我正在使用python3.6
当我尝试在pymc3中运行NUTS采样时,我的jupyter笔记本一次又一次崩溃。
我的笔记本电脑有16GB和i7,我认为应该足够了。我在8gb和i7笔记本电脑上运行了相同的代码,并且在那个时候起作用了。无法弄清楚这是什么问题。
我已使用此命令为jupyter生成了配置文件
$ jupyter notebook --generate-config
我无法确定需要修改哪个参数来解决此问题。
这是我正在使用的代码
with pm.Model() as model:
#hyperpriors
home = pm.Flat('home') #flat pdf is uninformative - means we have no idea
sd_att = pm.HalfStudentT('sd_att', nu=3, sd=2.5)
sd_def = pm.HalfStudentT('sd_def', nu=3, sd=2.5)
intercept = pm.Flat('intercept')
# team-specific model parameters
atts_star = pm.Normal("atts_star", mu=0, sd=sd_att, shape=num_teams)
defs_star = pm.Normal("defs_star", mu=0, sd=sd_def, shape=num_teams)
# To allow samples of expressions to be saved, we need to wrap them in pymc3
Deterministic objects
atts = pm.Deterministic('atts', atts_star - tt.mean(atts_star))
defs = pm.Deterministic('defs', defs_star - tt.mean(defs_star))
# Assume exponential search on home_theta and away_theta. With pymc3, need to
rely on theano.
# tt is theano.tensor.. why Sampyl may be easier to use..
home_theta = tt.exp(intercept + home + atts[home_team] + defs[away_team])
away_theta = tt.exp(intercept + atts[away_team] + defs[home_team])
# likelihood of observed data
home_points = pm.Poisson('home_points', mu=home_theta,
observed=observed_home_goals)
away_points = pm.Poisson('away_points', mu=away_theta,
observed=observed_away_goals)
这也是错误sc:
答案 0 :(得分:0)
是的,您可以在激活环境后使用以下命令:
jupyter notebook --NotbookApp.iopub_Data_Rate_Limit=1e10
如果需要更多或更少的内存,请更改1e10。默认情况下为1e6。
答案 1 :(得分:0)
实际上这不是内存问题。
Jupyter出现此错误的原因有很多,例如在SAFARI上运行时,由于浏览器问题而引起的错误。如果不是默认浏览器,则在Google Chrome上也会出现同样的问题。
Jupyter现在不适用于6.0.1版本的龙卷风服务器,请使用其他版本的龙卷风。