This package provides a function that generates a dot file from a pytorch autograd graph.

Saves into `result_file`

a dot file corresponding to the autograd graph for `variable`

, which can be either a single `Variable`

or a set of `Variable`

s. The dictionary `variable_labels`

associates strings to some variables, which will be used in the resulting graph.

A typical use would be:

```
import torch
from torch import nn
from torch.nn import functional as fn
from torch import Tensor
from torch.autograd import Variable
from torch.nn import Module
import agtree2dot
class MLP(Module):
def __init__(self, input_dim, hidden_dim, output_dim):
super(MLP, self).__init__()
self.fc1 = nn.Linear(input_dim, hidden_dim)
self.fc2 = nn.Linear(hidden_dim, output_dim)
def forward(self, x):
x = self.fc1(x)
x = fn.tanh(x)
x = self.fc2(x)
return x
mlp = MLP(10, 20, 1)
input = Variable(Tensor(100, 10).normal_())
target = Variable(Tensor(100).normal_())
output = mlp(input)
criterion = nn.MSELoss()
loss = criterion(output, target)
agtree2dot.save_dot(loss,
{ input: 'input', target: 'target', loss: 'loss' },
open('./mlp.dot', 'w'))
```

which would generate a file mlp.dot, which can then be translated to pdf using the Graphviz tools

`dot mlp.dot -Lg -T pdf -o mlp.pdf`

to produce mlp.pdf.