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https://api.github.com/repos/NVIDIA/NeMo/issues/2220 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2220/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2220/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2220/events | https://github.com/NVIDIA/NeMo/pull/2220 | 892,602,276 | MDExOlB1bGxSZXF1ZXN0NjQ1MjY3NTYw | 2,220 | Replace model names in VAD tutorials | {
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} | Fix some model names (MatchboxNet -> MarbleNet) in VAD tutorials.
(Thought I've fixed all of them before but it's still there hmm) | {
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"Seems theres some formatting errors, could you run `python setup.py style --scope nemo --fix`",
"This PR will be merged into another PR (https://github.com/NVIDIA/NeMo/pull/2240) due to inactivity. One difference is that it will not raise the error, but instead simply log that the file was not loaded properly.",... | 2021-05-15T23:13:34 | 2021-05-20T01:46:17 | 2021-05-19T23:41:38 | CONTRIBUTOR | {
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} | Signed-off-by: Anas Abou Allaban <aabouallaban@pm.me>
It would be helpful to know offending audio files that fail to load if they are corrupt and/or not supported. | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2218 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2218/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2218/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2218/events | https://github.com/NVIDIA/NeMo/issues/2218 | 892,544,245 | MDU6SXNzdWU4OTI1NDQyNDU= | 2,218 | TarredAudioToTextDataset assumes audio is always wav | {
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"We generally don't prefer to have other file formats for efficiency reasons (wav takes storage but at least it prevents on the fly resampling to 16khz monochannel audio). \r\n\r\nTarred datasets are meant for distributed training on clusters, where network I/O can have a significant impact on training speed. Likew... | 2021-05-15T21:33:30 | 2021-05-28T08:37:25 | 2021-05-28T08:37:25 | CONTRIBUTOR | {
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`TarredAudioToTextDataset` assumes audio is `wav`. However I was able to train a model with `mp3` files and would like `TarredAudioToTextDataset` to support other file types.
**Steps/Code to reproduce bug**
Use any dataset with non-wav files.
**Expected behavior**
Model should be tra... | {
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"These docs are quite outdated, could you point me to where they were referenced so we can update them ?\r\n\r\nThese are the latest docs - https://docs.nvidia.com/deeplearning/nemo/user-guide/docs/en/main/\r\n\r\nThis section (https://docs.nvidia.com/deeplearning/nemo/user-guide/docs/en/main/asr/asr_language_model... | 2021-05-15T21:28:17 | 2021-06-09T12:33:26 | 2021-05-15T23:06:14 | NONE | {
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Am I correct, based on (https://docs.nvidia.com/deeplearning/nemo/user-guide/docs/zh/latest/asr/tutorial.html#using-k... | {
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"Just a note - The manifest file can (and generally it should) have absolute paths to the dataset files when on a local machine, which the tarfile would then use. ",
"> Just a note - The manifest file can (and generally it should) have absolute paths to the dataset files when on a local machine, which the tarfile... | 2021-05-15T21:17:24 | 2021-05-17T22:55:28 | 2021-05-17T22:55:28 | CONTRIBUTOR | {
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} | To preserve disk space on my machine, I generally use symlinks to create different splits of my data.
The tarred audio dataset script doesn't follow symlinks, so simply pass `dereference=True` to the `tarfile.open()` method.
