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"I am also getting this error",
"It looks like the latest version of transformers (4.0.1) is being installed. I reverted to 3.5, and the code works.\r\nBefore importing nemo.collections, run the following and it should work:\r\n```\r\n!pip uninstall transformers\r\n!pip install transformers==3.5\r\n```\r\n",
"T... | 2020-12-16T11:17:09 | 2022-04-05T20:40:57 | 2020-12-18T04:57:17 | NONE | {
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} | null | null | null | Hello. I am getting an error.
I was using the[ Sentiment analysis notebook](https://colab.research.google.com/github/NVIDIA/NeMo/blob/v1.0.0b2/tutorials/nlp/Text_Classification_Sentiment_Analysis.ipynb#scrollTo=dzqD2WDFOIN-) on colab by NVIDIA NeMo
I followed the instructions as it said(run the first cell if you are... | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/1565 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/1565/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/1565/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/1565/events | https://github.com/NVIDIA/NeMo/pull/1565 | 768,337,144 | MDExOlB1bGxSZXF1ZXN0NTQwODA4ODEw | 1,565 | Correct ASR issues + Patch for Pytorch 1.8 | {
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"@blisc Could you review the TTS side changes to `stft` and `torch.ifft`?",
"trim_silence default in the model.transcribe method is still True!\r\nThis issue can be seen here:\r\ncollections/asr/models/ctc_models.py: _setup_transcribe_dataloader"
] | 2020-12-16T00:31:07 | 2021-07-06T07:22:02 | 2020-12-17T22:15:00 | COLLABORATOR | {
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} | # Changelog
- `trim_silence` will now be False by default for all dataloaders in ASR and only active for train_ds (set by flag in config).
- Update ASR stft, ifft ops to be compatible with Pytorch 1.8 deprecation warnings
Note:
- Due to change in `trim_silence`, scores obtained via trainer.test(), or model.transc... | {
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In the notebook [Token_Classification_Named_Entity_Recognition.ipynb](https://github.com/NVIDIA/NeMo/blob/main/tutorials/nlp/Token_Classification_Named_Entity_Recognition.ipynb), the last cell specifies a specific gpu, which happens to be the second gpu, when it most likely was meant to specify ... | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/1563 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/1563/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/1563/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/1563/events | https://github.com/NVIDIA/NeMo/pull/1563 | 768,261,262 | MDExOlB1bGxSZXF1ZXN0NTQwNzYwMjY2 | 1,563 | Adding the feature of variational noise to the RNNT-based models | {
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} | It is going to add Gaussian noise to the decoder's weights of rnnt models after each step to avoid overfitting.
This section need to be added to the model section of the config:
```
model:
variational_noise:
std: 0.075
start_step: 2000
```
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"ping @stasbel ",
"This pull request **introduces 2 alerts** when merging bb66ad0cb949eab426b3fd510525e4edcf0fdace into fc4017a08db4cf2aaad2288dd158e9c287f7107a - [view on LGTM.com](https://lgtm.com/projects/g/NVIDIA/NeMo/rev/pr-01fe481edaf7d6ac977150b56a2b758a568a4873)\n\n**new alerts:**\n\n* 1 for Unused impor... | 2020-12-15T15:43:36 | 2021-04-01T16:45:35 | 2021-03-09T22:47:19 | CONTRIBUTOR | {
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} | TODOs:
- [x] Pitch predictor (with available models)
- [x] Spect prediction new things (with available models)
- [x] Durs predictor (with available models)
- [x] LJSpeech with durs and f0
- [x] 3x pretrained models (no need)
- [x] Documentation
- [x] Update TTS Notebook inference
Signed-off-by: Stanislav Beli... | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/1561 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/1561/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/1561/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/1561/events | https://github.com/NVIDIA/NeMo/issues/1561 | 767,635,329 | MDU6SXNzdWU3Njc2MzUzMjk= | 1,561 | Nemo ASR silently trims silence on valid/test set | {
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"Hey @rbracco, thanks for pointing this out! I submitted a PR to patch this bug.",
"Thank you for all that you do for the repo! "
] | 2020-12-15T14:11:34 | 2020-12-16T01:04:17 | 2020-12-16T01:04:17 | CONTRIBUTOR | {
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My assumption would be that `trim_silence` would be False for valid/test unless explicitly turned on. It appears that that is the intention [here in the CTC Models Config](https://github.com/NVIDIA/NeMo/blob/f0378b10cdadc82752d70032bd80219e531519c0/nemo/collections/asr/models/configs/ctc_models_... | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/1560 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/1560/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/1560/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/1560/events | https://github.com/NVIDIA/NeMo/issues/1560 | 767,439,096 | MDU6SXNzdWU3Njc0MzkwOTY= | 1,560 | Docker image "v1.0.0b3 not found" | {
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"Do you mean v1.0.0b2? I haven't seen a b3 version yet, but there is a branch called r1.0.0b3.",
"Well, I assumed since there is [v1.0.0b3](https://github.com/NVIDIA/NeMo/releases/tag/v1.0.0b3) release, then is should be docker image for that version.",
"Sorry, I missed the 1.0.0b3 release, you are correct! In ... | 2020-12-15T10:32:08 | 2020-12-16T17:49:50 | 2020-12-16T17:49:50 | NONE | {
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```bash
docker pull nvcr.io/nvidia/nemo:v1.0.0b3
Error response from daemon: manifest for nvcr.io/nvidia/nemo:v1.0.0b3 not found: manifest unknown: manifest unknown
```
Similar to #1498 | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/1559 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/1559/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/1559/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/1559/events | https://github.com/NVIDIA/NeMo/pull/1559 | 766,952,546 | MDExOlB1bGxSZXF1ZXN0NTM5ODE3MDcx | 1,559 | Sphinx Bibtext Fix | {
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"This pull request **fixes 9 alerts** when merging 4f9ad400d51c3fe596d79169394c70ad936cb80b into d01b7bbc3fdb1bbf14789f71b8f368cf0aa8f86b - [view on LGTM.com](https://lgtm.com/projects/g/NVIDIA/NeMo/rev/pr-80363198ef854198c67fd4639ab1230057dd89b0)\n\n**fixed alerts:**\n\n* 9 for Unused import",
"This pull request... | 2020-12-14T19:33:39 | 2020-12-15T17:30:28 | 2020-12-15T17:30:24 | COLLABORATOR | {
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} | 1. Branch for Bio-related notebooks changed to `main`, for the rest of the notebooks to `v1.0.0b3`
2. Fixed Bio-megatron download issue | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/1557 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/1557/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/1557/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/1557/events | https://github.com/NVIDIA/NeMo/pull/1557 | 766,846,095 | MDExOlB1bGxSZXF1ZXN0NTM5NzQ1MTEy | 1,557 | Fix tacotron2 batch size 1 bug | {
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"Thanks for catching this bug. It should be fixed now"
] | 2020-12-14T16:26:23 | 2020-12-14T19:50:56 | 2020-12-14T19:50:37 | NONE | {
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} | null | null | null | **Describe the bug**
Training (or just passing input with ground-truth spectrogram) Tacotron2 with a batch dimension of 1 does not work due to a dimension problem when aggregating the gate outputs.
The line here
https://github.com/NVIDIA/NeMo/blob/d01b7bbc3fdb1bbf14789f71b8f368cf0aa8f86b/nemo/collections/tts/mod... | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/1555 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/1555/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/1555/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/1555/events | https://github.com/NVIDIA/NeMo/issues/1555 | 766,674,345 | MDU6SXNzdWU3NjY2NzQzNDU= | 1,555 | VAD infer script looks broken | {
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"Hi @diego-fustes Thanks for reporting this. \r\nYou don't need to include the parameter batch_size in the dict passed. [It's been set here.](https://github.com/NVIDIA/NeMo/blob/9da1d27ddd7f1d5d9b6cd75f7308787976680dd8/nemo/collections/asr/models/classification_models.py#L167) \r\nThere isn't a vad_infer.py in v1... | 2020-12-14T16:10:02 | 2020-12-15T18:10:15 | 2020-12-15T18:06:22 | CONTRIBUTOR | {
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} | null | null | null | I'm trying to perform Voice Activity Detection with NeMo using the script _vad_infer.py_ that is included in the examples. However, the following error comes at first:
```
Traceback (most recent call last):
File "/home/diego/Sutherland/speechanalytics/speechanalyticsapi/speechanalytics/test.py", line 159, in <... | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/1554 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/1554/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/1554/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/1554/events | https://github.com/NVIDIA/NeMo/issues/1554 | 766,416,344 | MDU6SXNzdWU3NjY0MTYzNDQ= | 1,554 | NLP Tutorial notebooks for Biomegatron-bert | {
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"@avikpal00 thank you for reporting the issue. PR #1558 should fix it, no need to change the transformers version.",
"@ekmb I am still getting this error for the tutorial notebook [Token_Classification-BioMegatron.ipynb](https://colab.research.google.com/github/NVIDIA/NeMo/blob/r1.0.0b3/tutorials/nlp/Token_Classi... | 2020-12-14T13:09:42 | 2021-01-06T00:10:23 | 2020-12-15T17:30:24 | NONE | {
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} | null | null | null | **Describe the bug**
Not able to download and initialize the pretrained biomegatron bert model.
config.model.language_model.pretrained_model_name = "biomegatron-bert-345m-cased"
Error Line: nemo_nlp.models.TokenClassificationModel(cfg=config.model, trainer=trainer)
Error: 'OSError: Distant resource does not h... | {
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"Can you share your training command? As well as the python file that you're using?",
"Sorry, It is my fault. I found that I was not pass parameter correctly to trainer, so it use default configuration. And solved this problem. I saw the example in \"speech_to_text.py\" and found I should pass parameters separate... | 2020-12-14T03:57:40 | 2020-12-16T02:14:49 | 2020-12-15T15:35:06 | NONE | {
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I setup the config.yaml and run the script. It thorw this message
"The pytorch lightning trainer that was passed to exp_manager contained a logger, and either "
nemo.utils.exp_manager.LoggerMisconfigurationError: The pytorch lightning trainer that was passed to exp_manager contained a logger, and ei... | {
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"\"pip install nemo_toolkit[all]\" will install an OLD version without PTL (0.11).\r\n\r\nTry: \"pip install nemo_toolkit[all]=1.0.0b3\"\r\n\r\nAt the moment we do not do... | 2020-12-13T14:12:51 | 2021-02-10T23:27:40 | 2021-02-10T23:27:40 | NONE | {
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NeMo installs flawessly with pip3 install nemo_toolkit[all]. Also reinstall.sh does not throw an error and ends with success message although it comments that nemo asr, nlp and tts will not be removed since they are not installed (?!).
Again nemo_toolkit[asr], nemo_toolkit[nlp... | {
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"@vladgets can ... | 2020-12-12T02:52:50 | 2020-12-14T22:49:51 | 2020-12-14T22:49:42 | CONTRIBUTOR | {
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"what is the task or example you were trying to run? Did you first run with internet data and then later without internet? Some examples where we fetch model from NGC needs to be run with the internet, probably your example got stuck there. "
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If this is the case, do you know where it happens? I can... | {
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"Any word on this @titu1994? I'm curious if theres a specific reason. I'm starting to use CommonVoice English and it's 56GB when stored as MP3 so it will be unusable in wav format. Thank you!",
"@vsl9 Any thoughts about this ? ",
"Hi\r\n\r\ntorchaudio developer here. Recently [I am adding support for file-like ... | 2020-12-11T17:25:49 | 2021-06-19T04:43:34 | 2021-06-19T04:43:34 | CONTRIBUTOR | {
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It appears that NeMo only works with wav files, but they are 10x larger than equivalent MP3s. Many popular datasets like Mozilla Commonvoice are stored as MP3 and have to be converted before being used. This is time consuming and also makes it harder... | {
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* added pytests
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"Some details can be found here - https://arxiv.org/abs/2010.12715"
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"Retrying building pytorch etc from source:\r\nUsing transformers==4.0.0:\r\npython\r\nimport nemo\r\nimport nemo.collections.asr as nemo_asr\r\nERROR .......\r\nsite-packages/transformers/trainer_pt_utils.py\", line 40, in <module>\r\n from torch.optim.lr_scheduler import SAVE_STATE_WARNING\r\nI believe SAVE_ST... | 2020-12-11T08:43:24 | 2020-12-11T13:45:44 | 2020-12-11T13:45:44 | NONE | {
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cuda 11.1
Latest built from source: torch, torchvision, torchaudio, torchtext, pytorch_lightning, apex, horovod, tf-nightly
To reproduce the error (usinng nemo_asr in the example below):
python
Python 3.7.9 (default, Aug 31 2020, 12:42:55)
[GCC 7.3.0] :: Anaconda, Inc. on linux
Type "help", "co... | {
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} | Modifications enabling TLT text classification train to use ExpManager
- [x] added postfix to ckpt callback structured config + its handling
- [x] minimally polished logic for explicit_log_dir
- [x] minor polish of names
- [x] Bumped versions in requirements: omegaconf, hydra to make Optional[List]] work
- [x] B... | {
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"@vinchg could you rebase this PR with main? There was a fix this morning that we need to pass CI.",
"@ericharper Yeah, PR has been rebased!"
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With the update of the requirements to transformers >= 4.0.0 on the main branch, calling a model now passes `return_dict=True` by default rather than a tuple previously: https://github.com/huggingface/transformers/releases/tag/v4.0.0
The fix is simple - any transformers model call should explic... | {
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} | # Changelog
- ASR BPE now will explicitly set Hugging Face flag `TOKENIZERS_PARALLELISM` if not provided by user
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} | - Removed unnecessary pyaudio stream from breaking VAD offline example
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"Fixed in main branch, thanks for pointing it out !"
] | 2020-12-08T14:41:48 | 2021-06-19T04:44:10 | 2021-06-19T04:44:09 | CONTRIBUTOR | {
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The inference code in the ASR tutorial 01_ASR_with_NeMo doesn't put the model in training mode before inference. If copied and used in someone's code, this would cause augmentation like SpecAugment to be inadvertantly be applied to the test set resulting in higher WER than the model actually pro... | {
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"@purn3ndu please check the default names for the class names in the 3 configs"
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2. more parameters for the segmentation tool exposed
3. updates for the latest asr.model config changes
4. added command to upgrade jupyter for LM models tutorial | {
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"Thanks!"
