update test reference outputs

VowpalWabbit · Dec 1, 2023 · c0443a8 · c0443a8
1 parent 33f8423
commit c0443a8
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Showing 8 changed files with 17 additions and 37 deletions.
diff --git a/test/train-sets/ref/search_dep_parser_cost_to_go.stderr b/test/train-sets/ref/search_dep_parser_cost_to_go.stderr
@@ -13,13 +13,13 @@ average    since      instance            current true      current predicted
 loss       last        counter           output prefix          output prefix  pass   pol     made     hits    gener  beta    
 88.000000  88.000000         1  [43:1 5:2 5:2 5:2 1..] [0:8 1:1 2:1 3:1 4:..]     0     0      144        0      141  0.000000
 46.500000  5.000000          2  [2:2 3:5 0:8 3:7 99..] [2:2 0:8 4:2 2:3 99..]     0     0      153        0      150  0.001409
-30.750000  15.000000         4  [2:2 3:5 0:8 3:7 99..] [2:2 3:5 0:8 3:7 99..]     1     0      306        0      300  0.002906
-17.125000  3.500000          8  [2:2 3:5 0:8 3:7 99..] [2:2 3:5 0:8 3:7 99..]     3     0      606        0      600  0.005893
+29.250000  12.000000         4  [2:2 3:5 0:8 3:7 99..] [2:2 3:5 0:8 3:7 99..]     1     0      306        0      300  0.002906
+16.375000  3.500000          8  [2:2 3:5 0:8 3:7 99..] [2:2 3:5 0:8 3:7 99..]     3     0      606        0      600  0.005893
 
 finished run
 number of examples per pass = 2
 passes used = 6
 weighted example sum = 12.000000
 weighted label sum = 0.000000
-average loss = 11.416667
-total feature number = 270404
+average loss = 10.916667
+total feature number = 269977
diff --git a/test/train-sets/ref/search_dep_parser_one_learner.stderr b/test/train-sets/ref/search_dep_parser_one_learner.stderr
@@ -15,11 +15,11 @@ Output pred = MULTICLASS
 average    since      instance            current true      current predicted   cur   cur   predic    cache  examples          
 loss       last        counter           output prefix          output prefix  pass   pol     made     hits    gener  beta    
 89.000000  89.000000         1  [43:1 5:2 5:2 5:2 1..] [20:9 20:9 20:9 20:..]     0     0       96        0       94  0.000930
-47.000000  5.000000          2  [2:2 3:5 0:8 3:7 99..] [2:12 3:7 4:4 0:8 9..]     0     0      102        0      100  0.000990
+46.500000  4.000000          2  [2:2 3:5 0:8 3:7 99..] [2:5 3:5 4:5 0:8 99..]     0     0      102        0      100  0.000990
 
 finished run
 number of examples = 2
 weighted example sum = 2.000000
 weighted label sum = 0.000000
-average loss = 47.000000
+average loss = 46.500000
 total feature number = 28636
diff --git a/test/train-sets/ref/search_wsj.stderr b/test/train-sets/ref/search_wsj.stderr
@@ -12,15 +12,15 @@ Output pred = MULTICLASS
 average    since      instance            current true      current predicted   cur   cur   predic    cache  examples          
 loss       last        counter           output prefix          output prefix  pass   pol     made     hits    gener  beta    
 30.000000  30.000000         1  [1 2 3 1 4 5 6 7 8 ..] [1 1 1 1 1 1 1 1 1 ..]     0     0       37        0       37  0.000036
-23.500000  17.000000         2  [11 2 3 11 11 11 15..] [1 2 1 1 4 1 2 1 1 ..]     0     0       64        0       64  0.000063
-16.000000  8.500000          4  [3 4 6 3             ] [11 11 2 3           ]     0     0       97        0       97  0.000096
-8.000000   0.000000          8  [3 4 6 3             ] [3 4 6 3             ]     1     0      194        0      194  0.000193
-4.000000   0.000000         16  [3 4 6 3             ] [3 4 6 3             ]     3     0      388        0      388  0.000387
+24.500000  19.000000         2  [11 2 3 11 11 11 15..] [1 2 1 1 4 1 12 9 1..]     0     0       64        0       64  0.000063
+16.250000  8.000000          4  [3 4 6 3             ] [1 4 6 3             ]     0     0       97        0       97  0.000096
+8.125000   0.000000          8  [3 4 6 3             ] [3 4 6 3             ]     1     0      194        0      194  0.000193
+4.062500   0.000000         16  [3 4 6 3             ] [3 4 6 3             ]     3     0      388        0      388  0.000387
 
