Incorrect aggregation when logging predictions into EvalResult with distributed_backend DP
🐛 Bug
It it possible to log some data in EvalResult like this:
result = pl.EvalResult(checkpoint_on=val_loss)
result.y_hat = y_hat.float()

Suppose I log some value with dimensions (32, 10) - batch size 32 and 10 classes. And I have N samples in total.
If distributed_backend is None, in validation_epoch_end outputs.y_hat.shape is (N, 10)
If distributed_backend is ddp, in validation_epoch_end outputs.y_hat.shape is (N, 10)
But if distributed_backend is dp, in validation_epoch_end outputs.y_hat.shape is (N) - the values are averaged over samples.
Code sample
https://colab.research.google.com/drive/16NQaMTho5gI0URzgh3CNsZvXmHHyynvh?usp=sharing