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102 lines
3.3 KiB
Python
102 lines
3.3 KiB
Python
import numpy as np
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from GPy.util import choleskies
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import GPy
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import pytest
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from ..util.config import config
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try:
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from ..util import choleskies_cython
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choleskies_cython_working = config.getboolean("cython", "working")
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except ImportError:
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choleskies_cython_working = False
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try:
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from ..kern.src import stationary_cython
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stationary_cython_working = config.getboolean("cython", "working")
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except ImportError:
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stationary_cython_working = False
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"""
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These tests make sure that the pure python and cython codes work the same
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"""
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@pytest.skipIf(
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not choleskies_cython_working,
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"Cython cholesky module has not been built on this machine",
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)
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class CythonTestChols:
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def setup(self):
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self.flat = np.random.randn(45, 5)
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self.triang = np.array([np.eye(20) for i in range(3)])
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def test_flat_to_triang(self):
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L1 = choleskies._flat_to_triang_pure(self.flat)
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L2 = choleskies._flat_to_triang_cython(self.flat)
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assert np.allclose(L1, L2), "Triang mismatch!"
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def test_triang_to_flat(self):
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A1 = choleskies._triang_to_flat_pure(self.triang)
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A2 = choleskies._triang_to_flat_cython(self.triang)
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assert np.allclose(A1, A2), "Flat mismatch!"
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@pytest.skipIf(
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not stationary_cython_working,
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"Cython stationary module has not been built on this machine",
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)
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class TestStationary:
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def setup(self):
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self.k = GPy.kern.RBF(10)
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self.X = np.random.randn(300, 10)
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self.Z = np.random.randn(20, 10)
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self.dKxx = np.random.randn(300, 300)
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self.dKzz = np.random.randn(20, 20)
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self.dKxz = np.random.randn(300, 20)
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def test_square_gradX(self):
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self.setup()
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g1 = self.k._gradients_X_cython(self.dKxx, self.X)
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g2 = self.k._gradients_X_pure(self.dKxx, self.X)
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assert np.allclose(g1, g2), "Gradient mismatch on square X!"
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def test_rect_gradx(self):
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self.setup()
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g1 = self.k._gradients_X_cython(self.dKxz, self.X, self.Z)
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g2 = self.k._gradients_X_pure(self.dKxz, self.X, self.Z)
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assert np.allclose(g1, g2), "Gradient mismatch on rect X!"
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def test_square_lengthscales(self):
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self.setup()
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g1 = self.k._lengthscale_grads_pure(self.dKxx, self.X, self.X)
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g2 = self.k._lengthscale_grads_cython(self.dKxx, self.X, self.X)
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assert np.allclose(g1, g2), "Gradient mismatch on square lengthscale!"
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def test_rect_lengthscales(self):
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self.setup()
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g1 = self.k._lengthscale_grads_pure(self.dKxz, self.X, self.Z)
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g2 = self.k._lengthscale_grads_cython(self.dKxz, self.X, self.Z)
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assert np.allclose(g1, g2), "Gradient mismatch on rect lengthscale!"
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@pytest.skipIf(
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not choleskies_cython_working,
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"Cython cholesky module has not been built on this machine",
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)
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class TestCholeskiesBackprop:
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def setup(self):
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a = np.random.randn(10, 12)
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A = a.dot(a.T)
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self.L = GPy.util.linalg.jitchol(A)
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self.dL = np.random.randn(10, 10)
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def test_backprop(self):
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self.setup()
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r1 = choleskies._backprop_gradient_pure(self.dL, self.L)
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r2 = choleskies_cython.backprop_gradient(self.dL, self.L)
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r3 = choleskies_cython.backprop_gradient_par_c(self.dL, self.L)
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assert np.allclose(r1, r2), "Gradient mismatch!"
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assert np.allclose(r1, r3), "Gradient mismatch!"
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