See more info in the python docs: https://docs.python.org/3/library/tarfile.html#tarfile.T... | {
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"Hi, again! I just tried with the `hi-mia` dataset and received the same error ",
"Hi, I just ran `speaker_reco_finetune.py` and everything looks good to me. \r\nCan you make sure you have set the following params in conf/SpeakerNet_verification_3x2x512.yaml:\r\ntrain_set\r\ndev_set\r\ndecoder.emb_sizes: 256\r\nd... | 2021-05-15T11:59:48 | 2021-05-23T11:42:04 | 2021-05-23T11:42:04 | NONE | {
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As an experiment, I was fine-tuning the pre-trained `SpeakerNet` model with the `an4` dataset plus my own voice recordings. I used the example script `speaker_reco_finetune.py` and changed the configuration file according to the documentation and the colab notebook tutorial. But it appears something is always wr... | {
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"I couldn't reproduce any training issues with [this notebook](https://colab.research.google.com/github/NVIDIA/NeMo/blob/r1.0.0rc1/tutorials/nlp/Relation_Extraction-BioMegatron.ipynb) running on Colab. A few warnings do appear during installation but they can be disregarded. \r\nCould you please specify the exact c... | 2021-05-15T01:45:26 | 2021-10-26T23:44:59 | 2021-10-26T23:44:59 | NONE | {
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} | null | null | null | **Describe the bug**
A clear and concise description of what the bug is.
I am trying to use a pretrained model on the relation extraction task and chem-rot dataset. As suggested by the authors, I'm using the notebook provided: Relation-Extraction-BioMegatron.ipynb
**Steps/Code to reproduce bug**
When I run th... | {
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} | # Bugfix
- Fix a memory leak in the WER calculation loop in the notebook
- (NOTE: The notebook content has not changed, the diff is just large cause colab version updated)
# Update
- Update the model notebook to use the new artifact system + log the loss properly
Closes https://github.com/NVIDIA/NeMo/issues/22... | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2212 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2212/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2212/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2212/events | https://github.com/NVIDIA/NeMo/issues/2212 | 892,297,081 | MDU6SXNzdWU4OTIyOTcwODE= | 2,212 | Problem installing NeMo from pip | {
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"which pip version do you have? Could be a problem with your environment. Are you able to pip install other packages? Like this: ```pip install pytorch-lightning==1.1.4``` ? I literally copy-pasted this: ```pip install nemo_toolkit[all]==1.0.0rc1``` and it worked."
] | 2021-05-14T23:11:58 | 2021-05-17T17:59:49 | 2021-05-17T17:59:49 | MEMBER | {
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I have a problem installing NeMo from pip. I'm using the instructions [here](https://docs.nvidia.com/deeplearning/nemo/user-guide/docs/en/stable/starthere/intro.html#pip)
Following them, I'm getting:
```
(venv) ✘ mszolucha@szal-workstation ~ sudo apt-get update && sudo apt-get install -y libsndfile1 ff... | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2211 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2211/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2211/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2211/events | https://github.com/NVIDIA/NeMo/pull/2211 | 892,233,163 | MDExOlB1bGxSZXF1ZXN0NjQ0OTc3Njc2 | 2,211 | Update models and notebook for 1.0 | {
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"This pull request **introduces 1 alert** when merging 85b00da1038709cc1b145f28c8e8dd043efb2932 into d1b37ed30a70bff00df4778b55b020d8bab2e6fb - [view on LGTM.com](https://lgtm.com/projects/g/NVIDIA/NeMo/rev/pr-df3f0c730d38a856855a25d9a48542d309857460)\n\n**new alerts:**\n\n* 1 for Variable defined multiple times",
... | 2021-05-14T20:48:05 | 2021-05-18T18:56:24 | 2021-05-18T18:56:22 | COLLABORATOR | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2210 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2210/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2210/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2210/events | https://github.com/NVIDIA/NeMo/pull/2210 | 891,991,299 | MDExOlB1bGxSZXF1ZXN0NjQ0NzcwNjE5 | 2,210 | Small updates in TalkNet and FastPitch | {
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} | * update `_loader` method in TalkNet and FastPitch for easy creating model from config for non-training/validating purposes (e.g. just check inference speed).
* update FastPitch config | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2209 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2209/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2209/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2209/events | https://github.com/NVIDIA/NeMo/pull/2209 | 891,550,956 | MDExOlB1bGxSZXF1ZXN0NjQ0NDA0OTc4 | 2,209 | fix the versioning name. | {
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"> \r\n> \r\n> Doesn't this just dump the files into the project dir? @blisc any thoughts if this is correct ?\r\n\r\nActually I made this from \"\" to None last time to hope it fixes the w&b but it made the issue that now we have a folder name \"None\" and then there is another folder under that named \"checkpoint... | 2021-05-14T02:58:08 | 2021-08-06T08:01:13 | 2021-05-17T13:30:09 | COLLABORATOR | {
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"Thanks for finding this, I'll send a PR tomorrow patching this. If you only need inference, you can freeze the model with model.freeze() and this will prevent any leak. \r\n\r\nIt's the notebook environment which has the potential for leaking cuda tensors, and scripts don't have this leakage.\r\n\r\nThe notebooks ... | 2021-05-14T02:07:58 | 2021-05-15T08:41:11 | 2021-05-15T08:41:11 | NONE | {
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} | null | null | null | Running 01_ASR_with_NeMo.ipynb WER cells appears to be leaking data in CUDA. With batch_size 32, using print(torch.cuda.memory_allocated()) prints 91,033,600 prior to running, then 129,805,824 after. There's a hard delete in https://github.com/NVIDIA/NeMo/blob/8e239ecc7d7bc1206c72daa207b0f122e85551f1/examples/asr/speec... | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2207 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2207/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2207/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2207/events | https://github.com/NVIDIA/NeMo/pull/2207 | 891,523,702 | MDExOlB1bGxSZXF1ZXN0NjQ0MzgyMzc0 | 2,207 | ASR patches for v1.0.0 | {
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"@okuchaiev fyi regarding the dockerfile ignore and correctly updating the self.trainer inside set_trainer."
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} | # Bugfixes
- Correct WER calculation for RNNT by resetting the metric after each computation.
- Prevent numba from performing a sync across PT cuda stream simply to initialize a cost vector.
- Correctly update the trainer value using `set_trainer`
- Adds .nemo and .ckpt files to dockerignore
# Additions
- Adds ... | {
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} | # Changelog
- cherry pick the bugfix from main for SpecCutout into v1.0.0
Refer to https://github.com/NVIDIA/NeMo/pull/2201 | {
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"Closing. re-open if issue is still relevant."
] | 2021-05-13T01:12:36 | 2022-04-05T23:35:56 | 2022-04-05T23:35:56 | CONTRIBUTOR | {
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I would like to store my checkpoints/models using AWS/GCP so that when I run training on ephemeral instances, I don't lose my progress.
**Describe the solution you'd like**
Register a new callback on epoch end to upload the ckpt/Nemo file to AWS/GCP... | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2201 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2201/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2201/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2201/events | https://github.com/NVIDIA/NeMo/pull/2201 | 890,224,909 | MDExOlB1bGxSZXF1ZXN0NjQzMjc4Mzk1 | 2,201 | Fix bug in SpecCutout | {
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"Thanks Robert for catching the bug! It looks like it has been around for a long time.\r\nWhy do you believe that \"it causes the placement of the masks to be limited to the lowest frequency bins\"?\r\nThe starting point for the frequency masking looks correct to me and can be any frequency. The only problem is tha... | 2021-05-12T15:39:02 | 2021-05-13T17:54:12 | 2021-05-13T17:54:12 | CONTRIBUTOR | {
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} | [Colab notebook demonstrating bug and fix](https://colab.research.google.com/drive/1Tksb-RXAeLSkBW72KDgm1DYUaPAnHXBx?usp=sharing)
There is a bug in the NeMo implementation of SpecCutout that causes the dimensions of masks to be transposed so that `rect_freq` is the size of the mask in the time dimension and `rect_ti... | {
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"You generally should not train with such long sequences, since it would use far too much memory + enormous amounts of training data + compute to train a model on long segments. Generally durations of 15-20 second segments are used for training. \r\n\r\nIt would be best to segment the audio in the second dataset. I... | 2021-05-12T07:13:23 | 2021-07-13T15:26:34 | 2021-07-13T15:26:34 | NONE | {
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I used QuartNet15*5 and fine-tuned it with the Persian Common Voice dataset. the WER was 30%.
Everything worked well and I saved it as a checkpoint.
After a while, I restored the checkpoint. I fine-tuned it with another Persian data set that has a longer duration than 16.7 seconds (i.e., 2 minutes, 3minutes, a... | {
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"Thanks for the PR, could you sign your commit according to the instructions on the dco bot ?(https://github.com/NVIDIA/NeMo/pull/2199/checks?check_run_id=2563046850)\r\n",
"@titu1994 done with the signoff",
"Thanks for the fix !"
] | 2021-05-12T05:38:08 | 2021-05-12T18:43:26 | 2021-05-12T15:55:37 | CONTRIBUTOR | {
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"wouldn't this break all the checkpoints trained with pre_ln=True?",
"This pull request **introduces 1 alert** when merging 06d1bb03d4144ea1d95b1656083db015711489c2 into d1b37ed30a70bff00df4778b55b020d8bab2e6fb - [view on LGTM.com](https://lgtm.com/projects/g/NVIDIA/NeMo/rev/pr-72c6d188f1fb006ed4703c0de0401a0abd5... | 2021-05-11T21:16:59 | 2021-05-18T17:07:28 | 2021-05-18T17:07:23 | COLLABORATOR | {
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Signed-off-by: Jocelyn Huang <jocelynh@nvidia.com> | {
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"+ please run tests in an env that does not have pynini installed to ensure pytest tests/ --cpu is runnable "
] | 2021-05-11T18:25:09 | 2021-05-12T21:23:01 | 2021-05-12T21:22:58 | CONTRIBUTOR | {
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} | * Allow models such as facebook/bart-large in NMT encoder
* Fixes in nmt webapp | {
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} | # Changelog
- Adds the support to change the SqueezeExcite context window post instantiation inside a given ConvASREncoder module.
- Adds tests to ensure the model updates the configs and changes the modules SE behaviour
# Usage
```python
model = ASRModel.from_pretrained("stt_en_citrinet_256")
model.change_co... | {
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"What are you trying to accomplish? a) just to extract .pt from .nemo or b) export the model to Torchscript ? \r\nIf a): then simply use 'tar xvf model.nemo'\r\nIf b): Megatron model currently is not exportable to Torchscript. You can export it to ONNX though by supplying name with .onnx extension to export()\r\n",... | 2021-05-10T23:34:11 | 2021-05-18T01:15:04 | 2021-05-18T01:15:04 | NONE | {
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When trying to do a `model.export()` of `qa_squadv2.0_megatron_uncased` nemo model I get `RuntimeError: Could not export Python function call '_ReduceFromModelParallelRegion'`
**Steps/Code to reproduce bug**
```
wget --content-disposition https://api.ngc.nvidia.com/v2/models/nvidia/nemo/... | {
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"LGTM."
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"I'm not too familiar with the internals of PTL, but I'm guessing the solution is to determine whether there are GPUs _or_ TPUs and not _just_ GPUs.",
"We don't support TPU training, and it's not tested. If you get it working, please let us know. ",
"looks like you can try disabling learning rate scheduler. but... | 2021-05-08T18:13:51 | 2021-05-10T22:18:39 | 2021-05-10T22:18:39 | CONTRIBUTOR | {
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Training any model does not work with TPUs due to an error with the way `modelPT.py` calculates `optim_config['sched']['t_num_workers']` [here](https://github.com/NVIDIA/NeMo/blob/main/nemo/core/classes/modelPT.py#L649).
When you have 0 GPUs, but are still using TPUs, `t_num_workers` is 0.
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- UI improvements
- refactored code | {
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"It's better to have higher number_of_samples/speaker with shorter durations (of about 4 sec) than vice versa. ",
"Hi, @nithinraok Thank you!"
