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[vardtc] missing data handling and stochastic update in d

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Max Zwiessele 2014-10-16 12:52:17 +01:00
parent 3358d06e42
commit 26396939e5
6 changed files with 124 additions and 37 deletions
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6
GPy/core/sparse_gp_mpi.py
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@ -34,7 +34,8 @@ 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):
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):
self._IN_OPTIMIZATION_ = False
if mpi_comm != None:
if inference_method is None:
@ -42,7 +43,8 @@ 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)
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)
self.update_model(False)
self.link_parameter(self.X, index=0)
if variational_prior is not None: