training_epoch_end's outputs doesn't have 'loss' key
pytorch-lightning: build from master
Traceback (most recent call last):
  File "main.py", line 140, in <module>
    main(hparams)
  File "main.py", line 72, in main
    trainer.fit(model)
  File "/mnt/lustre/maxiao1/anaconda3/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 881, in fit
    self.ddp_train(task, model)
  File "/mnt/lustre/maxiao1/anaconda3/lib/python3.7/site-packages/pytorch_lightning/trainer/distrib_data_parallel.py", line 539, in ddp_train
    self.run_pretrain_routine(model)
  File "/mnt/lustre/maxiao1/anaconda3/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 1091, in run_pretrain_routine
    self.train()
  File "/mnt/lustre/maxiao1/anaconda3/lib/python3.7/site-packages/pytorch_lightning/trainer/training_loop.py", line 376, in train
    self.run_training_epoch()
  File "/mnt/lustre/maxiao1/anaconda3/lib/python3.7/site-packages/pytorch_lightning/trainer/training_loop.py", line 510, in run_training_epoch
    self.run_training_epoch_end(epoch_output)
  File "/mnt/lustre/maxiao1/anaconda3/lib/python3.7/site-packages/pytorch_lightning/trainer/training_loop.py", line 535, in run_training_epoch_end
    epoch_output = model.training_epoch_end(epoch_output)
  File "/mnt/lustre/maxiao1/PVM/models/baseline.py", line 335, in training_epoch_end
    avg_loss = torch.stack([x['loss'] for x in outputs]).mean()
  File "/mnt/lustre/maxiao1/PVM/models/baseline.py", line 335, in <listcomp>
    avg_loss = torch.stack([x['loss'] for x in outputs]).mean()
KeyError: 'loss'

This is my code:
    def training_step(self, batch, batch_idx):
        ...
        return {'loss': loss, "train_acc": acc}

    def training_epoch_end(self, outputs):
        avg_loss = torch.stack([x['loss'] for x in outputs]).mean()
        avg_acc = torch.stack([x['train_acc'] for x in outputs]).mean()
        logs = {'loss': avg_loss, 'train_acc': avg_acc}
        progress_bar = {'train_loss': avg_loss, 'train_acc': avg_acc}
        results = {
            'log': logs,
            'progress_bar': progress_bar
        }
        return results