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Tree based trainers implement ICanGetSummaryAsIDataView #3892

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Merged
merged 16 commits into from
Jul 2, 2019
Merged

Tree based trainers implement ICanGetSummaryAsIDataView #3892

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6127f95
IDataView function
artidoro Jun 18, 2019
4fe7683
testing a first option in one line
artidoro Jun 18, 2019
58d4125
working on alternative schema
artidoro Jun 18, 2019
e6017b5
changed schema one node per row
artidoro Jun 20, 2019
2c4fa9b
cleaning up
artidoro Jun 20, 2019
cc64586
lightgbm fact
artidoro Jun 28, 2019
7f632ff
add entrypoint test
artidoro Jun 28, 2019
567a77f
baseline output file fors other summary tests
artidoro Jun 28, 2019
4e36d41
working on updating the utils
artidoro Jun 29, 2019
791f31d
refactored utils class
artidoro Jul 1, 2019
78f4f86
update tests to check categorical splits
artidoro Jul 1, 2019
a9d91e7
fixing summary test so that it trains the model and gets the summary
artidoro Jul 1, 2019
79e9e16
change file open mode
artidoro Jul 1, 2019
b85fbf6
setting threads on fasttreetest
artidoro Jul 1, 2019
60f4bd1
trying to reduce variance in test
artidoro Jul 2, 2019
65885b8
refreshing baseline
artidoro Jul 2, 2019
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working on alternative schema
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@artidoro
artidoro committed Jul 1, 2019
commit 58d4125f0f54a9f7f56e25d714cfe1762c10da5f
86 changes: 52 additions & 34 deletions src/Microsoft.ML.FastTree/FastTree.cs
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Expand Up @@ -3415,55 +3415,73 @@ IDataView ICanGetSummaryAsIDataView.GetSummaryDataView(RoleMappedSchema schema)
var builder = new ArrayDataViewBuilder(Host);

var trees = TrainedTreeEnsemble.Trees;
var numberOfRows = trees.Select(tree => tree.NumberOfNodes).Sum();

// Bias column. It will be repeated for every tree.
// Tree id indicates which tree the node belongs to.
var treeId = new List<int>();
for (int i = 0; i < trees.Count; i++)
treeId.AddRange(Enumerable.Repeat(i, trees[i].NumberOfNodes));

builder.AddColumn(nameof(RegressionTreeEnsemble.Bias), NumberDataViewType.Double, treeId);

// Bias column. This is a repeated value for all trees.
builder.AddColumn(nameof(RegressionTreeEnsemble.Bias), NumberDataViewType.Double,
new[] { TrainedTreeEnsemble.Bias });
Enumerable.Repeat(TrainedTreeEnsemble.Bias, numberOfRows));

// TreeWeights column.
builder.AddColumn(nameof(RegressionTreeEnsemble.TreeWeights), NumberDataViewType.Double,
new[] { TrainedTreeEnsemble.TreeWeights.ToArray() });
var treeWeights = new List<double>();
for (int i = 0; i < trees.Count; i ++)
treeWeights.AddRange(Enumerable.Repeat(TrainedTreeEnsemble.TreeWeights[i], trees[i].NumberOfNodes));

builder.AddColumn(nameof(RegressionTreeEnsemble.TreeWeights), NumberDataViewType.Double, treeWeights);

// LeftChild column.
var leftChild = new List<int>();
for (int i = 0; i < trees.Count; i++)
{
string currentTree = $"_Tree_{i}";
leftChild.AddRange(trees[i].LeftChild.AsEnumerable());

builder.AddColumn(nameof(RegressionTree.LeftChild), NumberDataViewType.Int32, leftChild);

// LeftChild column.
builder.AddColumn(nameof(RegressionTree.LeftChild) + currentTree, NumberDataViewType.Int32,
new[] { trees[i].LeftChild.ToArray() });
// RightChild column.
var rightChild = new List<int>();
for (int i = 0; i < trees.Count; i++)
rightChild.AddRange(trees[i].RightChild.AsEnumerable());

builder.AddColumn(nameof(RegressionTree.RightChild), NumberDataViewType.Int32, rightChild);

