# @package experiment
name: seanet-nfft=${experiment.nfft}-hl=${experiment.hop_length}

# Dataset related
lr_sr: 44100 # low resolution sample rate, added to support BWE. Should be included in training cfg
hr_sr: 44100 # high resolution sample rate. Should be included in training cfg
segment: 2
stride: 2    # in seconds, how much to stride between training examples
pad: true   # if training sample is too short, pad it
upsample: false
batch_size: 5
nfft: 1024
hop_length: 512

# models related
model: seanet
seanet:
  latent_space_size: 256
  ngf: 32
  n_residual_layers: 4
  resample: 1
  normalize: False
  floor: 0.0005
  ratios: [ 8,8,2,2 ]
  lr_sr: 44100
  hr_sr: 44100
  in_channels: 2
  out_channels: 2

adversarial: True
features_loss_lambda: 100
discriminator_models: [ msd, mpd ] #msd_melgan/msd_hifi/mpd/hifi
only_features_loss: False
only_adversarial_loss: False
msd:
  hidden: 16
  channels: 2
mpd:
  hidden: 16
  channels: 2
melgan_discriminator:
  n_layers: 5
  num_D: 3
  downsampling_factor: 1
  ndf: 16
  channels: 2