'tng_loss' vs 'loss' in in training_step
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What is the difference between tng_loss and loss in in training_step?
It seems both are displayed in my progress bar although only tng_loss is part of prog (unless loss comes from somewhere else but I don't think I specified it somewhere). But tng_loss jumps around alot more. My guess is tng_loss (or whatever I specify in prog is per batch). If this is correct the main question is, what is loss in the output, is it the same as specified in training_step and if yes, why is it different from tng_loss in the displayed output and why is it displayed although it is not part of prog?
Code
My training_step based on the the documentation example:
def training_step(model, data_batch, batch_nb):
    input, label = data_batch

    out = model.forward(input)
    loss = model.loss(out, label)

    output = {
        'loss': loss, # required
        'prog': {'tng_loss': loss, 'batch_nb': batch_nb} # optional
    }
    # return a dict
    return output