] | 2021-05-08T08:36:40 | 2021-05-28T08:39:41 | 2021-05-28T08:39:41 | NONE | {
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I was trying to fine-tune the pre-trained speaker recognition model [`Speakernet`](https://ngc.nvidia.com/catalog/models/nvidia:nemo:speakerrecognition_speakernet) in order for it to recognize our registered speakers. I noticed in the tutorials the dataset `an4` was only used for illustration purposes, I ... | {
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"This should be fixed via https://github.com/NVIDIA/NeMo/pull/2178"
] | 2021-05-08T03:44:37 | 2021-05-10T17:38:26 | 2021-05-10T17:38:26 | NONE | {
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`requirements/requirements.txt` has `pytorch-lightning>=1.2.8` which could lead the installation of pytorch-lightning 1.3.0.
Or aybe you are already planning on supporting 1.3.0? | {
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"Librispeech KenLM should be built on concatenated datasets of entire Librispeech lm text corpus (after normalization to lower case) + the 3 train transcripts. Overall it should be close to 41 M lines of text rather than the 300k lines of text here. \r\n\r\nSecondly, this sentence is confusing - \"However I got hig... | 2021-05-07T20:12:08 | 2021-05-10T22:16:19 | 2021-05-10T22:16:18 | NONE | {
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} | null | null | null | Hi,
I trained a Language Model with [train_kenlm.py](https://github.com/NVIDIA/NeMo/blob/main/scripts/asr_language_modeling/ngram_lm/train_kenlm.py) (**6-gram** with **286967 l**ines of text collected from LibriSpeech's train_clean_100, train_clean_360, train_other_500 and some other standard English text lines).
... | {
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} | Signed-off-by: Jocelyn Huang <jocelynh@nvidia.com> | {
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"This pull reque... | 2021-05-07T19:04:37 | 2021-05-07T21:50:39 | 2021-05-07T21:50:36 | CONTRIBUTOR | {
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} | improved cardinal in textnormalization in terms of perf | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2178 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2178/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2178/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2178/events | https://github.com/NVIDIA/NeMo/pull/2178 | 879,303,348 | MDExOlB1bGxSZXF1ZXN0NjMzMDMxOTcw | 2,178 | Update ptl to 1.3 on main branch | {
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} | # Changelog
- Update PTL to 1.3
- Fix related broken tests in NeMo | {
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"Thanks for noticing this bug. I'll fix this in #2166 ",
"Oh, it looks like someone already fixed it. We will fix this in the upcoming 1.0 release."
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} | variable name `spec_gen` was used for parsing text and creating spectogram, which should be `spec_generator` | {
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"If it's the KenLM binary causing the memory issue, then a smaller N-gram can be used. However we don't have much control over the c++ swig decoders so from our side there isn't a sufficient solution to reduce memory. Maybe @vsl9 has some ideas?",
"If the memory issue is from the beam search decoder, then you may... | 2021-05-07T12:50:17 | 2021-05-28T08:37:02 | 2021-05-28T08:37:02 | NONE | {
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"> exortable changes look good to me. @blisc what about tts changes?\r\n\r\ntts changes are to conform to new extended syntax accepted by onnx.export (optional Dict as the last input tuple element, representing kwargs) instead of former non-standard extended syntax I briefly introduced in previous revision (accepti... | 2021-05-07T04:16:52 | 2021-05-17T13:30:17 | 2021-05-17T13:30:17 | COLLABORATOR | {
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} | Also, removed previous (non–functional) extension for dicts in export - this schema matches what onnx.export expects.
Signed-off-by: Boris Fomitchev <bfomitchev@nvidia.com> | {
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} | # Bugfix
- Make all ITN tests optional (will run only if installed)
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https://github.com/NVIDIA/NeMo/issues/2161 | {
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} | # Changelog
- Upper bounds PTL version to 1.2.10 for main branch
Signed-off-by: smajumdar <titu1994@gmail.com> | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2169 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2169/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2169/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2169/events | https://github.com/NVIDIA/NeMo/pull/2169 | 878,129,291 | MDExOlB1bGxSZXF1ZXN0NjMxOTkxMDg0 | 2,169 | token classification models artifacts update | {
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"@okuchaiev @ericharper we need to enable the full CI before merging this",
"> @okuchaiev @ericharper we need to enable the full CI before merging this\r\n\r\nLooks like the Jenkinsfile reverted to main. I replaced with v1.0.0 again."
