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first attempt
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2 changed files with 28 additions and 2 deletions
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@ -5,6 +5,7 @@ import numpy as np
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from kern import CombinationKernel
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from ...util.caching import Cache_this
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import itertools
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import operator
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class Prod(CombinationKernel):
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"""
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@ -42,9 +43,19 @@ class Prod(CombinationKernel):
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return reduce(np.multiply, (p.Kdiag(X) for p in which_parts))
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def update_gradients_full(self, dL_dK, X, X2=None):
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np.seterr(invalid='raise')
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k = self.K(X,X2)*dL_dK
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for p in self.parts:
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p.update_gradients_full(k/p.K(X,X2),X,X2)
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try:
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for p in self.parts:
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p.update_gradients_full(k/p.K(X,X2),X,X2)
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except FloatingPointError:
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np.seterr(invalid='warn')
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print "Gradient warning: falling back to slow version due to zero-valued kernel"
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for combination in itertools.combinations(self.parts, len(self.parts) - 1):
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prod = reduce(operator.mul, [p.K(X, X2) for p in combination])
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to_update = list(set(self.parts) - set(combination))[0]
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to_update.update_gradients_full(dL_dK * prod, X, X2)
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def update_gradients_diag(self, dL_dKdiag, X):
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k = self.Kdiag(X)*dL_dKdiag
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@ -400,12 +400,27 @@ class Coregionalize_weave_test(unittest.TestCase):
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#reset the weave state for any other tests
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GPy.util.config.config.set('weave', 'working', 'False')
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class KernelTestsProductWithZeroValues(unittest.TestCase):
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def test_zero_valued_kernel(self):
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X = np.array([[0,1],[1,0]])
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Y = np.array([[1],[10]])
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lin = GPy.kern.Linear(2)
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bias = GPy.kern.Bias(2)
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k = lin * bias
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#k = lin
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m = GPy.models.GPRegression(X, Y, kernel=k)
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#m['mul.bias.variance'].constrain_fixed(0)
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m.optimize(messages=False)
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if __name__ == "__main__":
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print "Running unit tests, please be (very) patient..."
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unittest.main()
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#suite = unittest.TestLoader().loadTestsFromTestCase(KernelTestsProductWithZeroValues)
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#unittest.TextTestRunner().run(suite)
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# np.random.seed(0)
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# N0 = 3
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# N1 = 9
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