def testShape(self):
num_dims = 3
problem_defs = [{
"name": "simple",
"options": {}
} for _ in xrange(num_dims)]
ensemble = problems.ensemble(problem_defs)
f = ensemble()
self.assertEqual(f.get_shape().as_list(), [])
def testVariables(self):
num_dims = 3
problem_defs = [{"name": "simple", "options": {}} for _ in xrange(num_dims)]
ensemble = problems.ensemble(problem_defs)
ensemble()
variables = tf.trainable_variables()
self.assertEqual(len(variables), num_dims)
for v in variables:
self.assertEqual(v.get_shape().as_list(), [])
def testValues(self, value):
num_dims = 1
weight = 0.5
problem_defs = [{"name": "simple", "options": {}} for _ in xrange(num_dims)]
ensemble = problems.ensemble(problem_defs, weights=[weight])
f = ensemble()
with self.test_session() as sess:
output = sess.run(f, feed_dict={"problem_0/x:0": value})
self.assertEqual(output, weight * value**2)