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-rw-r--r--training/conf/experiment/vqgan_htr_char_iam_lines.yaml88
1 files changed, 0 insertions, 88 deletions
diff --git a/training/conf/experiment/vqgan_htr_char_iam_lines.yaml b/training/conf/experiment/vqgan_htr_char_iam_lines.yaml
deleted file mode 100644
index 27fdfda..0000000
--- a/training/conf/experiment/vqgan_htr_char_iam_lines.yaml
+++ /dev/null
@@ -1,88 +0,0 @@
-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: <s>
- end_token: <e>
- pad_token: <p>
- 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