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This commit is contained in:
Max Zwiessele 2014-03-13 12:29:35 +00:00
parent c6b1f513d3
commit e471ec7a15
1 changed files with 6 additions and 6 deletions
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12
GPy/models/mrd.py
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@ -104,23 +104,23 @@ class MRD(Model):
setattr(self, 'Y{}'.format(i), p)
self.add_parameter(p)
self._in_init_ = False
def parameters_changed(self):
self._log_marginal_likelihood = 0
self.posteriors = []
self.Z.gradient = 0.
self.X.mean.gradient = 0.
self.X.variance.gradient = 0.
for y, k, l, i in itertools.izip(self.Ylist, self.kern, self.likelihood, self.inference_method):
posterior, lml, grad_dict = i.inference(k, self.X, self.Z, l, y)
self.posteriors.append(posterior)
self._log_marginal_likelihood += lml
# likelihood gradients
l.update_gradients(grad_dict.pop('partial_for_likelihood'))
#gradients wrt kernel
dL_dKmm = grad_dict.pop('dL_dKmm')
k.update_gradients_full(dL_dKmm, self.Z, None)
@ -132,7 +132,7 @@ class MRD(Model):
self.Z.gradient += k.gradients_X(dL_dKmm, self.Z)
self.Z.gradient += k.gradients_Z_expectations(
grad_dict['dL_dpsi1'], grad_dict['dL_dpsi2'], Z=self.Z, variational_posterior=self.X)
dL_dmean, dL_dS = k.gradients_qX_expectations(variational_posterior=self.X, Z=self.Z, **grad_dict)
self.X.mean.gradient += dL_dmean
self.X.variance.gradient += dL_dS