experiments/STT-tensorflow
1
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

Fix default direction to left when almost no sparsity for a sparse inequality split.

Browse Source 
PiperOrigin-RevId: 196026149
This commit is contained in:
A. Unique TensorFlower 2018-05-09 14:07:17 -07:00 committed by TensorFlower Gardener
parent 5d47c53adb
commit 42ee0ef7bc
2 changed files with 69 additions and 1 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

9
tensorflow/contrib/boosted_trees/kernels/split_handler_ops.cc
View File

@ -422,6 +422,10 @@ class BuildSparseInequalitySplitsOp : public BaseBuildSplitOp {
GradientStats(*gradients_t, *hessians_t, bucket_idx);
}
present_gradient_stats *= normalizer_ratio;
GradientStats not_present =
root_gradient_stats - present_gradient_stats;
// If there was (almost) no sparsity, fix the default direction to LEFT.
bool fixed_default_direction = not_present.IsAlmostZero();
GradientStats left_gradient_stats;
for (int64 element_idx = start_index; element_idx < end_index;
@ -441,6 +445,7 @@ class BuildSparseInequalitySplitsOp : public BaseBuildSplitOp {
// backward pass gradients.
GradientStats right_gradient_stats =
present_gradient_stats - left_gradient_stats;
{
NodeStats left_stats_default_left =
ComputeNodeStats(root_gradient_stats - right_gradient_stats);
@ -457,7 +462,9 @@ class BuildSparseInequalitySplitsOp : public BaseBuildSplitOp {
best_dimension_idx = dimension_id;
}
}
{
// Consider calculating the default direction only when there were
// enough missing examples.
if (!fixed_default_direction) {
NodeStats left_stats_default_right =
ComputeNodeStats(left_gradient_stats);
NodeStats right_stats_default_right =

61
tensorflow/contrib/boosted_trees/python/kernel_tests/split_handler_ops_test.py
View File

@ -18,6 +18,8 @@ from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import random
from tensorflow.contrib.boosted_trees.proto import learner_pb2
from tensorflow.contrib.boosted_trees.proto import split_info_pb2
from tensorflow.contrib.boosted_trees.python.ops import split_handler_ops
@ -399,6 +401,65 @@ class SplitHandlerOpsTest(test_util.TensorFlowTestCase):
self.assertAllClose(0.6, split_node.split.threshold)
def testMakeSparseSplitDefaultDirectionIsStable(self):
"""Tests default direction is stable when no sparsity."""
random.seed(1123)
for _ in range(50):
with self.test_session() as sess:
grad = random.random()
hessian = random.random()
# The data looks like the following (divide by the num of steps 2).
# Gradients | Partition | bucket ID |
# (grad, hessian) | 0 | -1 |
# And then 100 buckets of
# (grad/100, hessian/100), so there is no sparsity.
n_buckets = 100
# 1 for the overall sum, and 100 buckets.
partition_ids = array_ops.constant(
[0] * (n_buckets + 1), dtype=dtypes.int32)
# We have only 1 dimension in our sparse feature column.
bucket_ids = [-1] + [n for n in range(100)]
bucket_ids = array_ops.constant(bucket_ids, dtype=dtypes.int64)
dimension_ids = array_ops.constant(
[0] * (n_buckets + 1), dtype=dtypes.int64)
bucket_ids = array_ops.stack([bucket_ids, dimension_ids], axis=1)
gradients = [grad] + [grad / n_buckets] * n_buckets
gradients = array_ops.constant(gradients)
hessians = [hessian] + [hessian / n_buckets] * n_buckets
hessians = array_ops.constant(hessians)
boundaries = [x * 1 for x in range(n_buckets + 1)]
bucket_boundaries = array_ops.constant(boundaries, dtype=dtypes.float32)
partitions, gains, splits = (
split_handler_ops.build_sparse_inequality_splits(
num_minibatches=2,
partition_ids=partition_ids,
bucket_ids=bucket_ids,
gradients=gradients,
hessians=hessians,
bucket_boundaries=bucket_boundaries,
l1_regularization=0,
l2_regularization=2,
tree_complexity_regularization=0,
min_node_weight=0,
feature_column_group_id=0,
bias_feature_id=-1,
class_id=-1,
multiclass_strategy=learner_pb2.LearnerConfig.TREE_PER_CLASS))
partitions, gains, splits = (sess.run([partitions, gains, splits]))
self.assertAllEqual([0], partitions)
self.assertEqual(1, len(splits))
split_info = split_info_pb2.SplitInfo()
split_info.ParseFromString(splits[0])
self.assertTrue(
split_info.split_node.HasField(
'sparse_float_binary_split_default_left'))
def testMakeMulticlassSparseSplit(self):
"""Tests split handler op."""
with self.test_session() as sess: