Update ssl example (#3060)

Summary:
- Rename the current `ssl` example to `self_supervised_learning`
- Add README to demonstrate how to run the recipe with hubert task

Pull Request resolved: https://github.com/pytorch/audio/pull/3060

Reviewed By: mthrok

Differential Revision: D43287868

Pulled By: nateanl

fbshipit-source-id: 10352682485ef147ca32f4c4c9f9cde995444aa0

examples/self_supervised_learning/README.md

+# Modularized Self-supervised Learning Recipe
+
+This directory contains the modularized training recipe for audio/speech self-supervised learning. The principle is to let users easily inject a new component (model, data_module, loss function, etc) to the existing recipe for different tasks (e.g. Wav2Vec 2.0, HuBERT, etc).
+
+
+## HuBERT Pre-training Example
+To get the K-Means labels for HuBERT pre-training, please check the [pre-processing step](../hubert/README.md#pre-processing-1st-iteration) in hubert example.
+
+In order to run the HuBERT pre-training script for the first iteration, users need to go to `examples` directory and run the following SLURM command:
+```
+cd examples
+
+srun \
+--gpus-per-node=8 \
+--ntasks-per-node=8 \
+-N 4 \
+--cpus-per-task=10 \
+python -m self_supervised_learning.train_hubert \
+--dataset-path hubert/exp/data/mfcc/ \
+--exp-dir self_supervised_learning/exp_iter1 \
+--feature-type mfcc \
+--num-class 100 \
+--max-updates 250000 \
+--learning-rate 0.0005 \
+--gpus 8 \
+--num-nodes 4
+```

examples/ssl/data_modules/_utils.py → examples/self_supervised_learning/data_modules/_utils.py

@@ -6,10 +6,11 @@ import numpy as np
 import torch
 import torch.distributed as dist
 import torchaudio
-from lightning import Batch
 from torch import Tensor
 from torch.utils.data import BatchSampler, Dataset, DistributedSampler
 
+from ..lightning import Batch
+
 
 class BucketizeBatchSampler(BatchSampler):
     """Buketized BatchSampler for sequential data with different lengths to reduce number of paddings.

examples/ssl/lr_schedulers/__init__.py → examples/self_supervised_learning/lr_schedulers/__init__.py

-from _linear_decay import LinearDecayLRScheduler
+from ._linear_decay import LinearDecayLRScheduler
 
 __all__ = [
     "LinearDecayLRScheduler",

examples/ssl/train_hubert.py → examples/self_supervised_learning/train_hubert.py

@@ -6,14 +6,15 @@ from typing import Dict, Tuple
 
 import torch
 import torchaudio.models
-from data_modules import HuBERTDataModule
-from lightning import SSLPretrainModule
-from losses import hubert_loss
-from lr_schedulers import LinearDecayLRScheduler
 from pytorch_lightning import Trainer
 from pytorch_lightning.callbacks import ModelCheckpoint
 from pytorch_lightning.utilities.seed import seed_everything
 
+from .data_modules import HuBERTDataModule
+from .lightning import SSLPretrainModule
+from .losses import hubert_loss
+from .lr_schedulers import LinearDecayLRScheduler
+
 
 class _Formatter(ArgumentDefaultsHelpFormatter, RawDescriptionHelpFormatter):
     # To use ArgumentDefaultsHelpFormatter as the formatter_class and