losses.py
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	import torch
	import torch.nn as nn
	import torch.nn.functional as F


	class TripletLoss(nn.Module):
	"""
	Triplet loss
	Takes embeddings of an anchor sample, a positive sample and a negative sample
	"""

	def __init__(self, margin):
	super(TripletLoss, self).__init__()
	self.margin = margin

	def forward(self, anchor, positive, negative, size_average=True):
	distance_positive = (anchor - positive).pow(2).sum(1) # .pow(.5)
	distance_negative = (anchor - negative).pow(2).sum(1) # .pow(.5)
	losses = F.relu(distance_positive - distance_negative + self.margin)
	return losses.mean() if size_average else losses.sum()