renwei2024/nemo-github-issues huggingface dataset:
[TN] raise NotImplementedError for unsupported languages and other minor fixes
State: closed | Pull request: yes


Signed-off-by: Xuesong Yang <1646669+XuesongYang@users.noreply.github.com>

# What does this PR do ?

* raised `NotImplementedError` for unsupported languages.
* added `@staticmethod` decor for member functions.
* fixed some typos.
* renamed argument name for the subroutine of `generate_permutations()` to avoid inner and outer scopes.

**Collection**: [Note which collection this PR will affect]

# Changelog 
- Add specific line by line info of high level changes in this PR.

# Usage
* You can potentially add a usage example below

```python
# Add a code snippet demonstrating how to use this 
```

# Before your PR is "Ready for review"
**Pre checks**:
- [x] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
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# Additional Information
* Related to # (issue)
Fix GPT generation when using sentencepiece tokenizer
State: closed | Pull request: yes

Signed-off-by: MaximumEntropy <sandeep.subramanian.1@umontreal.ca>

# What does this PR do ?

Fixes GPT text generation when using a sentencepiece tokenizer.

**Collection**: NLP

# Changelog 
- Add specific line by line info of high level changes in this PR.

# Usage
* You can potentially add a usage example below

```python
# Add a code snippet demonstrating how to use this 
```

# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
  - [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
  
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation

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# Additional Information
* Related to # (issue)
Universal Prompt encoder + Inference Web UI 
State: closed | Pull request: yes

# What does this PR do ?

1. Added Perceiver based Universal Prompt encoder.
2. Supports T0 datasets.
3. Added Text generation web server for GPT model and universal prompt encoder.
4. Added Retrieval text generation services and web server. 
5. fixed various bugs for text generation, sentence tokenizer for mGPT and allow data parallel for text generation.
Megatron norm
State: closed | Pull request: yes

# What does this PR do ?

Add a one line overview of what this PR aims to accomplish.

**Collection**: [Note which collection this PR will affect]

# Changelog 
- Add specific line by line info of high level changes in this PR.

# Usage
* You can potentially add a usage example below

```python
# Add a code snippet demonstrating how to use this 
```

# Before your PR is "Ready for review"
**Pre checks**:
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- [ ] Bugfix
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# Additional Information
* Related to # (issue)
Fix activation checkpoint args for T5
State: closed | Pull request: yes

Signed-off-by: MaximumEntropy <sandeep.subramanian.1@umontreal.ca>

# What does this PR do ?

Fixes args that were not present in the T5 configs for activation checkpointing

**Collection**: NLP

# Changelog 
- Add specific line by line info of high level changes in this PR.

# Usage
* You can potentially add a usage example below

```python
# Add a code snippet demonstrating how to use this 
```

# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
  - [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
  
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation

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# Additional Information
* Related to # (issue)
Add MoE support for T5 model (w/o expert parallel)
State: closed | Pull request: yes

# What does this PR do ?

Add Mixture of Experts support for T5 model

**Collection**: NLP

# Changelog 
- Add specific line by line info of high level changes in this PR.

# Usage
```
model.encoder.num_moe_experts=4 \
model.decoder.num_moe_experts=4 \
```


# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
  - [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
  
**PR Type**:
- [x] New Feature
- [ ] Bugfix
- [ ] Documentation

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## Who can review?

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# Additional Information
* Related to # (issue)
Fix for prompt table restore error
State: closed | Pull request: yes
Labels: name: cherry-pick

