defaults: - override /mapping: null - override /criterion: null - override /datamodule: null - override /network: null - override /model: null - override /lr_schedulers: null # - override /optimizers: null criterion: _target_: text_recognizer.criterions.label_smoothing.LabelSmoothingLoss smoothing: 0.1 ignore_index: 3 mapping: _target_: text_recognizer.data.emnist_mapping.EmnistMapping # extra_symbols: [ "\n" ] lr_schedulers: network: _target_: torch.optim.lr_scheduler.CosineAnnealingLR T_max: 512 eta_min: 4.5e-6 last_epoch: -1 interval: epoch monitor: val/loss datamodule: _target_: text_recognizer.data.iam_lines.IAMLines batch_size: 4 num_workers: 12 train_fraction: 0.8 augment: false pin_memory: false # optimizers: # - _target_: madgrad.MADGRAD # lr: 2.0e-4 # momentum: 0.9 # weight_decay: 0 # eps: 1.0e-7 # parameters: network network: _target_: text_recognizer.networks.vq_transformer.VqTransformer input_dims: [1, 56, 1024] encoder_dim: 32 hidden_dim: 32 dropout_rate: 0.1 num_classes: 58 pad_index: 3 no_grad: true decoder: _target_: text_recognizer.networks.transformer.Decoder dim: 32 depth: 4 num_heads: 8 attn_fn: text_recognizer.networks.transformer.attention.Attention attn_kwargs: dim_head: 32 dropout_rate: 0.2 norm_fn: torch.nn.LayerNorm ff_fn: text_recognizer.networks.transformer.mlp.FeedForward ff_kwargs: dim_out: null expansion_factor: 4 glu: true dropout_rate: 0.2 cross_attend: true pre_norm: true rotary_emb: null pretrained_encoder_path: "training/logs/runs/2021-09-26/23-27-57" model: _target_: text_recognizer.models.vq_transformer.VqTransformerLitModel start_token: end_token: pad_token:

max_output_len: 89 # 451 alpha: 0.0 trainer: max_epochs: 512 # limit_train_batches: 0.1 # limit_val_batches: 0.1 # gradient_clip_val: 0.5