summaryrefslogtreecommitdiff
path: root/dtrain
diff options
context:
space:
mode:
Diffstat (limited to 'dtrain')
-rwxr-xr-xdtrain/binning.rb35
-rw-r--r--dtrain/countofcounts3894
-rw-r--r--dtrain/dtrain.cc9
-rw-r--r--dtrain/dtrain.h2
-rw-r--r--dtrain/test/mira_update/Hildreth.cpp187
-rw-r--r--dtrain/test/mira_update/Hildreth.h10
-rw-r--r--dtrain/test/mira_update/dtrain.cc532
-rw-r--r--dtrain/test/mira_update/sample.h101
8 files changed, 838 insertions, 3932 deletions
diff --git a/dtrain/binning.rb b/dtrain/binning.rb
deleted file mode 100755
index 674f3246..00000000
--- a/dtrain/binning.rb
+++ /dev/null
@@ -1,35 +0,0 @@
-bins = []
-bin_sz = 0
-1.upto(3).each { |i|
- bin_sz = STDIN.gets.strip.split(",")[1].to_i
- bins.push [[i], bin_sz]
-}
-
-cur_bin = []
-cur_bin_sz = 0
-while line = STDIN.gets
- count, countcount = line.strip.split ","
- count = count.to_i
- countcount = countcount.to_i
- if (cur_bin_sz + countcount) > bin_sz
- bins.push [cur_bin, cur_bin_sz]
- cur_bin = []
- cur_bin_sz = countcount
- else
- cur_bin.push count
- cur_bin_sz += countcount
- end
-end
-bins.push [cur_bin, cur_bin_sz]
-
-c = 0
-e = 0
-bins.each { |i|
- puts "#{e} | #{i[0].size}: #{i[0][0]}.. #{i[1]}" if i[0].size > 0
- c += 1 if i[0].size > 0
- e += 1
-}
-puts "#{c} bins (#{bins.size})"
-puts "bin sz #{bin_sz}"
-
-
diff --git a/dtrain/countofcounts b/dtrain/countofcounts
deleted file mode 100644
index 8752b430..00000000
--- a/dtrain/countofcounts
+++ /dev/null
@@ -1,3894 +0,0 @@
-1,3109341
-2,1653564
-3,1047846
-4,746546
-5,576342
-6,462409
-7,382522
-8,326122
-9,280761
-10,248005
-11,219883
-12,195357
-13,177502
-14,162512
-15,146810
-16,135532
-17,127895
-18,116317
-19,109424
-20,101733
-21,96171
-22,90290
-23,86513
-24,80554
-25,76357
-26,71542
-27,66948
-28,63351
-29,62493
-30,59451
-31,56776
-32,54647
-33,52288
-34,50734
-35,48864
-36,47018
-37,43835
-38,41643
-39,40810
-40,39881
-41,38763
-42,36919
-43,36048
-44,36420
-45,34982
-46,32632
-47,32232
-48,30701
-49,31100
-50,29307
-51,28854
-52,28667
-53,27831
-54,26538
-55,24617
-56,24209
-57,24913
-58,24453
-59,23128
-60,23117
-61,20645
-62,21411
-63,21381
-64,19852
-65,20106
-66,19860
-67,19871
-68,18737
-69,19420
-70,18356
-71,16948
-72,17434
-73,17103
-74,16566
-75,16785
-76,16381
-77,17743
-78,15293
-79,15092
-80,15462
-81,15281
-82,14881
-83,14414
-84,13980
-85,13567
-86,14289
-87,13362
-88,13180
-89,13000
-90,13411
-91,13127
-92,12604
-93,12891
-94,12322
-95,11551
-96,11498
-97,10663
-98,11241
-99,11067
-100,12183
-101,10934
-102,10123
-103,10244
-104,10706
-105,10779
-106,10372
-107,10154
-108,9795
-109,9411
-110,9266
-111,8978
-112,9633
-113,9300
-114,8855
-115,9192
-116,9715
-117,9074
-118,8455
-119,9198
-120,8952
-121,8638
-122,9264
-123,8575
-124,8187
-125,8075
-126,7949
-127,7346
-128,8175
-129,8196
-130,7796
-131,7756
-132,7383
-133,7100
-134,7715
-135,7240
-136,8133
-137,7135
-138,7245
-139,6860
-140,7233
-141,7376
-142,6640
-143,5938
-144,6692
-145,6874
-146,5889
-147,5949
-148,5848
-149,7053
-150,6370
-151,6640
-152,5809
-153,5702
-154,6014
-155,5977
-156,5184
-157,5249
-158,5074
-159,5432
-160,5782
-161,5617
-162,5340
-163,5363
-164,5155
-165,4635
-166,4715
-167,5498
-168,5658
-169,4627
-170,5140
-171,5053
-172,4757
-173,5054
-174,4944
-175,5252
-176,4586
-177,5554
-178,5457
-179,4911
-180,5263
-181,4955
-182,5444
-183,4985
-184,5050
-185,4516
-186,4821
-187,4681
-188,4158
-189,4683
-190,4650
-191,4337
-192,3807
-193,4102
-194,4456
-195,4219
-196,4023
-197,3695
-198,4083
-199,4158
-200,4099
-201,4052
-202,4157
-203,3765
-204,3919
-205,3631
-206,3723
-207,3566
-208,3624
-209,3897
-210,3903
-211,4648
-212,3917
-213,3740
-214,3535
-215,2930
-216,3875
-217,4038
-218,3947
-219,3427
-220,3498
-221,3301
-222,3785
-223,3542
-224,3390
-225,3314
-226,3267
-227,3237
-228,3601
-229,3491
-230,3147
-231,3205
-232,3151
-233,3368
-234,3571
-235,2929
-236,2667
-237,3196
-238,3314
-239,3579
-240,3285
-241,3487
-242,3142
-243,3007
-244,2771
-245,2751
-246,2899
-247,2995
-248,3254
-249,2795
-250,2270
-251,2898
-252,3488
-253,2561
-254,2419
-255,2513
-256,2812
-257,2659
-258,2465
-259,3274
-260,2857
-261,2723
-262,2618
-263,2618
-264,2591
-265,2181
-266,2551
-267,2729
-268,3529
-269,3620
-270,2945
-271,2325
-272,2231
-273,2812
-274,2232
-275,3137
-276,2480
-277,2465
-278,2694
-279,3016
-280,2809
-281,2696
-282,2729
-283,2442
-284,2272
-285,2280
-286,1842
-287,2062
-288,2071
-289,2360
-290,2377
-291,1924
-292,2391
-293,2182
-294,1988
-295,1979
-296,1820
-297,2183
-298,1880
-299,2577
-300,2485
-301,2201
-302,1977
-303,1686
-304,2559
-305,2448
-306,2324
-307,2460
-308,2407
-309,2923
-310,2093
-311,1927
-312,1923
-313,2375
-314,1962
-315,1995
-316,1601
-317,2013
-318,2318
-319,1835
-320,1641
-321,1571
-322,1814
-323,1960
-324,1964
-325,1804
-326,1922
-327,2053
-328,1899
-329,1808
-330,1900
-331,1403
-332,1549
-333,1992
-334,1946
-335,1903
-336,1763
-337,2074
-338,1821
-339,1476
-340,1911
-341,2141
-342,1822
-343,1233
-344,1638
-345,1865
-346,2185
-347,2068
-348,1784
-349,2124
-350,2047
-351,1768
-352,2022
-353,1902
-354,1813
-355,1766
-356,1309
-357,1628
-358,1667
-359,1797
-360,1426
-361,1929
-362,2089
-363,1991
-364,1959
-365,2130
-366,1494
-367,1261
-368,1219
-369,1621
-370,1352
-371,1712
-372,1603
-373,1581
-374,1624
-375,1914
-376,1629
-377,1419
-378,947
-379,1014
-380,1403
-381,1234
-382,1181
-383,1378
-384,1549
-385,1221
-386,1359
-387,1511
-388,1316
-389,1068
-390,1514
-391,1309
-392,1561
-393,1519
-394,992
-395,1122
-396,1291
-397,1070
-398,1430
-399,1869
-400,1927
-401,1610
-402,1481
-403,960
-404,1501
-405,1259
-406,1117
-407,1127
-408,1075
-409,1231
-410,974
-411,1018
-412,1234
-413,1557
-414,1442
-415,1623
-416,1080
-417,1747
-418,1592
-419,987
-420,850
-421,1212
-422,1407
-423,1123
-424,1230
-425,1448
-426,1637
-427,1226
-428,1147
-429,1154
-430,971
-431,858
-432,797
-433,1212
-434,1267
-435,1110
-436,1184
-437,1365
-438,1112
-439,715
-440,1090
-441,957
-442,1141
-443,1093
-444,1048
-445,1004
-446,876
-447,1041
-448,1209
-449,1118
-450,1039
-451,1223
-452,1064
-453,1368
-454,1164
-455,1567
-456,974
-457,920
-458,601
-459,637
-460,983
-461,1261
-462,921
-463,845
-464,1059
-465,1000
-466,972
-467,970
-468,1078
-469,1021
-470,1011
-471,1195
-472,1144
-473,1130
-474,1345
-475,1101
-476,1166
-477,1110
-478,926
-479,743
-480,679
-481,619
-482,839
-483,703
-484,773
-485,801
-486,1432
-487,1166
-488,1015
-489,635
-490,1039
-491,1005
-492,665
-493,1046
-494,873
-495,864
-496,888
-497,830
-498,981
-499,1152
-500,775
-501,844
-502,916
-503,671
-504,769
-505,883
-506,1019
-507,804
-508,682
-509,592
-510,684
-511,765
-512,801
-513,863
-514,701
-515,671
-516,781
-517,662
-518,671
-519,478
-520,709