Signed-off-by: Virginia Adams <vadams@nvidia.com>

Every time a new low val loss is reached, the virtual tokens from the prompt encoder are moved to the prompt table in order to save a .nemo file for that checkpoint. This PR removes the premature virtual prompt tokens from the prompt table so that restoring from a .ckpt doesn't error. The error was:

```
Traceback (most recent call last):
  File "scripts/convert_prompt_learning_ckpt_to_nemo.py", line 85, in main
    model: MegatronGPTPromptLearningModel = MegatronGPTPromptLearningModel.load_from_checkpoint(
  File "/home/vadams/NeMo/nemo/collections/nlp/models/nlp_model.py", line 355, in load_from_checkpoint
    model = ptl_load_state(cls, checkpoint, strict=strict, cfg=cfg, **kwargs)
  File "/home/vadams/miniconda3/envs/dev/lib/python3.8/site-packages/pytorch_lightning/core/saving.py", line 259, in _load_state
    keys = obj.load_state_dict(checkpoint["state_dict"], strict=strict)
  File "/home/vadams/NeMo/nemo/collections/nlp/models/language_modeling/megatron_gpt_prompt_learning_model.py", line 382, in load_state_dict
    self.prompt_table.load_state_dict(state_dict_, strict)
  File "/home/vadams/miniconda3/envs/dev/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1667, in load_state_dict
    raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format(
RuntimeError: Error(s) in loading state_dict for PromptTable:
	Unexpected key(s) in state_dict: "prompt_table.squad.indices", "prompt_table.squad.prompt_embeddings.weight"
```

**Collection**: NLP

# Changelog 
- Updated GPT and T5 Prompt learning

# Usage
* You can potentially add a usage example below

```python
# Add a code snippet demonstrating how to use this 
```

# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
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- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
  
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- [ ] New Feature
- [x] Bugfix
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# Additional Information
* Related to # (issue)
add squad
State: closed | Pull request: yes

Signed-off-by: arendu <adithya.r@gmail.com>

# What does this PR do ?

add squad task template for gpt prompt learning.

**Collection**: [Note which collection this PR will affect]

# Changelog 
- Add specific line by line info of high level changes in this PR.

# Usage
* You can potentially add a usage example below

```python
# Add a code snippet demonstrating how to use this 
```

# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
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- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
  - [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
  
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation

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## Who can review?

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# Additional Information
* Related to # (issue)
Fix support for legacy sentencepiece models
State: closed | Pull request: yes

# What does this PR do ?

Fix NeMo support for legacy sentencepiece models (sentencepiece models that don't necessarily contain padding tokens).

**Collection**: NLP

# Changelog 
There were several places where the config value `sentencepiece_legacy` was not properly forwarded to all functions that require it. There was also one spot that set the `decoder_tokenizer_legacy` value using the encoder's config.

# Before your PR is "Ready for review"
**Pre checks**:
- [x] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [x] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [x] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
  - [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
  
**PR Type**:
- [ ] New Feature
- [x] Bugfix
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Segmentation fault (core dumped) when running nlp examples
State: closed | Pull request: no
Labels: name: bug

**Describe the bug**

A clear and concise description of what the bug is.

Run any example of Nemo from the repo, it will throw a Segmentation fault just at import steps. 

Please list *minimal* steps or code snippet for us to be able to reproduce the bug.
One I tried is
```
`python NeMo/examples/nlp/duplex_text_normalization/duplex_text_normalization_infer.py`
Segmentation fault (core dumped)
```


**Expected behavior**

A clear and concise description of what you expected to happen.

**Environment overview (please complete the following information)**

 - Environment location: AWS g5.xlarge
 - Method of NeMo install: followed exact conda command from NeMo repo. Only thing is that I am running as root.

**Environment details**

Otherwise, please provide:
- OS version ubuntu 20.04
- PyTorch version: '1.13.0'
- Python version: python 3.8.0

**Additional context**

Add any other context about the problem here.
nvidia-smi info
```
nvidia-smi
Mon Nov 14 06:30:28 2022       
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 515.65.01    Driver Version: 515.65.01    CUDA Version: 11.7     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|                               |                      |               MIG M. |
|===============================+======================+======================|
|   0  NVIDIA A10G         On   | 00000000:00:1E.0 Off |                    0 |
|  0%   18C    P0    56W / 300W |   6594MiB / 23028MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
                                                                               
+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
|    0   N/A  N/A    108946      C   tritonserver                     6592MiB |
+-----------------------------------------------------------------------------+
```
`StatsPoolLayer` ignores lengths
State: closed | Pull request: no
Labels: name: bug

name: ASR

**Describe the bug**

[StatsPoolLayer](https://github.com/NVIDIA/NeMo/blob/main/nemo/collections/asr/parts/submodules/tdnn_attention.py#L25) ignores the `length` argument; statistics are pooled across what should be padded elements in LID, etc.

Will submit PR.
New German Data Set Thorsten – 2022.10 Available for Re-Training
State: closed | Pull request: no
Labels: name: feature

name: TTS

name: stale

Are there any plans to re-train and provide new models based on the new German data set Thorsten 2022.10
which can be found here [https://www.thorsten-voice.de/en/datasets-2/)](https://www.thorsten-voice.de/en/datasets-2/)

Thanks.


https://github.com/NVIDIA/NeMo/issues/5400#tasklist-block-89576c70-693b-4727-bfc7-555815508f06
Add float32 type casting for get_samples function
State: closed | Pull request: yes

Signed-off-by: Taejin Park <tango4j@gmail.com>

# What does this PR do ?

Add float32 typecasting in get_samples function.
This typecasting was removed while int type filereading was being removed from the function.

**Collection**: [Note which collection this PR will affect]

ASR

# Changelog 
- Add specific line by line info of high level changes in this PR.

# Usage
* You can potentially add a usage example below

This function is used in multiple modules

# Before your PR is "Ready for review"
**Pre checks**:
- [x] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
  - [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
  
**PR Type**:
- [ ] New Feature
- [x] Bugfix
- [ ] Documentation

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## Who can review?

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[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.

# Additional Information
* Related to # (issue)
Can't convert my dataset to Tar
State: closed | Pull request: no
Labels: name: bug

name: stale

name: ASR

Trying to convert my own dataset to Tarred dataset

the number of wav files is almost 280k.

```
python ${NEMO_ROOT}/scripts/speech_recognition/convert_to_tarred_audio_dataset.py \
  --manifest_path=train_decoded_processed.json \
  --target_dir=train_tarred_6bk \
  --num_shards=1024 \
  --max_duration=20.0 \
  --min_duration=1.0 \
  --shuffle \
  --shuffle_seed=1 \
  --sort_in_shards \
  --workers=-1 \
  --buckets_num=6
```

but this would throw the exception

![image](https://user-images.githubusercontent.com/1567200/201321512-e32e1734-a80b-4647-addc-9e96493b0dcf.png)

single bucket is fine, but failed to create multiple buckets.

any idea?
Disable sync_batch_comm in validation_step for GPT
State: closed | Pull request: yes

# What does this PR do ?

With sync_batch_comm=True in validation step we sometimes get CUDA errors while running validation.

**Collection**: NLP
# Changelog 
- Add specific line by line info of high level changes in this PR.

# Usage
* You can potentially add a usage example below

```python
# Add a code snippet demonstrating how to use this 
```

# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
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- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
  - [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
  
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation

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## Who can review?

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# Additional Information
* Related to # (issue)
Force MHA QKV onto fp32
State: closed | Pull request: yes
Labels: name: cherry-pick

Signed-off-by: smajumdar <titu1994@gmail.com>

# What does this PR do ?

Attempt to fix fp16 with MHA in ASR

**Collection**: [ASR]

# Before your PR is "Ready for review"
**Pre checks**:
- [x] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [x] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
  - [x] Reviewer: Does the PR have correct import guards for all optional libraries?
  
**PR Type**:
- [ ] New Feature
- [x] Bugfix
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Fixed bug in notebook
State: closed | Pull request: yes
Labels: name: cherry-pick

Signed-off-by: Virginia Adams <vadams@nvidia.com>

Fix bug in prompt learning notebook inference

Add a one line overview of what this PR aims to accomplish.

**Collection**: NLP

# Changelog 
- Updated GPT prompt learning model class

# Usage
* You can potentially add a usage example below

```python
# Add a code snippet demonstrating how to use this 
```

# Before your PR is "Ready for review"
**Pre checks**:
- [x] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
 - [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
  
**PR Type**:
- [ ] New Feature
- [x] Bugfix
- [ ] Documentation

If you haven't finished some of the above items you can still open "Draft" PR.


## Who can review?

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[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.

