apunkt/GPy
1
0
Fork 0
mirror of https://github.com/SheffieldML/GPy.git synced 2026-06-02 14:45:15 +02:00
Code Issues Projects Releases Packages Wiki Activity Actions

change the behavior the optimize_restarts to keep the original model parameters for the firt run

Browse source
This commit is contained in:
Zhenwen Dai 2015-05-14 17:38:07 +01:00
parent 466b381443
commit 0547177f32
1 changed files with 2 additions and 2 deletions
Download patch file Download diff file Expand all files Collapse all files

4
GPy/core/model.py
View file

@ -76,7 +76,7 @@ class Model(Parameterized):
jobs = [] jobs = []
pool = mp.Pool(processes=num_processes) pool = mp.Pool(processes=num_processes)
for i in range(num_restarts): for i in range(num_restarts):
self.randomize() if i>0: self.randomize()
job = pool.apply_async(opt_wrapper, args=(self,), kwds=kwargs) job = pool.apply_async(opt_wrapper, args=(self,), kwds=kwargs)
jobs.append(job) jobs.append(job)
@ -90,7 +90,7 @@ class Model(Parameterized):
for i in range(num_restarts): for i in range(num_restarts):
try: try:
if not parallel: if not parallel:
self.randomize() if i>0: self.randomize()
self.optimize(**kwargs) self.optimize(**kwargs)
else: else:
self.optimization_runs.append(jobs[i].get()) self.optimization_runs.append(jobs[i].get())