loss.py

import numpy as np
import torch
import torch.nn as nn
from torch import Tensor


class L1Loss(nn.Module):
    """
    &#24050;&#30693;&#20687;&#32032;&#37096;&#20998;&#30340;L1 loss(&#24179;&#22343;&#32477;&#23545;&#35823;&#24046;)
    """
    def __init__(self):
        super(L1Loss, self).__init__()

    def forward(self, pred: Tensor, y: Tensor, mask: Tensor) -> Tensor:
        l_valid = torch.sum(torch.abs(pred*mask-y*mask))/torch.sum(mask)
        l_hole = torch.sum(torch.abs((1-mask)*(pred-y)))/torch.sum(torch.abs(1-mask))
        return l_valid


class L2Loss(nn.Module):
    """
    &#24050;&#30693;&#20687;&#32032;&#37096;&#20998;&#30340;L2 loss(&#22343;&#26041;&#24046;&#35823;&#24046;&#25439;&#22833;)
    """
    def __init__(self):
        super(L2Loss, self).__init__()

    def forward(self, pred: Tensor, y: Tensor, mask: Tensor) -> Tensor:
        pixel_diff = (pred*mask-y*mask)**2
        loss = torch.sum(pixel_diff)/torch.sum(mask)
        return loss