# Additional Information
* Related to # (issue)
Fix for prompt table restore error
State: closed | Pull request: yes

Signed-off-by: Virginia Adams <vadams@nvidia.com>

Every time a new low val loss is reached, the virtual tokens from the prompt encoder are moved to the prompt table in order to save a .nemo file for that checkpoint. This PR removes the premature virtual prompt tokens from the prompt table so that restoring from a .ckpt doesn't error. The error was:

```
Traceback (most recent call last):
  File "scripts/convert_prompt_learning_ckpt_to_nemo.py", line 85, in main
    model: MegatronGPTPromptLearningModel = MegatronGPTPromptLearningModel.load_from_checkpoint(
  File "/home/vadams/NeMo/nemo/collections/nlp/models/nlp_model.py", line 355, in load_from_checkpoint
    model = ptl_load_state(cls, checkpoint, strict=strict, cfg=cfg, **kwargs)
  File "/home/vadams/miniconda3/envs/dev/lib/python3.8/site-packages/pytorch_lightning/core/saving.py", line 259, in _load_state
    keys = obj.load_state_dict(checkpoint["state_dict"], strict=strict)
  File "/home/vadams/NeMo/nemo/collections/nlp/models/language_modeling/megatron_gpt_prompt_learning_model.py", line 382, in load_state_dict
    self.prompt_table.load_state_dict(state_dict_, strict)
  File "/home/vadams/miniconda3/envs/dev/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1667, in load_state_dict
    raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format(
RuntimeError: Error(s) in loading state_dict for PromptTable:
	Unexpected key(s) in state_dict: "prompt_table.squad.indices", "prompt_table.squad.prompt_embeddings.weight"
```

**Collection**: NLP

# Changelog 
- Updated GPT and T5 Prompt learning

# Usage
* You can potentially add a usage example below

```python
# Add a code snippet demonstrating how to use this 
```

# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
  
**PR Type**:
- [ ] New Feature
- [x] Bugfix
- [ ] Documentation

If you haven't finished some of the above items you can still open "Draft" PR.


## Who can review?

Anyone in the community is free to review the PR once the checks have passed. 
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.

# Additional Information
* Related to # (issue)
[TTS] replace pitch normalization params with ???
State: closed | Pull request: yes

Signed-off-by: Xuesong Yang <1646669+XuesongYang@users.noreply.github.com>

# What does this PR do ?

Follow up the discussion in https://github.com/NVIDIA/NeMo/pull/5383, we decided to replace pitch norm params with ??? for all YAML configs just in case users forget to update with dataset-specific values.

**Collection**: [Note which collection this PR will affect]

# Changelog 
- Add specific line by line info of high level changes in this PR.

# Usage
* You can potentially add a usage example below

```python
# Add a code snippet demonstrating how to use this 
```

# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
  - [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
  
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation

If you haven't finished some of the above items you can still open "Draft" PR.


## Who can review?

Anyone in the community is free to review the PR once the checks have passed. 
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.

# Additional Information
* Related to # (issue)
Force MHA QKV onto fp32
State: closed | Pull request: yes

Signed-off-by: smajumdar <titu1994@gmail.com>

# What does this PR do ?

Attempt to fix fp16 with MHA in ASR

**Collection**: [ASR]

# Before your PR is "Ready for review"
**Pre checks**:
- [x] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [x] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
  - [x] Reviewer: Does the PR have correct import guards for all optional libraries?
  
**PR Type**:
- [ ] New Feature
- [x] Bugfix
- [ ] Documentation
[TTS] Add Spanish model documentation
State: closed | Pull request: yes

Signed-off-by: Ryan <rlangman@nvidia.com>

# What does this PR do ?

Add new Spanish FastPitch model to available models

https://catalog.ngc.nvidia.com/orgs/nvidia/teams/nemo/models/tts_es_multispeaker_fastpitchhifigan/files

After change is reviewed, I need to update the nvidia catalog with the correct version & filenames.

