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} | # What does this PR do ?
Move mask and position id generation in GPT synthetic dataset to __init__. They are same for each data loading, so doing it for every data loading is redundant, it also can create big CPU overheads while seq_len is long. Hence, move them to __init__.
**Collection**: [Note which collection... | {
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} | # What does this PR do ?
Added some new configurations and updated some of the older configuration files for Conformer models.
# Changelog
- Added configs for cache-aware fastconformer and hybrid ASR.
- Added more info on batch size and precision suggestions in the configs.
**PR Type**:
- [X] New Feature
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Add Frame-VAD, including related datasets and models for multi-label audio classification. Also, ASR+VAD pipeline is updated to use Frame-VAD, and support for dropping frames instead of masking is added.
**Collection**: [ASR]
# Changelog
- Frame-VAD:
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} | # What does this PR do ?
This PR adds ramp up batch size support for GPT models. It allows to increase the batch size up to global batch size linearly during training in a given number of samples.
**Collection**: NLP
# Changelog
- Add rampup_batch_size value to the training config.
- Input rampup_batch_size... | {
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} | # What does this PR do ?
fixing the ability to use temp sampling with concat datasets
**Collection**: ASR
# Changelog
In `audio_to_text_dataset.py` check for sampling probabilities only if the sampling technique is random
# Usage
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} | # What does this PR do ?
Cache inputs (attention mask, loss mask, and position ids) and reuse.
This mitigates CPU-side overhead.
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
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Resolves exceptions when trying to train with empty test/ val ds config sections
**Collection**: ASR
# Changelog
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fixes exceptions when running with empty test /val ds sections
**Collection**: ASR
# Changelog
in `/nemo/utils/model_utils.py`, check if len(ds_values) > 0 before trying to assign dataset names
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Refactor PP conversion mechanism.
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**Collection**: TTS
# Changelog
- Adds multi-speaker FastPitch pre-training with Conditional Layer Normalization
- `nemo/collections/tts/modules/fastpitch.py`
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Fix typo in bucketing strategy in FastConformer configs.
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# Changelog
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# Before your PR is "Ready for review"
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fixed broken file path.
**Collection**: [Note which collection this PR will affect]
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The code [here](https://github.com/NVIDIA/NeMo/blob/ecc116c29a14534abfe393f6eee4339b24ca6e57/nemo/collections/nlp/modules/common/megatron/module.py#L262) init the super class [MegatronModule](https://github.com/NVIDIA/NeMo/blob/ecc116c29a14534abfe393f6eee4339b24ca6e57/nemo/collections/nlp/module... | {
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} | # What does this PR do ?
Update hyperparameter recommendation based on experiments
**Collection**: tools
# 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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} | # What does this PR do ?
Helps to speed up ASR models training without quality degradation.
**Collection**: ASR, Core
# Changelog
- Adds a semi sorted batch sampler and its prepare function to a new file (in the future it might be some other samplers or new techniques like dynamic batching):
`nemo/collect... | {
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Add a one line overview of what this PR aims to accomplish.
Adds documentation for preemption support.
**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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I would like to use NeMo model, but have an error Process finished with exit code 139 (interrupted by signal 11: SIGSEGV) at the asr importing step.
from nemo.collections.asr.models ... | {
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} | # What does this PR do ?
Remove bottleneck code in `perform_clustering` function
**Collection**: [ASR]
# Changelog
- remove `gc.collect()` code since it makes too slow.
# Usage
* You can potentially add a usage example below
```python
# Add a code snippet demonstrating how to use this
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Unescape the prompt template to allow providing escape sequences in the prompt template from the CLI.
**Collection**: NLP
# Changelog
- Add specific line by line info of high level changes in this PR.
