Function triplet_loss_hard_negative_mining

script/feature/misc.py:371–397

triplet loss with hard negative mining, inspired by http://www.bmva.org/bmvc/2016/papers/paper119/paper119.pdf section3.3 :param criterion: loss function :param f1: [lvl, B, C, H, W] :param f2: [lvl, B, C, H, W] :return: loss

(f1, f2, margin=1.)

    return loss

def triplet_loss_hard_negative_mining(f1, f2, margin=1.):
    ''' 
    triplet loss with hard negative mining, inspired by http://www.bmva.org/bmvc/2016/papers/paper119/paper119.pdf section3.3 
    :param criterion: loss function
    :param f1: [lvl, B, C, H, W]
    :param f2: [lvl, B, C, H, W]
    :return:
        loss
    '''
    criterion = nn.TripletMarginLoss(margin=margin, reduction='mean')
    anchor = f1
    anchor_negative = torch.roll(f1, shifts=1, dims=1)
    positive = f2
    negative = torch.roll(f2, shifts=1, dims=1)

    # select in-triplet hard negative, reference: section3.3 
    mse = nn.MSELoss(reduction='mean')
    with torch.no_grad():
        case1 = mse(anchor, negative)
        case2 = mse(positive, anchor_negative)
    
    # perform anchor swap if necessary
    if case1 < case2:
        loss = criterion(anchor, positive, negative)
    else:
        loss = criterion(positive, anchor, anchor_negative)
    return loss

def triplet_loss_hard_negative_mining_plus(f1, f2, margin=1.):
    ''&#x27;