pil example Project utils LossFunctions (snippet)

Python pil example 'Project utils LossFunctions'

Modules used in program:

import torch.nn.functional as F
import torch.nn as nn
import numpy.random as rng
import PIL.ImageOps
import torch
import random
import numpy as np
import torchvision.utils
import matplotlib.pyplot as plt
import torchvision.transforms as transforms
import torchvision.datasets as dset
import torchvision

python Project utils LossFunctions

Python pil example: Project utils LossFunctions

import torchvision
import torchvision.datasets as dset
import torchvision.transforms as transforms
from keras.layers import Dense
from keras.layers import merge
from torch.utils.data import DataLoader,Dataset
import matplotlib.pyplot as plt
import torchvision.utils
import numpy as np
import random
from PIL import Image
import torch
from keras import backend as K
from torch.autograd import Variable
import PIL.ImageOps
import numpy.random as rng
import torch.nn as nn
from torch import optim
import torch.nn.functional as F






class ContrastiveLoss(torch.nn.Module):
    """
    Contrastive loss function.
    Based on: http://yann.lecun.com/exdb/publis/pdf/hadsell-chopra-lecun-06.pdf
    """

    def __init__(self, margin=2.0):
        super(ContrastiveLoss, self).__init__()
        self.margin = margin

    def forward(self, output1, output2, label):
        euclidean_distance = F.pairwise_distance(output1, output2)
        loss_contrastive = torch.mean((1-label) * torch.pow(euclidean_distance, 2) +
                                      (label) * torch.pow(torch.clamp(self.margin - euclidean_distance, min=0.0), 2))


        return loss_contrastive

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