ PR to Bump `Dockerfile.ci`.
๐ Please remember the following to-do's before merge:
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๐ Please merge this PR only if the CI workflow completed successfully. | {
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} | # 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**:
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- [ ] 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
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๐ Please remember the following to-do's before merge:
- [ ] Verify the presubmit CI
๐ Please merge this PR only if the CI workflow completed successfully. | {
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} | # What does this PR do ?
Can be invoked with `nemo` or via the example
```
nemo llm pretrain --factory 'HfAutoModelForCausalLM(model_name="meta-llama/Llama-3.2-1B", num_gpus_per_node=1)'
```
the example:
```
cd examples/llm/sft/
python3 hf.py --model=meta-llama/Llama-3.2-1B --devices=1 --strategy=ddp
```
**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)
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} | # What does this PR do ?
CI-passed for DDP test= https://github.com/NVIDIA/NeMo/actions/runs/11409221189/job/31749224039
**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)
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Add a one line overview of what this PR aims to accomplish.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Change uses "sliding_window" arg in HF ckpt config to inform window_size. This makes it compatible with all sizes: 2B, 9B and 27B
- Gemma 2 9B, and Gemma 2 27B HF ckpts have "sliding_window" and "sliding_window_size" both set to 4096
- Gemma 2 2B config.json in HF ckpt does not have a "sliding_window_size" arg, and only has "sliding_window"
# Usage
* You can potentially add a usage example below
```bash
python3 /opt/NeMo/scripts/checkpoint_converters/convert_gemma_hf_to_nemo.py \
--input_name_or_path /path/to/gemma2/checkpoints/hf/2b \
--output_path /path/to/gemma2-2b.nemo \
--tokenizer_path /path/to/tokenizer.model \
[--cpu]
```
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**PR Type**:
- [ ] New Feature
- [x] Bugfix
- [ ] Documentation
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* The forward pass in Gemma 2 passes runtime_gather_output
* Leads to unexpected keyword arg error while finetuning gemma 2 2b without it
**Collection**: nlp/models/language_modeling/megatron/gemma2
# 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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- [x] Bugfix
- [ ] Documentation
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} | # What does this PR do ?
Add finetuning recipes for Baichuan, ChatGLM, Gemma
**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.
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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.
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"could you also update your branch to latest main, please? I think Pablo have made auto conf tests not optional recently.",
"[๐ค]: Hi @BoxiangW ๐,\n\nWe wanted to let you know that a [CICD pipeline](https://github.com/NVIDIA/NeMo/actions/runs/11804509420) for this PR just finished successfully\n\nSo it might be time to merge this PR or get some approvals\n\nI'm just a bot so I'll leave it you what to do next.\n\n//cc @pablo-garay @ko3n1g",
"[๐ค]: Hi @BoxiangW ๐,\n\nWe wanted to let you know that a [CICD pipeline](https://github.com/NVIDIA/NeMo/actions/runs/11807721394) for this PR just finished successfully\n\nSo it might be time to merge this PR or get some approvals\n\nI'm just a bot so I'll leave it you what to do next.\n\n//cc @pablo-garay @ko3n1g",
"@maanug-nv How does this relate to your work on validation of configs?",
"<!-- pylint-output-strict-mode-false -->\n\nbeep boop ๐ค: ๐ The following files have warnings. In case you are familiar with these, please try helping us to improve the code base.\n\n---\n\nYour code was analyzed with PyLint. The following annotations have been identified:\n\n```\n************* Module nemo.collections.llm.api\nnemo/collections/llm/api.py:602:0: C0116: Missing function or method docstring (missing-function-docstring)\n************* Module nemo.collections.llm.gpt.data.mock\nnemo/collections/llm/gpt/data/mock.py:33:0: C0115: Missing class docstring (missing-class-docstring)\nnemo/collections/llm/gpt/data/mock.py:75:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/llm/gpt/data/mock.py:86:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/llm/gpt/data/mock.py:91:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/llm/gpt/data/mock.py:96:4: C0116: Missing function or method docstring (missing-function-docstring)\n************* Module nemo.collections.llm.gpt.data.pre_training\nnemo/collections/llm/gpt/data/pre_training.py:136:0: C0301: Line too long (140/119) (line-too-long)\nnemo/collections/llm/gpt/data/pre_training.py:137:0: C0301: Line too long (145/119) (line-too-long)\nnemo/collections/llm/gpt/data/pre_training.py:138:0: C0301: Line too long (137/119) (line-too-long)\nnemo/collections/llm/gpt/data/pre_training.py:390:0: C0301: Line too long (124/119) (line-too-long)\nnemo/collections/llm/gpt/data/pre_training.py:397:0: C0301: Line too long (133/119) (line-too-long)\nnemo/collections/llm/gpt/data/pre_training.py:49:0: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/llm/gpt/data/pre_training.py:60:0: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/llm/gpt/data/pre_training.py:221:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/llm/gpt/data/pre_training.py:284:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/llm/gpt/data/pre_training.py:313:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/llm/gpt/data/pre_training.py:316:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/llm/gpt/data/pre_training.py:319:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/llm/gpt/data/pre_training.py:337:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/llm/gpt/data/pre_training.py:387:4: C0116: Missing function or method docstring (missing-function-docstring)\n\n-----------------------------------\nYour code has been rated at 9.60/10\n```\n\n---\n\nThank you for improving NeMo's documentation!",
"[๐ค]: Hi @BoxiangW ๐,\n\nWe wanted to let you know that a [CICD pipeline](https://github.com/NVIDIA/NeMo/actions/runs/11923229869) for this PR just finished successfully\n\nSo it might be time to merge this PR or get some approvals\n\nI'm just a bot so I'll leave it you what to do next.\n\n//cc @pablo-garay @ko3n1g",
"Hi @marcromeyn , can you help take a look at this PR again? Thanks"
] | 2024-10-19T00:11:13 | 2024-12-06T12:28:43 | 2024-12-06T12:28:42 | COLLABORATOR | {
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} | # What does this PR do ?
Add model config validations for NeMo 2.0
**Collection**: llm
# Changelog
- Added training and fine-tuning config validation basics for NeMo 2.0.
- Added unit tests for config validation.
# 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)
- [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**:
- [x] 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)
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"Also needs https://github.com/NVIDIA/NeMo-Run/pull/80 ",
"[๐ค]: Hi @akoumpa ๐,\n\nWe wanted to let you know that a [CICD pipeline](https://github.com/NVIDIA/NeMo/actions/runs/11421594558) for this PR just finished successfully\n\nSo it might be time to merge this PR or get some approvals\n\nI'm just a bot so I'll leave it you what to do next.\n\n//cc @pablo-garay @ko3n1g"
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} | # What does this PR do ?
Before
<img width="1284" alt="Screenshot 2024-10-18 at 4 06 18 PM" src="https://github.com/user-attachments/assets/0750f79b-dc83-4dc1-a76f-436812a18c88">
After
<img width="1284" alt="Screenshot 2024-10-18 at 4 22 44 PM" src="https://github.com/user-attachments/assets/15c160bc-228e-4644-aafe-27aefe2cb622">
**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)
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# Usage
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- [ ] Did you add or update any necessary documentation?
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- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
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- [ ] Bugfix
- [ ] Documentation
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## 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.
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**Collection**: [Note which collection this PR will affect]
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- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
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# GitHub Actions CI
The Jenkins CI system has been replaced by GitHub Actions self-hosted runners.
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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.
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C0301: Line too long (171/119) (line-too-long)\nnemo/collections/asr/models/ctc_bpe_models.py:502:0: C0301: Line too long (181/119) (line-too-long)\nnemo/collections/asr/models/ctc_bpe_models.py:508:0: C0301: Line too long (164/119) (line-too-long)\nnemo/collections/asr/models/ctc_bpe_models.py:509:0: C0301: Line too long (167/119) (line-too-long)\nnemo/collections/asr/models/ctc_bpe_models.py:515:0: C0301: Line too long (149/119) (line-too-long)\nnemo/collections/asr/models/ctc_bpe_models.py:516:0: C0301: Line too long (158/119) (line-too-long)\nnemo/collections/asr/models/ctc_bpe_models.py:522:0: C0301: Line too long (150/119) (line-too-long)\nnemo/collections/asr/models/ctc_bpe_models.py:523:0: C0301: Line too long (160/119) (line-too-long)\nnemo/collections/asr/models/ctc_bpe_models.py:529:0: C0301: Line too long (149/119) (line-too-long)\nnemo/collections/asr/models/ctc_bpe_models.py:530:0: C0301: Line too long (158/119) (line-too-long)\nnemo/collections/asr/models/ctc_bpe_models.py:536:0: C0301: Line too long (157/119) (line-too-long)\nnemo/collections/asr/models/ctc_bpe_models.py:537:0: C0301: Line too long (152/119) (line-too-long)\nnemo/collections/asr/models/ctc_bpe_models.py:543:0: C0301: Line too long (157/119) (line-too-long)\nnemo/collections/asr/models/ctc_bpe_models.py:544:0: C0301: Line too long (162/119) (line-too-long)\nnemo/collections/asr/models/ctc_bpe_models.py:550:0: C0301: Line too long (146/119) (line-too-long)\nnemo/collections/asr/models/ctc_bpe_models.py:551:0: C0301: Line too long (152/119) (line-too-long)\nnemo/collections/asr/models/ctc_bpe_models.py:557:0: C0301: Line too long (146/119) (line-too-long)\nnemo/collections/asr/models/ctc_bpe_models.py:558:0: C0301: Line too long (152/119) (line-too-long)\nnemo/collections/asr/models/ctc_bpe_models.py:564:0: C0301: Line too long (147/119) (line-too-long)\nnemo/collections/asr/models/ctc_bpe_models.py:565:0: C0301: Line too long (154/119) (line-too-long)\nnemo/collections/asr/models/ctc_bpe_models.py:571:0: C0301: Line too long (147/119) (line-too-long)\nnemo/collections/asr/models/ctc_bpe_models.py:572:0: C0301: Line too long (154/119) (line-too-long)\nnemo/collections/asr/models/ctc_bpe_models.py:578:0: C0301: Line too long (148/119) (line-too-long)\nnemo/collections/asr/models/ctc_bpe_models.py:579:0: C0301: Line too long (156/119) (line-too-long)\nnemo/collections/asr/models/ctc_bpe_models.py:585:0: C0301: Line too long (146/119) (line-too-long)\nnemo/collections/asr/models/ctc_bpe_models.py:586:0: C0301: Line too long (153/119) (line-too-long)\nnemo/collections/asr/models/ctc_bpe_models.py:592:0: C0301: Line too long (146/119) (line-too-long)\nnemo/collections/asr/models/ctc_bpe_models.py:593:0: C0301: Line too long (153/119) (line-too-long)\nnemo/collections/asr/models/ctc_bpe_models.py:599:0: C0301: Line too long (155/119) (line-too-long)\nnemo/collections/asr/models/ctc_bpe_models.py:600:0: C0301: Line too long (170/119) (line-too-long)\nnemo/collections/asr/models/ctc_bpe_models.py:606:0: C0301: Line too long (146/119) (line-too-long)\nnemo/collections/asr/models/ctc_bpe_models.py:607:0: C0301: Line too long (153/119) (line-too-long)\nnemo/collections/asr/models/ctc_bpe_models.py:613:0: C0301: Line too long (146/119) (line-too-long)\nnemo/collections/asr/models/ctc_bpe_models.py:614:0: C0301: Line too long (153/119) (line-too-long)\nnemo/collections/asr/models/ctc_bpe_models.py:620:0: C0301: Line too long (146/119) (line-too-long)\nnemo/collections/asr/models/ctc_bpe_models.py:621:0: C0301: Line too long (153/119) (line-too-long)\nnemo/collections/asr/models/ctc_bpe_models.py:627:0: C0301: Line too long (146/119) (line-too-long)\nnemo/collections/asr/models/ctc_bpe_models.py:628:0: C0301: Line too long (153/119) (line-too-long)\nnemo/collections/asr/models/ctc_bpe_models.py:634:0: C0301: Line too long (146/119) (line-too-long)\nnemo/collections/asr/models/ctc_bpe_models.py:635:0: C0301: Line too long (153/119) (line-too-long)\nnemo/collections/asr/models/ctc_bpe_models.py:641:0: C0301: Line too long (150/119) (line-too-long)\nnemo/collections/asr/models/ctc_bpe_models.py:642:0: C0301: Line too long (160/119) (line-too-long)\nnemo/collections/asr/models/ctc_bpe_models.py:648:0: C0301: Line too long (153/119) (line-too-long)\nnemo/collections/asr/models/ctc_bpe_models.py:649:0: C0301: Line too long (166/119) (line-too-long)\nnemo/collections/asr/models/ctc_bpe_models.py:655:0: C0301: Line too long (151/119) (line-too-long)\nnemo/collections/asr/models/ctc_bpe_models.py:656:0: C0301: Line too long (163/119) (line-too-long)\nnemo/collections/asr/models/ctc_bpe_models.py:662:0: C0301: Line too long (152/119) (line-too-long)\nnemo/collections/asr/models/ctc_bpe_models.py:663:0: C0301: Line too long (165/119) (line-too-long)\n************* Module nemo.collections.asr.models.ctc_models\nnemo/collections/asr/models/ctc_models.py:196:0: C0301: Line too long (120/119) (line-too-long)\nnemo/collections/asr/models/ctc_models.py:197:0: C0301: Line too long (120/119) (line-too-long)\nnemo/collections/asr/models/ctc_models.py:813:0: C0301: Line too long (133/119) (line-too-long)\nnemo/collections/asr/models/ctc_models.py:819:0: C0301: Line too long (140/119) (line-too-long)\nnemo/collections/asr/models/ctc_models.py:820:0: C0301: Line too long (143/119) (line-too-long)\nnemo/collections/asr/models/ctc_models.py:826:0: C0301: Line too long (139/119) (line-too-long)\nnemo/collections/asr/models/ctc_models.py:827:0: C0301: Line too long (141/119) (line-too-long)\nnemo/collections/asr/models/ctc_models.py:833:0: C0301: Line too long (140/119) (line-too-long)\nnemo/collections/asr/models/ctc_models.py:834:0: C0301: Line too long (143/119) (line-too-long)\nnemo/collections/asr/models/ctc_models.py:840:0: C0301: Line too long (140/119) (line-too-long)\nnemo/collections/asr/models/ctc_models.py:841:0: C0301: Line too long (143/119) (line-too-long)\nnemo/collections/asr/models/ctc_models.py:847:0: C0301: Line too long (140/119) (line-too-long)\nnemo/collections/asr/models/ctc_models.py:848:0: C0301: Line too long (143/119) (line-too-long)\nnemo/collections/asr/models/ctc_models.py:854:0: C0301: Line too long (140/119) (line-too-long)\nnemo/collections/asr/models/ctc_models.py:855:0: C0301: Line too long (143/119) (line-too-long)\nnemo/collections/asr/models/ctc_models.py:861:0: C0301: Line too long (140/119) (line-too-long)\nnemo/collections/asr/models/ctc_models.py:862:0: C0301: Line too long (143/119) (line-too-long)\nnemo/collections/asr/models/ctc_models.py:868:0: C0301: Line too long (140/119) (line-too-long)\nnemo/collections/asr/models/ctc_models.py:869:0: C0301: Line too long (143/119) (line-too-long)\nnemo/collections/asr/models/ctc_models.py:875:0: C0301: Line too long (140/119) (line-too-long)\nnemo/collections/asr/models/ctc_models.py:876:0: C0301: Line too long (143/119) (line-too-long)\nnemo/collections/asr/models/ctc_models.py:882:0: C0301: Line too long (139/119) (line-too-long)\nnemo/collections/asr/models/ctc_models.py:883:0: C0301: Line too long (141/119) (line-too-long)\nnemo/collections/asr/models/ctc_models.py:889:0: C0301: Line too long (151/119) (line-too-long)\nnemo/collections/asr/models/ctc_models.py:890:0: C0301: Line too long (162/119) (line-too-long)\nnemo/collections/asr/models/ctc_models.py:897:0: C0301: Line too long (151/119) (line-too-long)\nnemo/collections/asr/models/ctc_models.py:898:0: C0301: Line too long (162/119) (line-too-long)\nnemo/collections/asr/models/ctc_models.py:904:0: C0301: Line too long (139/119) (line-too-long)\nnemo/collections/asr/models/ctc_models.py:905:0: C0301: Line too long (146/119) (line-too-long)\nnemo/collections/asr/models/ctc_models.py:545:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/models/ctc_models.py:602:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/models/ctc_models.py:620:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/models/ctc_models.py:662:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/models/ctc_models.py:680:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/models/ctc_models.py:916:4: C0116: Missing function or method docstring (missing-function-docstring)\n************* Module nemo.collections.asr.models.hybrid_rnnt_ctc_bpe_models\nnemo/collections/asr/models/hybrid_rnnt_ctc_bpe_models.py:263:0: C0301: Line too long (123/119) (line-too-long)\nnemo/collections/asr/models/hybrid_rnnt_ctc_bpe_models.py:267:0: C0301: Line too long (129/119) (line-too-long)\nnemo/collections/asr/models/hybrid_rnnt_ctc_bpe_models.py:277:0: C0301: Line too long (139/119) (line-too-long)\nnemo/collections/asr/models/hybrid_rnnt_ctc_bpe_models.py:526:0: C0301: Line too long (156/119) (line-too-long)\nnemo/collections/asr/models/hybrid_rnnt_ctc_bpe_models.py:527:0: C0301: Line too long (173/119) (line-too-long)\nnemo/collections/asr/models/hybrid_rnnt_ctc_bpe_models.py:533:0: C0301: Line too long (156/119) (line-too-long)\nnemo/collections/asr/models/hybrid_rnnt_ctc_bpe_models.py:534:0: C0301: Line too long (173/119) (line-too-long)\nnemo/collections/asr/models/hybrid_rnnt_ctc_bpe_models.py:540:0: C0301: Line too long (156/119) (line-too-long)\nnemo/collections/asr/models/hybrid_rnnt_ctc_bpe_models.py:541:0: C0301: Line too long (173/119) (line-too-long)\nnemo/collections/asr/models/hybrid_rnnt_ctc_bpe_models.py:547:0: C0301: Line too long (156/119) (line-too-long)\nnemo/collections/asr/models/hybrid_rnnt_ctc_bpe_models.py:548:0: C0301: Line too long (173/119) (line-too-long)\nnemo/collections/asr/models/hybrid_rnnt_ctc_bpe_models.py:554:0: C0301: Line too long (156/119) (line-too-long)\nnemo/collections/asr/models/hybrid_rnnt_ctc_bpe_models.py:555:0: C0301: Line too long (190/119) (line-too-long)\nnemo/collections/asr/models/hybrid_rnnt_ctc_bpe_models.py:561:0: C0301: Line too long (156/119) (line-too-long)\nnemo/collections/asr/models/hybrid_rnnt_ctc_bpe_models.py:562:0: C0301: Line too long (173/119) (line-too-long)\nnemo/collections/asr/models/hybrid_rnnt_ctc_bpe_models.py:568:0: C0301: Line too long (156/119) (line-too-long)\nnemo/collections/asr/models/hybrid_rnnt_ctc_bpe_models.py:569:0: C0301: Line too long (173/119) (line-too-long)\nnemo/collections/asr/models/hybrid_rnnt_ctc_bpe_models.py:575:0: C0301: Line too long (156/119) (line-too-long)\nnemo/collections/asr/models/hybrid_rnnt_ctc_bpe_models.py:576:0: C0301: Line too long (173/119) (line-too-long)\nnemo/collections/asr/models/hybrid_rnnt_ctc_bpe_models.py:582:0: C0301: Line too long (156/119) (line-too-long)\nnemo/collections/asr/models/hybrid_rnnt_ctc_bpe_models.py:583:0: C0301: Line too long (173/119) (line-too-long)\nnemo/collections/asr/models/hybrid_rnnt_ctc_bpe_models.py:589:0: C0301: Line too long (156/119) (line-too-long)\nnemo/collections/asr/models/hybrid_rnnt_ctc_bpe_models.py:590:0: C0301: Line too long (173/119) (line-too-long)\nnemo/collections/asr/models/hybrid_rnnt_ctc_bpe_models.py:596:0: C0301: Line too long (175/119) (line-too-long)\nnemo/collections/asr/models/hybrid_rnnt_ctc_bpe_models.py:597:0: C0301: Line too long (211/119) (line-too-long)\nnemo/collections/asr/models/hybrid_rnnt_ctc_bpe_models.py:603:0: C0301: Line too long (166/119) (line-too-long)\nnemo/collections/asr/models/hybrid_rnnt_ctc_bpe_models.py:604:0: C0301: Line too long (193/119) (line-too-long)\nnemo/collections/asr/models/hybrid_rnnt_ctc_bpe_models.py:610:0: C0301: Line too long (168/119) (line-too-long)\nnemo/collections/asr/models/hybrid_rnnt_ctc_bpe_models.py:611:0: C0301: Line too long (197/119) (line-too-long)\nnemo/collections/asr/models/hybrid_rnnt_ctc_bpe_models.py:617:0: C0301: Line too long (169/119) (line-too-long)\nnemo/collections/asr/models/hybrid_rnnt_ctc_bpe_models.py:618:0: C0301: Line too long (199/119) (line-too-long)\nnemo/collections/asr/models/hybrid_rnnt_ctc_bpe_models.py:624:0: C0301: Line too long (170/119) (line-too-long)\nnemo/collections/asr/models/hybrid_rnnt_ctc_bpe_models.py:625:0: C0301: Line too long (201/119) (line-too-long)\nnemo/collections/asr/models/hybrid_rnnt_ctc_bpe_models.py:631:0: C0301: Line too long (169/119) (line-too-long)\nnemo/collections/asr/models/hybrid_rnnt_ctc_bpe_models.py:632:0: C0301: Line too long (199/119) (line-too-long)\n************* Module nemo.collections.asr.models.hybrid_rnnt_ctc_models\nnemo/collections/asr/models/hybrid_rnnt_ctc_models.py:717:0: C0301: Line too long (141/119) (line-too-long)\nnemo/collections/asr/models/hybrid_rnnt_ctc_models.py:718:0: C0301: Line too long (139/119) (line-too-long)\nnemo/collections/asr/models/hybrid_rnnt_ctc_models.py:16:0: W0611: Unused import json (unused-import)\nnemo/collections/asr/models/hybrid_rnnt_ctc_models.py:17:0: W0611: Unused import os (unused-import)\nnemo/collections/asr/models/hybrid_rnnt_ctc_models.py:18:0: W0611: Unused import tempfile (unused-import)\nnemo/collections/asr/models/hybrid_rnnt_ctc_models.py:24:0: W0611: Unused tqdm imported from tqdm.auto (unused-import)\n************* Module nemo.collections.asr.models.rnnt_bpe_models\nnemo/collections/asr/models/rnnt_bpe_models.py:53:0: C0301: Line too long (141/119) (line-too-long)\nnemo/collections/asr/models/rnnt_bpe_models.py:54:0: C0301: Line too long (142/119) (line-too-long)\nnemo/collections/asr/models/rnnt_bpe_models.py:60:0: C0301: Line too long (141/119) (line-too-long)\nnemo/collections/asr/models/rnnt_bpe_models.py:61:0: C0301: Line too long (142/119) (line-too-long)\nnemo/collections/asr/models/rnnt_bpe_models.py:67:0: C0301: Line too long (142/119) (line-too-long)\nnemo/collections/asr/models/rnnt_bpe_models.py:68:0: C0301: Line too long (144/119) (line-too-long)\nnemo/collections/asr/models/rnnt_bpe_models.py:74:0: C0301: Line too long (145/119) (line-too-long)\nnemo/collections/asr/models/rnnt_bpe_models.py:75:0: C0301: Line too long (150/119) (line-too-long)\nnemo/collections/asr/models/rnnt_bpe_models.py:81:0: C0301: Line too long (145/119) (line-too-long)\nnemo/collections/asr/models/rnnt_bpe_models.py:82:0: C0301: Line too long (150/119) (line-too-long)\nnemo/collections/asr/models/rnnt_bpe_models.py:88:0: C0301: Line too long (146/119) (line-too-long)\nnemo/collections/asr/models/rnnt_bpe_models.py:89:0: C0301: Line too long (152/119) (line-too-long)\nnemo/collections/asr/models/rnnt_bpe_models.py:95:0: C0301: Line too long (153/119) (line-too-long)\nnemo/collections/asr/models/rnnt_bpe_models.py:96:0: C0301: Line too long (166/119) (line-too-long)\nnemo/collections/asr/models/rnnt_bpe_models.py:102:0: C0301: Line too long (154/119) (line-too-long)\nnemo/collections/asr/models/rnnt_bpe_models.py:103:0: C0301: Line too long (168/119) (line-too-long)\nnemo/collections/asr/models/rnnt_bpe_models.py:109:0: C0301: Line too long (153/119) (line-too-long)\nnemo/collections/asr/models/rnnt_bpe_models.py:110:0: C0301: Line too long (167/119) (line-too-long)\nnemo/collections/asr/models/rnnt_bpe_models.py:116:0: C0301: Line too long (156/119) (line-too-long)\nnemo/collections/asr/models/rnnt_bpe_models.py:117:0: C0301: Line too long (172/119) (line-too-long)\nnemo/collections/asr/models/rnnt_bpe_models.py:123:0: C0301: Line too long (154/119) (line-too-long)\nnemo/collections/asr/models/rnnt_bpe_models.py:124:0: C0301: Line too long (169/119) (line-too-long)\nnemo/collections/asr/models/rnnt_bpe_models.py:130:0: C0301: Line too long (155/119) (line-too-long)\nnemo/collections/asr/models/rnnt_bpe_models.py:131:0: C0301: Line too long (170/119) (line-too-long)\nnemo/collections/asr/models/rnnt_bpe_models.py:137:0: C0301: Line too long (142/119) (line-too-long)\nnemo/collections/asr/models/rnnt_bpe_models.py:138:0: C0301: Line too long (144/119) (line-too-long)\nnemo/collections/asr/models/rnnt_bpe_models.py:144:0: C0301: Line too long (142/119) (line-too-long)\nnemo/collections/asr/models/rnnt_bpe_models.py:145:0: C0301: Line too long (142/119) (line-too-long)\nnemo/collections/asr/models/rnnt_bpe_models.py:151:0: C0301: Line too long (142/119) (line-too-long)\nnemo/collections/asr/models/rnnt_bpe_models.py:152:0: C0301: Line too long (144/119) (line-too-long)\nnemo/collections/asr/models/rnnt_bpe_models.py:158:0: C0301: Line too long (153/119) (line-too-long)\nnemo/collections/asr/models/rnnt_bpe_models.py:159:0: C0301: Line too long (166/119) (line-too-long)\nnemo/collections/asr/models/rnnt_bpe_models.py:165:0: C0301: Line too long (164/119) (line-too-long)\nnemo/collections/asr/models/rnnt_bpe_models.py:166:0: C0301: Line 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(line-too-long)\nnemo/collections/asr/models/rnnt_bpe_models.py:270:0: C0301: Line too long (158/119) (line-too-long)\nnemo/collections/asr/models/rnnt_bpe_models.py:271:0: C0301: Line too long (177/119) (line-too-long)\nnemo/collections/asr/models/rnnt_bpe_models.py:277:0: C0301: Line too long (159/119) (line-too-long)\nnemo/collections/asr/models/rnnt_bpe_models.py:278:0: C0301: Line too long (179/119) (line-too-long)\n************* Module nemo.collections.asr.models.rnnt_models\nnemo/collections/asr/models/rnnt_models.py:1084:0: C0301: Line too long (164/119) (line-too-long)\nnemo/collections/asr/models/rnnt_models.py:1085:0: C0301: Line too long (166/119) (line-too-long)\nnemo/collections/asr/models/rnnt_models.py:230:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/models/rnnt_models.py:705:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/models/rnnt_models.py:803:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/models/rnnt_models.py:820:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/models/rnnt_models.py:888:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/models/rnnt_models.py:896:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/models/rnnt_models.py:1061:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/models/rnnt_models.py:1092:4: C0116: Missing function or method docstring (missing-function-docstring)\n************* Module nemo.collections.asr.modules.conv_asr\nnemo/collections/asr/modules/conv_asr.py:197:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/modules/conv_asr.py:239:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/modules/conv_asr.py:399:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/modules/conv_asr.py:459:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/modules/conv_asr.py:503:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/modules/conv_asr.py:507:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/modules/conv_asr.py:603:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/modules/conv_asr.py:677:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/modules/conv_asr.py:689:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/modules/conv_asr.py:758:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/modules/conv_asr.py:858:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/modules/conv_asr.py:881:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/modules/conv_asr.py:900:0: C0115: Missing class docstring (missing-class-docstring)\nnemo/collections/asr/modules/conv_asr.py:945:0: C0115: Missing class docstring (missing-class-docstring)\nnemo/collections/asr/modules/conv_asr.py:969:0: C0115: Missing class docstring (missing-class-docstring)\nnemo/collections/asr/modules/conv_asr.py:983:0: C0115: Missing class docstring (missing-class-docstring)\nnemo/collections/asr/modules/conv_asr.py:992:0: C0115: Missing class docstring (missing-class-docstring)\n************* Module nemo.collections.asr.parts.mixins.transcription\nnemo/collections/asr/parts/mixins/transcription.py:40:0: C0115: Missing class docstring (missing-class-docstring)\nnemo/collections/asr/parts/mixins/transcription.py:57:0: C0115: Missing class docstring (missing-class-docstring)\nnemo/collections/asr/parts/mixins/transcription.py:95:0: C0115: Missing class docstring (missing-class-docstring)\nnemo/collections/asr/parts/mixins/transcription.py:119:4: C0116: Missing function or method docstring (missing-function-docstring)\n************* Module nemo.collections.asr.parts.submodules.rnnt_decoding\nnemo/collections/asr/parts/submodules/rnnt_decoding.py:1117:0: C0301: Line too long (125/119) (line-too-long)\nnemo/collections/asr/parts/submodules/rnnt_decoding.py:730:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/parts/submodules/rnnt_decoding.py:756:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/parts/submodules/rnnt_decoding.py:1770:0: C0115: Missing class docstring (missing-class-docstring)\nnemo/collections/asr/parts/submodules/rnnt_decoding.py:1827:0: C0115: Missing class docstring (missing-class-docstring)\n************* Module nemo.collections.asr.parts.utils.streaming_utils\nnemo/collections/asr/parts/utils/streaming_utils.py:426:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/parts/utils/streaming_utils.py:429:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/parts/utils/streaming_utils.py:473:0: C0115: Missing class docstring (missing-class-docstring)\nnemo/collections/asr/parts/utils/streaming_utils.py:546:0: C0115: Missing class docstring (missing-class-docstring)\nnemo/collections/asr/parts/utils/streaming_utils.py:569:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/parts/utils/streaming_utils.py:632:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/parts/utils/streaming_utils.py:644:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/parts/utils/streaming_utils.py:658:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/parts/utils/streaming_utils.py:671:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/parts/utils/streaming_utils.py:680:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/parts/utils/streaming_utils.py:685:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/parts/utils/streaming_utils.py:777:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/parts/utils/streaming_utils.py:783:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/parts/utils/streaming_utils.py:787:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/parts/utils/streaming_utils.py:824:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/parts/utils/streaming_utils.py:842:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/parts/utils/streaming_utils.py:1506:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/parts/utils/streaming_utils.py:1515:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/parts/utils/streaming_utils.py:1521:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/parts/utils/streaming_utils.py:1525:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/parts/utils/streaming_utils.py:1537:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/parts/utils/streaming_utils.py:1542:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/parts/utils/streaming_utils.py:1549:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/parts/utils/streaming_utils.py:1584:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/parts/utils/streaming_utils.py:1587:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/parts/utils/streaming_utils.py:1597:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/parts/utils/streaming_utils.py:1608:0: C0115: Missing class docstring (missing-class-docstring)\nnemo/collections/asr/parts/utils/streaming_utils.py:1612:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/parts/utils/streaming_utils.py:1683:0: C0115: Missing class docstring (missing-class-docstring)\nnemo/collections/asr/parts/utils/streaming_utils.py:1731:0: C0115: Missing class docstring (missing-class-docstring)\n************* Module nemo.collections.asr.parts.utils.transcribe_utils\nnemo/collections/asr/parts/utils/transcribe_utils.py:177:0: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/parts/utils/transcribe_utils.py:339:0: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/parts/utils/transcribe_utils.py:636:0: C0115: Missing class docstring (missing-class-docstring)\nnemo/collections/asr/parts/utils/transcribe_utils.py:651:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/parts/utils/transcribe_utils.py:659:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/parts/utils/transcribe_utils.py:662:4: C0116: Missing function or method docstring (missing-function-docstring)\nnemo/collections/asr/parts/utils/transcribe_utils.py:670:0: C0115: Missing class docstring (missing-class-docstring)\n\n-----------------------------------\nYour code has been rated at 9.42/10\n```\n\n---\n\nThank you for improving NeMo's documentation!",
"[๐ค]: Hi @nithinraok ๐,\n\nWe wanted to let you know that a [CICD pipeline](https://github.com/NVIDIA/NeMo/actions/runs/11766676240) for this PR just finished successfully\n\nSo it might be time to merge this PR or get some approvals\n\nI'm just a bot so I'll leave it you what to do next.\n\n//cc @pablo-garay @ko3n1g"
] | 2024-10-18T21:30:25 | 2024-11-10T20:01:58 | 2024-11-10T20:01:57 | COLLABORATOR | {
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} | # What does this PR do ?
