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[objective grads] undid the change, as this would lead to dramatic problems in reloading old models using the pickle module

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Max Zwiessele 2015-01-13 13:53:28 +00:00
parent 20eff02061
commit 53dcd3f9fa
2 changed files with 12 additions and 12 deletions
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6
GPy/core/model.py
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@ -257,7 +257,7 @@ class Model(Parameterized):
opt = optimizer(start, model=self, max_iters=max_iters, **kwargs) opt = optimizer(start, model=self, max_iters=max_iters, **kwargs)
with VerboseOptimization(self, opt, maxiters=max_iters, verbose=messages, ipython_notebook=ipython_notebook): with VerboseOptimization(self, opt, maxiters=max_iters, verbose=messages, ipython_notebook=ipython_notebook):
opt.run(f_fp=self._objective_and_grads, f=self._objective, fp=self._objective_grads) opt.run(f_fp=self._objective_grads, f=self._objective, fp=self._grads)
self.optimization_runs.append(opt) self.optimization_runs.append(opt)
@ -314,7 +314,7 @@ class Model(Parameterized):
# evaulate around the point x # evaulate around the point x
f1 = self._objective(x + dx) f1 = self._objective(x + dx)
f2 = self._objective(x - dx) f2 = self._objective(x - dx)
gradient = self._objective_grads(x) gradient = self._grads(x)
dx = dx[transformed_index] dx = dx[transformed_index]
gradient = gradient[transformed_index] gradient = gradient[transformed_index]
@ -360,7 +360,7 @@ class Model(Parameterized):
print "No free parameters to check" print "No free parameters to check"
return return
gradient = self._objective_grads(x).copy() gradient = self._grads(x).copy()
np.where(gradient == 0, 1e-312, gradient) np.where(gradient == 0, 1e-312, gradient)
ret = True ret = True
for nind, xind in itertools.izip(param_index, transformed_index): for nind, xind in itertools.izip(param_index, transformed_index):

18
GPy/core/verbose_optimization.py
View file

@ -12,8 +12,9 @@ def exponents(fnow, current_grad):
class VerboseOptimization(object): class VerboseOptimization(object):
def __init__(self, model, opt, maxiters, verbose=True, current_iteration=0, ipython_notebook=False): def __init__(self, model, opt, maxiters, verbose=True, current_iteration=0, ipython_notebook=False):
self.verbose = verbose self.verbose = verbose or ipython_notebook
if self.verbose or ipython_notebook: self.ipython_notebook = ipython_notebook
if self.verbose:
self.model = model self.model = model
self.iteration = current_iteration self.iteration = current_iteration
self.ipython_notebook = ipython_notebook self.ipython_notebook = ipython_notebook
@ -130,12 +131,11 @@ class VerboseOptimization(object):
def __exit__(self, type, value, traceback): def __exit__(self, type, value, traceback):
if self.verbose or self.ipython_notebook: if self.verbose or self.ipython_notebook:
self.stop = time.time()
self.model.remove_observer(self) self.model.remove_observer(self)
self.stop = time.time() self.print_out()
self.print_out() if not self.ipython_notebook:
print
if not self.ipython_notebook: print 'Optimization finished in {0:.5g} Seconds'.format(self.stop-self.start)
print print
print 'Optimization finished in {0:.5g} Seconds'.format(self.stop-self.start)
print