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Detach loss tensors before scalar conversion #5

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Detach loss tensors before scalar conversion #5

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15 changes: 10 additions & 5 deletions models/base_model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -123,11 +123,16 @@ def get_current_visuals(self):

def get_current_losses(self):
"""Return traning losses / errors. simple.py will print out these errors on console, and save them to a file"""
errors_ret = OrderedDict()
for name in self.loss_names:
if isinstance(name, str):
errors_ret[name] = float(getattr(self, 'loss_' + name)) # float(...) works for both scalar tensor and float number
return errors_ret
errors_ret = OrderedDict()
for name in self.loss_names:
if isinstance(name, str):
loss_value = getattr(self, 'loss_' + name)
if isinstance(loss_value, torch.Tensor):
# detach() avoids inadvertently keeping autograd history when converting tensors to scalars
errors_ret[name] = loss_value.detach().item()
else:
errors_ret[name] = float(loss_value)
return errors_ret

def save_networks(self, epoch):
"""Save all the networks to the disk.
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