mlflow training loss not reported until end of run
I think I'm logging correctly, this is my training_step
    result = pl.TrainResult(loss)
    result.log('loss/train', loss)
    return result

and validation_step
    result = pl.EvalResult(loss)
    result.log('loss/validation', loss)
    return result

The validation loss is updated in mlflow each epoch, however the training loss isn't displayed until training has finished. Then it's available for every step. This may be a mlflow rather than pytorch-lighting issue - somewhere along the line it seems to be buffered?

Versions:
pytorch-lightning==0.9.0
mlflow==1.11.0
Edit: logging TrainResult with on_epoch=True results in the metric appearing in mlflow during training, it's only the default train logging which gets delayed. i.e.
    result.log('accuracy/train', acc, on_epoch=True)

is fine