# Usage
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`NeMo Megatron supports 4 types of parallelisms (can be mixed together arbitraritly)`
The documentation at [https://docs.nvidia.com/deeplearning/nemo/user-guide/docs/en/stable... | {
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With TP=2 ,PP=2 and model.bias=false, GPT Training process hangs during dataloader sanity checking
**Steps/Code to reproduce bug**
Clone r1.15.0 realese branch and then run the offical GPT pretrain example with my trivial modification
```shell
git clone https://github.com/NVIDIA/NeMo.git
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Helps accelerate manifest loading via optional manifest sharding. This should speed up the loading of large manifests and reduce memory footprint - each worker loads just the shards that it needs.
**Collection**: ASR
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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
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} | # What does this PR do ?
This PR moves model parallelism in NeMo to use Megatron-core instead of Apex.
* All models use dataloader_iter in train and eval step (except eval for T5 p-tuning)
* All pre-training models that use a constant sequence length sample based on microbatches
* All downstream tasks - p-tunin... | {
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} | # What does this PR do ?
Remove bottleneck code in `perform_clustering` function
**Collection**: [ASR]
# Changelog
- remove `gc.collect()` code since it makes too slow.
# Usage
* You can potentially add a usage example below
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# Add a code snippet demonstrating how to use this
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} | # What does this PR do ?
PTuning and Adapters/IA3 have been implemented in diverging styles. Adapters and IA3 uses the elegant adapter_mixins framework. This PR implements P-Tuning via the same adapter_mixins framework.
The high level goal is to unify all PEFT methods to use adapter_mixins. This is allow us to th... | {
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I'm training a 44100 HifiGAN model on my own dataset.
After some epochs, `d_loss`, `g_loss`, etc. become `NaN`,
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Adds FastPitch speaker adaptation with adapters.
**Collection**: TTS
# Changelog
- Adds multi-speaker FastPitch pre-training with 1) Looked-up speaker embedding 2) Speaker verification model speaker embedding 3) Global Style Tokens 4) Conditional Layer Normalization
- `nemo/col... | {
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Adds support for untied embeddings for Megatron GPT for TP PP change
**Collection**: [NLP]
# Changelog
- Generalize indexing for tied vs untied gpt embeddings
# Before your PR is "Ready for review"
**Pre checks**:
- [x] Make sure you read and followed [Contributor guidelines](ht... | {
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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
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user selected max_seq_len should be less than model's max_seq_len
**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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Adds support for T5 Finetuning/Prompt tuning.
# Changelog
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# Usage
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Collecting mecab-python3
Using cached mecab-python3-1.0.6.tar.gz (77 kB)
Preparing metadata (setup.py) ... done
Installing collected packages: mecab-python3
DEPRECATION: mecab-python3 is being installed using the legacy 'setup.py i... | {
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PR [ #6311](https://github.com/NVIDIA/NeMo/pull/6311) (This is not yet in nemo 1.17.0, only https://github.com/NVIDIA/NeMo/pull/5837 is with more problems)
The model get's exported, but inferencing results in an exception.
This can be seen when th... | {
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Adds opengraph support for NeMo documentation page
**Collection**: [Docs]
# Changelog
- Add opengraph support for NeMo docs
# Before your PR is "Ready for review"
**Pre checks**:
- [x] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/m... | {
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Refines the suggested training parameters for the Fast Conformer models.
**Collection**: ASR
# Changelog
- In fast-conformer_ctc_bpe.yaml, change min_lr to 1e-4 (from 1e-6)
- in fast-conformer_transducer_bpe.yaml, change lr to 5e-3 and min_lr to 5e-4 (from 1e-6)
# Usage
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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
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Adds installation and inference instructions for Apple Mac.
**Collection**: [ASR (docs)]
# Changelog
- installation instructions
- ASR inference instructions
# Usage
Developing NeMo on Mac devices.
# Before your PR is "Ready for review"
**Pre checks**:
- [x] Make sure you... | {
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set model extracted dir such that the save restore connector can load expanded base models. This is required to load large base models so that we can avoid the untaring step during training.
**Collection**: [Note which collection this PR will affect]
# Changelog
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Now it's possible to control display of progress bar when calling `transcribe` method of ASR models.