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} | - Adds new GlowVocoder
- Removed the SqueezeWaveDenoiser module
- Denoisers are now moved into the GlowVocoder class with support for WaveGlow and SqueezeWave
- WaveGlow and SqueezeWave's denoisers are now enabled by default in their convert_spectrogram_to_audio() functions | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/1521 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/1521/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/1521/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/1521/events | https://github.com/NVIDIA/NeMo/pull/1521 | 757,300,811 | MDExOlB1bGxSZXF1ZXN0NTMyNzAwMDk3 | 1,521 | Patch refactoring bug for RNNT Char decoding + Update configs | {
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} | # Changelog
- Patch the abstract definition of RNNT decoding
- Update configs to use 8x stride to reduce memory and execution time
Fixes https://github.com/NVIDIA/NeMo/issues/1520
Signed-off-by: smajumdar <titu1994@gmail.com> | {
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"Yup that's a bug during the refactor, I'll send a patch in sometime. ",
"Added a PR https://github.com/NVIDIA/NeMo/pull/1521, it might take some time to get merged so you could update the code locally in the mean time (its a one liner at the end of the PR). \r\n\r\nBtw, just a heads up. The configs for RNNT are ... | 2020-12-04T17:40:22 | 2020-12-04T18:21:10 | 2020-12-04T18:21:10 | NONE | {
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On [line 209 of rnnt_wer.py](https://github.com/NVIDIA/NeMo/blob/main/nemo/collections/asr/metrics/rnnt_wer.py#L209) there is a reference to `self.tokenizer.ids_to_text(prediction)` which errors out because there is no tokenizer. This blocks the example script in speech_to_text_rnnt.py below at ... | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/1518 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/1518/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/1518/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/1518/events | https://github.com/NVIDIA/NeMo/issues/1518 | 757,128,967 | MDU6SXNzdWU3NTcxMjg5Njc= | 1,518 | log_every_n_steps only applies to training, not validation/test | {
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"This is still an issue but note you can turn off the validation output entirely with \r\n`quartznet._wer.log_prediction=False` where quartznet is your model instance.",
"Validation frequency is handled by PTL and can be configured in NeMo via YAML or command line. You can use either `val_check_interval`: https:/... | 2020-12-04T14:07:34 | 2021-05-28T08:32:45 | 2021-05-28T08:32:45 | CONTRIBUTOR | {
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} | null | null | null | **Describe the bug**
Forgive me if this is a [pytorch lightning issue](https://github.com/PyTorchLightning/pytorch-lightning/issues/4527), and not a NeMo one. If that's the case let me know and I'll close here and continue there. Setting log_every_n_steps on the trainer limits the output of decoded examples in ASR, ... | {
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"I support this change. Can you share code for how you validate using CER? I'm using the validate code from the ASR with NeMo tutorial and it does something like \r\n\r\n```\r\nfor test_batch in pb(model.test_dataloader()):\r\n test_batch = [x.cuda() for x in test_batch]\r\n xs, x_lens, ys, y_lens... | 2020-12-04T13:19:33 | 2021-08-17T01:00:01 | 2021-08-17T01:00:01 | CONTRIBUTOR | {
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"Heh let's hope this is the last time we ever need such a heavy update to configs",
"🤞 still, I expect one more change related to this project:\r\nhttps://github.com/pytorch/hydra-torch\r\nonce it will be mature enough...",
"@tkornuta-nvidia I miss you!\r\n\r\nMy goal is to have the initial versioned release ... | 2020-12-03T23:34:39 | 2021-01-20T02:27:00 | 2020-12-04T06:33:52 | COLLABORATOR | {
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} | # Changelog
- Update every ASR config to new hydra 1.x format | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/1515 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/1515/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/1515/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/1515/events | https://github.com/NVIDIA/NeMo/pull/1515 | 756,627,492 | MDExOlB1bGxSZXF1ZXN0NTMyMTQ3NTQy | 1,515 | Fastspeech2 | {
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"This pull request **introduces 2 alerts** when merging 51ac7df55e15ff6e742b6761ef5ee336208f4c94 into 97b1c96b64a64ebd45ca75409347bcf5514c0fb9 - [view on LGTM.com](https://lgtm.com/projects/g/NVIDIA/NeMo/rev/pr-832bc76fc446076c1c275776064deb558da6fc7e)\n\n**new alerts:**\n\n* 2 for Unused import"
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https://api.github.com/repos/NVIDIA/NeMo/issues/1514 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/1514/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/1514/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/1514/events | https://github.com/NVIDIA/NeMo/pull/1514 | 756,353,361 | MDExOlB1bGxSZXF1ZXN0NTMxOTExOTA5 | 1,514 | Fix quantization dependency | {
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} | There is only one python version of prebuild wheel of TensorRT's pytorch-quantization on nvidia pyindex, which causes install with all other version of python to fail with a confusion error message.
Removed requirement_quantization.txt. Instead, install from source in Dockerfile.
Also added error message if runn... | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/1513 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/1513/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/1513/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/1513/events | https://github.com/NVIDIA/NeMo/issues/1513 | 756,302,696 | MDU6SXNzdWU3NTYzMDI2OTY= | 1,513 | [Question] how to sold Jasper ASR Loss: inf or Gradient overflow issue? | {
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"try very small learning rate first. And / or learning rate policy with a longer warmup period. Then see if you can increase them."
