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# Copyright 2016 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Tests for tf.contrib.tensor_forest.ops.best_splits_op."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import tensorflow # pylint: disable=unused-import
from tensorflow.contrib.tensor_forest.python.ops import training_ops
from tensorflow.python.framework import test_util
from tensorflow.python.platform import googletest
class BestSplitsClassificationTests(test_util.TensorFlowTestCase):
def setUp(self):
self.finished = [3, 5]
self.node_map = [-1, -1, -1, 0, -1, 3, -1, -1, -1]
self.candidate_counts = [[[50., 60., 40., 3.], [70., 30., 70., 30.]],
[[0., 0., 0., 0.], [0., 0., 0., 0.]],
[[0., 0., 0., 0.], [0., 0., 0., 0.]],
[[10., 10., 10., 10.], [10., 5., 5., 10.]]]
self.total_counts = [[100., 100., 100., 100.],
[0., 0., 0., 0.],
[0., 0., 0., 0.],
[100., 100., 100., 100.]]
self.squares = []
self.ops = training_ops.Load()
def testSimple(self):
with self.test_session():
split_indices = self.ops.best_splits(
self.finished, self.node_map, self.candidate_counts, self.squares,
self.total_counts, self.squares, regression=False)
self.assertAllEqual([0, 1], split_indices.eval())
def testNoFinished(self):
with self.test_session():
split_indices = self.ops.best_splits(
[], self.node_map, self.candidate_counts, self.squares,
self.total_counts, self.squares, regression=False)
self.assertAllEqual([], split_indices.eval())
def testBadInput(self):
del self.total_counts[1]
with self.test_session():
with self.assertRaisesOpError(
'Number of accumulators should be the same in split_sums '
'and accumulator_sums.'):
self.ops.best_splits(
self.finished, self.node_map, self.candidate_counts, self.squares,
self.total_counts, self.squares, regression=False).eval()
class BestSplitsRegressionTests(test_util.TensorFlowTestCase):
def setUp(self):
self.finished = [3, 5]
self.node_map = [-1, -1, -1, 0, -1, 3, -1, -1, -1]
self.candidate_sums = [[[5., 8., 8., 8.], [5., 10., 10., 10.]],
[[0., 0., 0., 0.], [0., 0., 0., 0.]],
[[0., 0., 0., 0.], [0., 0., 0., 0.]],
[[10., 10., 20., 10.], [10., 5., 5., 5.]]]
self.candidate_squares = [[[5., 50., 50., 50.], [5., 50., 50., 50.]],
[[0., 0., 0., 0.], [0., 0., 0., 0.]],
[[0., 0., 0., 0.], [0., 0., 0., 0.]],
[[10., 40., 50., 60.], [10., 40., 40., 40.]]]
self.total_sums = [[15., 10., 10., 10.],
[0., 0., 0., 0.],
[0., 0., 0., 0.],
[20., 20., 20., 20.]]
self.total_squares = [[15., 50., 50., 50.],
[0., 0., 0., 0.],
[0., 0., 0., 0.],
[20., 60., 60., 60.]]
self.ops = training_ops.Load()
def testSimple(self):
with self.test_session():
split_indices = self.ops.best_splits(
self.finished, self.node_map, self.candidate_sums,
self.candidate_squares, self.total_sums, self.total_squares,
regression=True)
self.assertAllEqual([1, 0], split_indices.eval())
if __name__ == '__main__':
googletest.main()
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