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41 lines
1.1 KiB
Python
41 lines
1.1 KiB
Python
# Copyright (c) 2012, GPy authors (see AUTHORS.txt).
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# Licensed under the BSD 3-clause license (see LICENSE.txt)
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from kernpart import Kernpart
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import numpy as np
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class Fixed(Kernpart):
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def __init__(self, input_dim, K, variance=1.):
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"""
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:param input_dim: the number of input dimensions
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:type input_dim: int
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:param variance: the variance of the kernel
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:type variance: float
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"""
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self.input_dim = input_dim
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self.fixed_K = K
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self.num_params = 1
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self.name = 'fixed'
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self._set_params(np.array([variance]).flatten())
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def _get_params(self):
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return self.variance
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def _set_params(self, x):
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assert x.shape == (1,)
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self.variance = x
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def _get_param_names(self):
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return ['variance']
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def K(self, X, X2, target):
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target += self.variance * self.fixed_K
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def _param_grad_helper(self, partial, X, X2, target):
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target += (partial * self.fixed_K).sum()
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def gradients_X(self, partial, X, X2, target):
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pass
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def dKdiag_dX(self, partial, X, target):
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pass
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