How do I pass metric to tensorboards hparam interface
What is your question?
I have been unable to log metrics on the hparam menu in pytorch lightning. I've been googling for a few hours and found it difficult to get a straight explanation of how to do this. The only available metric is a generic one called hp_metric.
Code
def validation_epoch_end(self, outputs):
    avg_loss = torch.stack(outputs).mean()
    self.log("avg_val_loss", avg_loss)
    self.logger.log_metrics({"val_loss_metric": avg_loss})

What have you tried?
I have used self.save_hyperparameters in init and passed my config and added a self.logger.log_metrics function to my validation step. I've tried looking through the docs for tensorboard, torch and pytorch lightning and found myself unable to figure out what is needed here.
What's your environment?

OS: Linux
Packaging conda
Version1.0.7