 finished run
 number of examples per pass = 4
 passes used = 6
 weighted example sum = 24.000000
 weighted label sum = 0.000000
-average loss = 2.666667
+average loss = 2.708333
 total feature number = 52110
diff --git a/test/train-sets/ref/search_wsj2.dat.stderr b/test/train-sets/ref/search_wsj2.dat.stderr
@@ -12,8 +12,8 @@ Output pred = MULTICLASS
 average    since      instance            current true      current predicted   cur   cur   predic    cache  examples          
 loss       last        counter           output prefix          output prefix  pass   pol     made     hits    gener  beta    
 30.000000  30.000000         1  [1 2 3 1 4 5 6 7 8 ..] [1 1 1 1 1 1 1 1 1 ..]     0     0       37        0       37  0.000036
-24.000000  18.000000         2  [11 2 3 11 11 11 15..] [1 2 3 1 4 1 2 1 1 ..]     0     0       64        0       64  0.000063
-16.750000  9.500000          4  [3 4 6 3             ] [11 11 11 11         ]     0     0       97        0       97  0.000096
+24.500000  19.000000         2  [11 2 3 11 11 11 15..] [1 2 1 1 1 1 12 12 ..]     0     0       64        0       64  0.000063
+16.750000  9.000000          4  [3 4 6 3             ] [1 4 6 6             ]     0     0       97        0       97  0.000096
 8.375000   0.000000          8  [3 4 6 3             ] [3 4 6 3             ]     1     0      194        0      194  0.000193
 4.187500   0.000000         16  [3 4 6 3             ] [3 4 6 3             ]     3     1      388        0      388  0.000387
 

diff --git a/test/train-sets/ref/sequence_data.ldf.beam.test.predict b/test/train-sets/ref/sequence_data.ldf.beam.test.predict
@@ -1,11 +1 @@
-5 4 3 2 1 	0.000242054
-5 4 4 3 2 	1.00016
-5 4 3 3 2 	1.00018
-5 4 3 2 4 	1.00018
-5 4 5 4 3 	1.00019
-5 4 3 4 3 	1.00026
-5 4 2 1 4 	1.60554
-5 3 2 1 4 	1.60557
-5 4 1 4 3 	1.60563
-4 3 2 1 4 	1.60563
-
+5 4 3 2 1 
diff --git a/test/train-sets/ref/sequence_data.ldf.beam.test.stderr b/test/train-sets/ref/sequence_data.ldf.beam.test.stderr
@@ -12,7 +12,7 @@ Input label = MULTICLASS
 Output pred = MULTICLASS
 average    since      instance            current true      current predicted   cur   cur   predic    cache  examples          
 loss       last        counter           output prefix          output prefix  pass   pol     made     hits    gener  beta    
-0.000000   0.000000          1  [5 4 3 2 1           ] [5 4 3 2 1  0.00024..]     0     0       26        0        0  0.000000
+0.000000   0.000000          1  [5 4 3 2 1           ] [5 4 3 2 1           ]     0     0       26        0        0  0.000000
 
 finished run
 number of examples = 1

diff --git a/test/train-sets/ref/sequence_data.nonldf.beam.test.predict b/test/train-sets/ref/sequence_data.nonldf.beam.test.predict
@@ -1,11 +1 @@
-5 4 3 2 1 	8.34465e-07
-5 4 3 5 4 	1
-5 4 3 2 4 	1
-5 5 4 3 2 	1.02138
-5 4 3 2 3 	1.02816
-5 4 3 2 2 	1.03424
-5 3 2 1 1 	1.76761
-5 4 3 1 1 	1.79503
-4 3 2 1 1 	1.79576
-5 2 1 1 1 	2.53521
-
+5 4 3 2 1 
diff --git a/test/train-sets/ref/sequence_data.nonldf.beam.test.stderr b/test/train-sets/ref/sequence_data.nonldf.beam.test.stderr
@@ -12,7 +12,7 @@ Input label = MULTICLASS
 Output pred = MULTICLASS
 average    since      instance            current true      current predicted   cur   cur   predic    cache  examples          
 loss       last        counter           output prefix          output prefix  pass   pol     made     hits    gener  beta    
-0.000000   0.000000          1  [5 4 3 2 1           ] [5 4 3 2 1  8.34465..]     0     0       24        0        0  0.000000
+0.000000   0.000000          1  [5 4 3 2 1           ] [5 4 3 2 1           ]     0     0       24        0        0  0.000000
 
 finished run
 number of examples = 1