Add validation logging

golmschenk · Sep 3, 2024 · d15a6f9 · d15a6f9
1 parent fd6b344
commit d15a6f9
Showing 1 changed file with 8 additions and 5 deletions.
diff --git a/src/qusi/internal/module.py b/src/qusi/internal/module.py
@@ -57,7 +57,7 @@ def __init__(
         self._functional_logging_metric_cycle_totals: npt.NDArray = np.zeros(len(self.functional_logging_metrics),
                                                                              dtype=np.float32)
         self._loss_cycle_total: int = 0
-        self._steps_run_in_cycle: int = 0
+        self._steps_run_in_phase: int = 0
 
     def forward(self, inputs: Any) -> Any:
         return self.model(inputs)
@@ -76,7 +76,7 @@ def compute_loss_and_metrics(self, batch):
             functional_logging_metric_value = functional_logging_metric(predicted, target)
             self._functional_logging_metric_cycle_totals[
                 functional_logging_metric_index] += functional_logging_metric_value
-        self._steps_run_in_cycle += 1
+        self._steps_run_in_phase += 1
         return loss
 
     def on_train_epoch_end(self) -> None:
@@ -93,19 +93,22 @@ def log_loss_and_metrics(self, logging_name_prefix: str = ''):
             functional_logging_metric_cycle_total = float(self._functional_logging_metric_cycle_totals[
                                                               functional_logging_metric_index])
 
-            functional_logging_metric_cycle_mean = functional_logging_metric_cycle_total / self._steps_run_in_cycle
+            functional_logging_metric_cycle_mean = functional_logging_metric_cycle_total / self._steps_run_in_phase
             self.log(name=logging_name_prefix + functional_logging_metric_name,
                      value=functional_logging_metric_cycle_mean,
                      sync_dist=True)
-        mean_cycle_loss = self._loss_cycle_total / self._steps_run_in_cycle
+        mean_cycle_loss = self._loss_cycle_total / self._steps_run_in_phase
         self.log(name=logging_name_prefix + 'loss',
                  value=mean_cycle_loss, sync_dist=True)
         self._loss_cycle_total = 0
         self._functional_logging_metric_cycle_totals = np.zeros(len(self.functional_logging_metrics), dtype=np.float32)
-        self._steps_run_in_cycle = 0
+        self._steps_run_in_phase = 0
 
     def validation_step(self, batch: tuple[Any, Any], batch_index: int) -> STEP_OUTPUT:
         return self.compute_loss_and_metrics(batch)
 
+    def on_validation_epoch_end(self) -> None:
+        self.log_loss_and_metrics(logging_name_prefix='val_')
+
     def configure_optimizers(self):
         return self._optimizer