diff options
Diffstat (limited to 'src/training')
| -rw-r--r-- | src/training/experiments/default_config_emnist.yml | 1 | ||||
| -rw-r--r-- | src/training/experiments/embedding_experiment.yml | 58 | ||||
| -rw-r--r-- | src/training/experiments/line_ctc_experiment.yml | 3 | ||||
| -rw-r--r-- | src/training/experiments/sample_experiment.yml | 1 | ||||
| -rw-r--r-- | src/training/run_experiment.py | 3 | ||||
| -rw-r--r-- | src/training/trainer/callbacks/base.py | 2 |
6 files changed, 65 insertions, 3 deletions
diff --git a/src/training/experiments/default_config_emnist.yml b/src/training/experiments/default_config_emnist.yml index 12a0a9d..bf2ed0a 100644 --- a/src/training/experiments/default_config_emnist.yml +++ b/src/training/experiments/default_config_emnist.yml @@ -66,4 +66,5 @@ callback_args: null verbosity: 1 # 0, 1, 2 resume_experiment: null +train: true validation_metric: val_accuracy diff --git a/src/training/experiments/embedding_experiment.yml b/src/training/experiments/embedding_experiment.yml new file mode 100644 index 0000000..e674c26 --- /dev/null +++ b/src/training/experiments/embedding_experiment.yml @@ -0,0 +1,58 @@ +experiment_group: Embedding Experiments +experiments: + - train_args: + batch_size: 256 + max_epochs: &max_epochs 8 + dataset: + type: EmnistDataset + args: + sample_to_balance: true + subsample_fraction: null + transform: null + target_transform: null + seed: 4711 + train_args: + num_workers: 8 + train_fraction: 0.85 + model: CharacterModel + metrics: [] + network: + type: ResidualNetwork + args: + in_channels: 1 + num_classes: 64 # Embedding + depths: [2,2] + block_sizes: [32, 64] + activation: selu + stn: false + criterion: + type: EmbeddingLoss + args: + margin: 0.2 + type_of_triplets: semihard + 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: CosineAnnealingLR + args: + T_max: *max_epochs + callbacks: [Checkpoint, ProgressBar, WandbCallback] + callback_args: + Checkpoint: + monitor: val_loss + mode: min + ProgressBar: + epochs: *max_epochs + WandbCallback: + log_batch_frequency: 10 + verbosity: 1 # 0, 1, 2 + resume_experiment: null + train: true + test: true + test_metric: mean_average_precision_at_r diff --git a/src/training/experiments/line_ctc_experiment.yml b/src/training/experiments/line_ctc_experiment.yml index f309990..ef97527 100644 --- a/src/training/experiments/line_ctc_experiment.yml +++ b/src/training/experiments/line_ctc_experiment.yml @@ -27,7 +27,7 @@ experiments: # stn: false backbone: ResidualNetwork backbone_args: - pretrained: training/experiments/CharacterModel_EmnistDataset_ResidualNetwork/0920_010806/model/best.pt + pretrained: training/experiments/CharacterModel_EmnistDataset_ResidualNetwork/0920_025816/model/best.pt freeze: false flatten: false input_size: 64 @@ -87,5 +87,6 @@ experiments: num_examples: 6 verbosity: 1 # 0, 1, 2 resume_experiment: null + train: true test: true test_metric: test_cer diff --git a/src/training/experiments/sample_experiment.yml b/src/training/experiments/sample_experiment.yml index 8664a15..a073a87 100644 --- a/src/training/experiments/sample_experiment.yml +++ b/src/training/experiments/sample_experiment.yml @@ -95,5 +95,6 @@ experiments: use_transpose: true verbosity: 0 # 0, 1, 2 resume_experiment: null + train: true test: true test_metric: test_accuracy diff --git a/src/training/run_experiment.py b/src/training/run_experiment.py index cc882ad..9d45841 100644 --- a/src/training/run_experiment.py +++ b/src/training/run_experiment.py @@ -273,7 +273,8 @@ def run_experiment( ) # Train the model. - trainer.fit(model) + if experiment_config["train"]: + trainer.fit(model) # Run inference over test set. if experiment_config["test"]: diff --git a/src/training/trainer/callbacks/base.py b/src/training/trainer/callbacks/base.py index 8c7b085..f81fc1f 100644 --- a/src/training/trainer/callbacks/base.py +++ b/src/training/trainer/callbacks/base.py @@ -92,7 +92,7 @@ class CallbackList: def append(self, callback: Type[Callback]) -> None: """Append new callback to callback list.""" - self.callbacks.append(callback) + self._callbacks.append(callback) def on_fit_begin(self) -> None: """Called when fit begins.""" |