Moved code to lightning

Updating codebase to make use of pytorch-lightning

• Main train/valid loops are handled by lightning
• Removed device-handling code
• Each model implements its own train/valid/predict steps
• Updated config files for use with lightning
• Using lightning checkpointing and logging callbacks
• Updated DeviceMonitor to be compatible with lightning

src/ptbench/models/alexnet.py

@@ -60,6 +60,8 @@ class Alexnet(pl.LightningModule):
         # Forward pass on the network
         outputs = self(images)
 
+        # Manually move criterion to selected device, since not part of the model.
+        self.hparams.criterion = self.hparams.criterion.to(self.device)
         training_loss = self.hparams.criterion(outputs, labels.float())
 
         return {"loss": training_loss}
@@ -75,6 +77,11 @@ class Alexnet(pl.LightningModule):
 
         # data forwarding on the existing network
         outputs = self(images)
+
+        # Manually move criterion to selected device, since not part of the model.
+        self.hparams.criterion_valid = self.hparams.criterion_valid.to(
+            self.device
+        )
         validation_loss = self.hparams.criterion_valid(outputs, labels.float())
 
         return {"validation_loss": validation_loss}