README.md

   1 # Introduction #
   2
   3 This package provides a function that generates a
   4 [dot file](https://en.wikipedia.org/wiki/DOT_(graph_description_language))
   5 from a [pytorch](http://pytorch.org) autograd graph.
   6
   7 # Usage #
   8
   9 ## Functions ##
  10
  11 ### agtree2dot.save_dot(variable, variable_labels, result_file) ###
  12
  13 Saves into `result_file` a dot file corresponding to the autograd
  14 graph for the `Variable` `variable`. The dictionary `variable_labels`
  15 associates strings to some variables, which will be used in the
  16 resulting graph.
  17
  18 ## Example ##
  19
  20 A typical use is provided in [mlp.py](https://fleuret.org/git-extract/agtree2dot/mlp.py):
  21
  22 ```python
  23 import subprocess
  24
  25 from torch import nn
  26 from torch.nn import functional as fn
  27 from torch import Tensor
  28 from torch.autograd import Variable
  29 from torch.nn import Module
  30
  31 import agtree2dot
  32
  33 class MLP(Module):
  34     def __init__(self, input_dim, hidden_dim, output_dim):
  35         super(MLP, self).__init__()
  36         self.fc1 = nn.Linear(input_dim, hidden_dim)
  37         self.fc2 = nn.Linear(hidden_dim, output_dim)
  38
  39     def forward(self, x):
  40         x = self.fc1(x)
  41         x = fn.tanh(x)
  42         x = self.fc2(x)
  43         return x
  44
  45 mlp = MLP(10, 20, 1)
  46 input = Variable(Tensor(100, 10).normal_())
  47 target = Variable(Tensor(100).normal_())
  48 output = mlp(input)
  49 criterion = nn.MSELoss()
  50 loss = criterion(output, target)
  51
  52 agtree2dot.save_dot(loss,
  53                     {
  54                         input: 'input',
  55                         target: 'target',
  56                         loss: 'loss',
  57                         mlp.fc1.weight: 'weight1',
  58                         mlp.fc1.bias: 'bias1',
  59                         mlp.fc2.weight: 'weight2',
  60                         mlp.fc2.bias: 'bias2',
  61                     },
  62                     open('./mlp.dot', 'w'))
  63
  64 print('Generated mlp.dot')
  65
  66 try:
  67     subprocess.check_call(["dot", "mlp.dot", "-Lg", "-T", "pdf", "-o", "mlp.pdf" ])
  68 except subprocess.CalledProcessError:
  69     print('Calling the dot command failed. Is Graphviz installed?')
  70     sys.exit(1)
  71
  72 print('Generated mlp.pdf')
  73 ```
  74
  75 which would generate a file mlp.dot and try to generate
  76 [mlp.pdf](https://fleuret.org/git-extract/agtree2dot/mlp.pdf) from it
  77 with [Graphviz tools.](http://www.graphviz.org/)