Transfomer added, many other changes.

2 files changed, 14 insertions, 100 deletions

diff --git a/src/training/experiments/embedding_experiment.yml b/src/training/experiments/embedding_experiment.yml
index e674c26..1e5f941 100644
--- a/src/training/experiments/embedding_experiment.yml
+++ b/src/training/experiments/embedding_experiment.yml
@@ -1,8 +1,10 @@
 experiment_group: Embedding Experiments
 experiments:
     - train_args:
-        batch_size: 256
-        max_epochs: &max_epochs 8
+        transformer_model: false
+        batch_size: &batch_size 256
+        max_epochs: &max_epochs 32
+        input_shape: [[1, 28, 28]]
       dataset:
         type: EmnistDataset
         args:
@@ -14,17 +16,21 @@ experiments:
         train_args:
           num_workers: 8
           train_fraction: 0.85
+          batch_size: *batch_size
       model: CharacterModel
       metrics: []
       network:
-        type: ResidualNetwork
+        type: DenseNet
         args:
+          growth_rate: 4
+          block_config: [4, 4]
           in_channels: 1
-          num_classes: 64 # Embedding
-          depths: [2,2]
-          block_sizes: [32, 64]
-          activation: selu
-          stn: false
+          base_channels: 24
+          num_classes: 128
+          bn_size: 4
+          dropout_rate: 0.1
+          classifier: true
+          activation: elu
       criterion:
         type: EmbeddingLoss
         args:
diff --git a/src/training/experiments/line_ctc_experiment.yml b/src/training/experiments/line_ctc_experiment.yml
deleted file mode 100644
index ef97527..0000000
--- a/src/training/experiments/line_ctc_experiment.yml
+++ /dev/null
@@ -1,92 +0,0 @@
-experiment_group: Lines Experiments
-experiments:
-    - train_args:
-        batch_size: 64
-        max_epochs: &max_epochs 64
-      dataset:
-        type: IamLinesDataset
-        args:
-          subsample_fraction: null
-          transform: null
-          target_transform: null
-        train_args:
-          num_workers: 8
-          train_fraction: 0.85
-      model: LineCTCModel
-      metrics: [cer, wer]
-      network:
-        type: LineRecurrentNetwork
-        args:
-          # backbone: ResidualNetwork
-          # backbone_args:
-          #   in_channels: 1
-          #   num_classes: 64 # Embedding
-          #   depths: [2,2]
-          #   block_sizes: [32, 64]
-          #   activation: selu
-          #   stn: false
-          backbone: ResidualNetwork
-          backbone_args:
-            pretrained: training/experiments/CharacterModel_EmnistDataset_ResidualNetwork/0920_025816/model/best.pt
-            freeze: false
-          flatten: false
-          input_size: 64
-          hidden_size: 64
-          bidirectional: true
-          num_layers: 2
-          num_classes: 80
-          patch_size: [28, 18]
-          stride: [1, 4]
-      criterion:
-        type: CTCLoss
-        args:
-          blank: 79
-      optimizer:
-        type: AdamW
-        args:
-          lr: 1.e-02
-          betas: [0.9, 0.999]
-          eps: 1.e-08
-          weight_decay: 5.e-4
-          amsgrad: false
-      lr_scheduler:
-        type: OneCycleLR
-        args:
-          max_lr: 1.e-02
-          epochs: *max_epochs
-          anneal_strategy: cos
-          pct_start: 0.475
-          cycle_momentum: true
-          base_momentum: 0.85
-          max_momentum: 0.9
-          div_factor: 10
-          final_div_factor: 10000
-          interval: step
-      # lr_scheduler:
-      #   type: CosineAnnealingLR
-      #   args:
-      #     T_max: *max_epochs
-      swa_args:
-        start: 48
-        lr: 5.e-2
-      callbacks: [Checkpoint, ProgressBar, WandbCallback, WandbImageLogger, EarlyStopping]
-      callback_args:
-        Checkpoint:
-          monitor: val_loss
-          mode: min
-        ProgressBar:
-          epochs: *max_epochs
-        EarlyStopping:
-          monitor: val_loss
-          min_delta: 0.0
-          patience: 10
-          mode: min
-        WandbCallback:
-          log_batch_frequency: 10
-        WandbImageLogger:
-          num_examples: 6
-      verbosity: 1 # 0, 1, 2
-      resume_experiment: null
-      train: true
-      test: true
-      test_metric: test_cer