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Posted to issues@flink.apache.org by tillrohrmann <gi...@git.apache.org> on 2016/02/04 16:17:45 UTC
[GitHub] flink pull request: [FLINK-3330] [ml] Fix SparseVector support in ...
GitHub user tillrohrmann opened a pull request:
https://github.com/apache/flink/pull/1587
[FLINK-3330] [ml] Fix SparseVector support in GradientDescent
The GradientDescent implementation did not work with sparse input data
because it requires the gradient to be dense. This patch makes sure that
the gradient sum is always dense.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/tillrohrmann/flink fixSparseGradientDescent
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/flink/pull/1587.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #1587
----
commit 3eb72b8674e082d8d78445a282bea09921103a08
Author: Till Rohrmann <tr...@apache.org>
Date: 2016-02-04T15:13:10Z
[FLINK-3330] [ml] Fix SparseVector support in GradientDescent
The GradientDescent implementation did not work with sparse input data
because it requires the gradient to be dense. This patch makes sure that
the gradient sum is always dense.
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[GitHub] flink pull request: [FLINK-3330] [ml] Fix SparseVector support in ...
Posted by thvasilo <gi...@git.apache.org>.
Github user thvasilo commented on a diff in the pull request:
https://github.com/apache/flink/pull/1587#discussion_r51909968
--- Diff: flink-libraries/flink-ml/src/test/scala/org/apache/flink/ml/regression/RegressionData.scala ---
@@ -27,6 +27,21 @@ object RegressionData {
val expectedWeight0: Double = 9.8158
val expectedSquaredResidualSum: Double = 49.7596/2
+ val sparseData: Seq[LabeledVector] = Seq(
+ new LabeledVector(1.0, new SparseVector(10, Array(0, 2, 3), Array(1.0, 1.0, 1.0))),
+ new LabeledVector(1.0, new SparseVector(10, Array(0, 1, 5, 9), Array(1.0, 1.0, 1.0, 1.0))),
+ new LabeledVector(0.0, new SparseVector(10, Array(0, 2), Array(0.0, 1.0))),
+ new LabeledVector(0.0, new SparseVector(10, Array(0), Array(0.0))),
+ new LabeledVector(0.0, new SparseVector(10, Array(0, 2), Array(0.0, 1.0))),
+ new LabeledVector(0.0, new SparseVector(10, Array(0), Array(0.0))))
+
+ val expectedWeightsSparseInput = Array(0.5448906338353784, 0.15718880164669916,
+ 0.034001300318125725, 0.38770183218867915, 0.0,
+ 0.15718880164669916, 0.0, 0.0, 0.0, 0.15718880164669916)
--- End diff --
Indentation seems a bit off here.
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[GitHub] flink pull request: [FLINK-3330] [ml] Fix SparseVector support in ...
Posted by tillrohrmann <gi...@git.apache.org>.
Github user tillrohrmann commented on the pull request:
https://github.com/apache/flink/pull/1587#issuecomment-180292797
Travis passed. Will merge the PR then.
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[GitHub] flink pull request: [FLINK-3330] [ml] Fix SparseVector support in ...
Posted by tillrohrmann <gi...@git.apache.org>.
Github user tillrohrmann commented on a diff in the pull request:
https://github.com/apache/flink/pull/1587#discussion_r52001518
--- Diff: flink-libraries/flink-ml/src/main/scala/org/apache/flink/ml/optimization/GradientDescent.scala ---
@@ -192,10 +190,18 @@ abstract class GradientDescent extends IterativeSolver {
(left, right) =>
val (leftGradVector, leftCount) = left
val (rightGradVector, rightCount) = right
- // Add the left gradient to the right one
- BLAS.axpy(1.0, leftGradVector.weights, rightGradVector.weights)
+
+ // make the left gradient dense so that the following reduce operations (left fold) reuse
+ // it. This strongly depends on the underlying implementation of the ReduceDriver
--- End diff --
If this should change in the future, the code has to be adapted to reflect that as well.