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https://api.github.com/repos/NVIDIA/NeMo/issues/2168 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2168/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2168/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2168/events | https://github.com/NVIDIA/NeMo/pull/2168 | 878,088,379 | MDExOlB1bGxSZXF1ZXN0NjMxOTUzOTI3 | 2,168 | [DOCS] NLP Model parallel, NMT multi-val, CORE register artifacts | {
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"@titu1994 Could you review the register_artifact docs?\r\n\r\n@MaximumEntropy Could you review NLP/NMT docs?\r\n\r\n"
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] | 2021-05-06T08:31:24 | 2022-12-19T21:50:18 | 2021-05-17T16:24:47 | NONE | {
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It works fine after replacing `zero` with `o`
I think this is because `zero` is in `zero.tsv` not `digit.tsv`, and you are not including `zero.tsv` in the digit FST.
https://github.com/NVIDIA/NeMo/blob/74f1264e049c1... | {
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} | This PR adds support for multilingual training for NMT.
### Usage ###
To train a model in multilingual mode, simply set the following:
* `model.multilingual=True`
* `model.encoder_tokenizer.library=sentencepiece` and `model.decoder_tokenizer.library=sentencepiece`.
Currently we only support sentencepiece f... | {
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} | This PR makes changes to the HifiGan module that should make it jittable/torchscriptable. nemo export should work as well.
Verified compatible with checkpoint on NGC.
```python
from nemo.collections.tts.models import HifiGanModel
model = HifiGanModel.from_pretrained(model_name="tts_hifigan")
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} | This PR :
* Adds new NMSE spectral clustering method
* Updates Docs to include dataset creation for any dataset, with special mentions for AMI and CH109.
* Adds ability to diarize for unknown number of speakers/session with very good accuracies
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} | # Changelog
- All references of r1.0.0rc1 -> v1.0.0
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"Hello,\r\nIt looks like your nemo file does not have the model weights checkpoint that should be saved. Can you untar the nemo file and make sure it has a model_weights.ckpt and model_config.yaml? If it doesn't, please let me know what the contents are.",
"> Hello,\r\n> It looks like your nemo file does not have... | 2021-05-05T07:58:49 | 2021-05-12T07:06:54 | 2021-05-12T07:06:54 | NONE | {
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I use command for build jmir like in https://docs.nvidia.com/deeplearning/jarvis/user-guide/docs/service-tts.html#pipeline-configuration .
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"@ekmb note that v1.0.0 has been cut. If this is a bugfix, send it to v1.0.0\r\n"
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} | Signed-off-by: Vahid <vnoroozi@nvidia.com> | {
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"@VahidooX fyi",
"The transcribe method used to return Tensors, but now it returns numpy arrays. So softmax does not need the conversion. I think you are using an older version of NeMo with the old transcribe method.",
"@EmreOzkose \r\nHi!\r\n\r\nDid you try to run eval_beamsearch_ngram.py from inside of Docke... | 2021-05-03T09:18:08 | 2021-06-25T10:32:09 | 2021-05-03T09:18:14 | NONE | {
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} | null | null | null | Hi! I encountered a problem during inference of Citrinet-1024 with a language model. When I run [eval_beamsearch_ngram.py](https://github.com/NVIDIA/NeMo/blob/main/scripts/asr_language_modeling/ngram_lm/eval_beamsearch_ngram.py), output is :
```
Traceback (most recent call last):
File "eval_beamsearch_ngram.py",... | {
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"Thanks for the PR ! It was an oversight since for papers we use batch size 1 with transcribe() method, and it disables dithering inside."
] | 2021-05-01T22:42:49 | 2021-05-02T20:02:09 | 2021-05-02T20:00:14 | CONTRIBUTOR | {
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} | In the eval mode the model should be deterministic (return the same value for the same input).
