def __init__(self, **kwargs):
LossNM.__init__(self, **kwargs)
self._criterion = nn.MSELoss()
def __init__(self, weight=None, **kwargs):
LossNM.__init__(self, **kwargs)
if weight:
weight = torch.FloatTensor(weight).to(self._device)
self._criterion = nn.CrossEntropyLoss(weight=weight)
def __init__(self, *, num_inputs=2, **kwargs):
# Store number of inputs/losses.
self.num_losses = num_inputs
# kwargs["create_port_args"] = {"num_losses": num_inputs}
LossNM.__init__(self, **kwargs)
def __init__(self, label_smoothing=0.0, **kwargs):
LossNM.__init__(self, **kwargs)
self._criterion = SmoothedCrossEntropyLoss(label_smoothing)
def __init__(self):
LossNM.__init__(self)