**Collection**: [TTS]

# Changelog 
- Add Spanish FastPitch & HifiGan to available models and documentation.

# Usage

```python
import soundfile as sf
from nemo.collections.tts.models import FastPitchModel
from nemo.collections.tts.models import HifiGanModel

fastpitch_name = "tts_es_fastpitch_multispeaker"
hifigan_name = "tts_es_hifigan_ft_fastpitch_multispeaker"

# Load spectrogram generator
spec_generator = FastPitchModel.from_pretrained(model_name)

# Load Vocoder
model = HifiGanModel.from_pretrained(model_name=model_name)

# Generate audio
text = "Escribe tu texto aquí."
parsed = spec_generator.parse(text, normalize=False)
speaker = 5
spectrogram = spec_generator.generate_spectrogram(tokens=parsed, speaker=speaker)
audio = model.convert_spectrogram_to_audio(spec=spectrogram)
audio = audio.detach().cpu().numpy()

# Save the audio to disk in a file called speech.wav
sample_rate = 44100
sf.write("speech.wav", audio, sample_rate)
```

# Before your PR is "Ready for review"
**Pre checks**:
- [x] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [x] Did you add or update any necessary documentation?
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**PR Type**:
- [x] New Feature
- [ ] Bugfix
- [x] Documentation
SpeakerClustering: fix tensor dimennsions in forward()
State: closed | Pull request: yes

For some paramters in SpeakerClustering.forward(), tensor dimensions were not specified and this resulted in zero dimension tensor inputs. This causes error when inferencing exported model in Triton server.

# What does this PR do ?

Avoids zero dimension input tensors. Also extracts values from the tensors which have single dim of size 1. This avoids scattered use of item() to extract value from tensor.

**Collection**: ASR Diarizer

# Changelog 
- Add specific line by line info of high level changes in this PR.

# Usage
Fix is needed to use exported clustering model in Triton

```python
# Add a code snippet demonstrating how to use this 
```

# Before your PR is "Ready for review"
**Pre checks**:
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- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
- [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
  
**PR Type**:
- [ ] Bugfix

If you haven't finished some of the above items you can still open "Draft" PR.


## Who can review?

Anyone in the community is free to review the PR once the checks have passed. 
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.

# Additional Information
* Related to # (issue)
[TTS] add CI test for RADTTS training recipe.
State: closed | Pull request: yes

Signed-off-by: Xuesong Yang <1646669+XuesongYang@users.noreply.github.com>

# What does this PR do ?

Add a one line overview of what this PR aims to accomplish.

**Collection**: [Note which collection this PR will affect]

# Changelog 
- Add specific line by line info of high level changes in this PR.

# Usage
* You can potentially add a usage example below

```python
# Add a code snippet demonstrating how to use this 
```

# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
  - [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
  
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [ ] Documentation

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## Who can review?

Anyone in the community is free to review the PR once the checks have passed. 
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.

# Additional Information
* Related to # (issue)
fix for num worker 0 causing issues in losses after 1 epoch
State: closed | Pull request: yes
Labels: name: cherry-pick

# What does this PR do ?

fixes the bug where nw0 does weird things in training and validation after the first epoch.

**Collection**: [NLP]

# Changelog 
- changes gpt dataset creation by deep copy of inputs.

# Usage

```python
# Add a code snippet demonstrating how to use this 
```

# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
  - [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
  
**PR Type**:
- [ ] New Feature
- [X] Bugfix
- [ ] Documentation

If you haven't finished some of the above items you can still open "Draft" PR.



## Who can review?

Anyone in the community is free to review the PR once the checks have passed. 
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.

# Additional Information
* Related to # (issue)
[TTS] Add Spanish FastPitch training configs
State: closed | Pull request: yes

Signed-off-by: Ryan <rlangman@nvidia.com>

# What does this PR do ?

Add configurations for training FastPitch with Spanish tokenizers

**Collection**: [TTS]

# Changelog 
- Add .yaml configs with Spanish grapheme and IPA tokenizers

# Before your PR is "Ready for review"
**Pre checks**:
- [x] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
  - [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
  
**PR Type**:
- [x] New Feature
- [ ] Bugfix
- [ ] Documentation
Fixed bug in notebook
State: closed | Pull request: yes

Signed-off-by: Virginia Adams <vadams@nvidia.com>

Fix bug in prompt learning notebook inference

Add a one line overview of what this PR aims to accomplish.

