def testInferenceConstruction(self):
# pylint: disable=W0612
data = constant_op.constant(
[[random.uniform(-1, 1) for i in range(self.params.num_features)]
for _ in range(100)])
with variable_scope.variable_scope(
"DecisionsToDataThenNNTest_testInferenceConstruction"):
graph_builder = decisions_to_data_then_nn.DecisionsToDataThenNN(
self.params)
graph = graph_builder.inference_graph(data, None)
self.assertTrue(isinstance(graph, Tensor))
def testTrainingConstruction(self):
# pylint: disable=W0612
data = constant_op.constant(
[[random.uniform(-1, 1) for i in range(self.params.num_features)]
for _ in range(100)])
labels = [1 for _ in range(100)]
with variable_scope.variable_scope(
"DecisionsToDataThenNNTest_testTrainingConstruction"):
graph_builder = decisions_to_data_then_nn.DecisionsToDataThenNN(
self.params)
graph = graph_builder.training_graph(data, labels, None)
self.assertTrue(isinstance(graph, Operation))
def testHParams(self):
self.assertEquals(self.params.num_classes, 2)
self.assertEquals(self.params.num_features, 31)
self.assertEquals(self.params.layer_size, 11)
self.assertEquals(self.params.num_layers, 13)
self.assertEquals(self.params.num_trees, 17)
self.assertEquals(self.params.hybrid_tree_depth, 4)
self.assertEquals(self.params.connection_probability, 0.1)
# Building the graphs modifies the params.
with variable_scope.variable_scope("DecisionsToDataThenNNTest_testHParams"):
# pylint: disable=W0612
graph_builder = decisions_to_data_then_nn.DecisionsToDataThenNN(
self.params)
# Tree with depth 4 should have 2**0 + 2**1 + 2**2 + 2**3 = 15 nodes.
self.assertEquals(self.params.num_nodes, 15)
def testConstructionPollution(self):
"""Ensure that graph building doesn't modify the params in a bad way."""
# pylint: disable=W0612
data = [[random.uniform(-1, 1) for i in range(self.params.num_features)]
for _ in range(100)]
self.assertTrue(isinstance(self.params, tensor_forest.ForestHParams))
self.assertFalse(
isinstance(self.params.num_trees, tensor_forest.ForestHParams))
with variable_scope.variable_scope(
"DecisionsToDataThenNNTest_testContructionPollution"):
graph_builder = decisions_to_data_then_nn.DecisionsToDataThenNN(
self.params)
self.assertTrue(isinstance(self.params, tensor_forest.ForestHParams))
self.assertFalse(
isinstance(self.params.num_trees, tensor_forest.ForestHParams))
