PyTorch 可视化工具Visdom

参考链接：使用 Visdom 在 PyTorch 中进行可视化

                    PyTorch 可视化工具 Visdom 介绍

                    Visdom 教程

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from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals

'''
import torch
import visdom

# 新建一个连接客户端
# 指定env = u'test1'，默认端口为8097，host是‘localhost'
vis = visdom.Visdom(env='test2',use_incoming_socket=False)
x = torch.arange(1, 30, 0.01)
y = torch.sin(x)
vis.line(X=x, Y=y, win='sinx', opts={'title': 'y=sin(x)'})


# append 追加数据
for ii in range(0, 10):
    # y = x
    x = torch.Tensor([ii])
    y = x
    vis.line(X=x, Y=y, win='polynomial', update='append' if ii>0 else None)
# updateTrace 新增一条线
x = torch.arange(0, 9, 0.1)
y = (x ** 2) / 9
vis.line(X=x, Y=y, win='polynomial', name='this is a new Trace',update='new')
'''


from visdom import Visdom
import numpy as np
import math
import os.path
import getpass
from sys import platform as _platform
from six.moves import urllib
 
viz = Visdom(env='test3')
assert viz.check_connection()
 
try:
    # video demo: download video from http://media.w3.org/2010/05/sintel/trailer.ogv
    video_url = 'http://media.w3.org/2010/05/sintel/trailer.ogv'
    # linux
    if _platform == "linux" or _platform == "linux2":
        videofile = '/home/%s/trailer.ogv' % getpass.getuser()
    # MAC OS X
    elif _platform == "darwin":
        videofile = '/Users/%s/trailer.ogv' % getpass.getuser()
    # download video
    urllib.request.urlretrieve(video_url, videofile)
 
    if os.path.isfile(videofile):
        viz.video(videofile=videofile)
except ImportError:
    print('Skipped video example')