**Collection**: ASR
# Changelog
- `transcribe` method of ASR models now have `verbose` param, which allows to control display of tqdm progress bar
# Usage
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} | Add Hungarian (incoming in NeMo-text-processing)
# What does this PR do ?
Add a one line overview of what this PR aims to accomplish.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
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} | Cheery-pick from `main` to `r1.17.0_pt_23.04`
* Debug distopt support for BF16 grad reductions
* Dump and load FP32 main params
* Style tweaks
---------
# What does this PR do ?
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Add conformer char and bpe configs for hat model (https://arxiv.org/abs/2003.07705)
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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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**Collection**: [Note which collection this PR will affect]
# Changelog
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# Usage
* You can potentially add a usage example below
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} | # What does this PR do ?
Update previous script for ngram RNNT/HAT beam search decoding by analogy with CTC ngram decoding.
**Collection**: [ASR]
# Changelog
- Add option to return `return_encoder_embiddings` for `rnnt_mode.transcribe()` method (analogy of logits for CTC)
- Update `eval_beamsearch_ngram_tra... | {
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When following guide to Build a Customize Tokenizer, process_asr_text_tokenizer.py does not create intended tokenizer folder with required content. Unable to pre-trained on any models that use BPE vocab since no one can pass anything to the new_tokenizer_dir argument now.
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**Collection**: [NLP]
# Changelog
- Update configs to set tp pp and pp rank all to -1
- Check and update -1 to the model config results
# Before your PR is "Ready for review"
**Pre checks**:
- [x] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/N... | {
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} | # What does this PR do ?
Adds word boosting to the Flashlight decoder in Nemo to mirror this capability in Riva
For more info see here: https://docs.nvidia.com/deeplearning/riva/user-guide/docs/tutorials/asr-python-advanced-wordboosting.html
And here: https://docs.nvidia.com/deeplearning/riva/user-guide/docs/a... | {
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**Collection**: [Note which collection this PR will affect]
# Changelog
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# Usage
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} | # What does this PR do ?
Adds support for twitter cards in addition to open graph
**Collection**: [Docs]
# 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... | {
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} | # What does this PR do ?
Adds [OpenGraph](https://ogp.me/) support to NeMo website for richer URL linking.
**Collection**: [Docs]
# Usage
```markdown
---
title: Template 2022
author: [First Name, Second Name]
author_gh_user: [Github User 1, Github User 2]
read_time: Time to read
publish_date: Date o... | {
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} | # What does this PR do ?
Adds a script to extract p_tuned inference weights.
More details: The ptuning training saves all params including the prompt encoder weights. These are typically not required after training is completed. The script allows you to save the required representations for inference in a separate... | {
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} | # What does this PR do ?
Adds docs for the use of multiple test / validation manifests as enabled in #6306
**Collection**: ASR
# Changelog
- Added docs to `docs/source/asr/configs.rst`
# Usage
Docs only
```python
# Add a code snippet demonstrating how to use this
n/a
```
# Before your PR is "Re... | {
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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
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} | # What does this PR do ?
1. Add a optimization util file for linear sum assignment (LSA) solver algorithm for online-diarization/multi-speaker-ASR
LSA problem solver is needed for the following tasks in NeMo:
(1) Permutation Invariant Loss (PIL) for diarization model training
(2) Label permutatio... | {
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It is with this model "stt_ru_conformer_ctc_large" that I have problems. Can't get timestamps, I'm executing the code:
from nemo.collections.asr.parts.utils.decoder_timestamps_utils import ASRDecoderTimeStamps
asr_decoder_ts = ASRDecoderTimeStamps(cfg.diarizer)
asr_model = asr_decoder_ts.se... | {
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} | # What does this PR do ?
Faster implementation of non-numba specaug
**Collection**: ASR
# Changelog
Rather than repeatedly modify the features tensor in-place, build a mask and fill the features tensor once. By my measurements, about 20x faster on GPU.
