How to log cur_val_loss to tensorboard in validation_step?
I tried to get it to tensorboard this way
def validation_step(self, batch, batch_nb):
        data, target= batch
        output = self.forward(data)
        val_loss = nn.MSELoss(reduction = "mean")(output, target)
        return {'val_loss': val_loss, 'log':{'cur_val_loss':val_loss}}
but that didn't work.
How can I monitor validation loss not only at the end of each epoch, but during validation?