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**Making it a option to use thunder to jit-compile the dropout in LoRA adapters; thunder can reduce the memory footprint of this layer by recomputing the dropout mask in backprop.**
**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The Jenkins CI system has been replaced by GitHub Actions self-hosted runners.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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} | # What does this PR do ?
Adds Auto Configurator to NeMo github (based on NeMo 2,0)
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# GitHub Actions CI
The Jenkins CI system has been replaced by GitHub Actions self-hosted runners.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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When fine-tuning for a mamba2 hybrid model we can convert it to a .nemo format but we cannot convert back to HF/Pytorch.
**Describe the solution you'd like**
Converting script for a nemo mamba2 Hybrid model to HF / Pytorch format.
**Describe alternatives you've considered**
-None
**Additional context**
-None
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} | # What does this PR do ?
Configuring PTQ to use the same precision to load a model as `export.dtype` by default. This is to avoid possible OOM errors when casting weights on the model export step.
This is for use cases with less device memory available, for example, PTQ for Llama3-8b on L4 24GB GPU.
**Collection**: NLP
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* In order to use FP16 / BF16 weights precision enabling `model.megatron_amp_O2` is necessary
* Disabling `model.dist_ckpt_load_on_device` avoid GPU memory spikes on model loading
* Using a lower `inference.batch_size` (compared to default 64) might also be needed.
Example PTQ command is:
```
python megatron_gpt_ptq.py \
model.restore_from_path=Llama3-8b \
+model.dist_ckpt_load_on_device=false \
export.dtype=bf16 \
inference.batch_size=16
```
# 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**:
- [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?
- [ ] 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?
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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/10265 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/10265/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/10265/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/10265/events | https://github.com/NVIDIA/NeMo/pull/10265 | 2,487,986,708 | PR_kwDOC_bI7s55gCd6 | 10,265 | Do not overwrite wandb name in NeMo Logger | {
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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
```
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# Before your PR is "Ready for review"
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https://api.github.com/repos/NVIDIA/NeMo/issues/10264 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/10264/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/10264/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/10264/events | https://github.com/NVIDIA/NeMo/issues/10264 | 2,487,971,701 | I_kwDOC_bI7s6US291 | 10,264 | Converting HF model to Nemo gets an error | {
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"Following up regarding issue. Please let me know if any more information is needed.",
"According to this [HF implementation](https://github.com/huggingface/transformers/blob/v4.44.2/src/transformers/models/opt/modeling_opt.py):\n* `project_out` should be the final output layer, so it should be mapped to `model.o... | 2024-08-26T23:37:29 | 2024-11-15T02:02:42 | 2024-11-15T02:02:41 | NONE | {
"total": 0,
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} | null | null | null | **Describe the bug**
I am trying to convert the [OPT-350m](https://huggingface.co/facebook/opt-350m) hugging face model to Nemo format. How can I map the following keys?
```
- model.decoder.project_out.weight
- model.decoder.project_in.weight
```
for other weight names, I can successfully map to Nemo format.
A clear and concise description of what the bug is.
**Steps/Code to reproduce bug**
Please list *minimal* steps or code snippet for us to be able to reproduce the bug.
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**
A clear and concise description of what you expected to happen.
**Environment overview (please complete the following information)**
- Environment location: [Bare-metal, Docker, Cloud(specify cloud provider - AWS, Azure, GCP, Collab)] Docker
- Method of NeMo install: [pip install or from source]. Please specify exact commands you used to install. nemo:24.03.01.framework
- If method of install is [Docker], provide `docker pull` & `docker run` commands used
**Environment details**
If NVIDIA docker image is used you don't need to specify these.
Otherwise, please provide:
- OS version : Ubuntu 20.04
- PyTorch version : nemo:24.03.01.framework
- Python version : nemo:24.03.01.framework
**Additional context**
Add any other context about the problem here.
Example: GPU model : H100
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"> There are some unwanted changed in `cicd-main.yml`. Can you please revert these?\r\n\r\nDone.",
"Does the commit support the encoder and decoder are put into different devices? Could the encoder and decoder be model parallelized with their own parallism config?"
] | 2024-08-26T23:24:17 | 2024-10-08T03:00:52 | 2024-09-26T15:17:41 | COLLABORATOR | {
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} | # What does this PR do ?
Adding support for T5 in NeMo 2.0. Main files working on:
+ T5 specific:
- megatron_t5_pretraining.py
- pre_training.py (using T5Dataset from mcore)
- t5.py
+ Others:
- auto_tokenizer.py: adding inv_vocab() to tokenizer to be compatible with mcore's T5Dataset
- lr_scheduler.py: adding missing warmup support
**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 ?
Add Nemoron4 15b and 22b model 8k configs and Long Context Recipes for 16k and 64k along with it.
**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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"How do we enable the collection callback?",
"> How do we enable the collection callback?\r\n\r\nRefer to the usage in the PR description."
] | 2024-08-26T21:20:12 | 2024-08-28T18:34:29 | 2024-08-28T18:34:28 | COLLABORATOR | {
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} | # What does this PR do ?
Adding a Garbage-collection callback for a synchronized garbage-collection across ALL processes
**Collection**: [Note which collection this PR will affect]
Potentially affects all of them.
# Changelog
- Garbage Collection callback for NeMo 2.0
# Usage
```
trainer = nl.Trainer(
strategy = strategy,
devices=8,
num_nodes=1,
accelerator='gpu',
logger=False,
enable_checkpointing=False,
use_distributed_sampler=False,
#max_epochs=100,
max_steps=200,
log_every_n_steps=1,
val_check_interval=10,
limit_val_batches=10,
limit_test_batches=200,
accumulate_grad_batches=1,
gradient_clip_val=1.0,
benchmark=False,
enable_model_summary=False,
limit_train_batches=200,
enable_progress_bar=False,
num_sanity_val_steps=0,
**callbacks = [GarbageCollectionCallback(gc_interval_train=20, gc_interval_val=40)],**
plugins=nl.MegatronMixedPrecision(precision='bf16-mixed',)
)
```
# Testing
Log excerpt
```
self.communication_handle = torch.distributed._reduce_scatter_base(
[NeMo I 2024-08-26 14:07:29 garbage_collection:54] Running garbage collection at train global_step: 20
[NeMo I 2024-08-26 14:07:33 garbage_collection:54] Running garbage collection at train global_step: 40
[NeMo I 2024-08-26 14:07:34 garbage_collection:67] Running garbage collection at validation step: 40
[NeMo I 2024-08-26 14:07:37 garbage_collection:54] Running garbage collection at train global_step: 60
[NeMo I 2024-08-26 14:07:41 garbage_collection:54] Running garbage collection at train global_step: 80
[NeMo I 2024-08-26 14:07:42 garbage_collection:67] Running garbage collection at validation step: 80
[NeMo I 2024-08-26 14:07:45 garbage_collection:54] Running garbage collection at train global_step: 100
[NeMo I 2024-08-26 14:07:48 garbage_collection:54] Running garbage collection at train global_step: 120
[NeMo I 2024-08-26 14:07:49 garbage_collection:67] Running garbage collection at validation step: 120
[NeMo I 2024-08-26 14:07:52 garbage_collection:54] Running garbage collection at train global_step: 140
[NeMo I 2024-08-26 14:07:56 garbage_collection:54] Running garbage collection at train global_step: 160
[NeMo I 2024-08-26 14:07:56 garbage_collection:67] Running garbage collection at validation step: 160
[NeMo I 2024-08-26 14:07:59 garbage_collection:54] Running garbage collection at train global_step: 180
[NeMo I 2024-08-26 14:08:03 garbage_collection:54] Running garbage collection at train global_step: 200
[NeMo I 2024-08-26 14:08:04 garbage_collection:67] Running garbage collection at validation step: 200
`Trainer.fit` stopped: `max_steps=200` reached.
ENDING TIMING RUN AT 2024-08-26 02:08:12 PM
RESULT,large language model,1,79,root,2024-08-26 02:06:53 PM
```
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- [ ] Did you write any new necessary tests?
- [x] Did you add or update any necessary documentation?
- [x] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
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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.
## Who can review?
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"merged_at": "2024-08-27T22:41:35"
} | # 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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To re-run CI remove and add the label again.
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# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] 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 ?
This fixes a bug with nemo_logger that arises when the trainer's `logger.save_dir` is absolute, which happens by default. The fix is to convert the absolute path to a relative one before overwriting the logger directory.
**Collection**: LLM
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Add a one line overview of what this PR aims to accomplish.
**Collection**: [Note which collection this PR will affect]
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"Looks good. \r\n\r\n> This can cause hands, but for now let's try it.\r\n\r\n@titu1994 can you elaborate? do you expect an uneven number of validation batches per node (why), or something else?",
"Yes, the reason to avoid sync is two fold - I think I remember random hangs years ago due to a similar flag, dunno i... | 2024-08-26T16:04:48 | 2024-10-22T17:01:14 | 2024-09-18T01:55:43 | COLLABORATOR | {
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} | # What does this PR do ?
setting sync_dist=True for `on_validation_epoch_end` in `ModelPT.py`
This is in response to the recent slack discussion on "wiping out of checkpoints mid training and starting from scratch" in Canary training.
**Collection**: [all] - The change is in ModelPT.py
# Changelog
- setting sync_dist=true in `on_validation_epoch_end`
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} | # What does this PR do ?
This PR moves the imports for nemotron of transformers & tokenizer inline. This is needed for pip-installs where we don't want to throw an import error when someone doesn't have transformers installed.
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"Hey, sorry for the slow response. If I understand your question, you can have 1 AR model predict all 8 codebooks at the same time (eg. input the final output of your network into 8 independent softmax functions). You do not need 8 separate AR models.",
"> Hey, sorry for the slow response. If I understand your qu... | 2024-08-26T07:59:58 | 2024-09-24T02:30:26 | 2024-09-24T02:30:25 | NONE | {
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} | # What does this PR do ?
torchrun fix was broken; when making the model-import trainer, it was using the env-vars.
Reverting this as it's breaking other things.
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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.",
"Thanks for the request. We don't offer exact functionality now. However you could use [this script ](https://github.com/NVIDIA/NeMo/blob/main/scripts/asr_context_biasing/e... | 2024-08-24T12:57:05 | 2024-09-24T17:16:30 | 2024-09-24T17:16:30 | NONE | {
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} | null | null | null | **Is your feature request related to a problem? Please describe.**
is there a way for the canary and parakeet models (https://huggingface.co/nvidia/canary-1b) to steer transcription like whisper in order to have correct name spellings for example or adapt a certain style?
goal is to have better, more accurate subtitles
**Describe the solution you'd like**
pass string to the inference methods for these models to have more accurate resulting transcriptions. for example to fix spelling of names or titles
**additional context**
see whisper prompting here https://cookbook.openai.com/examples/whisper_prompting_guide | {
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"@stevehuang52 pls have a look at this. ",
"Thanks for pointing out the issue, it will be fixed in https://github.com/NVIDIA/NeMo/pull/10581",
"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 be... | 2024-08-24T12:13:07 | 2024-10-31T02:00:06 | 2024-10-31T02:00:06 | NONE | {
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} | null | null | null | **Describe the bug**
canary model chunked infer with `speech_to_text_aed_chunked_infer.py` throws this error:
`TypeError: 'TranscriptionConfig' object is not iterable`
**Steps/Code to reproduce bug**
run this `main` function: https://github.com/NVIDIA/NeMo/blob/7cc99e95fa753f46dffffc47a19e3c1fa375159c/examples/asr/asr_chunked_inference/aed/speech_to_text_aed_chunked_infer.py#L118
throws at this line
https://github.com/NVIDIA/NeMo/blob/7cc99e95fa753f46dffffc47a19e3c1fa375159c/examples/asr/asr_chunked_inference/aed/speech_to_text_aed_chunked_infer.py#L122
**misc**
might be legacy code?
might be that it will also throw here: https://github.com/NVIDIA/NeMo/blob/7cc99e95fa753f46dffffc47a19e3c1fa375159c/examples/asr/asr_chunked_inference/rnnt/speech_to_text_buffered_infer_rnnt.py#L149 | {
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} | # What does this PR do ?
Add SALM export
**Collection**: [NA] (nemo multimodal export)
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
Run export:
Please refer to `https://github.com/Slyne/NeMo/blob/salm_trtllm_llm/examples/multimodal/speech_llm/export/README.md`
Run deploy:
```bash
python3 NeMo/scripts/deploy/multimodal/deploy_triton.py \
--modality="audio" \
--visual_checkpoint=NeMo/examples/multimodal/speech_llm/export/output/speechllm_fc_llama2_7b_perception \
--llm_checkpoint=NeMo/examples/multimodal/speech_llm/export/speechllm_fc_llama2_7b_llm_merged.nemo \
--llm_model_type="llama" \
--model_type="salm" \
--triton_model_name="salm" \
--max_input_len=4096 \
--max_output_len=256 \
--max_multimodal_len=3072 \
--triton_model_repository=/tmp/trt_model_dir/
```
Run query:
```
python3 NeMo/scripts/deploy/multimodal/query.py \
--model_name="salm" \
--model_type="salm" \
--input_text="Q: what's the transcription of the audio? A:" \
--input_media=/ws/data/test-clean-processed/7729-102255-0009.wav
```
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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
```
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# Before your PR is "Ready for review"
**Pre checks**:
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**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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📝 Please remember the following to-do's before merge:
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} | # What does this PR do ?
For flash and fused attention kernels, the attention mask is implicitly generated by the kernel, so no need to generate the mask from the dataloader. This saves memory, especially for causal masks of long sequence lengths.
Flash attention and fused attention are well supported and should cover all the models supported by NeMo, and are already turned on by default, so turning this on by default as well.
This also removes a HtoD at the start of the first layer, since the attention mask is on CPU for GPTDataset. This gives a ~5% speedup on the first pipeline parallel stage:
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
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- saves weights and artifacts to separate directories
- provides the option to skip saving optimizer states on train end
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
# Add a code snippet demonstrating how to use this
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# Before your PR is "Ready for review"
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} | # What does this PR do ?
transformers support Nemotron start 4.44.0
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# GitHub Actions CI
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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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"Closing this for now. Sounds like this conflicts with another plan. To summarize that discussion with @marcromeyn:\r\n\r\n1. if I can call a function to get access to old checkpoint settings `old_ckpt = io.load(self.ckpt_init_path).model.checkpoint` which does not impact global state for the current context/run (t... | 2024-08-23T15:53:16 | 2024-08-31T00:12:11 | 2024-08-31T00:12:11 | COLLABORATOR | {
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} | # What does this PR do ?
Adds two helpful items for working with ABCs that eventually get IOMixin:
1. A parent `NeedsIOMixin` ABC that lets you inform a parent class that it will eventually be an IOMixin, and also catches cases where you use it before subclassing and inheriting from iomixin. This has been useful for making parent config types that children implement and extend.
2. A mutate_hparam function that allows you to change the init args that are saved in an iomixin object. This is useful for users who either want to initialize and lazily load configuration, or change configuration based on some other configuration in a way that you want to have saved for later as modified init args. This gives users a path to change a config object in code and save it, as well as have a config set some of it's parameters based on the contents of another config that it loads from a checkpoint, while also being savable itself into a new checkpoint with those modified parameters.
**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.
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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
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```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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Anyone in the community is free to review the PR once the checks have passed.
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The interface for megatron core distributed optimizer
# Changelog
- Support native fp8; fp8-param optimizer
- Support the overlap of param allgather with optimizer.step
- Support the alignment of param AllGather and grad ReduceScatter
# Usage
- Set `fp8_params` to enable fp8-param optimizer
- Set `optim.overlap_param_gather_with_optimizer_step` to enable the overlap of param AllGather with optim.step
- Set `optim align_grad_reduce` and `optim. align_param_gather` to align the data-parallel collectives across pipeline-parallel ranks
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# 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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The GitHub Actions CI will run automatically when the "Run CICD" label is added to the PR.
To re-run CI remove and add the label again.
To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".
# Before your PR is "Ready for review"
**Pre checks**:
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- [ ] Did you write any new necessary tests?
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**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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# Changelog
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# Usage
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```python
# Add a code snippet demonstrating how to use this
```
# GitHub Actions CI
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The GitHub Actions CI will run automatically when the "Run CICD" label is added to the PR.
To re-run CI remove and add the label again.
To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".
# Before your PR is "Ready for review"
**Pre checks**:
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- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
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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?
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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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"Hi @yangzhipeng1108, looking at the error, \r\n\r\n> ```\r\n> 2: File \"/usr/local/lib/python3.10/dist-packages/lightning_fabric/plugins/environments/torchelastic.py\", line 63, in world_size\r\n> 2: return int(os.environ[\"WORLD_SIZE\"])\r\n> 2: File \"/usr/lib/python3.10/os.py\", line 680, in getitem\r\n> 2: rai... | 2024-08-22T02:16:30 | 2024-10-04T01:58:56 | 2024-10-04T01:58:56 | NONE | {
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2: File "/workspace/NeMo/examples/nlp/language_modeling/tuning/megatron_gpt_finetuning.py", line 64, in main
2: model = MegatronGPTSFTModel.restore_from(cfg.model.restore_from_path, model_cfg, trainer=trainer)
2: File "/opt/NeMo/nemo/collections/nlp/models/nlp_model.py", line 465, in restore_from
2: return super().restore_from(
2: File "/opt/NeMo/nemo/core/classes/modelPT.py", line 464, in restore_from
2: instance = cls._save_restore_connector.restore_from(
2: File "/opt/NeMo/nemo/collections/nlp/parts/nlp_overrides.py", line 1122, in restore_from
2: loaded_params = super().load_config_and_state_dict(
2: File "/opt/NeMo/nemo/core/connectors/save_restore_connector.py", line 178, in load_config_and_state_dict
2: instance = calling_cls.from_config_dict(config=conf, trainer=trainer)
2: File "/opt/NeMo/nemo/core/classes/common.py", line 524, in from_config_dict
2: raise e
2: File "/opt/NeMo/nemo/core/classes/common.py", line 516, in from_config_dict
2: instance = cls(cfg=config, trainer=trainer)
2: File "/opt/NeMo/nemo/collections/nlp/models/language_modeling/megatron_gpt_sft_model.py", line 77, in init
2: super().init(cfg, trainer=trainer)
2: File "/opt/NeMo/nemo/collections/nlp/parts/mixins/nlp_adapter_mixins.py", line 79, in init
2: super().init(*args, **kwargs)
2: File "/opt/NeMo/nemo/collections/nlp/models/language_modeling/megatron_gpt_model.py", line 287, in init
2: super().init(cfg, trainer=trainer, no_lm_init=True)
2: File "/opt/NeMo/nemo/collections/nlp/models/language_modeling/megatron_base_model.py", line 175, in init
2: init_world_size = trainer.world_size
2: File "/usr/local/lib/python3.10/dist-packages/pytorch_lightning/trainer/trainer.py", line 1161, in world_size
2: return getattr(self.strategy, "world_size", 1)
2: File "/usr/local/lib/python3.10/dist-packages/pytorch_lightning/strategies/parallel.py", line 66, in world_size
2: return self.cluster_environment.world_size() if self.cluster_environment is not None else 1
2: File "/usr/local/lib/python3.10/dist-packages/lightning_fabric/plugins/environments/torchelastic.py", line 63, in world_size
2: return int(os.environ["WORLD_SIZE"])
2: File "/usr/lib/python3.10/os.py", line 680, in getitem
2: raise KeyError(key) from None
2: KeyError: 'WORLD_SIZE'
use slurm
#!/bin/bash
#SBATCH --exclusive --nodes=2 --mem=0 --overcommit --ntasks-per-node=8 --time=4:30:00 --job-name=multinode_sft_example
#Load necessary modules and set environment variables
export CUDA_DEVICE_MAX_CONNECTIONS=1
#Set model and training parameters
TRAIN_DS="[/workspace/data/databricks-dolly-15k/training.jsonl]"
VALID_DS="[/workspace/data/databricks-dolly-15k/validation.jsonl]"
TEST_DS="[/workspace/data/databricks-dolly-15k/test.jsonl]"
CKPT="/workspace/model_ckpts/llama2-7b.nemo"
TS=$(date +%s)
OUTPUT_PATH="/workspace/"
RESULTS_DIR="$OUTPUT_PATH/results_${TS}"
CONCAT_SAMPLING_PROBS="[1]"
TP_SIZE=1
PP_SIZE=1
BS=128
MAX_LEN=2048
#The NeMo command to run on each node.
run_cmd="python3 /workspace/NeMo/examples/nlp/language_modeling/tuning/megatron_gpt_finetuning.py
trainer.precision=bf16
trainer.devices=$SLURM_NTASKS_PER_NODE
trainer.num_nodes=$SLURM_JOB_NUM_NODES
trainer.val_check_interval=0.1
trainer.max_steps=50
model.restore_from_path=${CKPT}
model.micro_batch_size=1
model.global_batch_size=128
model.tensor_model_parallel_size=${TP_SIZE}
model.pipeline_model_parallel_size=${PP_SIZE}
model.megatron_amp_O2=True
model.activations_checkpoint_granularity=selective
model.activations_checkpoint_method=uniform
model.optim.name=distributed_fused_adam
model.optim.lr=5e-6
model.answer_only_loss=True
model.peft.peft_scheme=none
model.data.train_ds.file_names=${TRAIN_DS}
model.data.validation_ds.file_names=${VALID_DS}
model.data.test_ds.file_names=${TEST_DS}
model.data.train_ds.concat_sampling_probabilities=${CONCAT_SAMPLING_PROBS}
model.data.train_ds.max_seq_length=2048
model.data.validation_ds.max_seq_length=2048
model.data.train_ds.micro_batch_size=1
model.data.train_ds.global_batch_size=128
model.data.validation_ds.micro_batch_size=1
model.data.validation_ds.global_batch_size=128
model.data.test_ds.micro_batch_size=1
model.data.test_ds.global_batch_size=256
model.data.train_ds.num_workers=0
model.data.validation_ds.num_workers=0
model.data.test_ds.num_workers=0
model.data.validation_ds.metric.name=loss
model.data.test_ds.metric.name=loss
exp_manager.create_wandb_logger=False
exp_manager.explicit_log_dir=/workspace/results
exp_manager.resume_if_exists=True
exp_manager.resume_ignore_no_checkpoint=True
exp_manager.create_checkpoint_callback=True
exp_manager.checkpoint_callback_params.monitor=validation_loss
exp_manager.checkpoint_callback_params.save_best_model=False
exp_manager.checkpoint_callback_params.save_nemo_on_train_end=True
++cluster_type=BCP"
#Container
CONT=/root/nvcr.io+nvidia+nemo+24.06.sqsh
CONT_NAME=nemofw-training
CONT_MOUNT=/root/yovole:/workspace,/dev/infiniband:/dev/infiniband
#run on SLURM
srun -l
--ntasks-per-node=8
--container-name="${CONT_NAME}"
--container-image="${CONT}"
--container-mounts="${CONT_MOUNT}"
--container-entrypoint
--no-container-mount-home
bash -c "${run_cmd}"
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"@jbieniusiewi could you also add the same check for 2.0. The unfinished checkpoint filtering is [here](https://github.com/NVIDIA/NeMo/blob/main/nemo/lightning/resume.py#L112-L113) in 2.0.",
"Thank you for the review @maanug-nv. \r\nI've added checks for NeMo 2.0. One more approval is needed to merge it, so I re-... | 2024-08-22T00:22:30 | 2024-08-29T17:58:40 | 2024-08-29T17:58:38 | COLLABORATOR | {
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} | # What does this PR do ?
The following scenario was recently observed:
- Last checkpoint writing was interrupted due to an irrelevant issue
- Hence last checkpoint was marked as "unfinished" (and there was no other last checkpoint)
- Hence the following training silently skipped the last checkpoint and started from scratch
- As a result, training was not making expected progress despite many training runs
This PR adds some sanity checks to ensure that when the last/end checkpoint is unfinished, it wont get silently skipped and deleted. Instead, user is supposed to remove them manually.
**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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} | 🚀 PR to Bump `Dockerfile.ci`.
📝 Please remember the following to-do's before merge:
- [ ] Verify the presubmit CI
🙏 Please merge this PR only if the CI workflow completed successfully. | {
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# 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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## Who can review?
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Add a one line overview of what this PR aims to accomplish.
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# Changelog
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# Usage
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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.
## 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
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The GitHub Actions CI will run automatically when the "Run CICD" label is added to the PR.
To re-run CI remove and add the label again.
To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
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- [ ] 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 ?
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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} | # What does this PR do ?
24.07 perf numbers for experiments using vboost
**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
```
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If you haven't finished some of the above items you can still open "Draft" PR.
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"Thank you for the bug report. We're still working on a patch.",
"Hi,\r\n\r\nthis issue is fixed in our dev nightly container:\r\n[nvcr.io/nvidian/nemo:nightly](http://nvcr.io/nvidian/nemo:nightly)"
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} | null | null | null | **Describe the bug**
In version 24.05, the training continuation process was working smoothly. However, after upgrading to version 24.07, when resuming after a pause, the loss value spikes significantly.
This seems to be a highly critical issue that needs investigation. The problem occurs consistently, regardless of the model size or data, and resuming training is failing 100% of the time.
**Steps/Code to reproduce bug**
1. Perform llama 7b **pretraining** with a mock dataset
2. Save some checkpoints
3. Resume from the saved checkpoint
4. Loss spikes
**Expected behavior**
working normally
**Environment overview (please complete the following information)**
- using 24.07 docker container
- H100 | {
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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**:
- [ ] 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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📝 Please remember the following to-do's before merge:
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# Usage
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# Add a code snippet demonstrating how to use this
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# GitHub Actions CI
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# Before your PR is "Ready for review"
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**PR Type**:
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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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```python
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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?
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- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
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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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# Usage
* You can potentially add a usage example below
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# 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".
# Before your PR is "Ready for review"
**Pre checks**:
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- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**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?
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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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The goal is to avoid importing all tokenization libraries when the user will only use one.
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# Changelog
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```python
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## 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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# Changelog
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# Usage
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```python
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The GitHub Actions CI will run automatically when the "Run CICD" label is added to the PR.
To re-run CI remove and add the label again.
To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".
# Before your PR is "Ready for review"
**Pre checks**:
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- [ ] Did you write any new necessary tests?
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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
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## 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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This PR removes the attention mask generation to prevent CPU from running out of memory issue when using SFT chat dataset.
# 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".
**PR Type**:
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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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"LGTM! Besides a few docstrings and getter apis. Approving."
] | 2024-08-19T23:02:00 | 2024-09-06T05:14:40 | 2024-09-06T05:14:38 | CONTRIBUTOR | {
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} | # What does this PR do ?
Turns on various communication/compute overlap optimizations:
- Pipeline parallel overlap, data parallel overlap is well supported and this PR turns it on by default when available
- Tensor parallel overlap is not officially productized in TE, so its not guaranteed to work on all clusters. So it is disabled by default. It can be turned on by setting the `NEMO_ENABLE_TP_COMM_OVERLAP` environment variable.
Currently TP overlap only supports dense models, so Ive only added a TP overlap config for LLAMA70B, and can add more as more model recipes are added.
- Wgrad deferral, which overlaps wgrads over the pipeline bubble, has to be tuned per model, so this defaults false.
I tested the full 70b, 8b performance recipes using NeMo-Run as saw no differences to the loss, but a ~10% improvement in performance.
**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.
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# 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?
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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
* You can potentially add a usage example below
```python
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To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".
# Before your PR is "Ready for review"
**Pre checks**:
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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.
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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
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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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The GitHub Actions CI will run automatically when the "Run CICD" label is added to the PR.
To re-run CI remove and add the label again.
To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".
# Before your PR is "Ready for review"
**Pre checks**:
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- [ ] Did you write any new necessary tests?
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**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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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**:
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- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
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- [ ] New Feature
- [x] Bugfix
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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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```python
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"@ShriyaPalsamudram It seems a recent commit has changed that implementation, this PR... | 2024-08-19T17:30:59 | 2024-08-20T05:57:36 | 2024-08-20T05:57:34 | COLLABORATOR | {
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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
# Add a code snippet demonstrating how to use this
```
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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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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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"This PR is stale because it has been open for 14 days with no activity. Remove stale label or comment or update or this will be closed in 7 days.",
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**Collection**: [llm]
# Changelog
```
class DeltaTimingCallback(Callback):
```
# Usage
```python
import nemo_run as run
from nemo.utils.exp_manager import DeltaTimingCallback
from nemo.collections.llm.recipes.llama3_8b import pretrain_recipe
pretrain_recipe.trainer.callbacks.append(run.Config(DeltaTimingCallback))
```
# GitHub Actions CI
The Jenkins CI system has been replaced by GitHub Actions self-hosted runners.
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**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
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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.
## 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
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The GitHub Actions CI will run automatically when the "Run CICD" label is added to the PR.
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## Who can review?
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"This PR is stale because it has been open for 14 days with no activity. Remove stale label or comment or update or this will be closed in 7 days.",
"Looks good to me. ",
"Approving MR as review from Marcin is complete."
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} | # What does this PR do ?
1. Adds a feature similar to mcore's --skip-train flag.
3. Adds drop-layers feature support.
4. Adds script which loads the ckpt, trims needed layers, and saves trimmed checkpoint.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* Trim the model. Please, note that layer indices start from 1. Llama3 8b model example:
```ubuntu
python -m torch.distributed.launch --nproc_per_node=8 \
NeMo/examples/nlp/language_modeling/megatron_gpt_drop_layers.py \
--path_to_nemo /path/to/model.nemo \
--path_to_save /path/to/save/trimmed_model.nemo \
--tensor_model_parallel_size 8 \
--pipeline_model_parallel_size 1 \
--gpus_per_node 8 \
--drop_layers 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
```
If you want to save trimmed model in zarr ckpt format (deprecated), add this flag to the command:
```ubuntu
--zarr
```
* Validate the model:
```ubuntu
python NeMo/examples/nlp/language_modeling/megatron_gpt_pretraining.py \
--config-path=/path/to/folder/with/model/config \
--config-name=llama3_8b.yaml \
trainer.limit_val_batches=number_of_batches_in_validation_step \
model.restore_from_path=/path/to/trimmed_model.nemo \
model.skip_train=True \
model.data.data_impl=mock \
model.data.data_prefix=[]
```
To use specific dataset instead of mock dataset:
```ubuntu
model.data.data_impl=mmap \
model.data.data_prefix=["path/to/datafile1", "path/to/datafile2"]
```
* Validate Original Model
To validate the original model without specific layers, use the following script:
```ubuntu
python /NeMo/examples/nlp/language_modeling/megatron_gpt_pretraining.py \
--config-path=/path/to/folder/with/model/config \
--config-name=llama3_8b.yaml \
trainer.limit_val_batches=<limit_val_batches> \
model.restore_from_path=/path/to/original_model.nemo \
model.skip_train=True \
model.data.data_impl=mock \
model.data.data_prefix=[] \
model.drop_layers=[16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31]
```
# 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**:
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**PR Type**:
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- [ ] Bugfix
- [ ] Documentation
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## Who can review?
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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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} | # What does this PR do ?
