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-rw-r--r--training/conf/experiment/cnn_htr_char_lines.yaml109
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diff --git a/training/conf/experiment/cnn_htr_char_lines.yaml b/training/conf/experiment/cnn_htr_char_lines.yaml
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+# @package _global_
+
+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_: torch.nn.CrossEntropyLoss
+ ignore_index: 3
+
+mapping:
+ _target_: text_recognizer.data.emnist_mapping.EmnistMapping
+ # extra_symbols: [ "\n" ]
+
+optimizers:
+ madgrad:
+ _target_: madgrad.MADGRAD
+ lr: 1.0e-4
+ momentum: 0.9
+ weight_decay: 0
+ eps: 1.0e-6
+
+ parameters: network
+
+lr_schedulers:
+ network:
+ _target_: torch.optim.lr_scheduler.CosineAnnealingLR
+ T_max: 1024
+ eta_min: 4.5e-6
+ last_epoch: -1
+ interval: epoch
+ monitor: val/loss
+
+datamodule:
+ _target_: text_recognizer.data.iam_lines.IAMLines
+ batch_size: 24
+ num_workers: 12
+ train_fraction: 0.8
+ augment: true
+ pin_memory: false
+
+network:
+ _target_: text_recognizer.networks.conv_transformer.ConvTransformer
+ input_dims: [1, 56, 1024]
+ hidden_dim: 128
+ encoder_dim: 1280
+ dropout_rate: 0.2
+ num_classes: 58
+ pad_index: 3
+ encoder:
+ _target_: text_recognizer.networks.encoders.efficientnet.EfficientNet
+ arch: b0
+ out_channels: 1280
+ stochastic_dropout_rate: 0.2
+ bn_momentum: 0.99
+ bn_eps: 1.0e-3
+ decoder:
+ _target_: text_recognizer.networks.transformer.Decoder
+ dim: 128
+ depth: 3
+ num_heads: 4
+ 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
+
+model:
+ _target_: text_recognizer.models.transformer.TransformerLitModel
+ max_output_len: 89
+ start_token: <s>
+ end_token: <e>
+ pad_token: <p>
+
+trainer:
+ _target_: pytorch_lightning.Trainer
+ stochastic_weight_avg: false
+ auto_scale_batch_size: binsearch
+ auto_lr_find: false
+ gradient_clip_val: 0
+ fast_dev_run: false
+ gpus: 1
+ precision: 16
+ max_epochs: 1024
+ terminate_on_nan: true
+ weights_summary: top
+ limit_train_batches: 1.0
+ limit_val_batches: 1.0
+ limit_test_batches: 1.0
+ resume_from_checkpoint: null
+ accumulate_grad_batches: 4
+ overfit_batches: 0.0
+
+# summary: [[1, 1, 56, 1024], [1, 89]]