class_docstr: Siamese network for image similarity estimation.
  The network is composed of two identical networks, one for each input.
  The output of each network is concatenated and passed to a linear layer.
  The output of the linear layer passed through a sigmoid function.
  `"FaceNet" <https://arxiv.org/pdf/1503.03832.pdf>`_ is a variant of the Siamese network.
  This implementation varies from FaceNet as we use the `ResNet-18` model from
  `"Deep Residual Learning for Image Recognition" <https://arxiv.org/pdf/1512.03385.pdf>`
  as our feature extractor.
  In addition we use CIFAR10 dataset along with TripletMarginLoss
class_docstr_tok: ["Siamese","network","for","image","similarity","estimation",".","The","network","is","composed","of","two","identical","networks",",","one","for","each","input",".","The","output","of","each","network","is","concatenated","and","passed","to","a","linear","layer",".","The","output","of","the","linear","layer","passed","through","a","sigmoid","function",".","`","``","FaceNet","''","<","https",":","\/\/arxiv.org\/pdf\/1503.03832.pdf",">","`","_","is","a","variant","of","the","Siamese","network",".","This","implementation","varies","from","FaceNet","as","we","use","the","`","ResNet-18","`","model","from","`","``","Deep","Residual","Learning","for","Image","Recognition","''","<","https",":","\/\/arxiv.org\/pdf\/1512.03385.pdf",">","`","as","our","feature","extractor",".","In","addition","we","use","CIFAR10","dataset","along","with","TripletMarginLoss"]
code: def forward_once(self, x):
      output = self.resnet(x)
      output = output.view(output.size()[0], -1)
      return output
  
imports: import argparse
  import numpy
  import torch
  import torch.nn
  import torch.optim
  import torchvision
  from torch.optim.lr_scheduler import StepLR
  from torch.utils.data import DataLoader, Dataset
  from torchvision import datasets
  from ignite.contrib.handlers import ProgressBar
  from ignite.engine import Engine, Events
  from ignite.handlers.param_scheduler import LRScheduler
  from ignite.metrics import Accuracy, RunningAverage
  from ignite.utils import manual_seed
label_desc: Use image node_id 3 for calling the SiameseNetwork obj's underlying member method code with example usage: obj.forward_once(x) and returns: output