GPy/GPy/old_tests/mapping_tests.py
2015-03-23 12:38:15 +00:00

57 lines
2.1 KiB
Python

# Copyright (c) 2012, 2013 GPy authors (see AUTHORS.txt).
# Licensed under the BSD 3-clause license (see LICENSE.txt)
import unittest
import numpy as np
import GPy
class MappingGradChecker(GPy.core.Model):
"""
This class has everything we need to check the gradient of a mapping. It
implement a simple likelihood which is the sum of the outputs of the
mapping. the gradients are checked against the parameters of the mapping
and the input.
"""
def __init__(self, mapping, X, name):
super(MappingChecker).__init__(self, name)
self.mapping = mapping
self.add_parameter(self.mapping)
self.X = GPy.core.Param('X',X)
self.add_parameter(self.X)
self.dL_dY = np.ones((self.X.shape[0]. self.mapping.output_dim))
def log_likelihood(self):
return np.sum(self.mapping.f(X))
def parameters_changed(self):
self.X.gradient = self.mapping.gradients_X(self.dL_dY, self.X)
self.mapping.update_gradients(self.dL_dY, self.X)
class MappingTests(unittest.TestCase):
def test_kernelmapping(self):
verbose = False
mapping = GPy.mappings.Kernel(np.random.rand(10, 3), 2)
self.assertTrue(GPy.core.mapping.Mapping_check_df_dtheta(mapping=mapping).checkgrad(verbose=verbose))
self.assertTrue(GPy.core.mapping.Mapping_check_df_dX(mapping=mapping).checkgrad(verbose=verbose))
def test_linearmapping(self):
verbose = False
mapping = GPy.mappings.Linear(3, 2)
self.assertTrue(GPy.core.Mapping_check_df_dtheta(mapping=mapping).checkgrad(verbose=verbose))
self.assertTrue(GPy.core.Mapping_check_df_dX(mapping=mapping).checkgrad(verbose=verbose))
def test_mlpmapping(self):
verbose = False
mapping = GPy.mappings.MLP(input_dim=2, hidden_dim=[3, 4, 8, 2], output_dim=2)
self.assertTrue(GPy.core.Mapping_check_df_dtheta(mapping=mapping).checkgrad(verbose=verbose))
self.assertTrue(GPy.core.Mapping_check_df_dX(mapping=mapping).checkgrad(verbose=verbose))
if __name__ == "__main__":
print "Running unit tests, please be (very) patient..."
unittest.main()