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criterion_dis.py
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criterion_dis.py
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import torch
from torch.nn.modules.loss import _Loss
class DiscriminatorLoss_Wgan(_Loss):
'''
Wasserstein Distance
'''
def __init__(self, ) -> None:
super().__init__()
def forward(self, input, target):
# take the minus sign for maximum
return -(torch.mean(input) - torch.mean(target))
class DiscriminatorLoss_Maskrcnn(_Loss):
'''
L1 Distance
'''
def __init__(self, ) -> None:
super().__init__()
def forward(self, input, target):
# take the minus sign for maximum
return -torch.mean(torch.abs(input - target))
class GeneratorLoss_Maskrcnn(_Loss):
'''
L1 Distance
'''
def __init__(self, ) -> None:
super().__init__()
def forward(self, input, target):
# take the minus sign for maximum
return torch.mean(torch.abs(input - target))