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add mpi support for sparsegpregression

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This commit is contained in:
Zhenwen Dai 2014-11-05 17:50:23 +00:00
parent 1dbe3e34b0
commit f5377aa441
4 changed files with 46 additions and 7 deletions
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11
GPy/models/sparse_gp_regression.py
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@ -9,6 +9,7 @@ from .. import likelihoods
from .. import kern
from ..inference.latent_function_inference import VarDTC
from ..core.parameterization.variational import NormalPosterior
from GPy.inference.latent_function_inference.var_dtc_parallel import VarDTC_minibatch
class SparseGPRegression(SparseGP_MPI):
"""
@ -30,7 +31,7 @@ class SparseGPRegression(SparseGP_MPI):
"""
def __init__(self, X, Y, kernel=None, Z=None, num_inducing=10, X_variance=None, normalizer=None):
def __init__(self, X, Y, kernel=None, Z=None, num_inducing=10, X_variance=None, normalizer=None, mpi_comm=None):
num_data, input_dim = X.shape
# kern defaults to rbf (plus white for stability)
@ -48,8 +49,14 @@ class SparseGPRegression(SparseGP_MPI):
if not (X_variance is None):
X = NormalPosterior(X,X_variance)
if mpi_comm is not None:
from ..inference.latent_function_inference.var_dtc_parallel import VarDTC_minibatch
infr = VarDTC_minibatch(mpi_comm=mpi_comm)
else:
infr = VarDTC()
SparseGP_MPI.__init__(self, X, Y, Z, kernel, likelihood, inference_method=VarDTC(), normalizer=normalizer)
SparseGP_MPI.__init__(self, X, Y, Z, kernel, likelihood, inference_method=infr, normalizer=normalizer, mpi_comm=mpi_comm)
def parameters_changed(self):
from ..inference.latent_function_inference.var_dtc_parallel import update_gradients_sparsegp,VarDTC_minibatch