Fix https://github.com/NVIDIA/NeMo/issues/10060
**Collection**: ASR
# Changelog
- Improved test coverage for LazyNeMoIterator and fix for a case with `metadata_only=True` and offsets in manifest
# 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
- [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.
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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
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# Usage
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```python
# Add a code snippet demonstrating how to use this
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Fix formatting mistake in the ModelOpt Distillation documentation
**Collection**: NLP
# Changelog
- Indent code block in `docs/source/nlp/distillation.rst`
# Usage
N/A
# GitHub Actions CI
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**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [x] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
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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
* 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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Log (TFLOPs / sec) per gpu per step
**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"
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- [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.
## 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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📝 Please remember the following to-do's before merge:
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"@aimarz can you post a reproducer and the whole log?",
"Yes, this seems similar to what I've observed on 15B / 24.07. I've noticed that locally, a 15B/TP4 checkpointing (checkpoint size is 205GB) reserves 70GB of process memory and 290GB of CPU/buffered disk IO memory (360GB total). And when the run continues,... | 2024-08-18T09:00:49 | 2024-10-15T01:59:37 | 2024-10-15T01:59:36 | NONE | {
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The training works well when using the 24.05 version and the exact same configuration. So I don't understand why this is happening. I would appreciate some help on this matter.
These are the system specifications (I use 8 nodes for training):
- 2x Intel Xeon Platinum 8460Y+ 40C 2.3GHz (80 cores per node)
- 4x NVIDIA Hopper H100 64GB HBM2
- 16x DIMM 32GB 4800MHz DDR5 (512GB main memory per node)
And this is the error I get in SLURM:
srun: error: as01r3b17: task 3: Out Of Memory
srun: Terminating StepId=4777403.0
slurmstepd: error: *** STEP 4777403.0 ON as01r3b17 CANCELLED AT 2024-08-16T19:36:54 ***
slurmstepd: error: Detected 1 oom_kill event in StepId=4777403.0. Some of the step tasks have been OOM Killed.
/usr/lib/python3.10/multiprocessing/resource_tracker.py:224: UserWarning: resource_tracker: There appear to be 23 leaked semaphore objects to clean up at shutdown
warnings.warn('resource_tracker: There appear to be %d '
/usr/lib/python3.10/multiprocessing/resource_tracker.py:224: UserWarning: resource_tracker: There appear to be 23 leaked semaphore objects to clean up at shutdown
warnings.warn('resource_tracker: There appear to be %d '
slurmstepd: error: Detected 1 oom_kill event in StepId=4777403.0. Some of the step tasks have been OOM Killed. | {
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📝 Please remember the following to-do's before merge:
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"closing since already addressed in https://github.com/NVIDIA/NeMo/pull/10204 "
] | 2024-08-17T05:09:49 | 2024-08-20T18:48:03 | 2024-08-20T18:48:02 | MEMBER | {
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related
https://github.com/NVIDIA/NeMo/commit/98a0a53ca656e5ceb26ebb224c009fe8b6d4d95c#diff-5b6e58d7bd57dd9253e0fcc5cc1fe788cbb560e021b4d5b9240af46404fed61eR138
**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)
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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.
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📝 Please remember the following to-do's before merge:
- [ ] Verify the presubmit CI
🙏 Please merge this PR only if the CI workflow completed successfully. | {
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Fix parallelism reset bug with reinit in VP.
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} | # What does this PR do ?
Adding a tutorial with examples of using audio codec for inference: generating reconstructed audio, computing discrete tokens, and computing latent representation.
**Collection**: TTS
# Changelog
- Added a tutorial notebook
- Tested locally and on Google Collab
# Usage
N/A
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"This PR is stale because it has been open for 14 days with no activity. Remove stale label or comment or update or this will be closed in 7 days.",
"This PR was closed because it has been inactive for 7 days since being marked as stale."
] | 2024-08-16T19:26:33 | 2024-09-08T01:58:41 | 2024-09-08T01:58:40 | CONTRIBUTOR | {
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} | # What does this PR do ?
`CosineAnnealing` LR with linear warmup and `constant_steps` is `0` on the first step. This causes issues for AdamW optimizer which uses LR for `step_size` in the denominator. This is due to the fact on first step when this method is called `step=0` before the first optimizer step is complete.
Using the same protection as in:
* https://github.com/NVIDIA/NeMo/blob/d2f3f49aea7b282816063dad5ff2f2c3eedfc6cf/nemo/core/optim/lr_scheduler.py#L81
* https://github.com/NVIDIA/NeMo/blob/d2f3f49aea7b282816063dad5ff2f2c3eedfc6cf/nemo/core/optim/lr_scheduler.py#L315
* https://github.com/NVIDIA/NeMo/blob/d2f3f49aea7b282816063dad5ff2f2c3eedfc6cf/nemo/core/optim/lr_scheduler.py#L611
Updated unit tests not to tolerate LR=0.
**Collection**: [Note which collection this PR will affect]
Core
# Changelog
- fix cosine annealing linear warmup LR
# 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)
- [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**:
- [ ] New Feature
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"Hi @SkanderBS2024, I see you are mounting. You are not using the NeMo container `nvcr.io/nvidia/nemo:24.07`, and you are mounting the NeMo. I tested the conversion script in the `nvcr.io/nvidia/nemo:24.07`, and it works fine. However, there is an update needed for the latest main, for which I have raised a PR. ht... | 2024-08-16T13:17:42 | 2024-09-28T01:57:59 | 2024-09-28T01:57:58 | NONE | {
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} | null | null | null | **Describe the bug**
As described in the title, after finishing all of the installs and building nemo and megatron-lm from source, assuming that the model has been trained with megatron-lm.
