mirror of
https://github.com/SheffieldML/GPy.git
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Merge branch 'devel' of github.com:SheffieldML/GPy into devel
This commit is contained in:
James Hensman
commit
621de63fc8
16 changed files with 290 additions and 103 deletions
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@ -12,6 +12,7 @@ from ...core.parameterization.transformations import Logexp
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from ...util.caching import Cache_this
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from ...core.parameterization import variational
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from psi_comp import linear_psi_comp
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from ...util.config import *
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class Linear(Kern):
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"""
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@ -224,12 +225,23 @@ class Linear(Kern):
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AZZA = ZA.T[:, None, :, None] * ZA[None, :, None, :]
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AZZA = AZZA + AZZA.swapaxes(1, 2)
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AZZA_2 = AZZA/2.
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if config.getboolean('parallel', 'openmp'):
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pragma_string = '#pragma omp parallel for private(m,mm,q,qq,factor,tmp)'
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header_string = '#include <omp.h>'
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weave_options = {'headers' : ['<omp.h>'],
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'extra_compile_args': ['-fopenmp -O3'],
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'extra_link_args' : ['-lgomp'],
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'libraries': ['gomp']}
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else:
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pragma_string = ''
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header_string = ''
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weave_options = {'extra_compile_args': ['-O3']}
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#Using weave, we can exploit the symmetry of this problem:
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code = """
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int n, m, mm,q,qq;
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double factor,tmp;
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#pragma omp parallel for private(m,mm,q,qq,factor,tmp)
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%s
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for(n=0;n<N;n++){
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for(m=0;m<num_inducing;m++){
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for(mm=0;mm<=m;mm++){
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@ -253,26 +265,36 @@ class Linear(Kern):
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}
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}
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}
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"""
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""" % pragma_string
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support_code = """
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#include <omp.h>
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%s
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#include <math.h>
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"""
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weave_options = {'headers' : ['<omp.h>'],
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'extra_compile_args': ['-fopenmp -O3'], #-march=native'],
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'extra_link_args' : ['-lgomp']}
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""" % header_string
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mu = vp.mean
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N,num_inducing,input_dim,mu = mu.shape[0],Z.shape[0],mu.shape[1],param_to_array(mu)
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weave.inline(code, support_code=support_code, libraries=['gomp'],
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weave.inline(code, support_code=support_code,
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arg_names=['N','num_inducing','input_dim','mu','AZZA','AZZA_2','target_mu','target_S','dL_dpsi2'],
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type_converters=weave.converters.blitz,**weave_options)
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def _weave_dpsi2_dZ(self, dL_dpsi2, Z, vp, target):
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AZA = self.variances*self._ZAinner(vp, Z)
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if config.getboolean('parallel', 'openmp'):
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pragma_string = '#pragma omp parallel for private(n,mm,q)'
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header_string = '#include <omp.h>'
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weave_options = {'headers' : ['<omp.h>'],
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'extra_compile_args': ['-fopenmp -O3'],
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'extra_link_args' : ['-lgomp'],
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'libraries': ['gomp']}
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else:
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pragma_string = ''
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header_string = ''
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weave_options = {'extra_compile_args': ['-O3']}
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code="""
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int n,m,mm,q;
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#pragma omp parallel for private(n,mm,q)
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%s
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for(m=0;m<num_inducing;m++){
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for(q=0;q<input_dim;q++){
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for(mm=0;mm<num_inducing;mm++){
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@ -282,18 +304,15 @@ class Linear(Kern):
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}
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}
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}
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"""
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""" % pragma_string
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support_code = """
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#include <omp.h>
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%s
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#include <math.h>
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"""
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weave_options = {'headers' : ['<omp.h>'],
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'extra_compile_args': ['-fopenmp -O3'], #-march=native'],
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'extra_link_args' : ['-lgomp']}
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""" % header_string
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N,num_inducing,input_dim = vp.mean.shape[0],Z.shape[0],vp.mean.shape[1]
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mu = param_to_array(vp.mean)
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weave.inline(code, support_code=support_code, libraries=['gomp'],
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weave.inline(code, support_code=support_code,
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arg_names=['N','num_inducing','input_dim','AZA','target','dL_dpsi2'],
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type_converters=weave.converters.blitz,**weave_options)
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@ -10,6 +10,7 @@ from GPy.util.caching import Cache_this
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from ...core.parameterization import variational
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from psi_comp import ssrbf_psi_comp
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from psi_comp.ssrbf_psi_gpucomp import PSICOMP_SSRBF
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from ...util.config import *
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class RBF(Stationary):
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"""
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@ -231,6 +232,16 @@ class RBF(Stationary):
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@Cache_this(limit=1)
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def _psi2computations(self, Z, vp):
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if config.getboolean('parallel', 'openmp'):
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pragma_string = '#pragma omp parallel for private(tmp, exponent_tmp)'
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header_string = '#include <omp.h>'
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libraries = ['gomp']
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else:
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pragma_string = ''
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header_string = ''
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libraries = []
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mu, S = vp.mean, vp.variance
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N, Q = mu.shape
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@ -253,8 +264,7 @@ class RBF(Stationary):
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variance_sq = float(np.square(self.variance))
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code = """
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double tmp, exponent_tmp;
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#pragma omp parallel for private(tmp, exponent_tmp)
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%s
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for (int n=0; n<N; n++)
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{
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for (int m=0; m<M; m++)
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@ -278,20 +288,20 @@ class RBF(Stationary):
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tmp = -Zdist_sq(m,mm,q) - tmp - half_log_denom(n,q);
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exponent_tmp += tmp;
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}
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//compute psi2 by exponontiating
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//compute psi2 by exponentiating
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psi2(n,m,mm) = variance_sq * exp(exponent_tmp);
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psi2(n,mm,m) = psi2(n,m,mm);
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}
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}
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}
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"""
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""" % pragma_string
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support_code = """
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#include <omp.h>
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%s
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#include <math.h>
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"""
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""" % header_string
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mu = param_to_array(mu)
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weave.inline(code, support_code=support_code, libraries=['gomp'],
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weave.inline(code, support_code=support_code, libraries=libraries,
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arg_names=['N', 'M', 'Q', 'mu', 'Zhat', 'mudist_sq', 'mudist', 'denom_l2', 'Zdist_sq', 'half_log_denom', 'psi2', 'variance_sq'],
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type_converters=weave.converters.blitz, **self.weave_options)
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@ -303,12 +313,20 @@ class RBF(Stationary):
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#return 2.*np.einsum( 'ijk,ijk,ijkl,il->l', dL_dpsi2, psi2, Zdist_sq * (2.*S[:,None,None,:]/l2 + 1.) + mudist_sq + S[:, None, None, :] / l2, 1./(2.*S + l2))*self.lengthscale
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result = np.zeros(self.input_dim)
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if config.getboolean('parallel', 'openmp'):
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pragma_string = '#pragma omp parallel for reduction(+:tmp)'
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header_string = '#include <omp.h>'
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libraries = ['gomp']
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else:
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pragma_string = ''
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header_string = ''
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libraries = []
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code = """
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double tmp;
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for(int q=0; q<Q; q++)
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{
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tmp = 0.0;
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#pragma omp parallel for reduction(+:tmp)
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%s
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for(int n=0; n<N; n++)
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{
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for(int m=0; m<M; m++)
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@ -326,16 +344,16 @@ class RBF(Stationary):
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result(q) = tmp;
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}
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"""
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""" % pragma_string
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support_code = """
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#include <omp.h>
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%s
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#include <math.h>
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"""
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""" % header_string
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N,Q = S.shape
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M = psi2.shape[-1]
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S = param_to_array(S)
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weave.inline(code, support_code=support_code, libraries=['gomp'],
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weave.inline(code, support_code=support_code, libraries=libraries,
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arg_names=['psi2', 'dL_dpsi2', 'N', 'M', 'Q', 'mudist_sq', 'l2', 'Zdist_sq', 'S', 'result'],
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type_converters=weave.converters.blitz, **self.weave_options)
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