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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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# Changelog
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```python
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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?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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**Collection**: [Note which collection this PR will affect]
# 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.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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**Collection**: [Note which collection this PR will affect]
# 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 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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- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
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- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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**Collection**: [Note which collection this PR will affect]
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```python
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# Changelog
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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:
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Add a one line overview of what this PR aims to accomplish.
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# Usage
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# GitHub Actions CI
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# Before your PR is "Ready for review"
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If you haven't finished some of the above items you can still open "Draft" PR.
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[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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"Updated per above suggestions, and changed the image source, please check again"
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} | # What does this PR do ?
This PR aims to update Nemo distributed checkpoint user guide documentation, with best practices for parameter tuning, mechanism, FAQs, etc.
**Collection**: [Note which collection this PR will affect]
Distributed checkpoint.
# Changelog
- Update dist_ckpt.rst documentation in Nemo GitHub
- Update Introduction
- Add Mechanism with images
- Add Parameter Tuning Best Practices
- Add FAQs
- Add Glossary
# GitHub Actions CI
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# Before your PR is "Ready for 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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* Enabling detecting `model_type` for NeMo 2.0 checkpoints based on their **model.yaml** config
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* Deprecating `n_gpus`, `max_input_token`, and `max_output_token` in `TensorRTLLM.export(...)`
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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.
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To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
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**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
# Additional Information
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**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
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```python
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```
# 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.
# Additional Information
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} | # What does this PR do ?
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"root cause was due to usage of https://github.com/NVIDIA/NeMo/blob/9a268dd6cec33e0e7190cf9e1543e6473c32da2c/nemo/collections/nlp/data/language_modeling/megatron/data_samplers.py#L131\n\ninstead of the data samplers defined in https://github.com/NVIDIA/NeMo/blob/main/nemo/lightning/data.py"
] | 2024-12-05T12:20:05 | 2024-12-06T02:56:11 | 2024-12-06T02:56:10 | CONTRIBUTOR | {
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} | null | null | null | **Describe the bug**
NeMo has some custom logic to resume the dataloader state with Megatron-LM custom Batch sampler based on consumed samples and microbatches calculated by mcore.
But it does not seem to account for how Lightning itself attempts to restore the data fetcher state for within the training epoch loop.
This results in a previous state from a checkpoint being accounted for in the dataloader / data fetcher iterator, and can cause StopIteration to be raised early before reaching the expected max_steps
**Steps/Code to reproduce bug**
For example, if my initial training run setup is as follows
```
trainer:
accelerator: gpu
devices: 1
num_nodes: 1
max_epochs: 1
max_steps: 1000
limit_val_batches: 2
num_sanity_val_steps: 2
data:
micro_batch_size: 1
global_batch_size: 8
```
My data module should prepare max_steps * gbs = 1000 * 8 = 8000 samples total
I save a checkpoint at step 799, which has consumed 800 * gbz = 800 * 8 = 6400 samples
When I resume from checkpoint saved at step 799, it results in something like:
```
[NeMo I data_samplers:76] Instantiating MegatronPretrainingSampler with total_samples: 8040 and consumed_samples: 6400
```
With 200 steps remaining before 1,000 max_steps, I should expect to have 200 * 8 = 1600 samples remaining which must get loaded by the resumed dataloader.
However, pytorch lightning has the following logic in the TrainingEpochLoop
```
def on_run_start(self, data_fetcher: _DataFetcher) -> None:
...
# add the previous `fetched` value to properly track `is_last_batch` with no prefetching
data_fetcher.fetched += self.batch_progress.current.ready
...
```
As a result, this is the state of the lightning data fetcher:
```
{
'_batch': None,
'_batch_idx': 0,
'_dataloader_idx': 0,
'done': False,
'fetched': 798,
'iterator': < pytorch_lightning.utilities.combined_loader.CombinedLoader object at 0x7fc9240ebeb0 > ,
'iterator_wrapper': < pytorch_lightning.loops.fetchers._DataFetcherWrapper object at 0x7fc92410b730 > ,
'length': 1640
}
```
The internal pytorch lightning tracked attributed `_batch_idx` and `fetched` are not synced, which results in a StopIteration being raised early when the following condition is met:
```
class _DataFetcher(Iterator):
@override
def __next__(self) -> _ITERATOR_RETURN:
....
self.fetched += 1
if self.length is not None:
self.done = self.fetched >= self.length <---------------
return batch
class _DataLoaderIterDataFetcher(_DataFetcher):
@override
def __next__(self) -> Iterator["_DataFetcherWrapper"]: # type: ignore[override]
if self.done: <---------------
raise StopIteration
return self.iterator_wrapper
```
If trainer.max_epochs == 1, then training stops immediately before the expected 1000 steps. If unset, then it jumps to epoch 1 unexpectedly:
```
...
[0]:Training epoch 0, iteration 901/999 | global_batch_size: 8 | val_loss: 9.243 | lr: 3e-06 | consumed_samples: 7216 | global_step: 901 | reduced_train_loss: 9.531 | train_step_timing in s: 0.4671
[0]:Training epoch 0, iteration 902/999 | global_batch_size: 8 | val_loss: 9.243 | lr: 3e-06 | consumed_samples: 7224 | global_step: 902 | reduced_train_loss: 9.362 | train_step_timing in s: 0.3907
[0]:Training epoch 0, iteration 903/999 | global_batch_size: 8 | val_loss: 9.243 | lr: 3e-06 | consumed_samples: 7232 | global_step: 903 | reduced_train_loss: 9.038 | train_step_timing in s: 0.4661
[0]:`Trainer.fit` stopped: `max_epochs=1` reached.
```
**Expected behavior**
Instead, we expect to see the full 1000k steps completed when we resume from a checkpoint in the middle of an epoch:
```
...
[0]:Training epoch 0, iteration 997/999 | global_batch_size: 8 | val_loss: 9.243 | lr: 3e-06 | consumed_samples: 7984 | global_step: 997 | reduced_train_loss: 9.112 | train_step_timing in s: 0.4716
[0]:Training epoch 0, iteration 998/999 | global_batch_size: 8 | val_loss: 9.243 | lr: 3e-06 | consumed_samples: 7992 | global_step: 998 | reduced_train_loss: 9.261 | train_step_timing in s: 0.4639
[0]:Training epoch 0, iteration 999/999 | global_batch_size: 8 | val_loss: 9.243 | lr: 3e-06 | consumed_samples: 8000 | global_step: 999 | reduced_train_loss: 9.092 | train_step_timing in s: 0.4736
[0]:`Trainer.fit` stopped: `max_steps=1000` reached.
