# network architecture
# encoder related
encoder: branchformer
encoder_conf:
    output_size: 512
    use_attn: true
    attention_heads: 8
    attention_layer_type: rel_selfattn
    pos_enc_layer_type: rel_pos
    rel_pos_type: latest
    use_cgmlp: true
    cgmlp_linear_units: 3072
    cgmlp_conv_kernel: 31
    use_linear_after_conv: false
    gate_activation: identity
    merge_method: concat
    cgmlp_weight: 0.5               # used only if merge_method is "fixed_ave"
    attn_branch_drop_rate: 0.0      # used only if merge_method is "learned_ave"
    num_blocks: 18
    dropout_rate: 0.1
    positional_dropout_rate: 0.1
    attention_dropout_rate: 0.1
    input_layer: conv2d
    stochastic_depth_rate: 0.0

# decoder related
decoder: transformer
decoder_conf:
    attention_heads: 8
    linear_units: 2048
    num_blocks: 6
    dropout_rate: 0.1
    positional_dropout_rate: 0.1
    self_attention_dropout_rate: 0.1
    src_attention_dropout_rate: 0.1

# frontend related
frontend: wav_frontend
frontend_conf:
    fs: 16000
    window: hamming
    n_mels: 80
    frame_length: 25
    frame_shift: 10
    lfr_m: 1
    lfr_n: 1

# hybrid CTC/attention
model_conf:
    ctc_weight: 0.3
    lsm_weight: 0.1     # label smoothing option
    length_normalized_loss: false

# optimization related
accum_grad: 2
grad_clip: 5
max_epoch: 210
val_scheduler_criterion:
    - valid
    - acc
best_model_criterion:
-   - valid
    - acc
    - max
keep_nbest_models: 10

optim: adam
optim_conf:
    lr: 0.0025
    weight_decay: 0.000001
scheduler: warmuplr
scheduler_conf:
    warmup_steps: 40000

specaug: specaug
specaug_conf:
    apply_time_warp: true
    time_warp_window: 5
    time_warp_mode: bicubic
    apply_freq_mask: true
    freq_mask_width_range:
    - 0
    - 27
    num_freq_mask: 2
    apply_time_mask: true
    time_mask_width_ratio_range:
    - 0.
    - 0.05
    num_time_mask: 10

dataset_conf:
    data_names: speech,text
    data_types: sound,text
    shuffle: True
    shuffle_conf:
        shuffle_size: 2048
        sort_size: 500
    batch_conf:
        batch_type: token
        batch_size: 30000
    num_workers: 8

log_interval: 50
normalize: None