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library(RVowpalWabbit)
# Test 1:
# {VW} -b 17 -l 20 --initial_t 128000 --power_t 1 -d train-sets/0001.dat -f models/0001.model -c --passes 2 --compressed --ngram 3 --skips 1
test1 <- c("-b", "17",
"-l", "20",
"--initial_t", "128000",
"--power_t", "1",
"-d", system.file("test", "train-sets", "0001.dat", package="RVowpalWabbit"),
"-f", file.path(tempdir(), "0001.model"),
"--cache_file", file.path(tempdir(), "0001.cache"),
"-c",
"--passes", "2",
"--compressed",
"--ngram", "3",
"--skips", "1")
# Test 2: checking predictions as well
# {VW} -t train-sets/0001.dat -i models/0001.model -p 001.predict.tmp
test2 <- c("-t", system.file("test", "train-sets", "0001.dat", package="RVowpalWabbit"),
"-i", system.file("test", "models", "0001.model", package="RVowpalWabbit"),
"--cache_file", file.path(tempdir(), "0001.cache"),
"-p", file.path(tempdir(), "0001.predict.tmp"))
# Test 3: without -d, training only
# {VW} train-sets/0002.dat -f models/0002.model
test3 <- c("-t", system.file("test", "train-sets", "0002.dat", package="RVowpalWabbit"),
"--cache_file", file.path(tempdir(), "0002.cache"),
"-f", file.path(tempdir(), "0002.model"))
# Test 4: same, with -d
# {VW} -d train-sets/0002.dat -f models/0002.model
test4 <- c("-d", system.file("test", "train-sets", "0002.dat", package="RVowpalWabbit"),
"--cache_file", file.path(tempdir(), "0002.cache"),
"-f", file.path(tempdir(), "0002.model"))
# Test 5: add -q .., adaptive, and more (same input, different outputs)
# {VW} --initial_t 1 --power_t 0.5 --adaptive -q Tf -q ff -f models/0002a.model train-sets/0002.dat
test5 <- c("--initial_t", "1",
"--power_t", "0.5",
"--adaptive",
"-q", "Tf",
"-q", "ff",
"-f", file.path(tempdir(), "0002a.model"),
"--cache_file", file.path(tempdir(), "0002a.cache"),
system.file("test", "train-sets", "0002.dat", package="RVowpalWabbit"))
# Test 6: run predictions on Test 4 model
# Pretending the labels aren't there
# {VW} -t -i models/0002.model -d train-sets/0002.dat -p 0002b.predict
test6 <- c("-t", "-i", system.file("test", "models", "0002.model", package="RVowpalWabbit"),
"-d", system.file("test", "train-sets", "0002.dat", package="RVowpalWabbit"),
"--cache_file", file.path(tempdir(), "0002b.cache"),
"-p", file.path(tempdir(), "0002b.predict.tmp"))
# Test 7: using -q and multiple threads
# {VW} --adaptive -q ff -f models/0002c.model train-sets/0002.dat
test7 <- c("--adaptive", "-q", "ff",
"-f", file.path(tempdir(), "0002c.model"),
"--cache_file", file.path(tempdir(), "0002c.cache"),
system.file("test", "train-sets", "0002.dat", package="RVowpalWabbit"))
## Test 8: predicts on test 7 model
## {VW} -t -i models/0002c.model -d train-sets/0002.dat -p 0002c.predict
test8 <- c("-t",
"-i", system.file("test", "models", "0002c.model", package="RVowpalWabbit"),
"-d", system.file("test", "train-sets", "0002.dat", package="RVowpalWabbit"),
"--cache_file", file.path(tempdir(), "0002c.cache"),
"-p", file.path(tempdir(), "0002c.predict.tmp"))
## combine the tests
alltests <- list(test1, test2, test3, test4, test5, test6, test7, test8)
## and run them
res <- do.call(rbind, lapply(alltests, vw) ) # run the eight tests
print(res)
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