] | 2020-12-03T15:29:25 | 2020-12-04T02:00:57 | 2020-12-04T02:00:57 | NONE | {
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} | null | null | null | Hello,
I train Jasper ASR but the loss is inf and Gradient overflow. How should I solve it.
I already refer to the issue #637 and see that it is already fixed as suggested for the current version but my model still has the same issue.
Thank you
| {
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https://api.github.com/repos/NVIDIA/NeMo/issues/1512 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/1512/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/1512/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/1512/events | https://github.com/NVIDIA/NeMo/pull/1512 | 755,900,555 | MDExOlB1bGxSZXF1ZXN0NTMxNTMzNjcw | 1,512 | fix for fast/slow tokenizers compatibility | {
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"This pull request **fixes 1 alert** when merging 8ad7e9a62e964dcab1adc45a20f76b4bf09347d3 into e54a3b030e11bcc64327e10bed7ea70724651260 - [view on LGTM.com](https://lgtm.com/projects/g/NVIDIA/NeMo/rev/pr-656a0fc1adcb486ec3bbd4aec5fbac97896b62f7)\n\n**fixed alerts:**\n\n* 1 for Unused import",
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https://api.github.com/repos/NVIDIA/NeMo/issues/1511 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/1511/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/1511/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/1511/events | https://github.com/NVIDIA/NeMo/pull/1511 | 755,679,248 | MDExOlB1bGxSZXF1ZXN0NTMxMzQ2NjE0 | 1,511 | Update model config automatically inside ModelPT | {
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"Hey @titu1994 I am trying to deal with some circular/lazy imports in EFF and noticed in my NeMo Cookbook unit tests I have \r\n`asr_model()` fixture with old structure - and I took this fixture from NeMo.\r\n\r\nSo this is a reminder - please update the structure (params etc.) also down there (i.e. in NeMo unit te... | 2020-12-02T23:10:15 | 2020-12-03T22:36:54 | 2020-12-03T22:36:51 | COLLABORATOR | {
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} | # Changelog
- Immediately convert all Hydra 0.x configs to Hydra 1.x configs inside constructor of ModelPT
- Add tests to ensure that no backward incompatible changes exist
- Update every ASR side config at once - other domains can update as per convenience. | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/1510 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/1510/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/1510/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/1510/events | https://github.com/NVIDIA/NeMo/issues/1510 | 755,456,375 | MDU6SXNzdWU3NTU0NTYzNzU= | 1,510 | [Question] Fine-tuning Quartznet not going as expected, looking for advice/best practices | {
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"can you please share: (1) your python script, (2) yaml config and (3) command line args? I suspect smaller LR is not actually set.\r\nAlso, 1.0.0b2 is out - so I'd recommend you use it, but it shouldn't be the root cause.",
"@gtcooke94 which Quartznet15x5 are you using to finetune? Some of our models have been t... | 2020-12-02T17:09:55 | 2021-04-19T20:02:38 | 2020-12-07T15:19:10 | CONTRIBUTOR | {
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I've simply split swb into an 80/10/10 train/eval/test split.
I read through the ... | {
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} | # Changelog
- Preserve absolute path of provided path in order to correctly check whether its a tarfile - when cwd() is inside of another tarfile.
Signed-off-by: smajumdar <titu1994@gmail.com> | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/1508 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/1508/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/1508/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/1508/events | https://github.com/NVIDIA/NeMo/pull/1508 | 754,735,986 | MDExOlB1bGxSZXF1ZXN0NTMwNTgzMDkz | 1,508 | Add sentencepiece as dependency explicitly | {
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} | # Changelog
- Huggingface tokenizers 4.0+ drops the explicit dependency on sentencepiece
- Therefore add it as a dependency explicitly
Signed-off-by: smajumdar <titu1994@gmail.com> | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/1507 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/1507/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/1507/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/1507/events | https://github.com/NVIDIA/NeMo/issues/1507 | 754,706,368 | MDU6SXNzdWU3NTQ3MDYzNjg= | 1,507 | How to get encoder output as audio feature? | {
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"Both EncDecCTCModel and it's bpe counterpart are pytorch modules - so you will need to write your own function that is based off of the validation_step method inside these two models. "
] | 2020-12-01T20:33:44 | 2021-06-19T04:46:07 | 2021-06-19T04:46:07 | NONE | {
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How can I get the encoder part output in NeMo? Basically, I'm assuming that this part extracts audio features from the raw sample. I'm trying to do some sentiment analysis with those audio features. However, the examples provided use the whole encoder-decoder pipeline. Thanks in advance. | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/1506 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/1506/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/1506/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/1506/events | https://github.com/NVIDIA/NeMo/pull/1506 | 754,611,171 | MDExOlB1bGxSZXF1ZXN0NTMwNDgwOTg5 | 1,506 | ASR exportables fix | {
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} | Signed-off-by: Sergei Nikolaev <snikolaev@nvidia.com>
