code: def reparam(mu, std, do_sample=True, cuda=True):
      """Reparametrization for Normal distribution."""
      if do_sample:
          eps = torch.FloatTensor(std.size()).normal_()
          if cuda:
              eps = eps.cuda()
          eps = Variable(eps)
          return mu + eps * std
      else:
          return mu
  
imports: import matplotlib
  import matplotlib.pyplot
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from torch.autograd import Variable
  from torch.nn import Linear
  import os
label_desc: Use image node_id 4 for calling a global function with example usage: reparam(mu, std, do_sample, cuda) and returns: unknown, mu