Refactoring data with attrs and refactor conf for hydra

1 files changed, 84 insertions, 11 deletions

diff --git a/text_recognizer/callbacks/wandb_callbacks.py b/text_recognizer/callbacks/wandb_callbacks.py
index 4186b4a..d9d81f6 100644
--- a/text_recognizer/callbacks/wandb_callbacks.py
+++ b/text_recognizer/callbacks/wandb_callbacks.py
@@ -93,6 +93,40 @@ class LogTextPredictions(Callback):
     def __attrs_pre_init__(self) -> None:
         super().__init__()
 
+    def _log_predictions(
+        stage: str, trainer: Trainer, pl_module: LightningModule
+    ) -> None:
+        """Logs the predicted text contained in the images."""
+        if not self.ready:
+            return None
+
+        logger = get_wandb_logger(trainer)
+        experiment = logger.experiment
+
+        # Get a validation batch from the validation dataloader.
+        samples = next(iter(trainer.datamodule.val_dataloader()))
+        imgs, labels = samples
+
+        imgs = imgs.to(device=pl_module.device)
+        logits = pl_module(imgs)
+
+        mapping = pl_module.mapping
+        experiment.log(
+            {
+                f"OCR/{experiment.name}/{stage}": [
+                    wandb.Image(
+                        img,
+                        caption=f"Pred: {mapping.get_text(pred)}, Label: {mapping.get_text(label)}",
+                    )
+                    for img, pred, label in zip(
+                        imgs[: self.num_samples],
+                        logits[: self.num_samples],
+                        labels[: self.num_samples],
+                    )
+                ]
+            }
+        )
+
     def on_sanity_check_start(
         self, trainer: Trainer, pl_module: LightningModule
     ) -> None:
@@ -107,6 +141,27 @@ class LogTextPredictions(Callback):
         self, trainer: Trainer, pl_module: LightningModule
     ) -> None:
         """Logs predictions on validation epoch end."""
+        self._log_predictions(stage="val", trainer=trainer, pl_module=pl_module)
+
+    def on_train_epoch_end(self, trainer: Trainer, pl_module: LightningModule) -> None:
+        """Logs predictions on train epoch end."""
+        self._log_predictions(stage="test", trainer=trainer, pl_module=pl_module)
+
+
+@attr.s
+class LogReconstuctedImages(Callback):
+    """Log reconstructions of images."""
+
+    num_samples: int = attr.ib(default=8)
+    ready: bool = attr.ib(default=True)
+
+    def __attrs_pre_init__(self) -> None:
+        super().__init__()
+
+    def _log_reconstruction(
+        self, stage: str, trainer: Trainer, pl_module: LightningModule
+    ) -> None:
+        """Logs the reconstructions."""
         if not self.ready:
             return None
 
@@ -115,24 +170,42 @@ class LogTextPredictions(Callback):
 
         # Get a validation batch from the validation dataloader.
         samples = next(iter(trainer.datamodule.val_dataloader()))
-        imgs, labels = samples
+        imgs, _ = samples
 
         imgs = imgs.to(device=pl_module.device)
-        logits = pl_module(imgs)
+        reconstructions = pl_module(imgs)
 
-        mapping = pl_module.mapping
         experiment.log(
             {
-                f"Images/{experiment.name}": [
-                    wandb.Image(
-                        img,
-                        caption=f"Pred: {mapping.get_text(pred)}, Label: {mapping.get_text(label)}",
-                    )
-                    for img, pred, label in zip(
+                f"Reconstructions/{experiment.name}/{stage}": [
+                    [
+                        wandb.Image(img),
+                        wandb.Image(rec),
+                    ]
+                    for img, rec in zip(
                         imgs[: self.num_samples],
-                        logits[: self.num_samples],
-                        labels[: self.num_samples],
+                        reconstructions[: self.num_samples],
                     )
                 ]
             }
         )
+
+    def on_sanity_check_start(
+        self, trainer: Trainer, pl_module: LightningModule
+    ) -> None:
+        """Sets ready attribute."""
+        self.ready = False
+
+    def on_sanity_check_end(self, trainer: Trainer, pl_module: LightningModule) -> None:
+        """Start executing this callback only after all validation sanity checks end."""
+        self.ready = True
+
+    def on_validation_epoch_end(
+        self, trainer: Trainer, pl_module: LightningModule
+    ) -> None:
+        """Logs predictions on validation epoch end."""
+        self._log_reconstruction(stage="val", trainer=trainer, pl_module=pl_module)
+
+    def on_train_epoch_end(self, trainer: Trainer, pl_module: LightningModule) -> None:
+        """Logs predictions on train epoch end."""
+        self._log_reconstruction(stage="test", trainer=trainer, pl_module=pl_module)