I find it strange that this was not fixed before - this makes exports and evaluation non-deterministic. | {
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"Could you try quartzner with batch size 1?",
"Issue solved, SpecAugment and SpecCutout weren't getting the seed, setting the seed manually on their rng with `self._rng.seed(8)` in the `__init__()` of each solved the issue. Thank you. "
] | 2021-04-30T22:24:59 | 2021-05-01T14:01:45 | 2021-05-01T14:01:45 | CONTRIBUTOR | {
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} | null | null | null | I'm working on implementing something new but I'm having trouble getting the model to output the same thing each time. The output from the featurizer is consistent, but the output from Quartznet 15x5 (encoder + decoder) is slightly different each time. I am aware of #1030 and have taken the following steps.
- Set p... | {
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} | …orting
I did not remove graph surgeon install from Dockerfile - as it's nice to have anyway and maybe some users already use it.
But I did remove the extra GS step on export. | {
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} | Adding:
- Data loading test for the `FastSpeech2Dataset`
- FS2 data format documentation
- Some TTS class APIs | {
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"@EmreOzkose change. you have changed “Citrinet” in place of “quartznet”. you should change the class name which should be “nemo.asr.models.EncDecCTCModelBPE” at place of “nemo.asr.models.EncDecCTCModel”. ",
"I changed the class name, but it didn't work.",
"The kenlm model being used is meant for Character enc... | 2021-04-30T08:04:17 | 2024-01-28T09:24:12 | 2021-05-05T08:40:29 | NONE | {
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} | null | null | null | Hi, I am using Citrinet models to transcribe an audio (taken from Mini-Librispeech) and it transcribes good. However when I use beam search decoding [in this tutorial](https://github.com/NVIDIA/NeMo/blob/acbd88257f20e776c09f5015b8a793e1bcfa584d/tutorials/asr/Offline_ASR.ipynb), I am getting nonrelevant results. What ca... | {
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"@VahidooX Thank you for your response! I had to set `... | 2021-04-29T12:16:36 | 2021-05-06T13:43:24 | 2021-05-06T13:43:24 | NONE | {
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} | This PR changes the following:
* how register_artifacts work
* how save_to works
The usage of both register_artifacts and save_to method remains identical.
Key differences in behaiviour:
* register_artifacts always guarantees to return existing path to artifact at the time of call.
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"Can you send this to v1.0.0 instead?",
"@blisc ready for review",
"link is fixed\r\nbranch choice is yet to be commented by @blisc ",
"> link is fixed\r\n> branch choice is yet to be commented by @blisc\r\n\r\nPlease use `v1.0.0` for all files and branches",
"Okay, now it's ready to be merged."
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} | # Bugfix
- ASR BPE models did not correctly preserve the new tokenizer config after changing vocabulary
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* merge electronic (Evelina)
* updated docs for ITN and TN
* updated Tutorials
* unified deployment route
* unit tests for both | {
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"> The model is trained and I get a fina .nemo file at the end. Now, if I look at the config inside the final \"adapted\" model, I see\r\n\r\nQuite a silent bug there, sending a patch in https://github.com/NVIDIA/NeMo/pull/2126\r\n\r\nWe normally follow this procedure for finetuning our models as well, but didnt fa... | 2021-04-26T17:01:13 | 2021-05-28T08:36:21 | 2021-05-28T08:36:21 | NONE | {
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It seems that while the vocabulary is updated and the model is trained, trying to restore the model from checkpoint still uses the old tokenizer path.
