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[GPU] GPU version of varDTC is ready

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Zhenwen Dai 2014-04-07 10:25:16 +01:00
commit bbcba2553c
59 changed files with 2012 additions and 1186 deletions
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31
GPy/kern/_src/kern.py
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@ -11,13 +11,12 @@ from ...util.caching import Cache_this
class Kern(Parameterized):
#===========================================================================
# This adds input slice support. The rather ugly code for slicing can be
# This adds input slice support. The rather ugly code for slicing can be
# found in kernel_slice_operations
__metaclass__ = KernCallsViaSlicerMeta
#===========================================================================
_debug=False
_support_GPU=False
def __init__(self, input_dim, active_dims, name, useGPU=False,*a, **kw):
def __init__(self, input_dim, active_dims, name, useGPU=False, *a, **kw):
"""
The base class for a kernel: a positive definite function
which forms of a covariance function (kernel).
@ -178,22 +177,6 @@ class Kern(Parameterized):
#else: kernels.append(other)
return Prod([self, other], name)
def _getstate(self):
"""
Get the current state of the class,
here just all the indices, rest can get recomputed
"""
return super(Kern, self)._getstate() + [
self.active_dims,
self.input_dim,
self._sliced_X]
def _setstate(self, state):
self._sliced_X = state.pop()
self.input_dim = state.pop()
self.active_dims = state.pop()
super(Kern, self)._setstate(state)
class CombinationKernel(Kern):
"""
Abstract super class for combination kernels.
@ -211,9 +194,7 @@ class CombinationKernel(Kern):
:param array-like|slice extra_dims: if needed extra dimensions for the combination kernel to work on
"""
assert all([isinstance(k, Kern) for k in kernels])
active_dims = reduce(np.union1d, (np.r_[x.active_dims] for x in kernels), np.array([], dtype=int))
input_dim = active_dims.max()+1 + len(extra_dims)
active_dims = slice(active_dims.max()+1+len(extra_dims))
input_dim, active_dims = self.get_input_dim_active_dims(kernels, extra_dims)
# initialize the kernel with the full input_dim
super(CombinationKernel, self).__init__(input_dim, active_dims, name)
self.extra_dims = extra_dims
@ -223,6 +204,12 @@ class CombinationKernel(Kern):
def parts(self):
return self._parameters_
def get_input_dim_active_dims(self, kernels, extra_dims = None):
active_dims = reduce(np.union1d, (np.r_[x.active_dims] for x in kernels), np.array([], dtype=int))
input_dim = active_dims.max()+1 + (len(np.r_[extra_dims]) if extra_dims is not None else 0)
active_dims = slice(0, input_dim, 1)
return input_dim, active_dims
def input_sensitivity(self):
in_sen = np.zeros((self.num_params, self.input_dim))
for i, p in enumerate(self.parts):