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rbf andl inear fixes

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Max Zwiessele 2014-02-17 12:04:40 +00:00
parent ebd63e4a60
commit 07737b7ba7
4 changed files with 6 additions and 4 deletions
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3
GPy/kern/parts/bias.py
View file

@ -14,7 +14,8 @@ class Bias(Kernpart):
:type variance: float :type variance: float
""" """
super(Bias, self).__init__(input_dim, name) super(Bias, self).__init__(input_dim, name)
self.variance = Param("variance", variance) from ...core.parameterization.transformations import Logexp
self.variance = Param("variance", variance, Logexp())
self.add_parameter(self.variance) self.add_parameter(self.variance)
def K(self,X,X2,target): def K(self,X,X2,target):

2
GPy/kern/parts/linear.py
View file

@ -61,7 +61,7 @@ class Linear(Kernpart):
def update_gradients_full(self, dL_dK, X): def update_gradients_full(self, dL_dK, X):
#self.variances.gradient[:] = 0 #self.variances.gradient[:] = 0
self._param_grad_helper(dL_dK, X, self.variances.gradient) self._param_grad_helper(dL_dK, X, None, self.variances.gradient)
def update_gradients_sparse(self, dL_dKmm, dL_dKnm, dL_dKdiag, X, Z): def update_gradients_sparse(self, dL_dKmm, dL_dKnm, dL_dKdiag, X, Z):
tmp = dL_dKdiag[:, None] * X ** 2 tmp = dL_dKdiag[:, None] * X ** 2

4
GPy/kern/parts/rbf.py
View file

@ -264,7 +264,7 @@ class RBF(Kernpart):
} }
""" """
num_data, num_inducing, input_dim = X.shape[0], X.shape[0], self.input_dim num_data, num_inducing, input_dim = X.shape[0], X.shape[0], self.input_dim
X, dvardLdK = param_to_array(X, dvardLdK) X, dvardLdK, var_len3 = param_to_array(X, dvardLdK, var_len3)
weave.inline(code, arg_names=['num_data', 'num_inducing', 'input_dim', 'X', 'target', 'dvardLdK', 'var_len3'], type_converters=weave.converters.blitz, **self.weave_options) weave.inline(code, arg_names=['num_data', 'num_inducing', 'input_dim', 'X', 'target', 'dvardLdK', 'var_len3'], type_converters=weave.converters.blitz, **self.weave_options)
else: else:
code = """ code = """
@ -281,7 +281,7 @@ class RBF(Kernpart):
} }
""" """
num_data, num_inducing, input_dim = X.shape[0], X2.shape[0], self.input_dim num_data, num_inducing, input_dim = X.shape[0], X2.shape[0], self.input_dim
X, X2, dvardLdK = param_to_array(X, X2, dvardLdK) X, X2, dvardLdK, var_len3 = param_to_array(X, X2, dvardLdK, var_len3)
weave.inline(code, arg_names=['num_data', 'num_inducing', 'input_dim', 'X', 'X2', 'target', 'dvardLdK', 'var_len3'], type_converters=weave.converters.blitz, **self.weave_options) weave.inline(code, arg_names=['num_data', 'num_inducing', 'input_dim', 'X', 'X2', 'target', 'dvardLdK', 'var_len3'], type_converters=weave.converters.blitz, **self.weave_options)
return target return target

1
GPy/util/__init__.py
View file

@ -10,6 +10,7 @@ import datasets
import mocap import mocap
import decorators import decorators
import classification import classification
import subarray_and_sorting
import caching import caching
try: try: