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Visualizer.py
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Visualizer.py
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import visdom
import numpy as np
import time
class Visualizer(object):
"""
封装了visdom的基本操作,但是你仍然可以通过`self.vis.function`
或者`self.function`调用原生的visdom接口
比如
self.text('hello visdom')
self.histogram(t.randn(1000))
self.line(t.arange(0, 10),t.arange(1, 11))
"""
def __init__(self, env='default', **kwargs):
self.vis = visdom.Visdom(env=env, **kwargs)
# 画的第几个数,相当于横坐标
# 比如(’loss',23) 即loss的第23个点
self.index = {}
self.log_text = ''
def reinit(self, env='default', **kwargs):
"""
修改visdom的配置
"""
self.vis = visdom.Visdom(env=env, **kwargs)
return self
def plot_many(self, d):
"""
一次plot多个
@params d: dict (name, value) i.e. ('loss', 0.11)
"""
for k, v in d.iteritems():
self.plot(k, v)
def img_many(self, d):
for k, v in d.iteritems():
self.img(k, v)
def plot(self, name, y, **kwargs):
# self.plot('loss', 1.00)
x = self.index.get(name, 0)
self.vis.line(Y=np.array([y]), X=np.array([x]),
win=name,
opts=dict(title=name),
update=None if x == 0 else 'append',
**kwargs
)
self.index[name] = x + 1
def img(self, name, img_, **kwargs):
"""
self.img('input_img', t.Tensor(64, 64))
self.img('input_imgs', t.Tensor(3, 64, 64))
self.img('input_imgs', t.Tensor(100, 1, 64, 64))
self.img('input_imgs', t.Tensor(100, 3, 64, 64), nrows=10)
"""
self.vis.images(img_,
win=name,
opts=dict(title=name),
**kwargs
)
def log(self, info, win='log_text'):
"""
self.log({'loss':1, 'lr':0.0001})
"""
self.log_text += ('[{time}] {info} <br>'.format(
time=time.strftime('%m%d_%H%M%S'), info=info))
self.vis.text(self.log_text, win)
def __getattr__(self, name):
"""
self.function 等价于self.vis.function
自定义的plot,image,log,plot_many等除外
"""
return getattr(self.vis, name)