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from graphviz import Digraph | |
import re | |
import torch | |
import torch.nn.functional as F | |
from torch.autograd import Variable | |
from torch.autograd import Variable | |
import torchvision.models as models | |
def make_dot(var): | |
node_attr = dict(style='filled', | |
shape='box', | |
align='left', | |
fontsize='12', | |
ranksep='0.1', | |
height='0.2') | |
dot = Digraph(node_attr=node_attr, graph_attr=dict(size="12,12")) | |
seen = set() | |
def add_nodes(var): | |
if var not in seen: | |
if isinstance(var, Variable): | |
value = '('+(', ').join(['%d'% v for v in var.size()])+')' | |
dot.node(str(id(var)), str(value), fillcolor='lightblue') | |
else: | |
dot.node(str(id(var)), str(type(var).__name__)) | |
seen.add(var) | |
if hasattr(var, 'previous_functions'): | |
for u in var.previous_functions: | |
dot.edge(str(id(u[0])), str(id(var))) | |
add_nodes(u[0]) | |
add_nodes(var.creator) | |
return dot | |
inputs = torch.randn(1,3,224,224) | |
resnet18 = models.resnet18() | |
y = resnet18(Variable(inputs)) | |
# print(y) | |
g = make_dot(y) | |
g.view() |
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