title: How to visualize a pytorch graph (not a nn model) with tensorboard
body: <p>I'm wondering how to visualize the graph with tensorboard given just a few lines of codes(not a model)
  For example, for the following codes:</p>
  <pre><code>import torch
  import numpy as np
  from torch.autograd import Variable
  
  device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
  test1 = np.ones((70000,64))
  test1 = Variable(torch.Tensor(test1).to(device),requires_grad=True)
  p = test1[100:200]
  q = test1[200:300]
  ans2 = torch.sum(p + q)
  </code></pre>
  <p>How can I visualize the path from 'test1' to 'ans2'? I know how to visualize using tensorboard when a model (with forward function and input data) is given. But it is also important to me to check the forward and backpropagation graph of some functions.</p>
  <p>Thanks!</p>