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product kernel and combination kernel updates

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Max Zwiessele 2014-03-13 11:01:48 +00:00
parent 5fb0acbdb4
commit e9c96632ba
4 changed files with 58 additions and 54 deletions
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68
GPy/kern/_src/kernel_slice_operations.py
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@ -9,17 +9,17 @@ class KernCallsViaSlicerMeta(ParametersChangedMeta):
def __call__(self, *args, **kw):
instance = super(ParametersChangedMeta, self).__call__(*args, **kw)
instance.K = _slice_wrapper(instance, instance.K)
instance.Kdiag = _slice_wrapper(instance, instance.Kdiag, True)
instance.update_gradients_full = _slice_wrapper(instance, instance.update_gradients_full, False, True)
instance.update_gradients_diag = _slice_wrapper(instance, instance.update_gradients_diag, True, True)
instance.gradients_X = _slice_wrapper(instance, instance.gradients_X, False, True)
instance.gradients_X_diag = _slice_wrapper(instance, instance.gradients_X_diag, True, True)
instance.psi0 = _slice_wrapper(instance, instance.psi0, False, False)
instance.psi1 = _slice_wrapper(instance, instance.psi1, False, False)
instance.psi2 = _slice_wrapper(instance, instance.psi2, False, False)
instance.update_gradients_expectations = _slice_wrapper(instance, instance.update_gradients_expectations, psi_stat=True)
instance.gradients_Z_expectations = _slice_wrapper(instance, instance.gradients_Z_expectations, psi_stat_Z=True)
instance.gradients_qX_expectations = _slice_wrapper(instance, instance.gradients_qX_expectations, psi_stat=True)
instance.Kdiag = _slice_wrapper(instance, instance.Kdiag, diag=True)
instance.update_gradients_full = _slice_wrapper(instance, instance.update_gradients_full, diag=False, derivative=True)
instance.update_gradients_diag = _slice_wrapper(instance, instance.update_gradients_diag, diag=True, derivative=True)
instance.gradients_X = _slice_wrapper(instance, instance.gradients_X, diag=False, derivative=True)
instance.gradients_X_diag = _slice_wrapper(instance, instance.gradients_X_diag, diag=True, derivative=True)
instance.psi0 = _slice_wrapper(instance, instance.psi0, diag=False, derivative=False)
instance.psi1 = _slice_wrapper(instance, instance.psi1, diag=False, derivative=False)
instance.psi2 = _slice_wrapper(instance, instance.psi2, diag=False, derivative=False)
instance.update_gradients_expectations = _slice_wrapper(instance, instance.update_gradients_expectations, derivative=True, psi_stat=True)
instance.gradients_Z_expectations = _slice_wrapper(instance, instance.gradients_Z_expectations, derivative=True, psi_stat_Z=True)
instance.gradients_qX_expectations = _slice_wrapper(instance, instance.gradients_qX_expectations, derivative=True, psi_stat=True)
instance.parameters_changed()
return instance
@ -44,7 +44,29 @@ def _slice_wrapper(kern, operation, diag=False, derivative=False, psi_stat=False
finally:
kern._sliced_X -= 1
return ret
else:
elif psi_stat:
def x_slice_wrapper(dL_dpsi0, dL_dpsi1, dL_dpsi2, Z, variational_posterior):
Z, variational_posterior = kern._slice_X(Z) if not kern._sliced_X else Z, kern._slice_X(variational_posterior) if not kern._sliced_X else variational_posterior
kern._sliced_X += 1
try:
ret = operation(dL_dpsi0, dL_dpsi1, dL_dpsi2, Z, variational_posterior)
except:
raise
finally:
kern._sliced_X -= 1
return ret
elif psi_stat_Z:
def x_slice_wrapper(dL_dpsi1, dL_dpsi2, Z, variational_posterior):
Z, variational_posterior = kern._slice_X(Z) if not kern._sliced_X else Z, kern._slice_X(variational_posterior) if not kern._sliced_X else variational_posterior
kern._sliced_X += 1
try:
ret = operation(dL_dpsi1, dL_dpsi2, Z, variational_posterior)
except:
raise
finally:
kern._sliced_X -= 1
return ret
else:
def x_slice_wrapper(dL_dK, X, X2=None):
X, X2 = kern._slice_X(X) if not kern._sliced_X else X, kern._slice_X(X2) if X2 is not None and not kern._sliced_X else X2
kern._sliced_X += 1
@ -55,28 +77,6 @@ def _slice_wrapper(kern, operation, diag=False, derivative=False, psi_stat=False
finally:
kern._sliced_X -= 1
return ret
elif psi_stat:
def x_slice_wrapper(dL_dpsi0, dL_dpsi1, dL_dpsi2, Z, variational_posterior):
Z, variational_posterior = kern._slice_X(Z) if not kern._sliced_X else Z, kern._slice_X(variational_posterior) if not kern._sliced_X else variational_posterior
kern._sliced_X += 1
try:
ret = operation(dL_dpsi0, dL_dpsi1, dL_dpsi2, Z, variational_posterior)
except:
raise
finally:
kern._sliced_X -= 1
return ret
elif psi_stat_Z:
def x_slice_wrapper(dL_dpsi1, dL_dpsi2, Z, variational_posterior):
Z, variational_posterior = kern._slice_X(Z) if not kern._sliced_X else Z, kern._slice_X(variational_posterior) if not kern._sliced_X else variational_posterior
kern._sliced_X += 1
try:
ret = operation(dL_dpsi1, dL_dpsi2, Z, variational_posterior)
except:
raise
finally:
kern._sliced_X -= 1
return ret
else:
if diag:
def x_slice_wrapper(X, *args, **kw):