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[GitHub] flink pull request: [FLINK-3330] [ml] Fix SparseVector support in ...
Posted by thvasilo <gi...@git.apache.org>.
Github user thvasilo commented on a diff in the pull request:
https://github.com/apache/flink/pull/1587#discussion_r51910120
--- Diff: flink-libraries/flink-ml/src/main/scala/org/apache/flink/ml/optimization/GradientDescent.scala ---
@@ -192,10 +190,18 @@ abstract class GradientDescent extends IterativeSolver {
(left, right) =>
val (leftGradVector, leftCount) = left
val (rightGradVector, rightCount) = right
- // Add the left gradient to the right one
- BLAS.axpy(1.0, leftGradVector.weights, rightGradVector.weights)
+
+ // make the left gradient dense so that the following reduce operations (left fold) reuse
+ // it. This strongly depends on the underlying implementation of the ReduceDriver
--- End diff --
Hey @tillrohrmann could you explain what you mean by "strongly depends on the underlying implementation of the ReduceDriver"?
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[GitHub] flink pull request: [FLINK-3330] [ml] Fix SparseVector support in ...
Posted by tillrohrmann <gi...@git.apache.org>.
Github user tillrohrmann commented on a diff in the pull request:
https://github.com/apache/flink/pull/1587#discussion_r52001534
--- Diff: flink-libraries/flink-ml/src/test/scala/org/apache/flink/ml/regression/RegressionData.scala ---
@@ -27,6 +27,21 @@ object RegressionData {
val expectedWeight0: Double = 9.8158
val expectedSquaredResidualSum: Double = 49.7596/2
+ val sparseData: Seq[LabeledVector] = Seq(
+ new LabeledVector(1.0, new SparseVector(10, Array(0, 2, 3), Array(1.0, 1.0, 1.0))),
+ new LabeledVector(1.0, new SparseVector(10, Array(0, 1, 5, 9), Array(1.0, 1.0, 1.0, 1.0))),
+ new LabeledVector(0.0, new SparseVector(10, Array(0, 2), Array(0.0, 1.0))),
+ new LabeledVector(0.0, new SparseVector(10, Array(0), Array(0.0))),
+ new LabeledVector(0.0, new SparseVector(10, Array(0, 2), Array(0.0, 1.0))),
+ new LabeledVector(0.0, new SparseVector(10, Array(0), Array(0.0))))
+
+ val expectedWeightsSparseInput = Array(0.5448906338353784, 0.15718880164669916,
+ 0.034001300318125725, 0.38770183218867915, 0.0,
+ 0.15718880164669916, 0.0, 0.0, 0.0, 0.15718880164669916)
--- End diff --
Will fix it.
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[GitHub] flink pull request: [FLINK-3330] [ml] Fix SparseVector support in ...
Posted by asfgit <gi...@git.apache.org>.
Github user asfgit closed the pull request at:
https://github.com/apache/flink/pull/1587
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[GitHub] flink pull request: [FLINK-3330] [ml] Fix SparseVector support in ...
Posted by tillrohrmann <gi...@git.apache.org>.
Github user tillrohrmann commented on a diff in the pull request:
https://github.com/apache/flink/pull/1587#discussion_r52001489
--- Diff: flink-libraries/flink-ml/src/main/scala/org/apache/flink/ml/optimization/GradientDescent.scala ---
@@ -192,10 +190,18 @@ abstract class GradientDescent extends IterativeSolver {
(left, right) =>
val (leftGradVector, leftCount) = left
val (rightGradVector, rightCount) = right
- // Add the left gradient to the right one
- BLAS.axpy(1.0, leftGradVector.weights, rightGradVector.weights)
+
+ // make the left gradient dense so that the following reduce operations (left fold) reuse
+ // it. This strongly depends on the underlying implementation of the ReduceDriver
--- End diff --
The reduce is implemented somewhat like a left fold operation, just without having an initial value. Thus you should not convert the right element, because it will always be the newly read input element.
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