mirror of
https://github.com/SheffieldML/GPy.git
synced 2026-05-24 14:15:14 +02:00
[GPU] bug fix
This commit is contained in:
parent
c20cd69c4e
commit
73f690a4c9
2 changed files with 3 additions and 3 deletions
|
|
@ -410,7 +410,7 @@ class PSICOMP_SSRBF(object):
|
|||
dpsi1_dl_gpu = self.gpuCache['dpsi1_dl_gpu']
|
||||
dpsi2_dl_gpu = self.gpuCache['dpsi2_dl_gpu']
|
||||
psi1_comb_gpu = self.gpuCache['psi1_neq_gpu']
|
||||
psi2_comb_gpu = self.gpuCache['psi1_neq_gpu']
|
||||
psi2_comb_gpu = self.gpuCache['psi2_neq_gpu']
|
||||
grad_dl_gpu = self.gpuCache['grad_l_gpu']
|
||||
|
||||
# variance
|
||||
|
|
|
|||
|
|
@ -28,8 +28,8 @@ try:
|
|||
# log(1.0-X)
|
||||
logOne = ElementwiseKernel("double *in, double *out", "out[i] = log(1.-in[i])", "logOne_element")
|
||||
|
||||
# multiplication with broadcast on the last dimension (a has to be smaller than b)
|
||||
mul_bcast = ElementwiseKernel("double *out, double *a, double *b, int a_size", "out[i] = b[i]*a[i % a_size ]", "mul_bcast")
|
||||
# multiplication with broadcast on the last dimension
|
||||
mul_bcast = ElementwiseKernel("double *out, double *shorter, double *longer, int shorter_size", "out[i] = longer[i]*shorter[i%shorter_size]", "mul_bcast")
|
||||
|
||||
# sum through the middle dimension (size_2) of a 3D matrix (size_1, size_2, size_3)
|
||||
sum_axis = ElementwiseKernel("double *out, double *in, int size_1, int size_2", "out[i] += sum_axis_element(in, size_1, size_2, i)", "sum_axis",preamble="""
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue