Is there any way to increase memory assigned to jupyter notebook

Question

I am using python3.6

My jupyter notebook is crashing again and again when I try to run NUTS sampling in pymc3.

My laptop has 16gb and i7 I think it should be enough. I ran same code on 8gb and i7 laptop and it worked that time. Not able to fig out what the issue is in this one.

I have generated the config file for jupyter with this command

$ jupyter notebook --generate-config

I am not able to fig out which parameter I need to modify to tackle this issue.

This is code I am using

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)

Also this is the error sc:

Solution

Yes, you can use the following command after activating your environment:

jupyter notebook --NotbookApp.iopub_Data_Rate_Limit=1e10

If you need more or less memory change 1e10. By default it is 1e6.

Comments

[101]

32-bit or 64-bit Python?

[PriyalChaudhari]

64 bit python .

[Klaus D.]

Please extend your error description beyond 'is crashing'!

[PriyalChaudhari]

@KlausD. Added sc of the problem

[molbdnilo]

How do you know that it's a memory problem?

[molbdnilo]

Are you using the same versions of all packages on both machines?

[PriyalChaudhari]

@molbdnilo yes i am using same version. i didnt see any prob. its same code. thats why i though might be memory.

[E. Erfan]

This si the general way to change memory assigned to Jupyter notebook. This will solve your problem if the cause of it is memory.