graphviz 的使用及pytorch結構的生成

graphviz類似於excel，想要使用它需要先進行本地的安裝。

官方網站

http://www.graphviz.org/

可以選擇安裝

msi或者zip，我在win8.1下使用msi安裝失敗，所以下載的zip版本，然後把bin文件添加進系統路徑，供python調用

然後需要在python的環境中安裝graphviz-2.38-hfd603c8_2.tar.bz2，具體可以在清華的鏡像服務器中找到

https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/win-64/

現在之後利用 conda install --use-local path 進行本地的安裝即可

 

生成pytorch的結構

visualize.py

from graphviz import Digraph
import torch
from torch.autograd import Variable
import grpc

def make_dot(var, params=None):
    """ Produces Graphviz representation of PyTorch autograd graph
    Blue nodes are the Variables that require grad, orange are Tensors
    saved for backward in torch.autograd.Function
    Args:
        var: output Variable
        params: dict of (name, Variable) to add names to node that
            require grad (TODO: make optional)
    """
    if params is not None:
        assert isinstance(params.values()[0], Variable)
        param_map = {id(v): k for k, v in params.items()}

    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 size_to_str(size):
        return '('+(', ').join(['%d' % v for v in size])+')'

    def add_nodes(var):
        if var not in seen:
            if torch.is_tensor(var):
                dot.node(str(id(var)), size_to_str(var.size()), fillcolor='orange')
            elif hasattr(var, 'variable'):
                u = var.variable
                name = param_map[id(u)] if params is not None else ''
                node_name = '%s\n %s' % (name, size_to_str(u.size()))
                dot.node(str(id(var)), node_name, fillcolor='lightblue')
            else:
                dot.node(str(id(var)), str(type(var).__name__))
            seen.add(var)
            if hasattr(var, 'next_functions'):
                for u in var.next_functions:
                    if u[0] is not None:
                        dot.edge(str(id(u[0])), str(id(var)))
                        add_nodes(u[0])
            if hasattr(var, 'saved_tensors'):
                for t in var.saved_tensors:
                    dot.edge(str(id(t)), str(id(var)))
                    add_nodes(t)
    add_nodes(var.grad_fn)
    return dot

if __name__ == '__main__':
    dot = Digraph(comment='The Round Table')

    # 添加圓點 A, A的標籤是 King Arthur
    dot.node('A', 'king')
    dot.view()  # 後面這句就註釋了，也可以使用這個命令查看效果

調用

    my_res = resnet18(input_channels=3)
    board_state = torch.rand(1, 3, 70, 66)
    resout = my_res(board_state)
    g = make_dot(resout)
    g.render('convLstm3_resnet18', view=True)