ReduceLROnPlateau does not recognise val_loss despite progress_bar dict
🐛 Bug
When training my model, I get the following message:
  File "C:\Users\Luc\Miniconda3\envs\pytorch\lib\site-packages\pytorch_lightning\trainer\training_loop.py", line 371, in train
    raise MisconfigurationException(m)
pytorch_lightning.utilities.debugging.MisconfigurationException: ReduceLROnPlateau conditioned on metric val_loss which is not available. Available metrics are: loss

Ihis is similar to #321for instance, but I definitely return a progress_bar dict with a val_loss key in it (see code below).
Code sample
  def training_step(self, batch, batch_idx):
       z, y_true = batch
       y_pred = self.forward(z)
       loss_val = self.loss_function(y_pred, y_true)
       return {'loss': loss_val.sqrt()}

   def validation_step(self, batch, batch_idx):
       z, y_true = batch
       lr = torch.tensor(self.optim.param_groups[0]['lr'])
       y_pred = self.forward(z)
       loss_val = self.loss_function(y_pred, y_true)
       return {'val_loss': loss_val.sqrt(), 'lr': lr}

   def validation_epoch_end(self, outputs):
       val_loss_mean = torch.stack([x['val_loss'] for x in outputs]).mean()
       lr = outputs[-1]['lr']
       logs = {'val_loss': val_loss_mean, 'lr': lr}
       return {'val_loss': val_loss_mean, 'progress_bar': logs, 'log': logs}

Expected behavior
The val_loss value should be picked up by the progress bar.
Environment

PyTorch Version (e.g., 1.0): 1.4.0
OS (e.g., Linux): Windows 10
How you installed PyTorch (conda, pip, source): pip
Python version: 3.6.10
CUDA/cuDNN version: 10
GPU models and configuration: 1070Ti x 1
Any other relevant information: