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-rw-r--r--training/conf/experiment/cnn_transformer_paragraphs.yaml18
-rw-r--r--training/conf/experiment/cnn_transformer_paragraphs_wp.yaml155
2 files changed, 164 insertions, 9 deletions
diff --git a/training/conf/experiment/cnn_transformer_paragraphs.yaml b/training/conf/experiment/cnn_transformer_paragraphs.yaml
index b415c29..e9cd254 100644
--- a/training/conf/experiment/cnn_transformer_paragraphs.yaml
+++ b/training/conf/experiment/cnn_transformer_paragraphs.yaml
@@ -10,7 +10,7 @@ defaults:
- override /optimizers: null
-epochs: &epochs 512
+epochs: &epochs 1000
ignore_index: &ignore_index 3
num_classes: &num_classes 58
max_output_len: &max_output_len 682
@@ -36,7 +36,7 @@ callbacks:
optimizers:
madgrad:
_target_: madgrad.MADGRAD
- lr: 3.0e-4
+ lr: 2.0e-4
momentum: 0.9
weight_decay: 0
eps: 1.0e-6
@@ -46,11 +46,11 @@ optimizers:
lr_schedulers:
network:
_target_: torch.optim.lr_scheduler.OneCycleLR
- max_lr: 3.0e-4
+ max_lr: 2.0e-4
total_steps: null
epochs: *epochs
- steps_per_epoch: 52
- pct_start: 0.1
+ steps_per_epoch: 79
+ pct_start: 0.3
anneal_strategy: cos
cycle_momentum: true
base_momentum: 0.85
@@ -70,13 +70,13 @@ datamodule:
num_workers: 12
train_fraction: 0.8
augment: true
- pin_memory: false
+ pin_memory: true
word_pieces: false
resize: null
network:
_target_: text_recognizer.networks.conv_transformer.ConvTransformer
- input_dims: [1, 56, 1024]
+ input_dims: [1, 576, 640]
hidden_dim: &hidden_dim 128
encoder_dim: 1280
dropout_rate: 0.2
@@ -133,7 +133,7 @@ trainer:
stochastic_weight_avg: true
auto_scale_batch_size: binsearch
auto_lr_find: false
- gradient_clip_val: 0.5
+ gradient_clip_val: 0.0
fast_dev_run: false
gpus: 1
precision: 16
@@ -144,5 +144,5 @@ trainer:
limit_val_batches: 1.0
limit_test_batches: 1.0
resume_from_checkpoint: null
- accumulate_grad_batches: 32
+ accumulate_grad_batches: 16
overfit_batches: 0
diff --git a/training/conf/experiment/cnn_transformer_paragraphs_wp.yaml b/training/conf/experiment/cnn_transformer_paragraphs_wp.yaml
new file mode 100644
index 0000000..6d2bbdb
--- /dev/null
+++ b/training/conf/experiment/cnn_transformer_paragraphs_wp.yaml
@@ -0,0 +1,155 @@
+# @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
+
+
+epochs: &epochs 1000
+ignore_index: &ignore_index 1000
+num_classes: &num_classes 1006
+max_output_len: &max_output_len 451
+summary: [[1, 1, 576, 640], [1, 451]]
+
+criterion:
+ _target_: torch.nn.CrossEntropyLoss
+ ignore_index: *ignore_index
+
+mapping:
+ _target_: text_recognizer.data.word_piece_mapping.WordPieceMapping
+ num_features: 1000
+ tokens: iamdb_1kwp_tokens_1000.txt
+ lexicon: iamdb_1kwp_lex_1000.txt
+ data_dir: null
+ use_words: false
+ prepend_wordsep: false
+ special_tokens: [ <s>, <e>, <p> ]
+ extra_symbols: [ "\n" ]
+
+callbacks:
+ stochastic_weight_averaging:
+ _target_: pytorch_lightning.callbacks.StochasticWeightAveraging
+ swa_epoch_start: 0.75
+ swa_lrs: 1.0e-5
+ annealing_epochs: 10
+ annealing_strategy: cos
+ device: null
+
+optimizers:
+ madgrad:
+ _target_: madgrad.MADGRAD
+ lr: 3.0e-4
+ momentum: 0.9
+ weight_decay: 0
+ eps: 1.0e-6
+
+ parameters: network
+
+lr_schedulers:
+ network:
+ _target_: torch.optim.lr_scheduler.OneCycleLR
+ max_lr: 3.0e-4
+ total_steps: null
+ epochs: *epochs
+ steps_per_epoch: 79
+ pct_start: 0.3
+ anneal_strategy: cos
+ cycle_momentum: true
+ base_momentum: 0.85
+ max_momentum: 0.95
+ div_factor: 25
+ final_div_factor: 1.0e4
+ three_phase: false
+ last_epoch: -1
+ verbose: false
+ # Non-class arguments
+ interval: step
+ monitor: val/loss
+
+datamodule:
+ _target_: text_recognizer.data.iam_extended_paragraphs.IAMExtendedParagraphs
+ batch_size: 4
+ num_workers: 12
+ train_fraction: 0.8
+ augment: true
+ pin_memory: true
+ word_pieces: true
+ resize: null
+
+network:
+ _target_: text_recognizer.networks.conv_transformer.ConvTransformer
+ input_dims: [1, 576, 640]
+ hidden_dim: &hidden_dim 128
+ encoder_dim: 1280
+ dropout_rate: 0.2
+ num_classes: *num_classes
+ pad_index: *ignore_index
+ 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: *hidden_dim
+ depth: 3
+ num_heads: 4
+ attn_fn: text_recognizer.networks.transformer.attention.Attention
+ attn_kwargs:
+ dim_head: 32
+ dropout_rate: 0.2
+ norm_fn: text_recognizer.networks.transformer.norm.ScaleNorm
+ 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:
+ _target_: text_recognizer.networks.transformer.positional_encodings.rotary_embedding.RotaryEmbedding
+ dim: 32
+ pixel_pos_embedding:
+ _target_: text_recognizer.networks.transformer.positional_encodings.PositionalEncoding2D
+ hidden_dim: *hidden_dim
+ max_h: 18
+ max_w: 20
+ token_pos_embedding:
+ _target_: text_recognizer.networks.transformer.positional_encodings.PositionalEncoding
+ hidden_dim: *hidden_dim
+ dropout_rate: 0.2
+ max_len: *max_output_len
+
+model:
+ _target_: text_recognizer.models.transformer.TransformerLitModel
+ max_output_len: *max_output_len
+ start_token: <s>
+ end_token: <e>
+ pad_token: <p>
+
+trainer:
+ _target_: pytorch_lightning.Trainer
+ stochastic_weight_avg: true
+ auto_scale_batch_size: binsearch
+ auto_lr_find: false
+ gradient_clip_val: 0.0
+ fast_dev_run: false
+ gpus: 1
+ precision: 16
+ max_epochs: *epochs
+ terminate_on_nan: true
+ weights_summary: null
+ limit_train_batches: 1.0
+ limit_val_batches: 1.0
+ limit_test_batches: 1.0
+ resume_from_checkpoint: null
+ accumulate_grad_batches: 16
+ overfit_batches: 0