X-Git-Url: https://www.fleuret.org/cgi-bin/gitweb/gitweb.cgi?p=agtree2dot.git;a=blobdiff_plain;f=mlp.py;h=21d166bba9447a87315776cd741ad6d6f591e841;hp=8497848fa7c32413a05dbbf47e159d06764113fd;hb=HEAD;hpb=63f04303f0320d25d36e6a4f9f535e62cdb139e1

diff --git a/mlp.py b/mlp.py
index 8497848..4bf5841 100755
--- a/mlp.py
+++ b/mlp.py
@@ -17,36 +17,64 @@
 # Contact <francois.fleuret@idiap.ch> for comments & bug reports        #
 #########################################################################
 
+import subprocess
+
+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__()
+        super().__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 = torch.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()
+
+input = torch.randn(100, 10)
+target = torch.randn(100, 1)
+
+output = mlp(input)
+
 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'))
 
-print('Generated mlp.dot. You can convert it to pdf with')
-print('> dot mlp.dot -Lg -T pdf -o mlp.pdf')
+print('Generated mlp.dot')
+
+try:
+
+    fontname = 'Computer Modern'
+    fontsize = 12
+    subprocess.check_call(['dot', 'mlp.dot',
+                           '-Lg',
+                           '-T', 'pdf',
+                           '-Efontname=' + fontname, '-Efontsize=' + str(fontsize),
+                           '-Nfontname=' + fontname, '-Nfontsize=' + str(fontsize),
+                           '-o', 'mlp.pdf' ])
+
+except subprocess.CalledProcessError:
+
+    print('Calling the dot command failed. Is Graphviz installed?')
+    sys.exit(1)
+
+print('Generated mlp.pdf')