Cherry picked fix for fuzzy onnx modles' sizes | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/1505 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/1505/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/1505/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/1505/events | https://github.com/NVIDIA/NeMo/pull/1505 | 754,584,764 | MDExOlB1bGxSZXF1ZXN0NTMwNDU5NTMz | 1,505 | transformer version update and mnli-mm processor name fix | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/1504 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/1504/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/1504/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/1504/events | https://github.com/NVIDIA/NeMo/pull/1504 | 754,507,008 | MDExOlB1bGxSZXF1ZXN0NTMwMzk1NTg1 | 1,504 | Add tutorial entry for external language model | {
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"@okuchaiev Is there going to be any more work on external LMs? I'm asking as this seems like that notebook is not very direct to productionize, especially since we're moving some compute to the CPU (is this not an area where we could use the GPU effectively?). \r\n\r\nThere's also the issue where the timestamps ge... | 2020-12-01T15:44:13 | 2020-12-03T10:42:43 | 2020-12-01T17:19:52 | CONTRIBUTOR | {
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} | I asked this before I found the tutorial notebook: https://github.com/NVIDIA/NeMo/issues/1503
This question of how to add external language models is very common, so now that it is supported I think it would be worthwhile to add it to the chart of the main README - I'd guess you will all get fewer questions that way... | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/1503 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/1503/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/1503/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/1503/events | https://github.com/NVIDIA/NeMo/issues/1503 | 754,492,686 | MDU6SXNzdWU3NTQ0OTI2ODY= | 1,503 | [Question] External LM and Beam Search Notebook/Guide? | {
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"For anyone looking at this, I dug into the PRs and found this notebook added:\r\n\r\nhttps://github.com/NVIDIA/NeMo/blob/v1.0.0b2/tutorials/asr/Offline_ASR.ipynb"
] | 2020-12-01T15:26:59 | 2020-12-01T19:45:03 | 2020-12-01T19:45:03 | CONTRIBUTOR | {
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Is there a notebook on how to do this, or for now is it easiest to dig around in the code?
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https://api.github.com/repos/NVIDIA/NeMo/issues/1502 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/1502/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/1502/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/1502/events | https://github.com/NVIDIA/NeMo/issues/1502 | 754,382,943 | MDU6SXNzdWU3NTQzODI5NDM= | 1,502 | RuntimeError: arguments are located on different GPUs | {
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"I have the same issue.\r\n**Same Environment and GPUs**\r\n\r\n- python 3.6.10\r\n- Pytorch: 1.7.0a0+8deb4fe\r\n- pytorch-lightning==1.0.8\r\n- pytorch-lightning-bolts==0.2.5\r\n- pytorch-transformers==1.1.0",
"> I have the same issue.\r\n> **Same Environment and GPUs**\r\n> \r\n> * python 3.6.10\r\n> * Pytorch:... | 2020-12-01T13:12:52 | 2020-12-08T18:18:59 | 2020-12-08T18:18:59 | NONE | {
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During speech_to_text.py on my own data set training while using FilterbankFeatures,
at training step.
I get the error: RuntimeError: arguments are located on different GPUs
at line 358 in /nemo/collections/ast/parts/features.py
x = torch.matmul(self.fb.to(x.dtype), x)
**Steps/Code to r... | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/1501 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/1501/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/1501/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/1501/events | https://github.com/NVIDIA/NeMo/pull/1501 | 753,818,849 | MDExOlB1bGxSZXF1ZXN0NTI5ODIzNTk4 | 1,501 | Add quantization support | {
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"This pull request **introduces 1 alert** when merging 9d1ffa4eb969bae0402026edecde7b854df92928 into d15c09333d009f82ad6fb5996480c18fe7fc4d2b - [view on LGTM.com](https://lgtm.com/projects/g/NVIDIA/NeMo/rev/pr-562341bd8982145a858e9b5512c28f2b95117bd1)\n\n**new alerts:**\n\n* 1 for Unused import",
"This pull reque... | 2020-11-30T21:31:30 | 2020-12-03T01:07:47 | 2020-12-02T21:19:43 | CONTRIBUTOR | {
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} | Uses nvidia's quantization toolkit https://gitlab-master.nvidia.com/TensorRT/Tools/pytorch-quantization.
Added two scripts for ASR model, one for calibration, one for post training quantization.
usage
```shell
python examples/asr/speech_to_text_calibrate.py --asr_model QuartzNet15x5Base-En --dataset data/libris... | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/1499 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/1499/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/1499/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/1499/events | https://github.com/NVIDIA/NeMo/pull/1499 | 753,686,421 | MDExOlB1bGxSZXF1ZXN0NTI5NzE2NDgy | 1,499 | fixed bug where exp_manager would pass a .nemo file to PTL trainer | {
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} | The following line was passing a `.nemo` file as an argument for PTL Trainer's `resume_from_checkpoint` option.
This would lead to PTL trying to unpickle a tar file and raise an exception. | {
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"The docker image has been published and should be available now."
