IAM datasets implemented.

1 files changed, 73 insertions, 54 deletions

diff --git a/src/training/experiments/sample_experiment.yml b/src/training/experiments/sample_experiment.yml
index b00bd5a..17e220e 100644
--- a/src/training/experiments/sample_experiment.yml
+++ b/src/training/experiments/sample_experiment.yml
@@ -1,17 +1,20 @@
 experiment_group: Sample Experiments
 experiments:
-    - dataset: EmnistDataset
-      dataset_args:
-        sample_to_balance: true
-        subsample_fraction: null
-        transform: null
-        target_transform: null
-        seed: 4711
-      data_loader_args:
-        splits: [train, val]
-        shuffle: true
-        num_workers: 8
-        cuda: true
+    - train_args:
+        batch_size: 256
+        max_epochs: 32
+      dataset:
+        type: EmnistDataset
+        args:
+          sample_to_balance: true
+          subsample_fraction: null
+          transform: null
+          target_transform: null
+          seed: 4711
+        train_args:
+          num_workers: 6
+          train_fraction: 0.8
+
       model: CharacterModel
       metrics: [accuracy]
       # network: MLP
@@ -19,65 +22,81 @@ experiments:
       #   input_size: 784
       #   hidden_size: 512
       #   output_size: 80
-      #   num_layers: 3
-      #   dropout_rate: 0
+      #   num_layers: 5
+      #   dropout_rate: 0.2
       #   activation_fn: SELU
-      network: ResidualNetwork
-      network_args:
-        in_channels: 1
-        num_classes: 80
-        depths: [2, 1]
-        block_sizes: [96, 32]
+      network:
+        type: ResidualNetwork
+        args:
+          in_channels: 1
+          num_classes: 80
+          depths: [2, 2]
+          block_sizes: [64, 64]
+          activation: leaky_relu
+          stn: true
+      # network:
+      #   type: WideResidualNetwork
+      #   args:
+      #     in_channels: 1
+      #     num_classes: 80
+      #     depth: 10
+      #     num_layers: 3
+      #     width_factor: 4
+      #     dropout_rate: 0.2
+      #     activation: SELU
       # network: LeNet
       # network_args:
       #   output_size: 62
       #   activation_fn: GELU
-      train_args:
-        batch_size: 256
-        epochs: 32
-      criterion: CrossEntropyLoss
-      criterion_args:
-        weight: null
-        ignore_index: -100
-        reduction: mean
-      # optimizer: RMSprop
-      # optimizer_args:
-      #   lr: 1.e-3
-      #   alpha: 0.9
-      #   eps: 1.e-7
-      #   momentum: 0
-      #   weight_decay: 0
-      #   centered: false
-      optimizer: AdamW
-      optimizer_args:
-        lr: 1.e-03
-        betas: [0.9, 0.999]
-        eps: 1.e-08
-        # weight_decay: 5.e-4
-        amsgrad: false
-      # lr_scheduler: null
-      lr_scheduler: OneCycleLR
-      lr_scheduler_args:
-        max_lr: 1.e-03
-        epochs: 32
-        anneal_strategy: linear
-      callbacks: [Checkpoint, ProgressBar, EarlyStopping, WandbCallback, WandbImageLogger, OneCycleLR]
+      criterion:
+        type: CrossEntropyLoss
+        args:
+          weight: null
+          ignore_index: -100
+          reduction: mean
+      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-03
+      #     epochs: null
+      #     anneal_strategy: linear
+      lr_scheduler:
+        type: CosineAnnealingLR
+        args:
+          T_max: null
+      swa_args:
+        start: 2
+        lr: 5.e-2
+      callbacks: [Checkpoint, ProgressBar, WandbCallback, WandbImageLogger, EarlyStopping, SWA] # OneCycleLR]
       callback_args:
         Checkpoint:
           monitor: val_accuracy
         ProgressBar:
-          epochs: 32
+          epochs: null
           log_batch_frequency: 100
         EarlyStopping:
           monitor: val_loss
           min_delta: 0.0
-          patience: 3
+          patience: 5
           mode: min
         WandbCallback:
           log_batch_frequency: 10
         WandbImageLogger:
           num_examples: 4
-        OneCycleLR:
+          use_transpose: true
+        # OneCycleLR:
+        #   null
+        SWA:
           null
-      verbosity: 1 # 0, 1, 2
+      verbosity: 0 # 0, 1, 2
       resume_experiment: null
+      test: true
+      test_metric: test_accuracy