Github user felixcheung commented on a diff in the pull request:
https://github.com/apache/spark/pull/17757#discussion_r113362748
--- Diff: R/pkg/inst/tests/testthat/test_mllib_classification.R ---
@@ -284,22 +284,11 @@ test_that("spark.mlp", {
c("1.0", "1.0", "1.0", "1.0", "0.0", "1.0", "2.0", "2.0",
"1.0", "0.0"))
# test initialWeights
- model <- spark.mlp(df, label ~ features, layers = c(4, 3), maxIter = 2,
initialWeights =
+ model <- spark.mlp(df, label ~ features, layers = c(4, 3),
initialWeights =
c(0, 0, 0, 0, 0, 5, 5, 5, 5, 5, 9, 9, 9, 9, 9))
mlpPredictions <- collect(select(predict(model, mlpTestDF),
"prediction"))
expect_equal(head(mlpPredictions$prediction, 10),
- c("1.0", "1.0", "1.0", "1.0", "2.0", "1.0", "2.0", "2.0",
"1.0", "0.0"))
-
- model <- spark.mlp(df, label ~ features, layers = c(4, 3), maxIter = 2,
initialWeights =
- c(0.0, 0.0, 0.0, 0.0, 0.0, 5.0, 5.0, 5.0, 5.0, 5.0, 9.0, 9.0, 9.0,
9.0, 9.0))
- mlpPredictions <- collect(select(predict(model, mlpTestDF),
"prediction"))
- expect_equal(head(mlpPredictions$prediction, 10),
- c("1.0", "1.0", "1.0", "1.0", "2.0", "1.0", "2.0", "2.0",
"1.0", "0.0"))
-
- model <- spark.mlp(df, label ~ features, layers = c(4, 3), maxIter = 2)
- mlpPredictions <- collect(select(predict(model, mlpTestDF),
"prediction"))
- expect_equal(head(mlpPredictions$prediction, 10),
- c("1.0", "1.0", "1.0", "1.0", "0.0", "1.0", "0.0", "2.0",
"1.0", "0.0"))
+ c("1.0", "1.0", "1.0", "1.0", "0.0", "1.0", "2.0", "2.0",
"1.0", "0.0"))
--- End diff --
I got the uncoverged test with the maxIter.
My main concern at this end is to at least exercise calling from R to JVM
for each public API we export (ie. by calling `predict` on the MLP model) - we
have had issues in the past the API never works and/or it is broken and we
don't know.
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