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[VarDTC] reverted SparseGP to previous state, updated BGPLVM accordingly

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Max Zwiessele 2014-11-03 11:16:34 +00:00
parent 70afcd3ddd
commit 6b3888f163
5 changed files with 655 additions and 253 deletions
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6
GPy/core/sparse_gp_mpi.py
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@ -34,8 +34,7 @@ class SparseGP_MPI(SparseGP):
"""
def __init__(self, X, Y, Z, kernel, likelihood, variational_prior=None, inference_method=None, name='sparse gp mpi', Y_metadata=None, mpi_comm=None, normalizer=False,
missing_data=False, stochastic=False, batchsize=1):
def __init__(self, X, Y, Z, kernel, likelihood, variational_prior=None, inference_method=None, name='sparse gp mpi', Y_metadata=None, mpi_comm=None, normalizer=False):
self._IN_OPTIMIZATION_ = False
if mpi_comm != None:
if inference_method is None:
@ -43,8 +42,7 @@ class SparseGP_MPI(SparseGP):
else:
assert isinstance(inference_method, VarDTC_minibatch), 'inference_method has to support MPI!'
super(SparseGP_MPI, self).__init__(X, Y, Z, kernel, likelihood, inference_method=inference_method, name=name, Y_metadata=Y_metadata, normalizer=normalizer,
missing_data=missing_data, stochastic=stochastic, batchsize=batchsize)
super(SparseGP_MPI, self).__init__(X, Y, Z, kernel, likelihood, inference_method=inference_method, name=name, Y_metadata=Y_metadata, normalizer=normalizer)
self.update_model(False)
self.link_parameter(self.X, index=0)
if variational_prior is not None: