X-Git-Url: https://www.fleuret.org/cgi-bin/gitweb/gitweb.cgi?p=agtree2dot.git;a=blobdiff_plain;f=README.md;h=69806721794f3085c45668ec9d828f369addf76a;hp=007efc66d5af856bbe42cf8fafb161451967588a;hb=HEAD;hpb=a8b63a996712e71a274a9ef11fbe9dd262bd6ecd diff --git a/README.md b/README.md index 007efc6..6980672 100644 --- a/README.md +++ b/README.md @@ -1,7 +1,8 @@ # Introduction # -This package provides a function that generates a [dot file](https://en.wikipedia.org/wiki/DOT_(graph_description_language)) from the -autograd graph. +This package provides a function that generates a +[dot file](https://en.wikipedia.org/wiki/DOT_(graph_description_language)) +from a [PyTorch](http://pytorch.org) autograd graph. # Usage # @@ -9,19 +10,19 @@ autograd graph. ### agtree2dot.save_dot(variable, variable_labels, result_file) ### -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. +Saves into `result_file` a dot file corresponding to the autograd +graph for the `Variable` `variable`. The dictionary `variable_labels` +associates strings to some variables, which will be used in the +resulting graph. ## Example ## -A typical use would be: +A typical use is provided in [mlp.py](https://fleuret.org/git-extract/agtree2dot/mlp.py): ```python -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 @@ -39,22 +40,36 @@ class MLP(Module): return x mlp = MLP(10, 20, 1) -input = Variable(Tensor(100, 10).normal_()) -target = Variable(Tensor(100).normal_()) +input = Tensor(100, 10).normal_() +target = Tensor(100, 1).normal_() output = mlp(input) criterion = nn.MSELoss() loss = criterion(output, target) agtree2dot.save_dot(loss, - { input: 'input', target: 'target', loss: 'loss' }, + { + input: 'input', + target: 'target', + loss: 'loss', + mlp.fc1.weight: 'weight1', + mlp.fc1.bias: 'bias1', + mlp.fc2.weight: 'weight2', + mlp.fc2.bias: 'bias2', + }, open('./mlp.dot', 'w')) -``` -which would generate a file mlp.dot, which can then be translated to -pdf using the [Graphviz tools](http://www.graphviz.org/) +print('Generated mlp.dot') -``` -dot mlp.dot -Lg -T pdf -o mlp.pdf +try: + subprocess.check_call(['dot', 'mlp.dot', '-Lg', '-T', 'pdf', '-o', 'mlp.pdf' ]) + +except subprocess.CalledProcessError: + print('Calling the dot command failed. Is Graphviz installed?') + sys.exit(1) + +print('Generated mlp.pdf') ``` -to produce [mlp.pdf](https://fleuret.org/git-extract/agtree2dot/mlp.pdf). +which would generate a file mlp.dot and try to generate +[mlp.pdf](https://fleuret.org/git-extract/agtree2dot/mlp.pdf) from it +with [Graphviz tools.](http://www.graphviz.org/)