] | 2020-11-27T09:27:07 | 2020-12-02T17:51:01 | 2020-12-02T17:51:01 | NONE | {
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Error message:
docker pull nvcr.io/nvidia/nemo:v1.0.0b2
Error response from daemon: manifest for nvcr.io/nvidia/nemo:v1.0.0b2 not found: manifest unknown: manifest unknown | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/1497 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/1497/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/1497/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/1497/events | https://github.com/NVIDIA/NeMo/pull/1497 | 751,128,203 | MDExOlB1bGxSZXF1ZXN0NTI3NzAwOTk0 | 1,497 | Add transcription functionality to ASR Classification models | {
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"For transcription, duration is a dummy value that's not precalculated. It would cost too much compute to precompute the durations of all the samples simply for logging.",
"Hmm thinking about the vad case, it doesn't work with this dataloader at all. So feel free to push changes to this branch (or an addendum PR ... | 2020-11-25T21:29:16 | 2020-11-30T08:04:01 | 2020-11-30T08:00:25 | COLLABORATOR | {
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} | # Changelog
- Refactor TopKClassification accuracy to make `top_k` a property + perform top_k operation seperately
- Add tests for transcription scenarios
Signed-off-by: smajumdar <titu1994@gmail.com> | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/1496 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/1496/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/1496/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/1496/events | https://github.com/NVIDIA/NeMo/pull/1496 | 751,009,875 | MDExOlB1bGxSZXF1ZXN0NTI3NjA0Njg5 | 1,496 | Add torchscript export for IntentSlotClassificationModel. | {
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"Is there a way to check what jenkins is failing with? It seems the details link points to a non-public IP."
] | 2020-11-25T17:43:09 | 2020-12-12T01:00:52 | 2020-12-12T01:00:52 | CONTRIBUTOR | {
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} | A bit of a roundabout way of allowing `IntentSlotClassificationModel`s to be exported to torchscript. Not immediately sure how to do this in a cleaner way without adding/changing too much. | {
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"on the same machine, it works for \"nvcr.io/nvidia/nemo:v1.0.0b1 \"",
"closing as duplicate of https://github.com/NVIDIA/NeMo/issues/1498 "
] | 2020-11-25T11:10:05 | 2020-11-30T18:07:46 | 2020-11-30T18:07:46 | NONE | {
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docker pull nvcr.io/nvidia/nemo:v1.0.0b2
Error response from daemon: manifest for nvcr.io/nvidia/nemo:v1.0.0b2 not found: manifest unknown: manifest unknown
| {
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https://api.github.com/repos/NVIDIA/NeMo/issues/1494 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/1494/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/1494/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/1494/events | https://github.com/NVIDIA/NeMo/pull/1494 | 750,470,761 | MDExOlB1bGxSZXF1ZXN0NTI3MTUxNzYw | 1,494 | Patch for NLP vocab artifacts | {
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"shouldn't tokenizer_model be handled similarly?",
"> shouldn't tokenizer_model be handled similarly?\r\n\r\nok, got it."
] | 2020-11-25T05:35:33 | 2020-11-25T17:24:05 | 2020-11-25T17:24:01 | COLLABORATOR | {
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} | Changed setup_tokenizer logic so that if the model is being restored it will try to use the vocab file "tokenizer.vocab_file" first.
If "tokenizer.vocab_file" doesn't exist, then it will fall back to cfg.vocab_file.
If no `vocab_file` is given, we will try to get the vocab from the tokenizer and then register the... | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/1493 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/1493/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/1493/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/1493/events | https://github.com/NVIDIA/NeMo/pull/1493 | 750,128,813 | MDExOlB1bGxSZXF1ZXN0NTI2ODM2NjI4 | 1,493 | Allow .nemo to save best model instead of last model | {
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"this isn't something supported out-of-the box. But you can probably write your own PTL callback for that."