**Steps/Code to reproduce bug**
I did something very similar to what's in the 08_ASR_with_Subword_Tokenization.ipynb notebook:
```
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2. Perplexity metric refactored to take into account samples of different length in a batch. | {
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"Please post your environment - torch version, pytorch lightning version, colab of local, etc. \r\n\r\nThere's no official b4 docker container, so I assume a local docker container was built. \r\n\r\nAnother thing is main branch codebase does not work with RC1 container, please build a container for main specifical... | 2021-04-26T11:50:46 | 2021-06-19T04:37:32 | 2021-06-19T04:37:32 | COLLABORATOR | {
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Error during saving first checkpoint in 1.0.0rc1 and main branches
``` Epoch 0: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 563/563 [02:55<00:00, 3.20it/s, loss=767, v_num=6-59E... | {
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"UPDATE:\r\nI tried all the steps of inference in the [qa_model inference](https://github.com/NVIDIA/NeMo/blob/main/nemo/collections/nlp/models/question_answering/qa_model.py#L183) script, here instead of forward pass I did the pass through the onnx inference session and everything worked properly with exact result... | 2021-04-26T08:54:06 | 2021-05-11T13:59:49 | 2021-04-28T12:49:22 | NONE | {
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} | null | null | null | **Describe the bug**
I am trying to export the nemo_nlp QAModel to onnx format in order to deploy it on triton. I am able to do so using this block of code:
`restored_model = nemo_nlp.models.QAModel.restore_from('finetuning_bert_base_uncased_squad.nemo')
restored_model.export("test_bert_onnx/model.onnx")`
And i... | {
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"This pull request **introduces 2 alerts** when merging 1ce64a75065b53909e042395c27bf1a35f68309d into b4040fb37350ae86b64a5f53be911371d7a3879d - [view on LGTM.com](https://lgtm.com/projects/g/NVIDIA/NeMo/rev/pr-8c2c9c4c374e615c273837a54858c8611874091b)\n\n**new alerts:**\n\n* 1 for Unused local variable\n* 1 for Un... | 2021-04-26T06:13:54 | 2021-04-26T07:07:00 | 2021-04-26T07:05:54 | NONE | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2114 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2114/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2114/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2114/events | https://github.com/NVIDIA/NeMo/pull/2114 | 866,906,376 | MDExOlB1bGxSZXF1ZXN0NjIyNjkwNTEy | 2,114 | [docs] Reviewed/edited NeMo doc files | {
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"Hi Lynsey, could you resolve the merge conflicts with current main? I took a look and they seem to be from others' recent documentation updates.",
"looks like all these changes are already there."
] | 2021-04-25T04:07:31 | 2022-09-22T17:08:09 | 2021-07-19T23:04:54 | CONTRIBUTOR | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2113 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2113/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2113/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2113/events | https://github.com/NVIDIA/NeMo/pull/2113 | 866,836,900 | MDExOlB1bGxSZXF1ZXN0NjIyNjQ4NTg5 | 2,113 | [NMT] Add support for multiple validation and test dataloaders | {
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} | Specify multiple validation (or test) dataloaders by inputting a list of src (tgt) files.
# Usage
Replace `src_file_name` and `tgt_file_name` with a list of file paths.
```
model.validation_ds.src_file_name=/data/wmt14-en-de.src \
model.validation_ds.tgt_file_name=/data/wmt14-en-de.ref \
```
Becomes:
... | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/2112 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/2112/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/2112/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/2112/events | https://github.com/NVIDIA/NeMo/issues/2112 | 866,761,597 | MDU6SXNzdWU4NjY3NjE1OTc= | 2,112 | I get an incompatible library version error | {
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"(1) Please try running it Google's Colab (which would have a clean environment and should work)\r\n(2) If you try running it locally, I'd recommend creating a new conda environment with Python 3.8 (and without Pytorch, Torchtext, etc.). This way when you do \"pip install ...\" correct versions of torch and torchte... | 2021-04-24T14:39:12 | 2021-06-19T04:37:12 | 2021-06-19T04:37:12 | NONE | {
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} | null | null | null | I run the code in https://github.com/NVIDIA/NeMo/blob/main/tutorials/asr/06_Voice_Activiy_Detection.ipynb, however I got again an error while runing below cell:
1 # NeMo's "core" package
----> 2 import nemo
3 # NeMo's ASR collection - this collections contains complete ASR models and
4 # building blocks (module... | {
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