```
A simple fix to get the expected behavior above is:
```
class CustomTrainingLoop(_TrainingEpochLoop):
def on_run_start(self, data_fetcher: _DataFetcher) -> None:
super().on_run_start(data_fetcher)
data_fetcher.fetched = 0
def configure_custom_training_loop(trainer: pl.Trainer) -> None:
if type(trainer.fit_loop.epoch_loop) is not _TrainingEpochLoop:
print("Detected custom epoch loop. Skipping customizing training loop.", UserWarning)
return
loop = CustomTrainingLoop(trainer, trainer.min_steps, trainer.max_steps)
trainer.fit_loop.epoch_loop = loop
```
Alternatively, we could also modify the logic in BaseMegatronSampler (nemo/collections/nlp/data/language_modeling/megatron/data_samplers.py) to return the total samples, but this could likely cause issues with NeMo1.
```
def __len__(self):
num_available_samples: int = self.total_samples - self.consumed_samples
if self.global_batch_size is not None:
if self.drop_last:
num_global_batches = num_available_samples // self.global_batch_size
else:
num_global_batches = (num_available_samples + self.global_batch_size - 1) // self.global_batch_size
# return len of dataloader in terms of micro batches to avoid discrepancy between len of dataloader and
# num of batches fetched (as training step fetches in terms of micro batches)
return num_global_batches * (self.global_batch_size // self.micro_batch_times_data_parallel_size)
else:
return (num_available_samples - 1) // self.micro_batch_times_data_parallel_size + 1
```
**Environment**
```
pytorch-lightning 2.4.0
nemo-toolkit 2.1.0rc0
megatron-core 0.10.0rc0
```
**Additional context**
relevant: https://github.com/Lightning-AI/pytorch-lightning/issues/19764
Add any other context about the problem here.
Example: GPU model
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"This issue is stale because it has been open for 30 days with no activity. Remove stale label or comment or this will be closed in 7 days.",
"This issue was closed because it has been inactive for 7 days since being marked as stale."
] | 2024-12-05T11:34:45 | 2025-01-12T02:04:16 | 2025-01-12T02:04:16 | NONE | {
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} | null | null | null | **Describe the bug**
Unable to run the hello world script `nemo llm pretrain --factory llama3_8b` like in the documentation https://github.com/NVIDIA/NeMo/blob/main/examples/llm/pretrain/README.md
I get:
```
[rank0]: File "/opt/megatron-lm/megatron/core/parallel_state.py", line 532, in initialize_model_parallel
[rank0]: raise RuntimeError(f"world_size ({world_size}) is not divisible by {total_model_size}")
[rank0]: RuntimeError: world_size (1) is not divisible by 2
```
**Steps/Code to reproduce bug**
`srun -p batch -N 1 --container-image nvcr.io/nvidia/nemo:24.09 --pty bash`
The machine has 8 gpu according to nvidia-smi
`run nemo llm pretrain --factory llama3_8b`
**Expected behavior**
I would expect it to run seamlessly
**Environment overview (please complete the following information)**
`srun -p batch -N 1 --container-image nvcr.io/nvidia/nemo:24.09 --pty bash`
The machine has 8 gpu according to nvidia-smi
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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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} | [] | open | false | null | [] | null | [
"same problem with llama3.1",
"same problem here. "
] | 2024-12-05T08:49:36 | 2024-12-24T05:59:59 | null | NONE | {
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} | null | null | null | # 1. HF -> nemo
Convert [Qwen2.5-7B](https://huggingface.co/Qwen/Qwen2.5-7B/tree/main) to `Qwen2.5-7B.nemo`. After tar xvf, the `Qwen2.5-7B.nemo` is as following:
```shell
root@inp16075348439349544319-3-1:/mnt/tenant-home_speed/nemo_models# tar xvf Qwen2.5-7B.nemo
./
./model_config.yaml
./model_weights/
./model_weights/.metadata
./model_weights/__0_0.distcp
./model_weights/__0_1.distcp
./model_weights/common.pt
./model_weights/metadata.json
```
# 2. Inference using `Qwen2.5-7B.nemo`
Then I tried to do inference using `Qwen2.5-7B.nemo`.
```
python3 megatron_gpt_eval.py \
gpt_model_file=Qwen2.5-7B.nemo \
inference.greedy=True \
inference.add_BOS=True \
trainer.devices=1 \
trainer.num_nodes=1 \
tensor_model_parallel_size=1 \
pipeline_model_parallel_size=1 \
prompts='["who are you?", "What is the captial of China?"]'
```
The response seems wrong. Part of the output:
```shell
[NeMo I 2024-12-04 21:57:07 nlp_overrides:1386] Model MegatronGPTModel was successfully restored from Qwen2.5-7B.nemo.
prompt=========:['who are you?', 'What is the captial of China?']
setting number of microbatches to constant 1
***************************
{'sentences': ['who are you?1000000000000000000000000000000000', 'What is the captial of China?100000000000000000000000000000'], 'tokens': [['<|im_start|>', 'who', 'Ġare', 'Ġyou', '?', '1', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0'], ['<|im_start|>', 'What', 'Ġis', 'Ġthe', 'Ġcapt', 'ial', 'Ġof', 'ĠChina', '?', '1', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0']], 'logprob': None, 'full_logprob': None, 'token_ids': [[151644, 14623, 525, 498, 30, 16, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15], [151644, 3838, 374, 279, 6427, 530, 315, 5616, 30, 16, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15]], 'offsets': [[0, 0, 3, 7, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45], [0, 0, 4, 7, 11, 16, 19, 22, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58]]}
***************************
[NeMo I 2024-12-04 21:57:14 megatron_gpt_model:1717] Pipeline model parallel rank: 0, Tensor model parallel rank: 0, Number of model parameters on device: 7.62e+09. Number of precise model parameters on device: 7615616512.
LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2,3,4,5,6,7]
Predicting DataLoader 0: 0%| | 0/1 [00:00<?, ?it/s]setting number of microbatches to constant 1
Predicting DataLoader 0: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:01<00:00, 0.51it/s]
***************************
[{'sentences': ['who are you?1000000000000000000000000000000000', 'What is the captial of China?100000000000000000000000000000'], 'tokens': [['<|im_start|>', 'who', 'Ġare', 'Ġyou', '?', '1', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0'], ['<|im_start|>', 'What', 'Ġis', 'Ġthe', 'Ġcapt', 'ial', 'Ġof', 'ĠChina', '?', '1', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0', '0']], 'logprob': None, 'full_logprob': None, 'token_ids': [[151644, 14623, 525, 498, 30, 16, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15], [151644, 3838, 374, 279, 6427, 530, 315, 5616, 30, 16, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15]], 'offsets': [[0, 0, 3, 7, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45], [0, 0, 4, 7, 11, 16, 19, 22, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58]]}]
***************************
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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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```
if distributed_optimizer and overlap_param_gather:
disable_forward_pre_hook
...