] | 2020-11-24T17:57:32 | 2020-11-30T18:08:43 | 2020-11-30T18:08:42 | NONE | {
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} | # Changelog
- Revert a temporary patch for TLT
- Make ModelPT save_to and restore_from aware of restoration state
- Formalize artifact management
Signed-off-by: smajumdar <titu1994@gmail.com> | {
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"closing as this code is in https://github.com/NVIDIA/NeMo/pull/1491 "
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https://api.github.com/repos/NVIDIA/NeMo/issues/1488 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/1488/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/1488/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/1488/events | https://github.com/NVIDIA/NeMo/issues/1488 | 748,959,150 | MDU6SXNzdWU3NDg5NTkxNTA= | 1,488 | OneCycleLR and OneCycle training[Question] | {
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"Only optimizers/schedulers that exist within the AVAILABLE_OPTIMIZERS and AVAILABLE_SCHEDULERS can be resolved via config/classpath. \r\n\r\nYou can register your own scheduler via the following method - before your code calls the hydra main function, in order to add external optimizers and schedulers support wit... | 2020-11-23T16:44:11 | 2021-08-17T00:58:49 | 2021-08-17T00:58:49 | CONTRIBUTOR | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/1486 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/1486/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/1486/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/1486/events | https://github.com/NVIDIA/NeMo/issues/1486 | 748,905,238 | MDU6SXNzdWU3NDg5MDUyMzg= | 1,486 | ASR Inference from Tensor instead of file[Question] | {
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"All NeMo models are pytorch modules, so it should be easy enough to look at their validation/test step code and replicate for tensors. \r\n\r\nThe easiest possible way might be to simply copy paste the validation step code and modify it use individual tensors instead of a batch from a data loader. Make sure to use... | 2020-11-23T15:38:03 | 2020-11-23T17:43:38 | 2020-11-23T17:43:38 | CONTRIBUTOR | {
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"It's not supported out of the box, but you can easily add support for it by subclassing EncDecCTCModel and making the required modifications. ",
"So I finally got to work on this and I may need some help as I don't understand all the stuff under the hood. Here's what my subclass of `EncDecCTCModel` looks like. C... | 2020-11-23T15:21:37 | 2021-05-28T08:44:34 | 2021-05-28T08:44:34 | CONTRIBUTOR | {
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"The intended usage of the `evaluate_from_file()` is to run the final evaluation. The predictions for all examples are stored in a single line.\r\n\r\nIt's recommended to use `get_predictions()`. Note, each word in the input sequence could be split into one or more tokens. In our implementation, the prediction for... | 2020-11-23T09:08:34 | 2020-11-24T15:53:48 | 2020-11-24T15:53:48 | NONE | {
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`model_from_scratch.evaluate_from_file(
text_file= 'Imported_data.txt',
output_dir='.',
)`
Apparently, it's only reading the first line of my text file as shown below.
![importText](https://user-images.githubuser... | {
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} | I was benchmarking Megatron-LM and ran into this issue when recording memory values. This means on the main process there is a lot of unnecessary CUDA memory allocated when loading the state dictionary. Using the proposed fix remedied the issue! | {
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"PR https://github.com/NVIDIA/NeMo/pull/1497 addresses this. I'll update here once it's merged. ",
"This is merged now, closing issue. Please let us know if the solution is insufficient for your requirements"
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The current implementation seems to only taken into batch of wav files and its quite confusing to follow along. | {
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[](https://github.com/NVIDIA/NeMo/blob/main/tutorials/nlp/Token_Classification_Named_Entity_Recognition.ipynb)
I saved it with pytorch's suggestion,
` torch.save... | {
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"The tutorial `01_ASR_with_NeMo.ipynb` does a good job explaining how transfer learning can be done with Nemo. Thanks "
] | 2020-11-20T18:14:54 | 2020-11-21T17:21:50 | 2020-11-21T17:21:50 | NONE | {
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} | null | null | null | My use-case involves using nemo for new languages that have different phones and phoneme to text mappings. I would like to learn what options are available to do this, but one that came to mind was if `QuartzNet15x5Base-En` could predict phonemes, then I can have a layer that does the phone mapping from english to the ... | {
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} | null | null | null | I saw a new script that ports old checkpoints, but it is for 0.9+ versions
What if my Jasper is taught on a version lower than 0.9 and there is no way to retrain it?
P.S. the script does not work with this config
>>
model: "Jasper"
sample_rate: 16000
AudioToTextDataLayer:
max_duration: 16.7
tri... | {
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https://api.github.com/repos/NVIDIA/NeMo/issues/1477 | https://api.github.com/repos/NVIDIA/NeMo | https://api.github.com/repos/NVIDIA/NeMo/issues/1477/labels{/name} | https://api.github.com/repos/NVIDIA/NeMo/issues/1477/comments | https://api.github.com/repos/NVIDIA/NeMo/issues/1477/events | https://github.com/NVIDIA/NeMo/pull/1477 | 747,224,236 | MDExOlB1bGxSZXF1ZXN0NTI0NDgzMjUx | 1,477 | Fixes to IntentSlots init logic making all TLT scripts operational | {
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"@titu1994 The fix comes from me doing the cycles (save - restore - save), which is not a _typical_ NeMo use-case, but is a typical TLT workflow. Thanks for the comment though.\r\n",
"Save restore save is the general cycle of NeMo too - save when we train a model, convert to .Nemo and upload, use from_pretrained(... | 2020-11-20T06:49:12 | 2020-11-24T01:13:22 | 2020-11-24T01:13:19 | CONTRIBUTOR | {
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} | This is still work in progress - but at least:
- [x] CI passes
- [x] whole TLT workflow (train, finetune, evaluate, inference, export, infer ONNX scripts) work
- [x] setting datadir also "reconfigures" the model (e.g. slots/intents change => heads change too)
- [x] **!! change in the way ModelPT is handing artifa... | {
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"still some tests are not passing"
] | 2020-11-20T00:38:59 | 2021-01-22T15:27:21 | 2020-12-02T23:03:23 | MEMBER | {
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