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gradients

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Max Zwiessele 2014-02-26 13:18:29 +00:00
parent 3b82bc8f28
commit f6228abd4c
2 changed files with 3 additions and 3 deletions
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2
GPy/core/gp.py
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@ -70,7 +70,7 @@ class GP(Model):
def parameters_changed(self):
self.posterior, self._log_marginal_likelihood, grad_dict = self.inference_method.inference(self.kern, self.X, self.likelihood, self.Y, Y_metadata=self.Y_metadata)
self.kern.update_gradients_full(grad_dict['dL_dK'])
self.kern.update_gradients_full(grad_dict['dL_dK'], self.X)
def log_likelihood(self):
return self._log_marginal_likelihood

4
GPy/kern/_src/rbf.py
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@ -61,8 +61,8 @@ class RBF(Stationary):
#from psi2
S = variational_posterior.variance
denom, Zdist, Zdist_sq, mudist, mudist_sq, psi2 = self._psi2computations(Z, variational_posterior)
d_length = 2.*psi2[:, :, :, None] * (Zdist_sq[None, :,:,:] * denom + mudist_sq + S[:, None, None, :] / l2) / (self.lengthscale * denom)
denom, _, Zdist_sq, _, mudist_sq, psi2 = self._psi2computations(Z, variational_posterior)
d_length = 2.*psi2[:, :, :, None] * (Zdist_sq * denom + mudist_sq + S[:, None, None, :] / l2) / (self.lengthscale * denom)
#TODO: combine denom and l2 as denom_l2??
#TODO: tidy the above!
#TODO: tensordot below?