It could be faster still, but it gets hard to compa... | {
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**Collection**: [Core, ASR, NLP, TTS]
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This is a duplicate PR of https://github.com/NVIDIA/NeMo/pull/6320 merged in main branch, but the release branch needs this fix as well.
**Collection**: [Note which collection this PR will affect]
# Changelog
- Add specific line by line info of high level changes in this PR.
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**Collection**: NLP
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- Add custom functions to launch distopt communication in interleaved pipeline parallelism (#6183)
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remove pinned numba version in Dockerfile
**Collection**: ASR
# Changelog
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**Collection**: ASR
# Changelog
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Simplified the notebook for p-tuning. Sticks to a simple single task training and inference.
**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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Fixes a but in the signature of narrow().
Fixes #6328
**Collection**: [ASR]
# Changelog
- Casts the length input of all narrow() to int() explicitly
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Fixes #6328
**Collection**: [ASR]
# Changelog
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# Before your PR is "Ready for review"
**Pre checks**:
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Fixes typos in docstring. Removed unused imports
**Collection**: NLP
# Changelog
- fix docstring typos; remove unused imports
# Usage
n/a
# Before your PR is "Ready for review"
**Pre checks**:
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Fix RTD using this: https://github.com/geopandas/dask-geopandas/pull/247
**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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user selected max_seq_len should be less than model's max_seq_len
**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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This PR adds support in applying transformation to the hiddens in Megatron Encoder-Decoder model, and augmenting a corresponding loss. This enables support in latent variable models, like VAE and MIM.
**Collection**: [Note which collection this PR will affect]
# Changelog
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**Collection**: [Note which collection this PR will affect]
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An error occured when trying to finetune tts_en_hifitts_hifigan_ft_fastpitch.nemo
Using a target size (torch.Size([16, 80, 64])) that is different to the input size (torch.Size([16, 80, 129])). This will likely lead to incorrect results due to broadcasting. Please ensure they have the same s... | {
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Please, update the library so that we can use any pytorch models. | {
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Hi. In my scenario `RNNTJoint.forward` produces TypeError and error message is
```
narrow() received an invalid combination of arguments - got (length=Tensor, start=int, dim=int, ), but expected one of:
* (int dim, Tensor start, int length)
didn't match because some of the arguments ha... | {
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} | # What does this PR do ?
Adds functions to enable and disable activation checkpointing and sequence parallelism. This way, we can enable them during training and disable them during inference/generation.
**Collection**: nemo/collections/nlp/language_modeling
# Changelog
- Add specific line by line info of high... | {
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} | # What does this PR do ?
Simplified the notebook for p-tuning. Sticks to a simple single task training and inference.
**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 examp... | {
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} | Restore Thutmose Tagger tutorial, move it to nlp (earlier it was in text_processing)
# 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 P... | {
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} | # What does this PR do ?
This aims to move the megatron checkpoint to nemo conversion to cpu rather than using pytorch distributed following additions introduced [here](https://github.com/NVIDIA/NeMo/pull/6218). This is useful for large models where the user may have checkpoints to consolidate but don't want to use... | {
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} | # What does this PR do ?
If asr_model has preprocessor of type `AudioToMelSpectrogramPreprocessor`, `AudioToSpectrogram`, `AudioToMFCCPreprocessor`, etc., the `StreamingFeatureBufferer` incorrectly determines whether it uses log scale.
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When fine-tuning an ASR model, at some point throughout the first epoch of training, a Numba error occurs:
```
numba.cuda.cudadrv.driver.CudaAPIError: [1] Call to cuLaunchKernel results in CUDA_ERROR_INVALID_VALUE
```
**Steps/Code to reproduce bug**
Here is the code I run:
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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
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} | # What does this PR do ?
- Added RPE for MegatronNMT models
- Fixed an issue with RMSNorm
**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... | {
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} | # What does this PR do ?
This PR makes installation of AIS CLI optional.
**Collection**: Dockerfile
# Changelog
- Update `Dockerfile` to install AIS CLI only if `REQUIRE_AIS_CLI == true`
- Added an installer script for AIS CLI
# Usage
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