# network architecture
# encoder related
encoder: eend_ola_transformer
encoder_conf:
    idim: 345
    n_layers: 4
    n_units: 256

# encoder-decoder attractor related
encoder_decoder_attractor: eda
encoder_decoder_attractor_conf:
    n_units: 256

# model related
model: eend_ola
model_conf:
    max_n_speaker: 8

# optimization related
accum_grad: 1
grad_clip: 5
max_epoch: 25
val_scheduler_criterion:
    - valid
    - loss
best_model_criterion:
-   - valid
    - loss
    - min
keep_nbest_models: 100

optim: adam
optim_conf:
    lr: 1.0
    betas:
      - 0.9
      - 0.98
    eps: 1.0e-9
scheduler: noamlr
scheduler_conf:
    model_size: 256
    warmup_steps: 100000

dataset_conf:
    data_names: speech_speaker_labels
    data_types: kaldi_ark
    batch_conf:
        batch_type: unsorted
        batch_size: 64
    num_workers: 8

log_interval: 50