Steps to train a model:

• Download the urban sound datasets, and unzip it in the raw_data folder
  There should be 10 sub-folders in the raw_data folder
  UrbanSound8K
  UrbanSound
• Change the sample rate of the audio
  python src/wav16000.py --raw_data_dir raw_data --data_16000_dir wav_16000
• Perfrom STFT to the audio files and save each audio as a tensor
  python src/audio_pth.py --data_16000_dir wav_16000 --data_dir data
• Create train/eval/test manifest files
  python src/manifest.py
• Train
  python src/train.py
  The best model will be store in ./log/<date_time>/best.model.pth
• TODO
  Correct the train/eval/test splits: AVOID COMMON PITFALLS