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dim reduction adaption

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Max Zwiessele 2013-06-05 17:33:37 +01:00
parent a6ed003194
commit 71462a1347
3 changed files with 12 additions and 13 deletions
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10
GPy/inference/sgd.py
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@ -18,10 +18,10 @@ class opt_SGD(Optimizer):
"""
def __init__(self, start, iterations = 10, learning_rate = 1e-4, momentum = 0.9, Model = None, messages = False, batch_size = 1, self_paced = False, center = True, iteration_file = None, learning_rate_adaptation=None, actual_iter=None, schedule=None, **kwargs):
def __init__(self, start, iterations = 10, learning_rate = 1e-4, momentum = 0.9, model = None, messages = False, batch_size = 1, self_paced = False, center = True, iteration_file = None, learning_rate_adaptation=None, actual_iter=None, schedule=None, **kwargs):
self.opt_name = "Stochastic Gradient Descent"
self.Model = Model
self.Model = model
self.iterations = iterations
self.momentum = momentum
self.learning_rate = learning_rate
@ -42,11 +42,11 @@ class opt_SGD(Optimizer):
self.learning_rate_0 = self.learning_rate.mean()
self.schedule = schedule
# if len([p for p in self.Model.kern.parts if p.name == 'bias']) == 1:
# if len([p for p in self.model.kern.parts if p.name == 'bias']) == 1:
# self.param_traces.append(('bias',[]))
# if len([p for p in self.Model.kern.parts if p.name == 'linear']) == 1:
# if len([p for p in self.model.kern.parts if p.name == 'linear']) == 1:
# self.param_traces.append(('linear',[]))
# if len([p for p in self.Model.kern.parts if p.name == 'rbf']) == 1:
# if len([p for p in self.model.kern.parts if p.name == 'rbf']) == 1:
# self.param_traces.append(('rbf_var',[]))
self.param_traces = dict(self.param_traces)