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-rw-r--r--test/README91
1 files changed, 38 insertions, 53 deletions
diff --git a/test/README b/test/README
index d8527636..d87a38ae 100644
--- a/test/README
+++ b/test/README
@@ -1,53 +1,38 @@
-Num weight bits = 24
-learning rate = 2.56e+06
-initial_t = 128000
-power_t = 1
-decay_learning_rate = 0.707107
-Warning: decay_learning_rate has no effect when there is only one pass
-using no cache
-Reading from stdin
-final_regressor = test/t_r_temp
-learning_rate set to 2.56e+06
-average since example example current current current
-loss last counter weight label predict features
-0.3926 0.3926 3 3 0 0.3032 57
-0.31 0.2275 6 6 1 0.1897 31
-0.2852 0.2553 11 11 0 0.6957 38
-0.2845 0.2839 22 22 1 0.4427 88
-0.3088 0.3331 44 44 0 0.3216 66
-0.2803 0.2512 87 87 1 0.0781 61
-0.2874 0.2945 174 1.7e+02 1 0.6602 26
-
-finished run
-number of examples = 200
-weighted example sum = 200
-weighted label sum = 91
-average loss = 0.2873
-best constant's loss = 0.248
-total feature number = 15482
-Num weight bits = 24
-learning rate = 0.1
-initial_t = 1
-power_t = 0
-decay_learning_rate = 0.707107
-Warning: decay_learning_rate has no effect when there is only one pass
-using no cache
-predictions = test/t_p_out
-Reading from stdin
-only testing
-average since example example current current current
-loss last counter weight label predict features
-0.233 0.233 3 3 0 0.4552 62
-0.2315 0.2301 6 6 0 0.3615 144
-0.2524 0.2775 11 11 0 0.4932 56
-0.2256 0.1987 22 22 0 0.5193 36
-0.1768 0.1281 44 44 1 0.7838 34
-0.17 0.1629 87 87 1 1 15
-
-finished run
-number of examples = 100
-weighted example sum = 100
-weighted label sum = 57
-average loss = 0.1507
-best constant's loss = 0.2451
-total feature number = 5069
+Test suite for vw:
+
+You may add arbitrary (train/test/varying-options) tests
+by adding data (train, test) files and their expected reference
+STDOUT and STDERRs
+
+Test to run should be added below the __DATA__ section in RunTests
+
+Tests are separated by an empty line
+Each test is represented by a pair or triplet of items
+ 1st item is the command to run, {VW} represents the vw executable
+ 2nd item is the expected (reference file) standard output
+ 3rd item is the expected (reference file) standard error
+file-names are relative to this (test) directory
+
+Examples:
+
+__DATA__
+# Test 1:
+{VW} -d train-sets/0001.dat -f models/0001.model
+ train-sets/ref/0001.stdout
+ train-sets/ref/0001.stderr
+
+# Test 2:
+{VW} -t train-sets/0001.dat -i models/0001.model
+ test-sets/ref/0001.stdout
+ test-sets/ref/0001.stderr
+
+# Test 3: without -d, training only
+{VW} train-sets/0002.dat -f models/0002.model
+ train-sets/ref/0002.stdout
+ train-sets/ref/0002.stderr
+
+# Test 4: same, with -d
+{VW} -d train-sets/0002.dat -f models/0002.model
+ train-sets/ref/0002.stdout
+ train-sets/ref/0002.stderr
+