Adds support for extracting timestamps to .transcribe() method
**Collection**: ASR
# Changelog
- Add timestamps=None/True/False to .transcribe() method in mixin
- None: does nothing, restores state set outside with set_decoding_stratergy (default)
- True: Enables timestamping with help of return_hypothesis and compute_timestamps setting to decoding_stratergy
- False: Disables timestamping by disabling return_hypothesis and compute_timestamps to decoding_stratergy
- Adds corresponding support in
- ctc_models.py
- rnnt_models.py
- hybrid_rnnt-ctc_models.py
- Raise a notimplemented error for AED Based Models (Canary)
- Adds support to transcribe_speech.py
- merges two variables to one: (compute_timestamps, preserve_alignments -> timestamps) as both are mutually dependent
- cleans much of the code
- Add optional verbose=True option to change_decoding_strategy method. Default is True
- Move some of model loading to conftest.py to improve setup time for each module
- Add unit test for timestamps option for ctc and hybrid models
# Usage
## From command-line
### with transcribe_speech.py script
```bash
python transcribe_speech.py pretrained_name="nvidia/parakeet-ctc-1.1b.nemo" \
dataset_manifest=<manifest_path> \
output_filename=<output_filename> timestamps=True
```
## From Python Env
### For CTC based models
```python
from nemo.collections.asr.models import ASRModel
ctc_model = ASRModel.from_pretrained('nvidia/parakeet-ctc-1.1b')
output=ctc_model.transcribe(['<file_path>'], timestamps=True) # or manifest instead of individual filepaths
# by default you get timestamps for char, word and segment level. segment level differs based on model you use if it support punctuations and capitalizations natively or not.
# for word-level timestamps
print(output[0].timestep['word'][:10]) #prints first 10 timestamps *_offset corresponds to frame numbers and start and end are provided in seconds
# for segment-level timestamps
print(output[0].timestep['segment'][:10])
```
### For RNNT/TDT based models
(currently only difference is output type for both models, will be making it consistent in upcoming PR)
```python
from nemo.collections.asr.models import ASRModel
transducer_model = ASRModel.from_pretrained('nvidia/parakeet-rnnt-1.1b')
output=transducer_model.transcribe(['<file_path>'], timestamps=True)
# for word-level timestamps
print(output[0][0].timestep['word'][:10])
# for segment-level timestamps
print(output[0][0].timestep['segment'][:10])
```
### For Hybrid RNNT/TDT-CTC models
Same as above by default decoding would be with transducer (RNNT/TDT), if user wants to change decoder then change decoding strategy before running transcribe()
like:
```python
from nemo.collections.asr.models import ASRModel
from nemo.collections.asr.parts.submodules.ctc_decoding import CTCDecodingConfig
hybrid_model = ASRModel.from_pretrained('nvidia/parakeet-tdt_ctc-110m')
ctc_cfg = CTCDecodingConfig()
ctc_cfg.decoding = "greedy_batch"
hybrid_model.change_decoding_strategy(decoding_cfg=ctc_cfg, decoder_type="ctc")
output=hybrid_model.transcribe(['<file_path>'], timestamps=True)
# for word-level timestamps
print(output[0].timestep['word'][:10])
# for segment-level timestamps
print(output[0].timestep['segment'][:10])
```
### For AED Models
For AED models like Canary, support would be added soon.
# 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)
- [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
- [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)
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"[๐ค]: Hi @dimapihtar ๐,\n\nWe wanted to let you know that a [CICD pipeline](https://github.com/NVIDIA/NeMo/actions/runs/11556774592) for this PR just finished successfully\n\nSo it might be time to merge this PR or get some approvals\n\nI'm just a bot so I'll leave it you what to do next.\n\n//cc @pablo-garay @ko3n1g"
] | 2024-10-18T19:34:20 | 2024-10-29T12:08:51 | 2024-10-29T12:08:49 | COLLABORATOR | {
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**Collection**: [Note which collection this PR will affect]
# Changelog
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```python
# Add a code snippet demonstrating how to use this
```
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# Before your PR is "Ready for review"
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If you haven't finished some of the above items you can still open "Draft" PR.
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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
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```python
# Add a code snippet demonstrating how to use this
```
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- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
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- [ ] 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.
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"@erhoo82 Hi Sangkug, I guess Github Markdown system doesn't allow the HTML based table styling. This PR fixes the issue. Could you please review this.",
"LGTM, thanks",
"Doc only change & 2 approvals : PR good to merge"
] | 2024-10-18T16:18:48 | 2024-10-21T21:42:24 | 2024-10-21T21:42:24 | CONTRIBUTOR | {
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} | # What does this PR do ?
Hotfix for table style in long context performance documentation.
# 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.
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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)
- [ ] 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.
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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"
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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?
**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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[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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} | # What does this PR do ?
Aim of this PR is to push a tutorial of training speech enhancement models with online augmentation to NeMo.
**Collection**: audio
# Changelog
- New notebook file with the tutorial added to tutorials/audio/speech_enhancement
- New configuration file for the training "masking" model with online augmentation added to the examples/audio/conf/
- Problem with the RIR online augmentation is fixed in nemo/collections/audio/data/audio_to_audio_lhotse.py
# Usage
All instructions are in the notebook examples/audio/conf/masking_with_online_augmentation.yaml
# 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.
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* Related to # (issue)
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"> Thanks for this!\r\n> \r\n> Actually, the story is that I used to require model_downsample_factor to be in the config, but then I made some logic to calculate it, so that the user doesn't need to worry about it. The logic is here: https://github.com/NVIDIA/NeMo/blob/b6c3c0d5d41d2c695e6a1b23aa573e867b0ec729/tools/nemo_forced_aligner/utils/data_prep.py#L822\r\n> \r\n> \r\n> \r\n> But I forgot to update buffered case/buffered case was merged without realizing this was gone.\r\n> \r\n> Could you please update the code so that we calculate model_downsample_factor for the buffered case also?\r\n\r\n@erastorgueva-nv, in this case, itโs unlikely we can calculate the `model_downsampling_factor` for the bucketed chunked ASR scenario. The reason is that we need to know the number of tokens generated from inference, but to run the inference, we first need the `model_stride_in_sec`, which is computed as the `window_stride` multiplied by the `model_downsampling_factor`. Since the inference requires this value upfront, it seems unavoidable to include `model_downsampling_factor` in the configuration for the buffered case.\r\n\r\nLet me know your thoughts!",
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# 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)
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- [ ] 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
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} | # What does this PR do ?
Extra changes just for cleanup purposes related to https://github.com/NVIDIA/NeMo/pull/10904, isolated here to facilitate review for main functionalities.
**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
```
# 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)
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"this was solved in `r2.0.0rc1`",
"please install `!pip install huggingface-hub==0.23.3` ",
"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."
] | 2024-10-18T09:24:21 | 2024-11-23T08:03:53 | 2024-11-23T08:03:53 | NONE | {
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} | null | null | null | **Describe the bug**
NeMo is not loading a ASR model I wanted to run because of internal dependency issues on HuggingFace Hub.
**Steps/Code to reproduce bug**
Colab Link: [colab link](https://colab.research.google.com/drive/1JqMW-JkyHJ61UOFO9eQhoHkQx6I3cH05?usp=sharing)
```python
!pip install nemo_toolkit['all']
import nemo.collections.asr as nemo_asr
asr_model = nemo_asr.models.ASRModel.from_pretrained(model_name="nvidia/parakeet-tdt_ctc-110m")
```
**Expected behavior**
It should load up the model.
**Environment overview (please complete the following information)**
Check colab notebook
**Environment details**
Check colab notebook
**Additional context**
Check colab notebook | {
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"Thanks for reporting this bug, will look into it asap & push a fix.",
"Hi this has been fixed in https://github.com/NVIDIA/NeMo/pull/11081 please give it a try, will be merged soon. Thanks."
] | 2024-10-18T09:20:42 | 2024-10-30T12:55:13 | 2024-10-30T12:55:13 | NONE | {
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} | null | null | null | **Describe the bug**
A clear and concise description of what the bug is.
**Steps/Code to reproduce bug**
```
nemorun llm import llama3_8b hf://meta-llama/Meta-Llama-3-8B -y
nemorun llm export ~/.cache/nemo/models/meta-llama/Meta-Llama-3-8B/context hf exp/PreTrain/export_llama3_8b -y
```
error
```
Dry run for task nemo.collections.llm.api:export_ckpt
Resolved Arguments
โโโโโโโโโโโโโโโโโโโโโโโโณโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
โ Argument Name โ Resolved Value โ
โกโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฉ
โ load_connector โ <function load_connector_from_trainer_ckpt at โ
โ โ 0x7feaf6adfbe0> โ
โ output_path โ PosixPath('exp/PreTrain/export_llama3_8b') โ
โ overwrite โ False โ
โ path โ PosixPath('/root/.cache/nemo/models/meta-llama/Meta-Llama-3โฆ โ
โ target โ 'hf' โ
โโโโโโโโโโโโโโโโโโโโโโโโดโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
Launching None...
huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...
To disable this warning, you can either:
- Avoid using `tokenizers` before the fork if possible
- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)
GPU available: True (cuda), used: False
TPU available: False, using: 0 TPU cores
HPU available: False, using: 0 HPUs
[NeMo W 2024-10-18 09:16:11 nemo_logging:349] /usr/local/lib/python3.10/dist-packages/pytorch_lightning/trainer/setup.py:177: GPU available but not used. You can set it by doing `Trainer(accelerator='gpu')`.
GPU available: True (cuda), used: False
TPU available: False, using: 0 TPU cores
HPU available: False, using: 0 HPUs
GPU available: True (cuda), used: False
TPU available: False, using: 0 TPU cores
HPU available: False, using: 0 HPUs
GPU available: True (cuda), used: False
TPU available: False, using: 0 TPU cores
HPU available: False, using: 0 HPUs
GPU available: True (cuda), used: False
TPU available: False, using: 0 TPU cores
HPU available: False, using: 0 HPUs
[ERROR | root ]: An error occurred: PyTorch DDP is not enabled for mcore optimizer
Traceback (most recent call last):
File "/usr/local/bin/nemorun", line 8, in <module>
sys.exit(app())
File "/usr/local/lib/python3.10/dist-packages/typer/main.py", line 326, in __call__
raise e
File "/usr/local/lib/python3.10/dist-packages/typer/main.py", line 309, in __call__
return get_command(self)(*args, **kwargs)
File "/usr/local/lib/python3.10/dist-packages/click/core.py", line 1157, in __call__
return self.main(*args, **kwargs)
File "/usr/local/lib/python3.10/dist-packages/typer/core.py", line 723, in main
return _main(
File "/usr/local/lib/python3.10/dist-packages/typer/core.py", line 193, in _main
rv = self.invoke(ctx)
File "/usr/local/lib/python3.10/dist-packages/click/core.py", line 1688, in invoke
return _process_result(sub_ctx.command.invoke(sub_ctx))
File "/usr/local/lib/python3.10/dist-packages/click/core.py", line 1688, in invoke
return _process_result(sub_ctx.command.invoke(sub_ctx))
File "/usr/local/lib/python3.10/dist-packages/click/core.py", line 1434, in invoke
return ctx.invoke(self.callback, **ctx.params)
File "/usr/local/lib/python3.10/dist-packages/click/core.py", line 783, in invoke
return __callback(*args, **kwargs)
File "/usr/local/lib/python3.10/dist-packages/typer/main.py", line 692, in wrapper
return callback(**use_params)
File "/home/lifeiteng/code/NeMo-Run/src/nemo_run/cli/api.py", line 793, in command
self.cli_execute(fn, ctx.args, type)
File "/home/lifeiteng/code/NeMo-Run/src/nemo_run/cli/api.py", line 845, in cli_execute
self._execute_task(fn, filtered_args)
File "/home/lifeiteng/code/NeMo-Run/src/nemo_run/cli/api.py", line 895, in _execute_task
run_task()
File "/home/lifeiteng/code/NeMo-Run/src/nemo_run/cli/api.py", line 874, in run_task
run.run(
File "/home/lifeiteng/code/NeMo-Run/src/nemo_run/run/api.py", line 65, in run
direct_run_fn(fn_or_script, dryrun=dryrun)
File "/home/lifeiteng/code/NeMo-Run/src/nemo_run/run/task.py", line 77, in direct_run_fn
built_fn()
File "/home/lifeiteng/code/NeMo/nemo/collections/llm/api.py", line 432, in export_ckpt
return io.export_ckpt(path, target, output_path, overwrite, load_connector)
File "/home/lifeiteng/code/NeMo/nemo/lightning/io/api.py", line 197, in export_ckpt
return exporter(overwrite=overwrite, output_path=_output_path)
File "/home/lifeiteng/code/NeMo/nemo/lightning/io/connector.py", line 85, in __call__
to_return = self.apply(_output_path)
File "/home/lifeiteng/code/NeMo/nemo/collections/llm/gpt/model/llama.py", line 301, in apply
source, _ = self.nemo_load(str(self))
File "/home/lifeiteng/code/NeMo/nemo/lightning/io/connector.py", line 216, in nemo_load
_trainer.strategy.connect(model)
File "/home/lifeiteng/code/NeMo/nemo/lightning/pytorch/strategies/megatron_strategy.py", line 286, in connect
raise ValueError("PyTorch DDP is not enabled for mcore optimizer")
ValueError: PyTorch DDP is not enabled for mcore optimizer
```
**Expected behavior**
The export of the Meta-Llama-3-8B model should complete successfully without errors, resulting in a checkpoint file stored in the specified path.
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"@Victor49152 Hi, Can you help me? I just used the config provided in the NeMo/examples/multimodal/text_to_image/stable_diffusion/conf and follow the tutorials.\nI also use the nemo docker to run sd_xl_infer.py๏ผand is still noise output image. ",
"Thanks for your post. Could you please check the log executing 'convert_hf_ckpt_to_nemo.py', I think you might see some unexpected keys and missing keys warning. \n\nSome layer names might be changed in NeMo so the conversion script is not mapping the keys properly. Please let me know if that is the case, I will try to update the conversion script. Thanks.",
"Thanks for your reply. \nThis is the log executing 'convert_hf_ckpt_to_nemo.py': [convert_nemo_test.log](https://github.com/user-attachments/files/17469050/convert_nemo_test.log)\nI also saw some Missing and Unexpected keys in the SDXL Quantization.ipynb you provided. I thought they were normal, so I didn't pay much attention to them. Please help me to see if they are normal. Thank you.\n\n\n",
"This conversion script is obsolete. Can you try https://github.com/NVIDIA/NeMo/blob/main/scripts/checkpoint_converters/convert_stablediffusion_hf_to_nemo.py and https://github.com/NVIDIA/NeMo/blob/409f1d847ff53a66e56763da3a83e2980e9afe53/examples/multimodal/text_to_image/stable_diffusion/conf/sd_xl_infer_v2.yaml as the new inference config. \n\nLet me know if these work for you. I will update the notebook later.",
"I use this script(https://github.com/NVIDIA/NeMo/blob/main/scripts/checkpoint_converters/convert_stablediffusion_hf_to_nemo.py)to convert a safetensors model to nemo.ckpt\nI notice that the saved model uses torch.save to save a ckpt model, is not a .nemo model.\nand use this config.\n```python\n model_cfg.unet_config.from_pretrained = \"/opt/NeMo/nemo_out/sdxl_base_new_test1023A_nemo.ckpt\"\n model_cfg.unet_config.from_NeMo = True\n model_cfg.first_stage_config.from_pretrained = \"/opt/NeMo/nemo_out/sdxl_vae_new_test1023A_nemo.ckpt\"\n model_cfg.first_stage_config.from_NeMo = True\n``` \n```shell\npython3 /opt/NeMo/examples/multimodal/text_to_image/stable_diffusion/sd_xl_infer.py model.restore_from_path=/opt/NeMo/nemo_out/sdxl_base_new_test1023A_nemo.ckpt out_path=/opt/NeMo/infer_out\n``` \nI got the error:\n```shell\nroot@d392d2e1fa20:~# python3 /opt/NeMo/examples/multimodal/text_to_image/stable_diffusion/sd_xl_infer.py model.restore_from_path=/opt/NeMo/nemo_out/sdxl_base_new_test1023A_nemo.ckpt out_path=/opt/NeMo/infer_out\n[NeMo I 2024-10-23 03:19:48 utils:285] FSDP is False, using DDP strategy.\nGPU available: True (cuda), used: True\nTPU available: False, using: 0 TPU cores\nIPU available: False, using: 0 IPUs\nHPU available: False, using: 0 HPUs\n[NeMo W 2024-10-23 03:19:48 utils:333] Loading from .ckpt checkpoint for inference is experimental! It doesn't support models with model parallelism!\nError executing job with overrides: ['model.restore_from_path=/opt/NeMo/nemo_out/sdxl_base_new_test1023A_nemo.ckpt', 'out_path=/opt/NeMo/infer_out']\nTraceback (most recent call last):\n File \"/opt/NeMo/examples/multimodal/text_to_image/stable_diffusion/sd_xl_infer.py\", line 37, in main\n trainer, megatron_diffusion_model = setup_trainer_and_model_for_inference(\n File \"/opt/NeMo/nemo/collections/multimodal/parts/utils.py\", line 337, in setup_trainer_and_model_for_inference\n model = model_provider.load_from_checkpoint(\n File \"/opt/NeMo/nemo/collections/nlp/models/nlp_model.py\", line 385, in load_from_checkpoint\n model = ptl_load_state(cls, checkpoint, strict=strict, cfg=cfg, **kwargs)\n File \"/usr/local/lib/python3.10/dist-packages/pytorch_lightning/core/saving.py\", line 158, in _load_state\n obj = cls(**_cls_kwargs)\n File \"/opt/NeMo/nemo/collections/multimodal/models/text_to_image/stable_diffusion/diffusion_engine.py\", line 367, in __init__\n super().__init__(cfg, trainer=trainer)\n File \"/opt/NeMo/nemo/collections/nlp/parts/mixins/nlp_adapter_mixins.py\", line 88, in __init__\n super().__init__(*args, **kwargs)\n File \"/opt/NeMo/nemo/collections/nlp/models/language_modeling/megatron_base_model.py\", line 118, in __init__\n with open_dict(cfg):\n File \"/usr/lib/python3.10/contextlib.py\", line 135, in __enter__\n return next(self.gen)\nAttributeError: 'dict' object has no attribute '_get_node_flag'\n\nSet the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.\n``` \nAre there any other parameters or code I need to change here ?\n\nIf the.nemo suffix model is used as the file name for saving the model, an error will be reported when loading sdxl_infer.\n```\nroot@d392d2e1fa20:~# python3 /opt/NeMo/scripts/checkpoint_converters/convert_stablediffusion_hf_to_nemo.py --input_name_or_path /sdxl_ckpts/stable-diffusion-xl-base-1.0/unet/ --output_path /opt/NeMo/nemo_out/sdxl_base_new_test1023A.nemo --model unet --debug\n[NeMo I 2024-10-23 02:22:15 convert_stablediffusion_hf_to_nemo:413] loading checkpoint /sdxl_ckpts/stable-diffusion-xl-base-1.0/unet/\n[NeMo I 2024-10-23 02:22:15 convert_stablediffusion_hf_to_nemo:418] converting unet...\n[NeMo I 2024-10-23 02:22:15 convert_stablediffusion_hf_to_nemo:268] Add embedding found...\n[NeMo I 2024-10-23 02:22:15 convert_stablediffusion_hf_to_nemo:273] Time embedding found...\n[NeMo I 2024-10-23 02:23:16 convert_stablediffusion_hf_to_nemo:447] Saved nemo file to /opt/NeMo/nemo_out/sdxl_base_new_test1023A.nemo\nroot@d392d2e1fa20:~# python3 /opt/NeMo/examples/multimodal/text_to_image/stable_diffusion/sd_xl_infer.py model.restore_from_path=/opt/NeMo/nemo_out/sdxl_base_new_test1023A.nemo out_path=/opt/NeMo/infer_out\n[NeMo I 2024-10-23 02:24:52 utils:285] FSDP is False, using DDP strategy.\nGPU available: True (cuda), used: True\nTPU available: False, using: 0 TPU cores\nIPU available: False, using: 0 IPUs\nHPU available: False, using: 0 HPUs\nError executing job with overrides: ['model.restore_from_path=/opt/NeMo/nemo_out/sdxl_base_new_test1023A.nemo', 'out_path=/opt/NeMo/infer_out']\nTraceback (most recent call last):\n File \"/usr/lib/python3.10/tarfile.py\", line 1870, in gzopen\n t = cls.taropen(name, mode, fileobj, **kwargs)\n File \"/usr/lib/python3.10/tarfile.py\", line 1847, in taropen\n return cls(name, mode, fileobj, **kwargs)\n File \"/usr/lib/python3.10/tarfile.py\", line 1707, in __init__\n self.firstmember = self.next()\n File \"/usr/lib/python3.10/tarfile.py\", line 2622, in next\n raise e\n File \"/usr/lib/python3.10/tarfile.py\", line 2595, in next\n tarinfo = self.tarinfo.fromtarfile(self)\n File \"/usr/lib/python3.10/tarfile.py\", line 1285, in fromtarfile\n buf = tarfile.fileobj.read(BLOCKSIZE)\n File \"/usr/lib/python3.10/gzip.py\", line 301, in read\n return self._buffer.read(size)\n File \"/usr/lib/python3.10/_compression.py\", line 68, in readinto\n data = self.read(len(byte_view))\n File \"/usr/lib/python3.10/gzip.py\", line 488, in read\n if not self._read_gzip_header():\n File \"/usr/lib/python3.10/gzip.py\", line 436, in _read_gzip_header\n raise BadGzipFile('Not a gzipped file (%r)' % magic)\ngzip.BadGzipFile: Not a gzipped file (b'PK')\n\nThe above exception was the direct cause of the following exception:\n\nTraceback (most recent call last):\n File \"/opt/NeMo/examples/multimodal/text_to_image/stable_diffusion/sd_xl_infer.py\", line 37, in main\n trainer, megatron_diffusion_model = setup_trainer_and_model_for_inference(\n File \"/opt/NeMo/nemo/collections/multimodal/parts/utils.py\", line 314, in setup_trainer_and_model_for_inference\n model_cfg = model_provider.restore_from(\n File \"/opt/NeMo/nemo/collections/nlp/models/nlp_model.py\", line 478, in restore_from\n return super().restore_from(\n File \"/opt/NeMo/nemo/core/classes/modelPT.py\", line 468, in restore_from\n instance = cls._save_restore_connector.restore_from(\n File \"/opt/NeMo/nemo/collections/nlp/parts/nlp_overrides.py\", line 1298, in restore_from\n loaded_params = super().load_config_and_state_dict(\n File \"/opt/NeMo/nemo/core/connectors/save_restore_connector.py\", line 148, in load_config_and_state_dict\n members = self._filtered_tar_info(restore_path, filter_fn=filter_fn)\n File \"/opt/NeMo/nemo/core/connectors/save_restore_connector.py\", line 622, in _filtered_tar_info\n with SaveRestoreConnector._tar_open(tar_path) as tar:\n File \"/usr/lib/python3.10/contextlib.py\", line 135, in __enter__\n return next(self.gen)\n File \"/opt/NeMo/nemo/core/connectors/save_restore_connector.py\", line 661, in _tar_open\n tar = tarfile.open(path2file, tar_header)\n File \"/usr/lib/python3.10/tarfile.py\", line 1817, in open\n return func(name, filemode, fileobj, **kwargs)\n File \"/usr/lib/python3.10/tarfile.py\", line 1874, in gzopen\n raise ReadError(\"not a gzip file\") from e\ntarfile.ReadError: not a gzip file\n\nSet the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.\n``` \n",
"@Victor49152 @ntajbakhsh Hi๏ผwill there be any updates here in the near future? ",
"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."