**Steps/Code to reproduce bug**
```python
[NeMo W 2024-08-16 12:43:58 nemo_logging:349] /workspace/megatron/Megatron-LM/megatron/core/tensor_parallel/layers.py:280: FutureWarning: `torch.cuda.amp.custom_fwd(args...)` is deprecated. Please use `torch.amp.custom_fwd(args..., device_type='cuda')` instead.
def forward(ctx, input, weight, bias, allreduce_dgrad):
[NeMo W 2024-08-16 12:43:58 nemo_logging:349] /workspace/megatron/Megatron-LM/megatron/core/tensor_parallel/layers.py:290: FutureWarning: `torch.cuda.amp.custom_bwd(args...)` is deprecated. Please use `torch.amp.custom_bwd(args..., device_type='cuda')` instead.
def backward(ctx, grad_output):
[NeMo W 2024-08-16 12:43:58 nemo_logging:349] /workspace/megatron/Megatron-LM/megatron/core/tensor_parallel/layers.py:380: FutureWarning: `torch.cuda.amp.custom_fwd(args...)` is deprecated. Please use `torch.amp.custom_fwd(args..., device_type='cuda')` instead.
def forward(
[NeMo W 2024-08-16 12:43:58 nemo_logging:349] /workspace/megatron/Megatron-LM/megatron/core/tensor_parallel/layers.py:419: FutureWarning: `torch.cuda.amp.custom_bwd(args...)` is deprecated. Please use `torch.amp.custom_bwd(args..., device_type='cuda')` instead.
def backward(ctx, grad_output):
[WARNING | megatron.core.dist_checkpointing.strategies.zarr]: `zarr` distributed checkpoint backend is deprecated. Please switch to PyTorch Distributed format (`torch_dist`).
[NeMo W 2024-08-16 12:43:59 nemo_logging:349] /workspace/megatron/Megatron-LM/megatron/core/dist_checkpointing/strategies/torch.py:22: DeprecationWarning: `torch.distributed._sharded_tensor` will be deprecated, use `torch.distributed._shard.sharded_tensor` instead
from torch.distributed._sharded_tensor import ShardedTensor as TorchShardedTensor
[NeMo W 2024-08-16 12:43:59 nemo_logging:349] /usr/local/lib/python3.10/dist-packages/modelopt/torch/quantization/tensor_quant.py:84: FutureWarning: `torch.library.impl_abstract` was renamed to `torch.library.register_fake`. Please use that instead; we will remove `torch.library.impl_abstract` in a future version of PyTorch.
scaled_e4m3_abstract = torch.library.impl_abstract("trt::quantize_fp8")(
[NeMo W 2024-08-16 12:44:02 nemo_logging:349] /usr/local/lib/python3.10/dist-packages/mamba_ssm/ops/selective_scan_interface.py:164: FutureWarning: `torch.cuda.amp.custom_fwd(args...)` is deprecated. Please use `torch.amp.custom_fwd(args..., device_type='cuda')` instead.
def forward(ctx, xz, conv1d_weight, conv1d_bias, x_proj_weight, delta_proj_weight,
[NeMo W 2024-08-16 12:44:02 nemo_logging:349] /usr/local/lib/python3.10/dist-packages/mamba_ssm/ops/selective_scan_interface.py:240: FutureWarning: `torch.cuda.amp.custom_bwd(args...)` is deprecated. Please use `torch.amp.custom_bwd(args..., device_type='cuda')` instead.
def backward(ctx, dout):
[NeMo W 2024-08-16 12:44:02 nemo_logging:349] /usr/local/lib/python3.10/dist-packages/mamba_ssm/ops/triton/layer_norm.py:959: FutureWarning: `torch.cuda.amp.custom_fwd(args...)` is deprecated. Please use `torch.amp.custom_fwd(args..., device_type='cuda')` instead.
def forward(
[NeMo W 2024-08-16 12:44:02 nemo_logging:349] /usr/local/lib/python3.10/dist-packages/mamba_ssm/ops/triton/layer_norm.py:1018: FutureWarning: `torch.cuda.amp.custom_bwd(args...)` is deprecated. Please use `torch.amp.custom_bwd(args..., device_type='cuda')` instead.
def backward(ctx, dout, *args):
[NeMo W 2024-08-16 12:44:02 nemo_logging:349] /usr/local/lib/python3.10/dist-packages/mamba_ssm/distributed/tensor_parallel.py:26: FutureWarning: `torch.cuda.amp.custom_fwd(args...)` is deprecated. Please use `torch.amp.custom_fwd(args..., device_type='cuda')` instead.
def forward(ctx, x, weight, bias, process_group=None, sequence_parallel=True):
[NeMo W 2024-08-16 12:44:02 nemo_logging:349] /usr/local/lib/python3.10/dist-packages/mamba_ssm/distributed/tensor_parallel.py:62: FutureWarning: `torch.cuda.amp.custom_bwd(args...)` is deprecated. Please use `torch.amp.custom_bwd(args..., device_type='cuda')` instead.
def backward(ctx, grad_output):
[NeMo W 2024-08-16 12:44:03 nemo_logging:349] /usr/local/lib/python3.10/dist-packages/mamba_ssm/ops/triton/ssd_combined.py:736: FutureWarning: `torch.cuda.amp.custom_fwd(args...)` is deprecated. Please use `torch.amp.custom_fwd(args..., device_type='cuda')` instead.
def forward(ctx, zxbcdt, conv1d_weight, conv1d_bias, dt_bias, A, D, chunk_size, initial_states=None, seq_idx=None, dt_limit=(0.0, float("inf")), return_final_states=False, activation="silu",
[NeMo W 2024-08-16 12:44:03 nemo_logging:349] /usr/local/lib/python3.10/dist-packages/mamba_ssm/ops/triton/ssd_combined.py:814: FutureWarning: `torch.cuda.amp.custom_bwd(args...)` is deprecated. Please use `torch.amp.custom_bwd(args..., device_type='cuda')` instead.
def backward(ctx, dout, *args):
Traceback (most recent call last):
File "/workspace/nemo/NeMo/scripts/checkpoint_converters/convert_mamba2_pyt_to_nemo.py", line 190, in <module>
convert(args)
File "/workspace/nemo/NeMo/scripts/checkpoint_converters/convert_mamba2_pyt_to_nemo.py", line 115, in convert
num_layers = max(layer_numbers) + 1'
```
**Expected behavior**
Expected to convert the mamba trained model to a .nemo format for fine-tuning.
**Environment overview (please complete the following information)**
- Environment location: ubuntu, Docker, fluidstack VM 2 * A100 80.
- Method of NeMo install: Installed from source and integrated megatron from source.
- If method of install is [Docker], provide `docker pull` & `docker run` commands used :
Docker pull command :
```bash
sudo docker pull nvcr.io/nvidia/pytorch:24.07-py3
```
Docker Run command :
```bash
docker run --gpus all -it --rm --ipc=host \
--shm-size=40g \
-v /ephemeral/megatron:/workspace/megatron \
-v /ephemeral/data:/workspace/dataset/data \
-v /ephemeral/outfix:/workspace/dataset/outfix \
-v /ephemeral/tok:/workspace/dataset/tok \
-v /ephemeral/checkpoints:/workspace/checkpoints \
-v /ephemeral/nemo:/workspace/nemo \
nvcr.io/nvidia/pytorch:24.07-py3
```
**Environment details**
If NVIDIA docker image is used you don't need to specify these.