// NumericalSplitFeatureIndexes column.
var numericalSplitFeatureIndexes = new List<int>();
for (int i = 0; i < trees.Count; i++)
numericalSplitFeatureIndexes.AddRange(trees[i].NumericalSplitFeatureIndexes.AsEnumerable());

// RightChild column.
builder.AddColumn(nameof(RegressionTree.RightChild) + currentTree, NumberDataViewType.Int32,
new[] { trees[i].RightChild.ToArray() });
builder.AddColumn(nameof(RegressionTree.NumericalSplitFeatureIndexes), NumberDataViewType.Int32, numericalSplitFeatureIndexes);

// NumericalSplitFeatureIndexes column.
builder.AddColumn(nameof(RegressionTree.NumericalSplitFeatureIndexes) + currentTree, NumberDataViewType.Int32,
new[] { trees[i].NumericalSplitFeatureIndexes.ToArray() });
// NumericalSplitThresholds column.
var numericalSplitThresholds = new List<float>();
for (int i = 0; i < trees.Count; i++)
numericalSplitThresholds.AddRange(trees[i].NumericalSplitThresholds.AsEnumerable());

// NumericalSplitThresholds column.
builder.AddColumn(nameof(RegressionTree.NumericalSplitThresholds) + currentTree, NumberDataViewType.Single,
new[] { trees[i].NumericalSplitThresholds.ToArray() });
builder.AddColumn(nameof(RegressionTree.NumericalSplitThresholds), NumberDataViewType.Single, numericalSplitThresholds);

// CategoricalSplitFlags column.
builder.AddColumn(nameof(RegressionTree.CategoricalSplitFlags) + currentTree, BooleanDataViewType.Instance,
new[] { trees[i].CategoricalSplitFlags.ToArray() });
// CategoricalSplitFlags column.
builder.AddColumn(nameof(RegressionTree.CategoricalSplitFlags), BooleanDataViewType.Instance,
new[] { trees[i].CategoricalSplitFlags.ToArray() });

// LeafValues column.
builder.AddColumn(nameof(RegressionTree.LeafValues) + currentTree, NumberDataViewType.Double,
new[] { trees[i].LeafValues.ToArray() });
// LeafValues column.
builder.AddColumn(nameof(RegressionTree.LeafValues), NumberDataViewType.Double,
new[] { trees[i].LeafValues.ToArray() });

// SplitGains column.
builder.AddColumn(nameof(RegressionTree.SplitGains) + currentTree, NumberDataViewType.Double,
new[] { trees[i].SplitGains.ToArray() });
// SplitGains column.
builder.AddColumn(nameof(RegressionTree.SplitGains), NumberDataViewType.Double,
new[] { trees[i].SplitGains.ToArray() });

// NumberOfLeaves column.
builder.AddColumn(nameof(RegressionTree.NumberOfLeaves) + currentTree, NumberDataViewType.Int32,
new[] { trees[i].NumberOfLeaves });
// NumberOfLeaves column.
builder.AddColumn(nameof(RegressionTree.NumberOfLeaves), NumberDataViewType.Int32,
new[] { trees[i].NumberOfLeaves });

// NumberOfNodes column.
builder.AddColumn(nameof(RegressionTree.NumberOfNodes) + currentTree, NumberDataViewType.Int32,
new[] { trees[i].NumberOfNodes });
}
// NumberOfNodes column.
builder.AddColumn(nameof(RegressionTree.NumberOfNodes), NumberDataViewType.Int32,
new[] { trees[i].NumberOfNodes });

// REVIEW: Should these two be exposed, if so how?
// public IReadOnlyList<int> GetCategoricalSplitFeaturesAt(int nodeIndex)
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