**Collection**: NLP

# Changelog 
- Updated GPT prompt learning model class

# Usage
* You can potentially add a usage example below

```python
# Add a code snippet demonstrating how to use this 
```

# Before your PR is "Ready for review"
**Pre checks**:
- [x] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
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- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
 - [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
  
**PR Type**:
- [ ] New Feature
- [x] Bugfix
- [ ] Documentation

If you haven't finished some of the above items you can still open "Draft" PR.


## Who can review?

Anyone in the community is free to review the PR once the checks have passed. 
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.

# Additional Information
* Related to # (issue)
Rename Speech Dataset Processor to Speech Data Processor
State: closed | Pull request: yes
Labels: name: cherry-pick

Signed-off-by: Elena Rastorgueva <erastorgueva@nvidia.com>

# What does this PR do ?
Rename Speech Dataset Processor to Speech Data Processor.

Add a one line overview of what this PR aims to accomplish.
Update directory name and contents of README to reflect name change.

**Collection**: [Note which collection this PR will affect]
tools/speech_data_processor

# 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 
```

# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
  - [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
  
**PR Type**:
- [ ] New Feature
- [x] Bugfix
- [ ] Documentation

If you haven't finished some of the above items you can still open "Draft" PR.


## Who can review?

Anyone in the community is free to review the PR once the checks have passed. 
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.

# Additional Information
* Related to # (issue)
fix for num worker 0 causing issues in losses after 1 epoch
State: closed | Pull request: yes

# What does this PR do ?

fixes the bug where nw0 does weird things in training and validation after the first epoch.

**Collection**: [NLP]

# Changelog 
- changes gpt dataset creation by deep copy of inputs.

# Usage

```python
# Add a code snippet demonstrating how to use this 
```

# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
  - [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
  
**PR Type**:
- [ ] New Feature
- [X] Bugfix
- [ ] Documentation

If you haven't finished some of the above items you can still open "Draft" PR.



## Who can review?

Anyone in the community is free to review the PR once the checks have passed. 
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.

# Additional Information
* Related to # (issue)
Rename Speech Dataset Processor to Speech Data Processor
State: closed | Pull request: yes

Signed-off-by: Elena Rastorgueva <erastorgueva@nvidia.com>

# What does this PR do ?
Rename Speech Dataset Processor to Speech Data Processor.

Add a one line overview of what this PR aims to accomplish.
Update directory name and contents of README to reflect name change.

**Collection**: [Note which collection this PR will affect]
tools/speech_data_processor

# 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 
```

# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
  - [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
  
**PR Type**:
- [ ] New Feature
- [x] Bugfix
- [ ] Documentation

If you haven't finished some of the above items you can still open "Draft" PR.


## Who can review?

Anyone in the community is free to review the PR once the checks have passed. 
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.

# Additional Information
* Related to # (issue)
num_workers bug in gpt prompt learning dataset bug
State: closed | Pull request: yes

# What does this PR do ?

fixes the bug where nw0 does weird things in training and validation after the first epoch.

**Collection**: [NLP]

# Changelog 
- changes gpt dataset creation by deep copy of inputs.

# Usage

```python
# Add a code snippet demonstrating how to use this 
```

# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
  - [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
  
**PR Type**:
- [ ] New Feature
- [X] Bugfix
- [ ] Documentation

If you haven't finished some of the above items you can still open "Draft" PR.


## Who can review?

Anyone in the community is free to review the PR once the checks have passed. 
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.

# Additional Information
* Related to # (issue)
Add SDP documentation
State: closed | Pull request: yes
Labels: name: cherry-pick