Otherwise, please provide:
- OS version : Ubuntu 22.04.3 LTS
- PyTorch version : 2.4
- Python version : 3.10.12
**Additional context**
Nvidia pytorch container : 24.07 (assmuming training was made with 24.03)
GPUS : 2 * GPU A100 80
Followed steps here : tutorials/llm/mamba/mamba.rst
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**Collection**: ASR
# Changelog
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# Usage
NA
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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?
@titu1994
# Additional Information
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"Sorry, we didn't reply to your comment, but we did read it.\r\n\r\nWe don't plan to make updates to FSDP for NeMo 1.0 but NeMo 2.0 FSDP support will continue to be maintained.\r\n\r\nI'm going to go close this issue, if there's a specific bug or feature request with NeMo 2.0 + FSDP please file a new issue with det... | 2024-08-16T08:49:16 | 2024-08-22T07:07:59 | 2024-08-21T17:30:40 | CONTRIBUTOR | {
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} | null | null | null | Since it seems like [my comment in the FSDP PR for NeMo 2.0](https://github.com/NVIDIA/NeMo/pull/9748#issuecomment-2268403302) was missed in the activities of code reviews, I wrote this issue to raise visibility for the current problems with FSDP integration in NeMo.
To summarize the original comment, FSDP support is really not well-integrated across the code base. Many scripts do not work with it because they only implement `NLPDDPStrategy`, checkpoint conversion was a huge undertaking to get working (PR pending), and some feature flags straight-up [don't work](https://github.com/NVIDIA/NeMo/issues/9531) or [had bugs](https://github.com/NVIDIA/NeMo/pull/9335).
The original reason for the comment was desiring a better integration in NeMo 2.X since FSDP actually achieves better performance with default settings compared to 4D parallelism. There is also desire to help with this; however, because of past/current experiences with PRs getting ignored, my motivation to fix things in this public code without prior discussion is highly limited. I don't want to have to post redundant comments to even more PRs to prevent them from getting closed as "stale due to no activity". | {
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"Dido is busy with other stuff, I made some modification on top of her changes.\r\nHere is the new PR: https://github.com/NVIDIA/NeMo/pull/10288, please review there, than... | 2024-08-16T07:19:42 | 2024-08-29T01:25:14 | 2024-08-29T01:25:14 | NONE | {
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"Can we rebase this to the TOT?",
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# Before your PR is "Ready for review"
**Pre checks**:
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"The fix from #8884 worked for me. See [this commit](https://github.com/aklemen/NeMo/commit/69fa4bb7cd42d135d1925ea632cc4745840013e3).\r\n\r\nBut I am using `decoding_strategy=\"beam\"` and without KenLM.",
"> The fix from #8884 worked for me. See [this commit](https://github.com/aklemen/NeMo/commit/69fa4bb7cd42d... | 2024-08-16T02:18:11 | 2024-11-20T02:01:34 | 2024-11-20T02:01:29 | NONE | {
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} | null | null | null | Unable to use KenLM rescore due to missing logprobs on transcribe.
**Steps/Code to reproduce the bug**
1. Cloned the repo [7916269](https://github.com/NVIDIA/NeMo/commit/79162696ea8c48734a260dd2dfd6e60602d73a22).
2. Used script `scripts/asr_language_modeling/ngram_lm/eval_beamsearch_ngram_ctc.py`.
It throws the following error: `TypeError: EncDecCTCModel.transcribe() got an unexpected keyword argument 'logprobs'`.
3. Applied the change suggested on https://github.com/NVIDIA/NeMo/issues/8884#issuecomment-2049063944.
```python
Logits_hyps = asr_model.transcribe(
self.audio_file_list, batch_size=self.asr_batch_size, return_hypotheses=True
) # type: List[nemo_asr.parts.Hypothesis]
Logits = [hyp.alignments for hyp in Logits_hyps]
```
With this change, a new error occurs:
```
[NeMo I 2024-08-13 19:24:30 ctc_decoding:359] Beam search requires that consecutive CTC tokens are not folded.
Overriding provided value of `fold_consecutive` = True to False
Segmentation fault (core dumped)
```
4. I thought it was KenLM failing, so I applied this fix: https://github.com/flashlight/wav2letter/issues/875, but it did not work.
I've searched more in the docs, PR, and comments and discovered the karpnv/beamsearch branch from https://github.com/NVIDIA/NeMo/pull/8428. Using the beamsearch branch, I'm still unable to search for alpha and beta values.
The command:
```bash
python eval_beamsearch_ngram_ctc.py \
model_path=/media/carlos/asr/Conformer-CTC-BPE.nemo \
dataset_manifest=/media/carlos/asr/asr/supervised/test-files/test-all.json \
preds_output_folder=preds/ \
cache_file=null \
ctc_decoding.beam.kenlm_path=/media/carlos/asr/conformerlm3.binary \
ctc_decoding.beam.flashlight_cfg.lexicon_path=/media/carlos/asr/conformerlm3.binary.tmp.lexicon \
ctc_decoding.beam.beam_size=[100,200,500] \
ctc_decoding.beam.beam_alpha=[1,2,3,4] \
ctc_decoding.beam.beam_beta=[1,2,3,4] \
ctc_decoding.strategy=flashlight
```
Shows this error:
```
raise NotImplementedError("Wrong parameter combination")
NotImplementedError: Wrong parameter combination
```
¿Any updated guide or help? It will be greatly appreciated. I can provide any extra details if needed.
**Expected behavior**
Being able to search alpha and beta using the generated KenLM. We need those values to use RIVA.
**Environment overview (please complete the following information)**
- **Environment location**: Bare-metal
- **Method of NeMo install**: From source using `./reinstall.sh`
**Environment details**
- **OS version**: Ubuntu 22.04.3 LTS
- **PyTorch version**: 2.4.0+cu121
- **Python version**: 3.10.12
**Additional context**
- **GPU model**: Nvidia A100 | {
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# Changelog
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# Usage
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```python
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} | # What does this PR do ?
Fix doc feature section warnings
**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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# Before your PR is "Ready for review"
**Pre checks**:
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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?
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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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**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
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If you haven't finished some of the above items you can still open "Draft" PR.
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Fixing rope config defaults.
**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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**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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