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# @package _global_
defaults:
- override /mapping: null
- override /network: null
- override /model: null
mapping:
_target_: text_recognizer.data.emnist_mapping.EmnistMapping
extra_symbols: [ "\n" ]
datamodule:
word_pieces: false
batch_size: 8
augment: false
criterion:
ignore_index: 3
network:
_target_: text_recognizer.networks.vq_transformer.VqTransformer
input_dims: [1, 576, 640]
encoder_dim: 32
hidden_dim: 256
dropout_rate: 0.1
num_classes: 58
pad_index: 3
no_grad: true
decoder:
_target_: text_recognizer.networks.transformer.Decoder
dim: 256
depth: 2
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/2021-09-25/23-07-28"
model:
_target_: text_recognizer.models.vq_transformer.VqTransformerLitModel
start_token: <s>
end_token: <e>
pad_token: <p>
max_output_len: 682 # 451
alpha: 1.0
trainer:
max_epochs: 64
limit_train_batches: 0.1
limit_val_batches: 0.1
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