mirror of
https://github.com/SheffieldML/GPy.git
synced 2026-05-07 11:02:38 +02:00
Added hessian and skew gradient checkers, some block functions
This commit is contained in:
parent
8f34bed6d7
commit
dff9ca8e6b
4 changed files with 323 additions and 18 deletions
|
|
@ -8,7 +8,7 @@ import itertools
|
|||
|
||||
def index_to_slices(index):
|
||||
"""
|
||||
take a numpy array of integers (index) and return a nested list of slices such that the slices describe the start, stop points for each integer in the index.
|
||||
take a numpy array of integers (index) and return a nested list of slices such that the slices describe the start, stop points for each integer in the index.
|
||||
|
||||
e.g.
|
||||
>>> index = np.asarray([0,0,0,1,1,1,2,2,2])
|
||||
|
|
@ -79,10 +79,10 @@ class IndependentOutputs(CombinationKernel):
|
|||
|
||||
def update_gradients_full(self,dL_dK,X,X2=None):
|
||||
slices = index_to_slices(X[:,self.index_dim])
|
||||
if self.single_kern:
|
||||
if self.single_kern:
|
||||
target = np.zeros(self.kern.size)
|
||||
kerns = itertools.repeat(self.kern)
|
||||
else:
|
||||
else:
|
||||
kerns = self.kern
|
||||
target = [np.zeros(kern.size) for kern, _ in zip(kerns, slices)]
|
||||
def collate_grads(kern, i, dL, X, X2):
|
||||
|
|
@ -94,7 +94,7 @@ class IndependentOutputs(CombinationKernel):
|
|||
else:
|
||||
slices2 = index_to_slices(X2[:,self.index_dim])
|
||||
[[[collate_grads(kern, i, dL_dK[s,s2],X[s],X2[s2]) for s in slices_i] for s2 in slices_j] for i,(kern,slices_i,slices_j) in enumerate(zip(kerns,slices,slices2))]
|
||||
if self.single_kern:
|
||||
if self.single_kern:
|
||||
self.kern.gradient = target
|
||||
else:
|
||||
[kern.gradient.__setitem__(Ellipsis, target[i]) for i, [kern, _] in enumerate(zip(kerns, slices))]
|
||||
|
|
@ -104,12 +104,14 @@ class IndependentOutputs(CombinationKernel):
|
|||
kerns = itertools.repeat(self.kern) if self.single_kern else self.kern
|
||||
if X2 is None:
|
||||
# TODO: make use of index_to_slices
|
||||
# FIXME: Broken as X is already sliced out
|
||||
print "Warning, gradients_X may not be working, I believe X has already been sliced out by the slicer!"
|
||||
values = np.unique(X[:,self.index_dim])
|
||||
slices = [X[:,self.index_dim]==i for i in values]
|
||||
[target.__setitem__(s, kern.gradients_X(dL_dK[s,s],X[s],None))
|
||||
for kern, s in zip(kerns, slices)]
|
||||
#slices = index_to_slices(X[:,self.index_dim])
|
||||
#[[np.add(target[s], kern.gradients_X(dL_dK[s,s], X[s]), out=target[s])
|
||||
#[[np.add(target[s], kern.gradients_X(dL_dK[s,s], X[s]), out=target[s])
|
||||
# for s in slices_i] for kern, slices_i in zip(kerns, slices)]
|
||||
#import ipdb;ipdb.set_trace()
|
||||
#[[(np.add(target[s ], kern.gradients_X(dL_dK[s ,ss],X[s ], X[ss]), out=target[s ]),
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue