Made val & test loss like train loss (#664)

Co-authored-by: O'Donnell, Garry (DLSLtd,RAL,LSCI) <garry.o'donnell@diamond.ac.uk>
Co-authored-by: mergify[bot] <37929162+mergify[bot]@users.noreply.github.com>

pl_bolts/models/regression/logistic_regression.py

@@ -78,8 +78,8 @@ def training_step(self, batch: Tuple[Tensor, Tensor], batch_idx: int) -> Dict[st
  def validation_step(self, batch: Tuple[Tensor, Tensor], batch_idx: int) -> Dict[str, Tensor]:
  x, y = batch
  x = x.view(x.size(0), -1)
- y_hat = self(x)
- acc = accuracy(y_hat, y)
+ y_hat = self.linear(x)
+ acc = accuracy(F.softmax(y_hat, -1), y)
  return {'val_loss': F.cross_entropy(y_hat, y), 'acc': acc}
 
  def validation_epoch_end(self, outputs: List[Dict[str, Tensor]]) -> Dict[str, Tensor]:
@@ -91,8 +91,8 @@ def validation_epoch_end(self, outputs: List[Dict[str, Tensor]]) -> Dict[str, Te
 
  def test_step(self, batch: Tuple[Tensor, Tensor], batch_idx: int) -> Dict[str, Tensor]:
  x = x.view(x.size(0), -1)
- y_hat = self(x)
- acc = accuracy(y_hat, y)
+ y_hat = self.linear(x)
+ acc = accuracy(F.softmax(y_hat, -1), y)
  return {'test_loss': F.cross_entropy(y_hat, y), 'acc': acc}
 
  def test_epoch_end(self, outputs: List[Dict[str, Tensor]]) -> Dict[str, Tensor]: