mem_test.py

import numpy as np
import GPy
from sklearn.svm import SVR
import sys
import memory_profiler as mprof

model = sys.argv[1]

feats = np.random.random(size=(100,10))
labels = np.random.random(size=(100,1))

def f():
    for i in xrange(its):
        if model == "gpy":
            m = GPy.models.GPRegression(feats, labels)
        elif model == "svm":
            m = SVR(feats, labels.flatten())

if model == 'svm':
    its = 500000
elif model == 'gpy':
    its = 1000
mem_usage = mprof.memory_usage(f, timeout=10, interval=0.2)
print mem_usage