] | 2024-10-18T08:56:38 | 2024-12-13T02:06:08 | 2024-12-13T02:06:08 | NONE | {
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} | null | null | null | **Describe the bug**
I follow the [tutorial](https://github.com/NVIDIA/NeMo/blob/main/tutorials/multimodal/SDXL%20Quantization.ipynb) convert a model download from https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0/resolve/main/unet/diffusion_pytorch_model.safetensors.
and I only convert from pytorch model to nemo model.
and infer the nemo model.
but the output image is full of noise.
Is there a bug or am I doing something wrong๏ผ
**Steps/Code to reproduce bug**
I just follow the [tutorial](https://github.com/NVIDIA/NeMo/blob/main/tutorials/multimodal/SDXL%20Quantization.ipynb) .
No quantization model is needed, the nemo model is converted, and the sd_xl_infer.py script is directly used for inference
The same result can be deduced from quantified model
1. download model:
```shell
mkdir -p /sdxl_ckpts/stable-diffusion-xl-base-1.0/unet && wget -P /sdxl_ckpts/stable-diffusion-xl-base-1.0/unet https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0/resolve/main/unet/diffusion_pytorch_model.safetensors
```
```shell
mkdir -p /sdxl_ckpts/stable-diffusion-xl-base-1.0/vae && wget -P /sdxl_ckpts/stable-diffusion-xl-base-1.0/vae https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0/resolve/main/vae/diffusion_pytorch_model.safetensors
```
2. convert safetensors to nemo model
```shell
python3 /opt/NeMo/examples/multimodal/text_to_image/convert_hf_ckpt_to_nemo.py \
--model_type sdxl \
--ckpt_path /sdxl_ckpts/stable-diffusion-xl-base-1.0/unet/diffusion_pytorch_model.safetensors \
--hparams_file /opt/NeMo/examples/multimodal/text_to_image/stable_diffusion/conf/sd_xl_base_train.yaml \
--nemo_file_path $WORKDIR/sdxl_base.nemo
```
3. infer nemo model
```shell
python3 /opt/NeMo/examples/multimodal/text_to_image/stable_diffusion/sd_xl_infer.py model.restore_from_path=/sdxl_base.nemo out_path=/sdxl_infer_out
```
**Expected behavior**
Expect to produce a normal image instead of all noise
**Environment details**
- OS version ubuntu 22.04
- PyTorch version 2.3.0
- Python version 3.10.12
**Additional context**
The output image:
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} | # What does this PR do ?
convert script from nemo1 checkpoint to nemo2 checkpoint
**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?
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- [ ] 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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If you haven't finished some of the above items you can still open "Draft" PR.
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"[๐ค]: Hi @JRD971000 ๐,\n\nWe wanted to let you know that a [CICD pipeline](https://github.com/NVIDIA/NeMo/actions/runs/11408866558) for this PR just finished successfully\n\nSo it might be time to merge this PR or get some approvals\n\nI'm just a bot so I'll leave it you what to do next.\n\n//cc @pablo-garay @ko3n1g",
"@cuichenx The CodeQL points are addressed in the last commit \r\n",
"[๐ค]: Hi @JRD971000 ๐,\n\nWe wanted to let you know that a [CICD pipeline](https://github.com/NVIDIA/NeMo/actions/runs/11443024141) for this PR just finished successfully\n\nSo it might be time to merge this PR or get some approvals\n\nI'm just a bot so I'll leave it you what to do next.\n\n//cc @pablo-garay @ko3n1g"
] | 2024-10-17T22:33:42 | 2024-10-21T18:37:18 | 2024-10-21T18:37:17 | COLLABORATOR | {
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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.
# Usage
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```python
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```
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# Before your PR is "Ready for review"
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- [ ] Did you write any new necessary tests?
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- [ ] 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.
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https://api.github.com/repos/NVIDIA/NeMo/issues/10934 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/10934/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/10934/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/10934/events | https://github.com/NVIDIA/NeMo/pull/10934 | 2,595,825,649 | PR_kwDOC_bI7s5_BcOJ | 10,934 | Wrap batch_sampler with _IndexBatchSamplerWrapper | {
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"> 3e3e39b\r\n\r\nSure, I made the changes here: [3e3e39b](https://github.com/NVIDIA/NeMo/pull/10934/commits/3e3e39b5e1a93a85431333eafc74d80f4f4942ae)\r\nI have also removed the `drop_last` arg that I have added in https://github.com/NVIDIA/NeMo/pull/10837 since we can use the dataloader `mode` to avoid dropping the incomplete batches only during inference.",
"One of the commits is not signed and I wasn't able to fix that by reverting and recommitting the changes. Is there anyway to fix that?",
"Hi @cuichenx, thanks for the review. How do I see what caused the CI failure?",
"> Hi @cuichenx, thanks for the review. How do I see what caused the CI failure?\r\n\r\nCI was cancelled yesterday to expedite some higher priority jobs. I will restart CI",
"@cuichenx There is an import error in the failed tests. Isn't `lightning` a dependency?\r\n```\r\n from lightning.pytorch.overrides.distributed import _IndexBatchSamplerWrapper\r\nE ModuleNotFoundError: No module named 'lightning'\r\n```"
] | 2024-10-17T21:49:59 | 2024-10-29T00:24:55 | 2024-10-29T00:24:55 | CONTRIBUTOR | {
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"merged_at": "2024-10-29T00:24:55"
} | # What does this PR do ?
### NeMo `MegatronDataSampler` is not tracking the `batch_indices`.
In BioNeMo 2.0 we use `PredictionWriter` callback of `BasePredictionWriter` that supposed to capture the `batch_indices` from dataloader's batch sampler and predictions from `predict_step` of the Lightning module. However, `batch_indices` are not being tracked properly and that prevents us from mapping the predictions to input sequences.
`MegatronDataSampler` is [transforming the dataloaders](https://github.com/NVIDIA/NeMo/blob/1757ff9ed10272bf5ee7332d64fccd4bd9676f1b/nemo/lightning/pytorch/plugins/data_sampler.py#L67) by adding megatron batch sampler. But [Lightning prediction loop](https://github.com/Lightning-AI/pytorch-lightning/blob/8ad3e29816a63d8ce5c00ac104b14729a4176f4f/src/lightning/pytorch/loops/prediction_loop.py#L304) tracks `batch_indices` only if the batch sampler is an instance of `lightning.pytorch.overrides.distributed._IndexBatchSamplerWrapper`. To get this fixed I propose the following change in [nemo.lightning.data.add_megatron_sampler](https://github.com/NVIDIA/NeMo/blob/1757ff9ed10272bf5ee7332d64fccd4bd9676f1b/nemo/lightning/data.py#L218)
```python
def add_megatron_sampler(...)
...
return DataLoader(
dataloader.dataset,
batch_sampler=_IndexBatchSamplerWrapper(batch_sampler),
num_workers=dataloader.num_workers,
pin_memory=dataloader.pin_memory,
persistent_workers=dataloader.persistent_workers,
collate_fn=dataloader.collate_fn,
)
```
# 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.
CC: @jstjohn @ericharper
BioNeMo PR: https://github.com/NVIDIA/bionemo-framework/pull/319
## 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.
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"@pzelasko Ive added the AIS check, as well as a flag in cluster config `check_ais_paths` which can be disabled (via config or commandline) in case folks want to preserve speed instead of doing path checks. ",
"[๐ค]: Hi @titu1994 ๐,\n\nWe wanted to let you know that a [CICD pipeline](https://github.com/NVIDIA/NeMo/actions/runs/11563509862) for this PR just finished successfully\n\nSo it might be time to merge this PR or get some approvals\n\nI'm just a bot so I'll leave it you what to do next.\n\n//cc @pablo-garay @ko3n1g",
"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 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."
] | 2024-10-17T20:52:34 | 2024-12-10T02:06:21 | 2024-12-10T02:06:20 | COLLABORATOR | {
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} | # What does this PR do ?
Adds NeMo run support to ASR and common utilities for Run to common collections
**Collection**: [ASR, Common]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
## Local Execution
conf/run_local.yaml
```yaml
# The script to be run.
script: ???
script_config: ???
exp_name: null # populated by exp_manager.name if not provided
results_dir: ??? # Where to store the results of the run
num_runs: 1
num_tasks_per_node: 1
########################################################################################################################
executor: local
containers:
asr: nvcr.io/nvidia/nemo:24.07 # or nvcr.io/nvidia/nemo:dev
mounts:
- "~/.cache/torch/NeMo:/cache/torch/NeMo" # To mount your nemo cache dir (if needed for pretrained models)
```
Call run_helper.py
```python
python run_helper.py --config-path "conf" --config-name "run_local.yaml" \
script=asr_ctc/speech_to_text_ctc_bpe.py \
script_config=conf/conformer/conformer_ctc_bpe.yaml \
results_dir=$PWD/results \
++model.train_ds.manifest_filepath=/manifests/train_clean_5.json \
++model.validation_ds.manifest_filepath="/manifests/dev_clean_2.json" \
++model.tokenizer.dir=/manifests/librispeech_tokenizer_spe_unigram_v1024 \
++mount_1="<Path to Manifests>/librispeech/manifests:/manifests" \
++mount_2="<Data Path>:/data"
```
## Cluster Execution
conf/run_slurm.yaml
```yaml
# The script to be run.
script: ???
script_config: ???
exp_name: null # populated by exp_manager.name if not provided
results_dir: ??? # Where to store the results of the run
# Optional arguments
num_runs: 1
num_tasks_per_node: 8
max_runtime: "00:03:45:00"
########################################################################################################################
executor: slurm
ssh_tunnel:
host: <CLUSTER HOST>
# ------------------------------- Fill this up! -------------------------------
user: "${USER}" # your username; or resolved from ${USER} environment variable
job_dir: <DIRECTORY TO STORE NEMO RUN JOB INFO>
identity: "${CLUSTER_SSH_IDENTITY}"
# -----------------------------------------------------------------------------
account: <SLURM ACCOUNT>
partition: <SLURM PARTITIONS>
job_name_prefix: <JOB PREFIX NAMES>
containers:
asr: <CONTAINER NAME>
# These env vars are propagated to slurm runtime
env_vars:
- 'TOKENIZERS_PARALLELISM=false'
- 'LHOTSE_AUDIO_DURATION_MISMATCH_TOLERANCE=0.3'
- 'TORCH_CUDNN_V8_API_ENABLED=1'
- 'PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True'
- 'HYDRA_FULL_ERROR=1'
# These env vars are propagated to slurm runtime
required_env_vars:
- 'HF_TOKEN'
mounts:
# Replace with your own paths in your cluster config
- <DATA PATH>:/data
- <CHECKPOINTS PATH>:/asr_checkpoints
timeouts:
interactive: 04:00:00
########################################################################################################################
```
#### IMPORTANT NOTE
**NOTE**: Be very careful with using `${}` syntax inside of your hydra overrides - it will try to resolve using your env variables if you use double quotes ("). If you want to provide "hydra placeholders" - use SINGLE QUOTES (') as shown below for `++name` and `++results_dir`
Call run_helper.py
```python
python run_helper.py --config-path conf/ --config-name \
run_slurm script=speech_multitask/speech_to_text_aed.py \
script_config=conf/aed_config.yaml \
exp_name=<JOB NAME> \
results_dir='/results/${exp_name}' \
num_runs=2 \
++trainer.num_nodes=2 \
++name='${exp_name}' \
++exp_manager.wandb_logger_kwargs.project="nemo_asr" \
++USER=$USER \
++CLUSTER_SSH_IDENTITY=$CLUSTER_SSH_IDENTITY
```
# 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**:
- [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.
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} | [๐ค]: Hi @hemildesai ๐,<br><br>we've cherry picked #10914 into `r2.0.0` for you! ๐<br><br>Please review and approve this cherry pick by your convenience\! | {
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} | # What does this PR do ?
Add environment markers according to [PIP documentation](https://pip.pypa.io/en/stable/reference/requirement-specifiers/) for optional requirements not installable on MacOS.
This fixes `pip install -e ".[all]"` on MacOS.
**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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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.
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Implemented ClipScoreFusion model (UniIR) which leverages Clip models for multimodal retrieval tasks
**Collection**: [Note which collection this PR will affect]
multimodal
# Usage
```python
model = MegatronCLIPScoreFusionModel(cfg.model, trainer)
```
# 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?
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- [ ] 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.
## Who can review?
@JRD971000
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merge base model and lora adapter in nemo2
**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)
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} | # What does this PR do ?
This PR extends NeMo and SpeechLLM with the following:
* EMMeTT (optimized training) support for SpeechLLM
* Support for joint audio and text training for `modular_models.py` and `modular_t5_models.py`
* Dedicated `estimate_token_bins.py` and `oomptimizer.py` in `scripts/speech_llm`.
* Dedicated data types for text and multimodal conversation data
* APIs for registering prompt formatting functions for tuples of (data_type, prompt_formatter_type)
* APIs for sequence length measurement (input, output, total) of various data types, seqlen filtering, and 1D+2D bucketing
* Generally a major cleanup of past messy half-solutions related to the above
* Tutorial about the changes related to data loading
**Collection**: multimodal
# 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**:
- [x] 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)
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} | # What does this PR do ?
Add performance optimizations as a param
**Collection**: [llm]
# Changelog
```
if performance_mode:
recipe = pretrain_performance_optimizations(recipe)
```
# Usage
```python
from nemo.collections.llm.recipes.llama3_8b import pretrain_recipe
recipe = pretrain_recipe(dir='a/b/c', performance_mode=True)
```
# GitHub Actions CI
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To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".
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**PR Type**:
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- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
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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.
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"cc @oyilmaz-nvidia "
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} | [๐ค]: Hi @janekl ๐,<br><br>we've cherry picked #10906 into `r2.0.0` for you! ๐<br><br>Please review and approve this cherry pick by your convenience\! | {
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"[๐ค]: Hi @huvunvidia ๐,\n\nWe wanted to let you know that a [CICD pipeline](https://github.com/NVIDIA/NeMo/actions/runs/11554919357) for this PR just finished successfully\n\nSo it might be time to merge this PR or get some approvals\n\nI'm just a bot so I'll leave it you what to do next.\n\n//cc @pablo-garay @ko3n1g"
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} | # What does this PR do ?
Re-organizing inference pipeline in NeMo 2.0 for support both decoder and encoder-decoder (and other models).
Tested with GPT and T5.
**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
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**Collection**: [Note which collection this PR will affect]
# Changelog
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# 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.
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.
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"CI passed: https://github.com/NVIDIA/NeMo/actions/runs/11412081765"
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Removes deprecated ci tests and ads a deprecation note for features which are no longer supported in NeMo.
**Collection**: [Note which collection this PR will affect]
# Changelog
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* You can potentially add a usage example below
```python
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If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
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Adds default settings to LlamaConfig and classes which inherit from it for better out-of-the-box perf.
**Collection**: llm
# 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**:
- [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.
[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)
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} | # What does this PR do ?
When running LoRA with NeMo 2.0 and setting tp_overlap_comm=false and sequence_parallel=true, training crashes with `RuntimeError: The size of tensor a (4096) must match the size of tensor b (8192) at non-singleton dimension 0`. This crash occurs because when `tp_overlap_comm=false`:
- ParallelLinearAdapter checks for `tp_overlap_comm_disable_qkv=false` ([this line](https://github.com/NVIDIA/NeMo/blob/9a66eeeac2aa62541476bb4b66ae375b70d2db83/nemo/collections/nlp/modules/common/megatron/adapters/parallel_adapters.py#L259)) and assumes TP overlap is enabled, so it does not disable `self._sequence_parallel`
- LoRA checks `ub_overlap_ag` instead ([this line](https://github.com/NVIDIA/NeMo/blob/9a66eeeac2aa62541476bb4b66ae375b70d2db83/nemo/collections/llm/peft/lora.py#L150)), finds that it is false so TP overlap is disabled, and enables `return_layernorm_output_gathered` for the module.
- Then with both `_sequence_parallel` and `return_layernorm_output_gathered` enabled for this module, a shape mismatch crash occurs.
This PR edits the line in ParallelLinearAdapter to also disable `self._sequence_parallel` if `tp_comm_overlap` is set to false.
++ Folded in #10921 and #10985.
**Collection**: nlp, llm
# 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**:
- [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)
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๐ Please remember the following to-do's before merge:
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} | # What does this PR do ?
1. Add wildcard matching to LoRA, so that it is more flexible to select which linear layer LoRA is applied on
2. Make module class type (TE vs Mcore local, column vs row) more explicit inside LoRA
3. Allow users to customize freeze strategy
4. (Bug fix) Set mode to training for frozen lora modules
**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?
- [ ] 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.
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**Collection**: [Note which collection this PR will affect]
# Changelog
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# Usage
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```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.
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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"
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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?
**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.
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* Related to # (issue)
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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.
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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".
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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?
**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.
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"[๐ค]: Hi @ShriyaPalsamudram ๐,\n\nWe wanted to let you know that a [CICD pipeline](https://github.com/NVIDIA/NeMo/actions/runs/11501631982) for this PR just finished successfully\n\nSo it might be time to merge this PR or get some approvals\n\nI'm just a bot so I'll leave it you what to do next.\n\n//cc @pablo-garay @ko3n1g"
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Enable async ckpt, ckpt every 15mins and reduce preemption time from 5mins to 1min. Disable async ckpt save for the PEFT test as it is not supported at this time.
**Collection**: [Note which collection this PR will affect]
llm
# 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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# Before your PR is "Ready for review"
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- [ ] 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.
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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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- [ ] 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.
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* Add registry to register all needed classes with artifacts in nemo.lightning.io
* Apply isort and black reformatting
* Fixes
* Apply isort and black reformatting
* Fix
* comments
* Apply isort and black reformatting
* Apply isort and black reformatting
* Remove cyclic import
---------
# 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".
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} | * Save yaml config for model in nemo.lightning.io
* Apply isort and black reformatting
* Fix bug
* Fix bug
* fix bug
* Add explicit yaml comparison
* Apply isort and black reformatting
* relax test
---------
# 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
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} | # What does this PR do ?
Remove opencc upperbound
**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
```
# 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?
- [ ] 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.
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} | # What does this PR do ?
Remove upper bound on opencc version
**Collection**: [nlp]
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* test fix
* turn off SP
---------
# 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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```python
# Add a code snippet demonstrating how to use this
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"[๐ค]: Hi @janekl ๐,\n\nWe wanted to let you know that a [CICD pipeline](https://github.com/NVIDIA/NeMo/actions/runs/11370588797) for this PR just finished successfully\n\nSo it might be time to merge this PR or get some approvals\n\nI'm just a bot so I'll leave it you what to do next.\n\n//cc @pablo-garay @ko3n1g"
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} | # What does this PR do ?
Warning for missing FP8 checkpoint support for vLLM deployment.
**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
```
# GitHub Actions CI
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# Before your PR is "Ready for review"
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- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
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- [ ] 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.
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* Related to # (issue)
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"This issue was closed because it has been inactive for 7 days since being marked as stale."
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Shouldn't the total number of tokens per global batch size remain the same? | {
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"FYI @apanteleev ",
"[๐ค]: Hi @janekl ๐,\n\nWe wanted to let you know that a [CICD pipeline](https://github.com/NVIDIA/NeMo/actions/runs/11518135457) for this PR just finished successfully\n\nSo it might be time to merge this PR or get some approvals\n\nI'm just a bot so I'll leave it you what to do next.\n\n//cc @pablo-garay @ko3n1g"
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} | # What does this PR do ?
Enabling FP8 quantization for vLLM engines. For now only the basic variant based on on-line dynamic scaling is supported. Depending on a use-case it gives up to 20% inference speedup.
Static quantization will follow in a subsequent MR.
