def _compute_losses(self):
losses = votenet_module.get_loss(self.input, self.output, self.loss_params)
for loss_name, loss in losses.items():
if torch.is_tensor(loss):
if not self.losses_has_been_added:
self.loss_names += [loss_name]
setattr(self, loss_name, loss)
self.losses_has_been_added = True
def _compute_losses(self):
if self._weight_classes is not None:
self._weight_classes = self._weight_classes.to(self.device)
losses = votenet_module.get_loss(self.input,
self.output,
self.loss_params,
weight_classes=self._weight_classes)
for loss_name, loss in losses.items():
if torch.is_tensor(loss):
if not self.losses_has_been_added:
self.loss_names += [loss_name]
setattr(self, loss_name, loss)
self.losses_has_been_added = True
def _compute_losses(self):
losses = votenet_module.get_loss(self.input, self.output,
self.loss_params)
for loss_name, loss in losses.items():
if torch.is_tensor(loss):
if not self.losses_has_been_added:
self.loss_names += [loss_name]
setattr(self, loss_name, loss)
if self.semantic_logits is not None:
if not self.losses_has_been_added:
self.loss_names += ["semantic_loss"]
self.semantic_loss = torch.nn.functional.nll_loss(
self.semantic_logits,
self.semantic_labels,
ignore_index=IGNORE_LABEL)
self.loss += 10 * self.semantic_loss
self.losses_has_been_added = True