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...
if distributed_optimizer and overlap_param_gather:
enable_forward_pre_hook
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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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Pipeline parallel was broken in all finetuning tasks unless `pad_max_length=True`. Unfortunately the CI script also had a bug and the PP bug slipped through. This PR fixes both.
**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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- [ ] 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 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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# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
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- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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This PR adds TensorRT inference support for the Cosmos Tokenizers
**Collection**: common/video_tokenizers
# Changelog
- It adds the tokenizer configs and modules from the[ Cosmos Tokenizer repo](https://github.com/NVIDIA/Cosmos-Tokenizer/tree/main/cosmos_tokenizer) which enables the models to be exported to TensorRT.
- It provides an example of how to write a wrapper class that enables the tokenizers to be exported to TensorRT
# Usage
The script `common/video_tokenizers/cosmos_trt_run.py` provides an example of how to export the CosmosTokenizer to TensorRT and run inference.
# 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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- [ ] 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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**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# GitHub Actions CI
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The GitHub Actions CI will run automatically when the "Run CICD" label is added to the PR.
To re-run CI remove and add the label again.
To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
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- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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Add a one line overview of what this PR aims to accomplish.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# GitHub Actions CI
The Jenkins CI system has been replaced by GitHub Actions self-hosted runners.
The GitHub Actions CI will run automatically when the "Run CICD" label is added to the PR.
To re-run CI remove and add the label again.
To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
# Additional Information
* Related to # (issue)
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📝 Please remember the following to-do's before merge:
- [ ] Verify the presubmit CI
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"just curious why the TImerCallback is inconsistent across ranks? also, if it's inconsistent, but goes in the common state, is only one rank's state saved? does that affect restore?\r\n\r\n",
"> just curious why the TImerCallback is inconsistent across ranks? \r\n\r\nThe times aren't synchronized across ranks, so... | 2024-12-03T22:36:34 | 2025-01-16T01:56:11 | null | COLLABORATOR | {
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} | # What does this PR do ?
Megatron core distributed checkpointing gathers the common state dict and compares values across ranks to ensure they are consistent. By default, non-tensor values get accumulated there, but certan application-specific data will differ across ranks. Megatron core offers the `preprocess_common_before_consistancy_check` option as part of saving to handle this type of filtering.
This PR adds a function to remove values known to be different across ranks from consideration during the consistency check. For now, this hardcodes removing the Timer Callback states from the consistency check, but the function can be extended if/when more such cases emerge.
Now warnings like the following will no longer be logged:
```
[NeMo W 2024-12-02 11:45:59 validation:387] There is difference in the common state dict in different ranks. The differences are {1: ([], [], [(('callbacks', 'Timer', 'time_elapsed', 'train'), <class 'float'>, <class 'float'>), (('callbacks', 'Timer', 'time_elapsed', 'validate'), <class 'float'>, <class 'float'>)]), 2: ([], [], [(('callbacks', 'Timer', 'time_elapsed', 'train'), <class 'float'>, <class 'float'>), (('callbacks', 'Timer', 'time_elapsed', 'validate'), <class 'float'>, <class 'float'>)]), 3: ([], [], [(('callbacks', 'Timer', 'time_elapsed', 'train'), <class 'float'>, <class 'float'>), (('callbacks', 'Timer', 'time_elapsed', 'validate'), <class 'float'>, <class 'float'>)]), 4: ([], [], [(('callbacks', 'Timer', 'time_elapsed', 'train'), <class 'float'>, <class 'float'>), (('callbacks', 'Timer', 'time_elapsed', 'validate'), <class 'float'>, <class 'float'>)]), 5: ([], [], [(('callbacks', 'Timer', 'time_elapsed', 'train'), <class 'float'>, <class 'float'>), (('callbacks', 'Timer', 'time_elapsed', 'validate'), <class 'float'>, <class 'float'>)]), 6: ([], [], [(('callbacks', 'Timer', 'time_elapsed', 'train'), <class 'float'>, <class 'float'>), (('callbacks', 'Timer', 'time_elapsed', 'validate'), <class 'float'>, <class 'float'>)]), 7: ([], [], [(('callbacks', 'Timer', 'time_elapsed', 'train'), <class 'float'>, <class 'float'>), (('callbacks', 'Timer', 'time_elapsed', 'validate'), <class 'float'>, <class 'float'>)])}
```
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```python
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"[🤖]: Hi @haifengqian 👋,\n\nWe wanted to let you know that a [CICD pipeline](https://github.com/NVIDIA/NeMo/actions/runs/12147597441) for this PR just finished successfully\n\nSo it might be time to merge this PR or get some approvals\n\nI'm just a bot so I'll leave it you what to do next.\n\n//cc @pablo-garay @k... | 2024-12-03T20:22:54 | 2024-12-27T01:58:17 | 2024-12-27T01:58:16 | COLLABORATOR | {
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} | # What does this PR do ?
add batching support in inference server
**Collection**: nlp
# 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.
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# 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)
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**PR Type**:
- [x] New Feature
- [ ] Bugfix
- [ ] Documentation
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**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
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To re-run CI remove and add the label again.
To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
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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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Adds AutoModelSeq2Seq HF support
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} | # What does this PR do ?
Updated the LLM model conversion and deployment scripts to be in-line with OpenAI standards and for a more streamlined execution process.
**Collection**: NLP
# Changelog
* Change /v1/completions/ endpoint to /v1/completions to be aligned with OpenAI API specs.
* Update default Triton port to be consistent between deployment and API scripts.
* Set the requested environment variables used by the API in the deployment script.
# Usage
* Deploy an existing `.nemo` model with the following:
```
python3 scripts/deploy/nlp/deploy_triton.py --nemo_checkpoint /path/to/pretrained-model.nemo --tensor_parallelism_size 4 --start_rest_service True --triton_model_name triton-model --model_type mixtral --max_input_len 4096 --max_output_len 8192
```
Then, you can send a query to the service one deployed with:
```
curl -X POST http://0.0.0.0:8080/v1/completions/ -H "Content-Type: application/json" -H "accept: application/json" -d '{"prompt": "User: Write me a story about a baby dragon learning how to fly\nAssistant:", "model": "triton-model"}'
```
# 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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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)
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**PR Type**:
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- [x] Bugfix
- [ ] Documentation
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} | # What does this PR do ?
Support for EMMETT, VoiceTextBlender, enhanced prompt formatter, and various SpeechLLM improvements.
**Collection**: multimodal
# Changelog
- Support for multimodal SpeechLLM dataloading and training
- Support for TP and FSDP training of SpeechLLM
- Support for EMMETT https://arxiv.org/abs/2409.13523
- Support for VoiceTextBlender https://arxiv.org/abs/2410.17485
- Data types for various text data formats (NMT, chat, multimodal conversation)
- Enhanced prompt formatter with dynamically registered support for data types
- Documentation and tutorials
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# GitHub Actions CI
The Jenkins CI system has been replaced by GitHub Actions self-hosted runners.
The GitHub Actions CI will run automatically when the "Run CICD" label is added to the PR.
To re-run CI remove and add the label again.
To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [x] New Feature
- [ ] Bugfix
- [x] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
# Additional Information
* Related to # (issue)
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} | # What does this PR do ?
This PR enables fabric by:
1. fixes pre_training and fine_tuning so they don't depend on a trainer
2. fixes the setup method in the fabric class
**Collection**: [Note which collection this PR will affect]
LLM
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# GitHub Actions CI
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# Before your PR is "Ready for review"
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# What does this PR do ?
Support for initializing lhotse shar dataloader via field: list[path] mapping
**Collection**: [Note which collection this PR will affect]
# Changelog
- Support for initializing lhotse shar dataloader via field: list[path] mapping
# 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.
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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?
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- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
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[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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} | # What does this PR do ?
* Addressing CLI type hint issue `Unexpected error: Unserializable value /models/LLAMA31-8B-base-fp8 of type <class 'pathlib.PosixPath'>. Error occurred at path '<root>.export_config.path'.")` in [https://github.com/NVIDIA/NeMo/blob/a635607eea98b95a41f0f7a336ae083f38633630/nemo/collections/llm/quantization/quantizer.py#L83](https://github.com/NVIDIA/NeMo/blob/a635607eea98b95a41f0f7a336ae083f38633630/nemo/collections/llm/quantization/quantizer.py#L83)
* Some renaming
**Collection**: NLP / LLM
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# GitHub Actions CI
The Jenkins CI system has been replaced by GitHub Actions self-hosted runners.
The GitHub Actions CI will run automatically when the "Run CICD" label is added to the PR.
To re-run CI remove and add the label again.
To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] 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
- [x] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
# Additional Information
* Related to https://github.com/NVIDIA/NeMo-Run/pull/118 (prerequisite)
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"Use reinstall.sh in the instructions. Do not use pip. There are a little differences, which you can see from documents.\nOr use this:\n\n> !pip install git+https://github.com/NVIDIA/NeMo.git"
] | 2024-12-03T12:43:57 | 2025-01-03T06:32:27 | null | NONE | {
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} | null | null | null | **Describe the bug**
I was following the tutorials provided in ```/tutorials/asr``` directory. In the ```Training with PyTorch Lightning``` section of ```ASR_with_NeMo.ipynb```, when I run the second code block, I get the following error -
```
valueError: trainer constructor argument must be either None or pytorch_lightning.Trainer. But got <class 'lightning.pytorch.trainer.trainer.Trainer'> instead.
```
This error can be solved by updating the pytorch lightning import to ```import pytorch_lightning as pl```.
I am happy to open a PR to fix this if required!
**Steps/Code to reproduce bug**
The error can be reproduced by running the notebook ```ASR_with_NeMo.ipynb```.
**Expected behavior**
The NeMo model should load from the config.
**Environment overview (please complete the following information)**
- Environment location: Local
- Method of NeMo install: Source
**Environment details**
- OS version Ubuntu 22.04
- PyTorch version 2.5.1
- Python version 3.11
- RTX 3060
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Add [nvidia/low-frame-rate-speech-codec-22khz](https://huggingface.co/nvidia/low-frame-rate-speech-codec-22khz) model on docs
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"This issue was closed because it has been inactive for 7 days since being marked as stale."
] | 2024-12-03T09:47:54 | 2025-01-10T02:00:20 | 2025-01-10T02:00:20 | NONE | {
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} | null | null | null | **Describe the bug**
In trying to generate confidence scores with timestamps using an RNN transducer model (`stt_en_conformer_transducer_large`), with buffering, there is a type mismatch error on [this line](https://github.com/NVIDIA/NeMo/blob/9abd81bee41b44a3946a6e535025752eaa4314cd/nemo/collections/asr/parts/submodules/rnnt_decoding.py#L687) `for ts, te in zip(hyp.timestep, hyp.timestep[1:] + [len(hyp.frame_confidence)])`
```
Sample:: 100%|██████████| 1/1 [00:00<00:00, 11618.57it/s]
[NeMo W 2024-12-03 14:55:42 rnnt_decoding:1184] Specified segment seperators are not in supported punctuation {"'"}. If the seperators are not punctuation marks, ignore this warning. Otherwise, specify 'segment_gap_threshold' parameter in decoding config to form segments.
<class 'dict'>
Backend macosx is interactive backend. Turning interactive mode on.