Signed-off-by: Elena Rastorgueva <erastorgueva@nvidia.com>

# What does this PR do ?

Adds documentation to Speech Dataset Processor

**Collection**: [Note which collection this PR will affect]
tools/speech_dataset_processor

# 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 
```

# Before your PR is "Ready for review"
**Pre checks**:
- [ ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
  - [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
  
**PR Type**:
- [ ] New Feature
- [ ] Bugfix
- [x] Documentation

If you haven't finished some of the above items you can still open "Draft" PR.


## Who can review?

Anyone in the community is free to review the PR once the checks have passed. 
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.

# Additional Information
* Related to # (issue)
[Bugfix] Added rm -f / wget- nc command in multispeaker sim notebook to r1.13.0
State: closed | Pull request: yes

# What does this PR do ?

The former PR was not merged for r1.13.0 so merging it into r.1.13.0

This PR fixes minor bugs in multispeaker simulation tutorial notebook
https://github.com/NVIDIA/NeMo/blob/main/tutorials/tools/Multispeaker_Simulator.ipynb

Bugfix for 
https://nvbugswb.nvidia.com/NvBugs5/SWBug.aspx?bugid=3848353

- rm throws out an error if there is no such file

**Collection**: [Note which collection this PR will affect]

# Changelog 


added rm -f (try deleting only if file exists)
added wget -nc  (no duplication)


# Usage

Please run the tutorial notebook

# Before your PR is "Ready for review"
**Pre checks**:
- [x] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [x] Did you write any new necessary tests?
- [x] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
  - [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
  
**PR Type**:
- [] New Feature
- [x] Bugfix
- [ ] Documentation

If you haven't finished some of the above items you can still open "Draft" PR.


## Who can review?

any one in ASR

# Additional Information
* Related to # (issue)
[Bugfix] Added rm -f / wget- nc command in multispeaker sim notebook pushing to r1.13.0
State: closed | Pull request: yes

Signed-off-by: Taejin Park <tango4j@gmail.com>

# What does this PR do ?

Fix minor bugs in multispeaker simulation tutorial notebook
https://github.com/NVIDIA/NeMo/blob/main/tutorials/tools/Multispeaker_Simulator.ipynb

Bugfix for 
https://nvbugswb.nvidia.com/NvBugs5/SWBug.aspx?bugid=3848353

- rm throws out an error if there is no such file

**Collection**: [Note which collection this PR will affect]

# Changelog 


added rm -f (try deleting only if file exists)
added wget -nc  (no duplication)


# Usage

Please run the tutorial notebook

# Before your PR is "Ready for review"
**Pre checks**:
- [x] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [x] Did you write any new necessary tests?
- [x] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
  - [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
  
**PR Type**:
- [] New Feature
- [x] Bugfix
- [ ] Documentation

If you haven't finished some of the above items you can still open "Draft" PR.


## Who can review?

any one in ASR

# Additional Information
* Related to # (issue)
Fix Python type hints according to Python Docs
State: closed | Pull request: yes

# What does this PR do ?

Fix Python type annotations according to the documentation (correct syntax, missing imports, fix incompatible return types).

**Collection**: [Note which collection this PR will affect]

# Changelog 
- remove duplicated type annotations
- fix tuple annotation in function return types according to [python docs](https://docs.python.org/3.8/library/typing.html#typing.Tuple)
- add missing imports (only when module is used, but not imported)
- fix return type in some places where return type is obvious, but not compatible with the annotation (e.g. use `Optional[str]` instead of `str` if `return None` is used)
- avoid quotes for type annotations in some places (if possible): quotes are useful only for forward declaration, in other cases this can lead to [inconsistent or incorrect types](https://stackoverflow.com/a/46458497).
    - Also, if quotes are used and the necessary type is not imported, IDEs / linters can't correctly infer the type. If the type is imported, some tools (including the LGTM bot) consider such import as unused.

# Usage
No executed code is affected (except for missing imports).
Changes only affect type hints by PyCharm or type checkers output (e.g. `syntax error` in `mypy`).

## Example
Before (incorrect return type – unclear automatic signature in PyCharm):
<img width="777" alt="check_lib_version_incorrect" src="https://user-images.githubusercontent.com/9380560/200830147-f5c8435b-a8dd-42e6-9e32-c080166f9723.png">

After (corrected type – PyCharm correctly adds hints):
<img width="809" alt="check_lib_version_correct" src="https://user-images.githubusercontent.com/9380560/200830176-ba824995-eaa4-4a71-97ea-466570c5f9d1.png">

# Before your PR is "Ready for review"
**Pre checks**:
- [x] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [ ] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
  - [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
  
**PR Type**:
- [ ] New Feature
- [x] Bugfix
- [ ] Documentation

If you haven't finished some of the above items you can still open "Draft" PR.


## Who can review?

Anyone in the community is free to review the PR once the checks have passed. 
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.


# Additional Information
* Related to # (issue)