**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
# Using in nemo_export.py
python tests/export/nemo_export.py \
--model_name local \
--model_type llama \
--checkpoint_dir /models/LLAMA3-8B-base-1.nemo \
--min_tps 1 \
--run_accuracy True \
--test_data_path /data/lambada.json \
--use_vllm True \
--vllm_export_kwargs '{"quantization": "fp8"}' \
--debug
# Using in deploy_vllm_triton.py
python scripts/deploy/nlp/deploy_vllm_triton.py \
--nemo_checkpoint /models/LLAMA3-8B-base-1.nemo \
--model_type llama \
--tensor_parallelism_size 1 \
--triton_model_name local \
--quantization fp8
```
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**Pre checks**:
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**PR Type**:
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- [ ] Bugfix
- [ ] Documentation
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# Additional Information
* Related to https://github.com/NVIDIA/NeMo/pull/10941
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"[๐ค]: Hi @lilithgrigoryan ๐,\n\nWe wanted to let you know that a [CICD pipeline](https://github.com/NVIDIA/NeMo/actions/runs/11368371947) for this PR just finished successfully\n\nSo it might be time to merge this PR or get some approvals\n\nI'm just a bot so I'll leave it you what to do next.\n\n//cc @pablo-garay @ko3n1g",
"[๐ค]: Hi @lilithgrigoryan ๐,\n\nWe wanted to let you know that a [CICD pipeline](https://github.com/NVIDIA/NeMo/actions/runs/11699371415) for this PR just finished successfully\n\nSo it might be time to merge this PR or get some approvals\n\nI'm just a bot so I'll leave it you what to do next.\n\n//cc @pablo-garay @ko3n1g",
"[๐ค]: Hi @lilithgrigoryan ๐,\n\nWe wanted to let you know that a [CICD pipeline](https://github.com/NVIDIA/NeMo/actions/runs/11704247416) for this PR just finished successfully\n\nSo it might be time to merge this PR or get some approvals\n\nI'm just a bot so I'll leave it you what to do next.\n\n//cc @pablo-garay @ko3n1g",
"[๐ค]: Hi @lilithgrigoryan ๐,\n\nWe wanted to let you know that a [CICD pipeline](https://github.com/NVIDIA/NeMo/actions/runs/11708944947) for this PR just finished successfully\n\nSo it might be time to merge this PR or get some approvals\n\nI'm just a bot so I'll leave it you what to do next.\n\n//cc @pablo-garay @ko3n1g",
"[๐ค]: Hi @lilithgrigoryan ๐,\n\nWe wanted to let you know that a [CICD pipeline](https://github.com/NVIDIA/NeMo/actions/runs/11711230499) for this PR just finished successfully\n\nSo it might be time to merge this PR or get some approvals\n\nI'm just a bot so I'll leave it you what to do next.\n\n//cc @pablo-garay @ko3n1g",
"[๐ค]: Hi @lilithgrigoryan ๐,\n\nWe wanted to let you know that a [CICD pipeline](https://github.com/NVIDIA/NeMo/actions/runs/11725685642) for this PR just finished successfully\n\nSo it might be time to merge this PR or get some approvals\n\nI'm just a bot so I'll leave it you what to do next.\n\n//cc @pablo-garay @ko3n1g",
"[๐ค]: Hi @lilithgrigoryan ๐,\n\nWe wanted to let you know that a [CICD pipeline](https://github.com/NVIDIA/NeMo/actions/runs/11799130744) for this PR just finished successfully\n\nSo it might be time to merge this PR or get some approvals\n\nI'm just a bot so I'll leave it you what to do next.\n\n//cc @pablo-garay @ko3n1g",
"[๐ค]: Hi @lilithgrigoryan ๐,\n\nWe wanted to let you know that a [CICD pipeline](https://github.com/NVIDIA/NeMo/actions/runs/11806381641) for this PR just finished successfully\n\nSo it might be time to merge this PR or get some approvals\n\nI'm just a bot so I'll leave it you what to do next.\n\n//cc @pablo-garay @ko3n1g",
"<!-- pylint-output-strict-mode-false -->\n\nbeep boop ๐ค: ๐ The following files have warnings. In case you are familiar with these, please try helping us to improve the code base.\n\n---\n\nYour code was analyzed with PyLint. The following annotations have been identified:\n\n```\n\n------------------------------------\nYour code has been rated at 10.00/10\n```\n\n---\n\nThank you for improving NeMo's documentation!",
"[๐ค]: Hi @lilithgrigoryan ๐,\n\nWe wanted to let you know that a [CICD pipeline](https://github.com/NVIDIA/NeMo/actions/runs/11814247497) for this PR just finished successfully\n\nSo it might be time to merge this PR or get some approvals\n\nI'm just a bot so I'll leave it you what to do next.\n\n//cc @pablo-garay @ko3n1g"
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} | # What does this PR do ?
PR introduces default beam search and mAES (with Ngram LM fusion) decoding implementations for TDT models.
**Collection**: ASR
# Changelog
- [nemo/collections/asr/parts/submodules/tdt_beam_decoding.py]: Default Beam Search and mAES implementations for TDT.
# Usage
```python
python examples/asr/speech_to_text_eval.py \
model_path="$NEMO_MODEL_PATH" \
dataset_manifest="$DATASET_MANIFEST_PATH" \
rnnt_decoding.strategy=maes \
rnnt_decoding.beam.beam_size=8 \
rnnt_decoding.beam.ngram_lm_model="$KENLM_NGRAM_MODEL_PATH"
```
# 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**:
- [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
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)
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} | # What does this PR do ?
* Update default pruning parameters based on optimal results
* Disable `sequence_parallel` by default since it does not work with pipeline parallel
* Add an option to prune `num_layers` (depth) as well
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} | # What does this PR do ?
Improve performance of mask calculations.
**Collection**: VLM
# 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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"@JRD971000 "
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I am wondering if the scripts implemented in Mamba Megatron pipeline parallel will be possibly used inside Nemo? Specifically Mamba Megatron supports converting Mamba both to Tensor Parallel & Pipeline Parallel [at here](https://github.com/NVIDIA/Megatron-LM/blob/main/tools/checkpoint/hybrid_conversion.py). The pipeline parallel code has been using Megatron's [without interleaved implementation](https://github.com/NVIDIA/Megatron-LM/blob/main/megatron/core/pipeline_parallel/schedules.py#L1274). Will we be able to utilize any of that Megatron implementation for SFT on Mamba in Nemo?
Thank you! | null | {
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```
Follow the steps from [here](https://nemo-framework-tme.gitlab-master-pages.nvidia.com/documentation/user-guide/latest/llms/gemma/dataprep.html) to obtain and preprocess the fine-tuning dataset.
```
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} | # What does this PR do ?
1. Save packed dataset in different folders according to the model name, so that different packed datasets don't clash with each other
2. Fix hanging if preparing packed data before a multi-gpu training session
3. Raise mbs>1 error and provide suggestion to user instead of automatically changing the config
**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?
- [ ] 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)
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"[๐ค]: Hi @ashors1 ๐,\n\nWe wanted to let you know that a [CICD pipeline](https://github.com/NVIDIA/NeMo/actions/runs/11578772531) for this PR just finished successfully\n\nSo it might be time to merge this PR or get some approvals\n\nI'm just a bot so I'll leave it you what to do next.\n\n//cc @pablo-garay @ko3n1g",
"peft test passed https://github.com/NVIDIA/NeMo/actions/runs/11672168085/job/32500417335 launching full ci now",
"[๐ค]: Hi @ashors1 ๐,\n\nWe wanted to let you know that a [CICD pipeline](https://github.com/NVIDIA/NeMo/actions/runs/11687383039) for this PR just finished successfully\n\nSo it might be time to merge this PR or get some approvals\n\nI'm just a bot so I'll leave it you what to do next.\n\n//cc @pablo-garay @ko3n1g"
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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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# 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.
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"Close in favor of #10973\r\n"
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} | [๐ค]: Hi @malay-nagda ๐,<br><br>we've cherry picked #10853 into `r2.0.0` for you! ๐<br><br>Please review and approve this cherry pick by your convenience\! | {
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"[๐ค]: Hi @akoumpa ๐,\n\nWe wanted to let you know that a [CICD pipeline](https://github.com/NVIDIA/NeMo/actions/runs/11354229992) for this PR just finished successfully\n\nSo it might be time to merge this PR or get some approvals\n\nI'm just a bot so I'll leave it you what to do next.\n\n//cc @pablo-garay @ko3n1g",
"[๐ค]: Hi @akoumpa ๐,\n\nWe wanted to let you know that a [CICD pipeline](https://github.com/NVIDIA/NeMo/actions/runs/11374388366) for this PR just finished successfully\n\nSo it might be time to merge this PR or get some approvals\n\nI'm just a bot so I'll leave it you what to do next.\n\n//cc @pablo-garay @ko3n1g"
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**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.
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* Related to # (issue)
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"waiting to cherrypick #10898 as well"
] | 2024-10-15T19:27:00 | 2024-10-22T06:36:54 | 2024-10-22T06:36:53 | COLLABORATOR | {
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} | # What does this PR do ?
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**Collection**: [Note which collection this PR will affect]
# Changelog
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# Usage
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```python
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# What does this PR do ?
Logging is showing UnicodeEncodeError for Spanish (Non-english character) in [tutorials/asr/Multilang_ASR.ipynb](https://github.com/NVIDIA/NeMo/blob/r2.0.0/tutorials/asr/Multilang_ASR.ipynb). Need to specify the encoding scheme to 'utf-8' to avoid that issue.
**Collection**: [Note which collection this PR will affect]
NeMo/utils
# GitHub Actions CI
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**PR Type**:
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- [x] Bugfix
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## Who can review?
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Add a one line overview of what this PR aims to accomplish.
PR to support nemo 2.0 ckpt in TRT-LLM export
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"Update on the procedure I'm following:\n- I use the Nemo framework 24.07 image\n- Launch a container with the image (witha couple of volumes): docker run --runtime=nvidia --gpus all -it --rm \\\n -v /mnt/shared_demos/dreambooth/nemo:/opt/NeMo \\\n -v /mnt/shared_models/huggingface/cache/hub/models--runwayml--stable-diffusion-v1-5/snapshots/1d0c4ebf6ff58a5caecab40fa1406526bca4b5b9:/opt/models \\\n --shm-size=8g -p 8888:8888 \\\n --ulimit memlock=-1 --ulimit stack=67108864 \\\n nvcr.io/nvidia/nemo:24.05\n- I install the main branch from the nemo repository in order to get the nemo toolkit installed: python -m pip install git+https://github.com/NVIDIA/NeMo.git@main#egg=nemo_toolkit[all]\n- The one above installs the megatron library in /opt/megatron-lm. However, this is version 0.8; and if I go to the path where it's located, the contents of /megatron/core are not updated, for example, there's no folder called extensions. \n\nThus, it installs something that cannot be used for the dreambooth example. \n\nThere's also a section (Megatron-LM) where it is specified to run the following in roder to use it:\n\n- git clone https://github.com/NVIDIA/Megatron-LM.git && \\\n- cd Megatron-LM && \\\n- git checkout $mcore_commit && \\\n- pip install .\n\nThis has the versions updated but installs a version of megatron incompatible with dreambooth files (0.10) and image, I believe. \n\nCould you help me with this issue please? is it related to the branch I'm installing? to the image?\n",
"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."
] | 2024-10-15T07:04:50 | 2024-11-24T02:06:03 | 2024-11-24T02:06:02 | NONE | {
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[NeMo W 2024-10-08 09:12:02 megatron_lm_encoder_decoder_model:78] Megatron num_microbatches_calculator not found, using Apex version.
Traceback (most recent call last):
File "/opt/NeMo/clip/convert_external_clip_to_nemo.py", line 53, in <module>
from nemo.collections.multimodal.models.vision_language_foundation.clip.megatron_clip_models import MegatronCLIPModel
File "/usr/local/lib/python3.10/dist-packages/nemo/collections/multimodal/models/vision_language_foundation/clip/megatron_clip_models.py", line 311, in <module>
class SiglipMHAPoolingHead(TransformerLayer):
NameError: name 'TransformerLayer' is not defined
I don't think you specify which NeMo image is compatible with this example. Two months ago it was working with the image nvcr.io/nvidia/nemo:24.02, but now it gives the error I put above.
Please could you tell me which image works with this tutorial? or which versions of the libraries are needed?
Thank you so much.
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"[๐ค]: Hi @cuichenx ๐,\n\nWe wanted to let you know that a [CICD pipeline](https://github.com/NVIDIA/NeMo/actions/runs/11336668220) for this PR just finished successfully\n\nSo it might be time to merge this PR or get some approvals\n\nI'm just a bot so I'll leave it you what to do next.\n\n//cc @pablo-garay @ko3n1g"
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} | # What does this PR do ?
1. Fix assertion error due to "context" folder in base model checkpoint
2. Fix tokenizer loading issue during 3rd restart (First time training: tokenizer is loaded from base model and saved. Second time training: tokenizer is loaded from first checkpoint, but is not saved if the first checkpoint is deleted due to save_top_k=1. Third time training: tokenizer cannot be loaded from second checkpoint)
**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)
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