Error executing job with overrides: ['model_path=null', 'pretrained_name=stt_en_conformer_transducer_large', 'audio_dir=/Users/aanchan/work/podcast_transcription_using_nemo/test', 'output_filename=/Users/aanchan/work/podcast_transcription_using_nemo/test_rnn_t_f1.json', 'total_buffer_in_secs=4.0', 'chunk_len_in_secs=1.6', 'model_stride=4', 'batch_size=32', 'merge_algo=lcs', 'lcs_alignment_dir=$PWD/lcs']
Traceback (most recent call last):
File "/Users/aanchan/work/podcast_transcription_using_nemo/env_nemo_1/lib/python3.10/site-packages/hydra/_internal/utils.py", line 394, in _run_hydra
_run_app(
File "/Users/aanchan/work/podcast_transcription_using_nemo/env_nemo_1/lib/python3.10/site-packages/hydra/_internal/utils.py", line 457, in _run_app
run_and_report(
File "/Users/aanchan/work/podcast_transcription_using_nemo/env_nemo_1/lib/python3.10/site-packages/hydra/_internal/utils.py", line 223, in run_and_report
raise ex
File "/Users/aanchan/work/podcast_transcription_using_nemo/env_nemo_1/lib/python3.10/site-packages/hydra/_internal/utils.py", line 220, in run_and_report
return func()
File "/Users/aanchan/work/podcast_transcription_using_nemo/env_nemo_1/lib/python3.10/site-packages/hydra/_internal/utils.py", line 458, in <lambda>
lambda: hydra.run(
File "/Users/aanchan/work/podcast_transcription_using_nemo/env_nemo_1/lib/python3.10/site-packages/hydra/_internal/hydra.py", line 132, in run
_ = ret.return_value
File "/Users/aanchan/work/podcast_transcription_using_nemo/env_nemo_1/lib/python3.10/site-packages/hydra/core/utils.py", line 260, in return_value
raise self._return_value
File "/Users/aanchan/work/podcast_transcription_using_nemo/env_nemo_1/lib/python3.10/site-packages/hydra/core/utils.py", line 186, in run_job
ret.return_value = task_function(task_cfg)
File "/Users/aanchan/work/podcast_transcription_using_nemo/rnnt_timestamps.py", line 301, in main
hyps = get_buffered_pred_feat_rnnt(
File "/Users/aanchan/work/podcast_transcription_using_nemo/env_nemo_1/lib/python3.10/site-packages/nemo/collections/asr/parts/utils/transcribe_utils.py", line 95, in get_buffered_pred_feat_rnnt
hyp_list = asr.transcribe(tokens_per_chunk, delay)
File "/Users/aanchan/work/podcast_transcription_using_nemo/env_nemo_1/lib/python3.10/site-packages/nemo/collections/asr/parts/utils/streaming_utils.py", line 1309, in transcribe
self.infer_logits()
File "/Users/aanchan/work/podcast_transcription_using_nemo/env_nemo_1/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 116, in decorate_context
return func(*args, **kwargs)
File "/Users/aanchan/work/podcast_transcription_using_nemo/env_nemo_1/lib/python3.10/site-packages/nemo/collections/asr/parts/utils/streaming_utils.py", line 1081, in infer_logits
self._get_batch_preds()
File "/Users/aanchan/work/podcast_transcription_using_nemo/env_nemo_1/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 116, in decorate_context
return func(*args, **kwargs)
File "/Users/aanchan/work/podcast_transcription_using_nemo/env_nemo_1/lib/python3.10/site-packages/nemo/collections/asr/parts/utils/streaming_utils.py", line 1148, in _get_batch_preds
best_hyp, _ = self.asr_model.decoding.rnnt_decoder_predictions_tensor(
File "/Users/aanchan/work/podcast_transcription_using_nemo/env_nemo_1/lib/python3.10/site-packages/nemo/collections/asr/parts/submodules/rnnt_decoding.py", line 569, in rnnt_decoder_predictions_tensor
hypotheses = self.compute_confidence(hypotheses)
File "/Users/aanchan/work/podcast_transcription_using_nemo/env_nemo_1/lib/python3.10/site-packages/nemo/collections/asr/parts/submodules/rnnt_decoding.py", line 688, in compute_confidence
for ts, te in zip(hyp.timestep, hyp.timestep[1:] + [len(hyp.frame_confidence)]):
TypeError: unhashable type: 'slice'
```
A clear and concise description of what the bug is.
From the debugger it looks like hyp.timestamp is a dict, and really the zip should be happening over hyp.timestamp['timestamp'] which happens to be a PyTorch tensor. The slicing over a dict type seems incorrect e.g. hyp.timestamp[1:]
**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.
- Start with the code example [speech_to_text_buffered_infer_rnnt.py](https://github.com/NVIDIA/NeMo/blob/main/examples/asr/asr_chunked_inference/rnnt/speech_to_text_buffered_infer_rnnt.py)
- Add a ConfidenceConfig as in the ASR with [confidence estimation tutorial ](https://github.com/NVIDIA/NeMo/blob/main/tutorials/asr/ASR_Confidence_Estimation.ipynb)
```
from nemo.collections.asr.parts.utils.asr_confidence_utils import (
ConfidenceConfig,
ConfidenceConstants,
ConfidenceMethodConfig,
ConfidenceMethodConstants,
)
confidence_cfg = ConfidenceConfig(
preserve_frame_confidence=True, # Internally set to true if preserve_token_confidence == True
# or preserve_word_confidence == True
preserve_token_confidence=True, # Internally set to true if preserve_word_confidence == True
preserve_word_confidence=True,
aggregation="prod", # How to aggregate frame scores to token scores and token scores to word scores
exclude_blank=False, # If true, only non-blank emissions contribute to confidence scores
tdt_include_duration=False, # If true, calculate duration confidence for the TDT models
method_cfg=ConfidenceMethodConfig( # Config for per-frame scores calculation (before aggregation)
name="max_prob", # Or "entropy" (default), which usually works better
entropy_type="gibbs", # Used only for name == "entropy". Recommended: "tsallis" (default) or "renyi"
alpha=0.5, # Low values (<1) increase sensitivity, high values decrease sensitivity
entropy_norm="lin" # How to normalize (map to [0,1]) entropy. Default: "exp"
)
)
```
- Change the decoding strategy and attach the confidence config to the RNNTDecoderConfig being used
```
asr_model.change_decoding_strategy(
RNNTDecodingConfig(compute_timestamps=True,
preserve_alignments=True,
confidence_cfg=confidence_cfg)
)
```
- Run the script with the following arguments
```speech_to_text_buffered_infer_rnnt.py
model_path=null
pretrained_name=stt_en_conformer_transducer_large
audio_dir=/Users/aanchan/work/podcast_transcription_using_nemo/test
output_filename=/Users/aanchan/work/podcast_transcription_using_nemo/test_rnn_t_f1.json
total_buffer_in_secs=4.0
chunk_len_in_secs=1.6
model_stride=4
batch_size=32
merge_algo="lcs"
lcs_alignment_dir=$PWD/lcs
```
An example code file and input is in [this Google Drive folder](https://drive.google.com/drive/folders/1fzYkRT6ZRQcU7BvJLTrNCyB4bYWbN8uB?usp=sharing)
**Expected behavior**
A clear and concise description of what you expected to happen.
The expected output was a json file with time stamps written out.
**Environment overview (please complete the following information)**
- Environment location: [Bare-metal, Docker, Cloud(specify cloud provider - AWS, Azure, GCP, Collab)]
The environment is a local laptop installation
- Method of NeMo install: [pip install or from source]. Please specify exact commands you used to install.
```
pip install Cython packaging
pip install --upgrade pip
export BRANCH="main"
pip install torch torchvision torchaudio
pip install git+https://github.com/NVIDIA/NeMo.git@$BRANCH#egg=nemo_toolkit[asr]
```
- 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 : MacOS Monterey 12.5
- PyTorch version : 2.5.1
- Python version 3.10.4
**Additional context**
Add any other context about the problem here.
