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fixing fitc
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2 changed files with 3 additions and 12 deletions
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@ -19,7 +19,7 @@ class DTC(object):
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def __init__(self):
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self.const_jitter = 1e-6
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def inference(self, kern, X, X_variance, Z, likelihood, Y):
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def inference(self, kern, X, Z, likelihood, Y):
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assert X_variance is None, "cannot use X_variance with DTC. Try varDTC."
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#TODO: MAX! fix this!
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@ -80,10 +80,6 @@ class DTC(object):
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grad_dict = {'dL_dKmm': dL_dK, 'dL_dKdiag':np.zeros_like(Knn), 'dL_dKnm':dL_dU.T}
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#update gradients
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kern.update_gradients_sparse(X=X, Z=Z, **grad_dict)
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likelihood.update_gradients(dL_dR)
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#construct a posterior object
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post = Posterior(woodbury_inv=Kmmi-P, woodbury_vector=v, K=Kmm, mean=None, cov=None, K_chol=L)
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@ -17,8 +17,7 @@ class FITC(object):
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def __init__(self):
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self.const_jitter = 1e-6
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def inference(self, kern, X, X_variance, Z, likelihood, Y):
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assert X_variance is None, "cannot use X_variance with FITC. Try varDTC."
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def inference(self, kern, X, Z, likelihood, Y):
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#TODO: MAX! fix this!
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from ...util.misc import param_to_array
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@ -81,11 +80,7 @@ class FITC(object):
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dL_dU *= beta_star
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dL_dU -= 2.*KiU*dL_dR
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grad_dict = {'dL_dKmm': dL_dK, 'dL_dKdiag':dL_dR, 'dL_dKnm':dL_dU.T}
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#update gradients
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kern.update_gradients_sparse(X=X, Z=Z, **grad_dict)
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likelihood.update_gradients(dL_dR)
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grad_dict = {'dL_dKmm': dL_dK, 'dL_dKdiag':dL_dR, 'dL_dKnm':dL_dU.T, 'partial_for_likelihood':dL_dR}
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#construct a posterior object
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post = Posterior(woodbury_inv=Kmmi-P, woodbury_vector=v, K=Kmm, mean=None, cov=None, K_chol=L)
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