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added Alan's bugfix to this version of GPy:

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sympykern is now forced to recompile if the function changes.

Also re-enabled openmp loops, since I only diabled them for bugfinding
This commit is contained in:
James Hensman 2012-12-17 11:04:42 +00:00
parent abde9fd22d
commit 7ae0c163c1
1 changed files with 20 additions and 16 deletions
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36
GPy/kern/sympykern.py
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@ -56,16 +56,14 @@ class spkern(kernpart):
self.weave_kwargs = {\ self.weave_kwargs = {\
'support_code':self._function_code,\ 'support_code':self._function_code,\
'include_dirs':[tempfile.gettempdir(), os.path.join(current_dir,'symbolic/')],\ 'include_dirs':[tempfile.gettempdir(), os.path.join(current_dir,'kern/')],\
'headers':['"sympy_helpers.h"'],\ 'headers':['"sympy_helpers.h"'],\
'sources':[os.path.join(current_dir,"symbolic/sympy_helpers.cpp")],\ 'sources':[os.path.join(current_dir,"kern/sympy_helpers.cpp")],\
#'extra_compile_args':['-ftree-vectorize', '-mssse3', '-ftree-vectorizer-verbose=5'],\ #'extra_compile_args':['-ftree-vectorize', '-mssse3', '-ftree-vectorizer-verbose=5'],\
'extra_compile_args':[],\ 'extra_compile_args':[],\
'extra_link_args':['-lgomp'],\ 'extra_link_args':['-lgomp'],\
'verbose':True} 'verbose':True}
def __add__(self,other): def __add__(self,other):
return spkern(self._sp_k+other._sp_k) return spkern(self._sp_k+other._sp_k)
@ -126,13 +124,14 @@ class spkern(kernpart):
int N = target_array->dimensions[0]; int N = target_array->dimensions[0];
int M = target_array->dimensions[1]; int M = target_array->dimensions[1];
int D = X_array->dimensions[1]; int D = X_array->dimensions[1];
//#pragma omp parallel for private(j) #pragma omp parallel for private(j)
for (i=0;i<N;i++){ for (i=0;i<N;i++){
for (j=0;j<M;j++){ for (j=0;j<M;j++){
target[i*M+j] = k(%s); target[i*M+j] = k(%s);
} }
} }
"""%(arglist) %s
"""%(arglist,"/*"+str(self._sp_k)+"*/") #adding a string representation forces recompile when needed
diag_arglist = re.sub('Z','X',arglist) diag_arglist = re.sub('Z','X',arglist)
diag_arglist = re.sub('j','i',diag_arglist) diag_arglist = re.sub('j','i',diag_arglist)
@ -142,11 +141,12 @@ class spkern(kernpart):
int i; int i;
int N = target_array->dimensions[0]; int N = target_array->dimensions[0];
int D = X_array->dimensions[1]; int D = X_array->dimensions[1];
//#pragma omp parallel for #pragma omp parallel for
for (i=0;i<N;i++){ for (i=0;i<N;i++){
target[i] = k(%s); target[i] = k(%s);
} }
"""%diag_arglist %s
"""%(diag_arglist,"/*"+str(self._sp_k)+"*/") #adding a string representation forces recompile when needed
#here's some code to compute gradients #here's some code to compute gradients
funclist = '\n'.join([' '*16 + 'target[%i] += partial[i*M+j]*dk_d%s(%s);'%(i,theta.name,arglist) for i,theta in enumerate(self._sp_theta)]) funclist = '\n'.join([' '*16 + 'target[%i] += partial[i*M+j]*dk_d%s(%s);'%(i,theta.name,arglist) for i,theta in enumerate(self._sp_theta)])
@ -157,13 +157,14 @@ class spkern(kernpart):
int N = partial_array->dimensions[0]; int N = partial_array->dimensions[0];
int M = partial_array->dimensions[1]; int M = partial_array->dimensions[1];
int D = X_array->dimensions[1]; int D = X_array->dimensions[1];
//#pragma omp parallel for private(j) #pragma omp parallel for private(j)
for (i=0;i<N;i++){ for (i=0;i<N;i++){
for (j=0;j<M;j++){ for (j=0;j<M;j++){
%s %s
} }
} }
"""%funclist %s
"""%(funclist,"/*"+str(self._sp_k)+"*/") #adding a string representation forces recompile when needed
#here's some code to compute gradients for Kdiag TODO: thius is yucky. #here's some code to compute gradients for Kdiag TODO: thius is yucky.
diag_funclist = re.sub('Z','X',funclist,count=0) diag_funclist = re.sub('Z','X',funclist,count=0)
@ -177,7 +178,8 @@ class spkern(kernpart):
for (i=0;i<N;i++){ for (i=0;i<N;i++){
%s %s
} }
"""%diag_funclist %s
"""%(diag_funclist,"/*"+str(self._sp_k)+"*/") #adding a string representation forces recompile when needed
#Here's some code to do gradients wrt x #Here's some code to do gradients wrt x
gradient_funcs = "\n".join(["target[i*D+%i] += partial[i*M+j]*dk_dx%i(%s);"%(q,q,arglist) for q in range(self.D)]) gradient_funcs = "\n".join(["target[i*D+%i] += partial[i*M+j]*dk_dx%i(%s);"%(q,q,arglist) for q in range(self.D)])
@ -188,13 +190,14 @@ class spkern(kernpart):
int N = partial_array->dimensions[0]; int N = partial_array->dimensions[0];
int M = partial_array->dimensions[1]; int M = partial_array->dimensions[1];
int D = X_array->dimensions[1]; int D = X_array->dimensions[1];
//#pragma omp parallel for private(j) #pragma omp parallel for private(j)
for (i=0;i<N; i++){ for (i=0;i<N; i++){
for (j=0; j<M; j++){ for (j=0; j<M; j++){
%s %s
} }
} }
"""%gradient_funcs %s
"""%(gradient_funcs,"/*"+str(self._sp_k)+"*/") #adding a string representation forces recompile when needed
#Here's some code to do gradients wrt z (should be the same as for X, but this is easier #Here's some code to do gradients wrt z (should be the same as for X, but this is easier
gradient_funcs_Z = "\n".join(["target[j*D+%i] += partial[i*M+j]*dk_dz%i(%s);"%(q,q,arglist) for q in range(self.D)]) gradient_funcs_Z = "\n".join(["target[j*D+%i] += partial[i*M+j]*dk_dz%i(%s);"%(q,q,arglist) for q in range(self.D)])
@ -210,8 +213,8 @@ class spkern(kernpart):
%s %s
} }
} }
"""%gradient_funcs_Z %s
"""%(gradient_funcs_Z,"/*"+str(self._sp_k)+"*/") #adding a string representation forces recompile when needed
#now for gradients of Kdiag wrt X #now for gradients of Kdiag wrt X
self._dKdiag_dX_code= \ self._dKdiag_dX_code= \
@ -225,7 +228,8 @@ class spkern(kernpart):
j = i; j = i;
%s %s
} }
"""%gradient_funcs %s
"""%(gradient_funcs,"/*"+str(self._sp_k)+"*/") #adding a string representation forces recompile when needed
#TODO: insert multiple functions here via string manipulation #TODO: insert multiple functions here via string manipulation