Example: GPU model
This was run on a CPU, and not a GPU
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"@nithinraok, @titu1994 ?",
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"@pzelasko did you have a check to look?",
"<!-- pylint-output-strict-mode-false -->\n\nbeep boop 🤖: 🙏 The following files have warnings. In case you are familia... | 2024-12-03T01:00:00 | 2025-01-16T01:56:13 | 2025-01-16T01:56:13 | CONTRIBUTOR | {
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📝 Please remember the following to-do's before merge:
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} | # What does this PR do ?
If not saving optimizers in the checkpoint, don't generate the sharded optimizer state dict, as it will ultimately be discarded. The ckpt contents are the same, and this is strictly a perf improvement
**Collection**: NLP
# Changelog
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Add a one line overview of what this PR aims to accomplish.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
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## Who can review?
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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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# Before your PR is "Ready for 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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} | # Add iterative pseudo-labeling for any ASR NeMo model
**Collection**: ASR
# Usage
* You can potentially add a usage example below
```python
examples/asr/run_ipl.py config_path='./', config_name='run_ipl'
```
**PR Type**:
- [V ] 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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} | # What does this PR do ?
The PR attempts to restore functionality with recent `numpy` versions; `numpy` 2.0 removed `sctypes` and this is breaking `asr` functionality.
**Collection**: `asr`
# Changelog
- As said above `numpy` from version 2.0 onwards removed `sctypes` functionality, which breaks `asr` functionality in various places (e.g. transcribe_speech, example notebooks etc).
- The changes reside in the `_convert_samples_to_float32` function residing in both [feature_loader.py](https://github.com/NVIDIA/NeMo/blob/main/nemo/collections/asr/parts/preprocessing/feature_loader.py#48) and [segment.py](https://github.com/NVIDIA/NeMo/blob/main/nemo/collections/asr/parts/preprocessing/segment.py#257).
- There have been other issues relating to this (e.g. #10839 and #10180), however these _do not replicate existing functionality_.
# Usage
The usage is that ASR tasks that call `_convert_samples_to_float32` functions now succeed. As noted above, while this has been attempted to be addressed in the PRs mentioned above, I believe that the functionality is not replicated accurately.
More concretely, if you check the output of `sctype` for the types of `int` and `float` in supported versions of `numpy` you'd get the following:
```python
print(np.sctypes["int"])
[<class 'numpy.int8'>, <class 'numpy.int16'>, <class 'numpy.int32'>, <class 'numpy.int64'>]
print(np.sctypes["float"])
[<class 'numpy.float16'>, <class 'numpy.float32'>, <class 'numpy.float64'>]
```
However, if we use the `issubdtype` to perform this the set will be wider, case on point for floating point:
```python
import numpy as np
float128 = np.floating[128]
np.issubdtype(float128, np.floating)
Out[6]: True
```
And, also for integers the set mostly covers the output of `sctype` for _signed_ ones. However any subclass from `signedinteger` or `unsignedinteger` will return true. A more concrete example would be,
```python
import numpy as np
int96 = np.signedinteger[96]
np.issubdtype(int96, np.integer)
Out[4]: True
uint96 = np.unsignedinteger[96]
np.issubdtype(uint96, np.integer)
Out[5]: True
```
Therefore, in this case not only we consider `int{8,16,32,64}` but also `uint{8,16,32,64}` which is not the expected result when querying `sctype['int']` leading to potentially unexpected behavior. Case on point,
```python
import numpy as np
np.issubdtype(np.uint8, np.integer)
Out[3]: True
```
# GitHub Actions CI
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The GitHub Actions CI will run automatically when the "Run CICD" label is added to the PR.
To re-run CI remove and add the label again.
To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".
# Before your PR is "Ready for review"
**Pre checks**:
- [x] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [x] Did you write any new necessary tests? _No new tests were required._
- [x] Did you add or update any necessary documentation? _No documentation update required_.
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc) _No optional components are affected_.
- [x] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [x] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
# Additional Information
The fix is _backwards compatible_ with all supported `numpy` 1.x versions as well. Therefore, it should pose minimal risk wrt to integration.
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} | # What does this PR do ?
The PR attempts to restore functionality with recent `numpy` versions; `numpy` 2.0 removed `sctypes` and this is breaking `asr` functionality.
edit: closed the PR due to commits not being signed-off properly and rebasing caused issues :)
**Collection**: `asr`
# Changelog
- As said above `numpy` from version 2.0 onwards removed `sctypes` functionality, which breaks `asr` functionality in various places (e.g. transcribe_speech, example notebooks etc).
- The changes reside in the `_convert_samples_to_float32` function residing in both [feature_loader.py](https://github.com/NVIDIA/NeMo/blob/main/nemo/collections/asr/parts/preprocessing/feature_loader.py#48) and [segment.py](https://github.com/NVIDIA/NeMo/blob/main/nemo/collections/asr/parts/preprocessing/segment.py#257).
- There have been other issues relating to this (e.g. #10839 and #10180), however these _do not replicate existing functionality_.
# Usage
The usage is that ASR tasks that call `_convert_samples_to_float32` functions now succeed. As noted above, while this has been attempted to be addressed in the PRs mentioned above, I believe that the functionality is not replicated accurately.
More concretely, if you check the output of `sctype` for the types of `int` and `float` in supported versions of `numpy` you'd get the following:
```python
print(np.sctypes["int"])
[<class 'numpy.int8'>, <class 'numpy.int16'>, <class 'numpy.int32'>, <class 'numpy.int64'>]
print(np.sctypes["float"])
[<class 'numpy.float16'>, <class 'numpy.float32'>, <class 'numpy.float64'>]
```
However, if we use the `issubdtype` to perform this the set will be wider, case on point for floating point:
```python
import numpy as np
float128 = np.floating[128]
np.issubdtype(float128, np.floating)
Out[6]: True
```
And, also for integers the set mostly covers the output of `sctype` for _signed_ ones. However any subclass from `signedinteger` or `unsignedinteger` will return true. A more concrete example would be,
```python
import numpy as np
int96 = np.signedinteger[96]
np.issubdtype(int96, np.integer)
Out[4]: True
uint96 = np.unsignedinteger[96]
np.issubdtype(uint96, np.integer)
Out[5]: True
```
Therefore, in this case not only we consider `int{8,16,32,64}` but also `uint{8,16,32,64}` which is not the expected result when querying `sctype['int']` leading to potentially unexpected behavior. Case on point,
```python
import numpy as np
np.issubdtype(np.uint8, np.integer)
Out[3]: True
```
# 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? _No new tests were required._
- [x] Did you add or update any necessary documentation? _No documentation update required_.
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc) _No optional components are affected_.
- [x] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [x] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
# Additional Information
The fix is _backwards compatible_ with all supported `numpy` 1.x versions as well. Therefore, it should pose minimal risk wrt to integration.
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**Collection**: [Note which collection this PR will affect]
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"@akoumpa could you trigger CI",
"<!-- pylint-output-strict-mode-false -->\n\nbeep boop 🤖: 🙏 The following files have warnings. In case you are familiar with these, please try helping us to improve the code base.\n\n---\n\nYour code was analyzed with PyLint. The following annotations have been identified:\n\n``... | 2024-11-30T22:42:25 | 2024-12-06T18:02:27 | 2024-12-06T18:02:26 | CONTRIBUTOR | {
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} | # What does this PR do ?
Make the use of megatron RankGenerator consistent with recent megatron changes [!1940](https://github.com/NVIDIA/Megatron-LM/commit/7f22e210cddc3215adda25d9e16ea512dc32458c)
**Collection**: [Note which collection this PR will affect]
# Changelog
Make the use of RankGenerator consistent with recent Mcore changes [!1940](https://github.com/NVIDIA/Megatron-LM/commit/7f22e210cddc3215adda25d9e16ea512dc32458c)
In `fake_initialize_model_parallel` function in `nemo/collections/nlp/modules/common/megatron/megatron_init.py`
* use ep=1 for decoder_rank_generator, making it treat EP as part of DP
* define a new expert_decoder_rank_generator to handle EP groups/ranks only
# 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
- [x ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
# Additional Information
* Related to # (issue)
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"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.",
"Touching this so it's no longer stale. I must be doing something wrong as I am not getting a response to the PR or to this issue. Can anyone see this?"
] | 2024-11-30T11:02:20 | 2025-01-01T02:03:33 | null | NONE | {
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} | null | null | null | I have submitted a PR to fix a bug in nemo diarization, but I believe it is stuck in the workflow process. Here is the PR: https://github.com/NVIDIA/NeMo/pull/11049
I have change 2 lines, in this commit:
https://github.com/NVIDIA/NeMo/pull/11049/commits/86dc207d713b260d4a76b1c4518b82a72b0277c7
But there are several other automatic commits and merges that have occurred, and the PR seems to be waiting for integration tests. I believe I have tagged the right people for review, but I am not getting any response.
Can someone assist me? Apologies if I am doing this wrong - I am new to git and the nemo PR process.
Thank you. | null | {
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} | 🚀 PR to bump `NVIDIA/Megatron-LM` in `Dockerfile.ci` to `MCORE_TAG=31a29b87cf25f28d524e313de197a8359d2d6789`.
📝 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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"This PR is stale because it has been open for 14 days with no activity. Remove stale label or comment or update or this will be closed in 7 days.",
"This PR is stale because it has been open for 14 days with no activity. Remove stale label or comment or update or this will be closed in 7 days.",
"A vLLM test w... | 2024-11-29T13:17:45 | 2025-01-03T12:02:25 | 2025-01-03T12:02:25 | COLLABORATOR | {
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} | # What does this PR do ?
Add vLLM nemo_export.py test in GitHub CI.
**Collection**: NLP / LLM
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# GitHub Actions CI
The Jenkins CI system has been replaced by GitHub Actions self-hosted runners.
The GitHub Actions CI will run automatically when the "Run CICD" label is added to the PR.
To re-run CI remove and add the label again.
To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] 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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test
# Changelog
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Introduce extra checks based on `in_framework_supported` flag when some imports from `nemo.deploy.nlp` fail, which may happen for virtual environment `/opt/venv` that is used for vLLM.
**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
```
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# Before your PR is "Ready for review"
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- [x] Bugfix
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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
* Related to https://github.com/NVIDIA/NeMo/pull/11413
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📝 Please remember the following to-do's before merge:
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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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- [ ] Did you write any new necessary tests?
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**PR Type**:
- [ ] 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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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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- [ ] 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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* Related to # (issue)
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Hi,
I was reading the paper "A Compact End-to-End Model with Local and Global Context for Spoken Language Identification".
In the paper, it is mentioned that "We open-source the model through NVIDIA NeMo". However, after searching the repository, I could only find AmberNet.
Could you please advise where I can find the setup or training scripts for TitaNet-LID? Is there a pre-trained model available for experimentation?
Thank you for your help!
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Add a one line overview of what this PR aims to accomplish.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
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**Collection**: audio
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- Added `PretrainedModelInfo`
# Usage
N/A
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This PR adds documentation for audio collection.
**Collection**: audio, docs
# Changelog
- Adding initial documentation
# Usage
To build locally:
```python
conda create -n nemo_docs python=3.10
conda activate nemo_docs
pip install -r requirements/requirements_docs.txt
cd docs
make clean && make html && make html
```
# GitHub Actions CI
The Jenkins CI system has been replaced by GitHub Actions self-hosted runners.
The GitHub Actions CI will run automatically when the "Run CICD" label is added to the PR.
To re-run CI remove and add the label again.
To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".
# Before your PR is "Ready for review"
**Pre checks**:
- [x] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [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
- [ ] Bugfix
- [x] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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* Related to # (issue)
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- modify pretrain recipe to have pretrained language model path
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# GitHub Actions CI
The Jenkins CI system has been replaced by GitHub Actions self-hosted runners.
The GitHub Actions CI will run automatically when the "Run CICD" label is added to the PR.
To re-run CI remove and add the label again.
To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".
# Before your PR is "Ready for review"
**Pre checks**:
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- [x] Did you write any new necessary tests?
- [x] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [x] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
# Additional Information
* Related to # (issue)
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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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**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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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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Adjust CLI support for PTQ based on https://github.com/NVIDIA/NeMo-Run/pull/118 (prerequisite).
**Collection**: LLM
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```bash
# With default quantization_config
nemo llm ptq nemo_checkpoint=/models/Llama-3-70b \
calib_tp=8 \
export_config.inference_tensor_parallel=2 \
export_config.path=/models/Llama-3-70b-FP8
# Changing quantization_config
nemo llm ptq nemo_checkpoint=/models/Llama-3-70b \
calib_tp=8 \
export_config.inference_tensor_parallel=1 \
export_config.path=/models/Llama-3-70b-INT4_AWQ \
quantization_config.algorithm=int4_awq
```
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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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* Related to https://github.com/NVIDIA/NeMo-Run/pull/118
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Use config's default dtype, otherwise fall-back to default_dtype constructor param value.
**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 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.
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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- [ ] 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:
- [ ] Verify the presubmit CI
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"recipes + HF converters will be in subsequent PRs",
"<!-- pylint-output-strict-mode-true -->\n\nbeep boop 🤖: 🚨 The following files must be fixed before merge!\n\n---\n\nYour code was analyzed with PyLint. The following annotations have been identified:\n\n```\n\n------------------------------------\nYour code ... | 2024-11-26T22:35:57 | 2024-12-05T06:50:43 | 2024-12-05T06:50:42 | COLLABORATOR | {
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} | # What does this PR do ?
Add canonical LoRA (aka unfused LoRA) to NeMo 2.0.
This variant follows the HF implementation more closely and adds three separate adapters for attention q_proj, k_proj, and v_proj, as well as two separate adapters for MLP up_proj and gate_proj. In NeMo/Mcore, these are fused into one adapter for performance reasons.
Convergence test:
**Collection**: [Note which collection this PR will affect]
# Changelog
- Renamed `AdapterParallelAdd` to `LoRALinear` to be more explicit.
# 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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"> @ko3n1g Any idea what t... | 2024-11-26T22:16:43 | 2024-12-05T21:24:33 | 2024-12-05T21:24:33 | CONTRIBUTOR | {
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} | # What does this PR do ?
Handle exception during import of RetroGPTChunkDatasets
**Collection**: [Note which collection this PR will affect]
# Changelog
- Handle Exception during import to allow a graceful fallback when importing RetroGPTChunkDatasets from megatron.
Currently on arm linux platform, `from megatron.core.datasets.retro.config import RetroGPTChunkDatasets` fails with an exception which is [a known issue](https://github.com/facebookresearch/faiss/issues/3936) with its dependency, faiss. When the exception happens, we want to gracefully fall back to the codepath without megatron retro support.
# 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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I mostly work with instruct models, and most of the recipes are focused on base models. This is particularly prominent in the sequence packing, which doesn't account for instruct templates in the sequence.
**Describe the solution you'd like**
Examples of performing PEFT, with and without sequence packing on llama 3.1 8b instruct would be helpful.
**Describe alternatives you've considered**
Right now we've patched nemo 1 to work with this.
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} | # What does this PR do ?
When loading checkpoints trained in 24.09 container, `io_unflatten_object` incorrectly processes `values=[None]`, leading to TypeError when attempting to export to HF format[1].
**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"
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- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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Add a one line overview of what this PR aims to accomplish.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# GitHub Actions CI
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- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
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* Related to # (issue)
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"Please fill in the MR **Usage** section with details on `fp8_quantized` & `fp8_kvcache` params so that people can immediately get to know what is added here",
"<!-- pylint-output-strict-mode-false -->\n\nbeep boop 🤖: 🙏 The following files have warnings. In case you are familiar with these, please try helping u... | 2024-11-26T15:20:23 | 2024-12-31T08:13:20 | 2024-12-31T08:13:18 | COLLABORATOR | {
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"merged_at": "2024-12-31T08:13:18"
} | # What does this PR do ?
Support FP8 TE TRT-LLM export with mcore path
**Collection**: llm/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
from nemo.export.tensorrt_llm import TensorRTLLM
trt_llm_exporter = TensorRTLLM(model_dir="/opt/checkpoints/tmp_triton_model_repository/")
trt_llm_exporter.export(nemo_checkpoint_path="/path/to/quantized/model", model_type="llama", fp8_quantized=True, fp8_kvcache=True)
# Autodetects when quantisation flags are not set
output = trt_llm_exporter.forward(["What is the best city in the world?"], max_output_token=17, top_k=1, top_p=0.0, temperature=1.0)
print("output: ", output)
```
# GitHub Actions CI
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The GitHub Actions CI will run automatically when the "Run CICD" label is added to the PR.
To re-run CI remove and add the label again.
To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
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**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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**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 back tests that were originally in #11117
**Collection**: [llm]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# GitHub Actions CI
The Jenkins CI system has been replaced by GitHub Actions self-hosted runners.
The GitHub Actions CI will run automatically when the "Run CICD" label is added to the PR.
To re-run CI remove and add the label again.
To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] 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 ?
Added nemo run recipe's and example scripts for Llava Next
**Collection**:
VLM
# Changelog
- Added pretrain, finetune nemo run recipes for llava next.
- Added example scripts for custom pretrain, finetune and generation examples
- Fixing some model configs
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
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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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# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
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This PR modifies the processing script to preserve the directory structure when saving output files.
**Collection**: audio
# Changelog
- Updated processing script to resolve `input_dir` based on the input manifest and individual filepaths
- Added an `input_dir` option to `process`
# Usage
N/A
# GitHub Actions CI
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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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**Collection**: Scripts
# Changelog
- Changed default seed from `42` to `None`
# Usage
If necessary, the original behavior can be reproduced using
```python
python add_noisy.py ... --seed 42
```
# GitHub Actions CI
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} | # What does this PR do ?
Added data modules for llava_next
**Collection**:
VLM
# Changelog
- Mock data module for llava next
- Energon data module for llava next
# 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.
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**PR Type**:
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- [ ] 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 ?
Adding LLava-Next model class
**Collection**:
VLM
# Changelog
- Model class for Llava-next.
- HF Importer class for llava-next.
- Utility functions supporting image tiling and feature merging
# GitHub Actions CI
The Jenkins CI system has been replaced by GitHub Actions self-hosted runners.
The GitHub Actions CI will run automatically when the "Run CICD" label is added to the PR.
To re-run CI remove and add the label again.
To run CI on an untrusted fork, a NeMo user with write access must first click "Approve and run".
# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
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- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [x] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
# Additional Information
* Related to # (issue)
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Add a one line overview of what this PR aims to accomplish.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
```
# GitHub Actions CI
The Jenkins CI system has been replaced by GitHub Actions self-hosted runners.
The GitHub Actions CI will run automatically when the "Run CICD" label is added to the PR.
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# Before your PR is "Ready for review"
**Pre checks**:
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- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation
If you haven't finished some of the above items you can still open "Draft" PR.
## Who can review?
Anyone in the community is free to review the PR once the checks have passed.
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.
# Additional Information
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"[🤖]: Hi @Ssofja 👋,\n\nWe wanted to let you know that a [CICD pipeline](https://github.com/NVIDIA/NeMo/actions/runs/12351033732) for this PR just finished successfully\n\nSo it might be time to merge this PR or get some approvals\n\nI'm just a bot so I'll leave it you what to do next.\n\n//cc @pablo-garay @ko3n1g... | 2024-11-25T20:34:08 | 2024-12-16T15:25:56 | 2024-12-16T15:25:53 | COLLABORATOR | {
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} | # What does this PR do ?
In this PR ASR documentation fixes have added and outdated data was removed.
**Collection**: docs/asr
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [x] Documentation | {
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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."
] | 2024-11-25T19:46:23 | 2024-12-18T02:02:06 | 2024-12-18T02:02:05 | 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
- 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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