-521,594
-522,686
-523,853
-524,714
-525,821
-526,637
-527,582
-528,617
-529,824
-530,921
-531,794
-532,817
-533,832
-534,699
-535,894
-536,611
-537,413
-538,336
-539,439
-540,689
-541,464
-542,545
-543,778
-544,711
-545,838
-546,798
-547,1023
-548,767
-549,696
-550,676
-551,634
-552,493
-553,675
-554,453
-555,758
-556,528
-557,725
-558,474
-559,854
-560,688
-561,802
-562,781
-563,753
-564,525
-565,452
-566,483
-567,741
-568,706
-569,693
-570,651
-571,637
-572,516
-573,260
-574,161
-575,907
-576,790
-577,645
-578,502
-579,547
-580,799
-581,613
-582,340
-583,542
-584,904
-585,629
-586,581
-587,491
-588,943
-589,640
-590,414
-591,818
-592,792
-593,623
-594,593
-595,653
-596,414
-597,462
-598,586
-599,661
-600,520
-601,666
-602,646
-603,554
-604,500
-605,315
-606,435
-607,479
-608,498
-609,564
-610,605
-611,577
-612,424
-613,544
-614,492
-615,365
-616,529
-617,826
-618,510
-619,591
-620,522
-621,552
-622,743
-623,580
-624,643
-625,820
-626,362
-627,352
-628,613
-629,882
-630,644
-631,900
-632,765
-633,487
-634,437
-635,623
-636,574
-637,505
-638,789
-639,489
-640,495
-641,558
-642,730
-643,521
-644,311
-645,625
-646,372
-647,616
-648,510
-649,497
-650,491
-651,717
-652,420
-653,401
-654,506
-655,450
-656,471
-657,240
-658,422
-659,480
-660,413
-661,807
-662,617
-663,416
-664,301
-665,208
-666,293
-667,442
-668,611
-669,360
-670,316
-671,458
-672,521
-673,813
-674,546
-675,254
-676,323
-677,303
-678,445
-679,481
-680,478
-681,318
-682,333
-683,457
-684,343
-685,356
-686,225
-687,344
-688,381
-689,549
-690,272
-691,360
-692,306
-693,347
-694,532
-695,483
-696,262
-697,316
-698,417
-699,452
-700,644
-701,371
-702,175
-703,539
-704,253
-705,417
-706,318
-707,242
-708,393
-709,425
-710,372
-711,502
-712,431
-713,396
-714,211
-715,375
-716,469
-717,308
-718,310
-719,337
-720,380
-721,447
-722,291
-723,412
-724,267
-725,208
-726,277
-727,284
-728,613
-729,360
-730,335
-731,310
-732,198
-733,498
-734,282
-735,350
-736,283
-737,399
-738,358
-739,409
-740,413
-741,330
-742,326
-743,412
-744,361
-745,319
-746,154
-747,233
-748,361
-749,257
-750,390
-751,471
-752,257
-753,138
-754,208
-755,496
-756,494
-757,405
-758,426
-759,162
-760,385
-761,316
-762,350
-763,375
-764,422
-765,381
-766,382
-767,280
-768,261
-769,457
-770,503
-771,367
-772,211
-773,245
-774,171
-775,247
-776,301
-777,280
-778,208
-779,215
-780,166
-781,132
-782,239
-783,300
-784,278
-785,374
-786,196
-787,246
-788,292
-789,319
-790,155
-791,420
-792,281
-793,297
-794,142
-795,256
-796,412
-797,220
-798,326
-799,152
-800,89
-801,378
-802,240
-803,430
-804,151
-805,181
-806,83
-807,179
-808,261
-809,127
-810,227
-811,381
-812,282
-813,476
-814,324
-815,306
-816,298
-817,330
-818,499
-819,537
-820,351
-821,181
-822,172
-823,306
-824,353
-825,331
-826,226
-827,204
-828,180
-829,494
-830,475
-831,238
-832,416
-833,264
-834,212
-835,349
-836,311
-837,171
-838,284
-839,160
-840,286
-841,298
-842,115
-843,218
-844,220
-845,357
-846,188
-847,198
-848,356
-849,156
-850,161
-851,167
-852,131
-853,175
-854,364
-855,362
-856,180
-857,60
-858,107
-859,143
-860,355
-861,271
-862,210
-863,134
-864,162
-865,157
-866,191
-867,188
-868,174
-869,234
-870,108
-871,212
-872,579
-873,408
-874,210
-875,182
-876,248
-877,420
-878,668
-879,283
-880,414
-881,298
-882,353
-883,149
-884,253
-885,213
-886,264
-887,406
-888,303
-889,244
-890,245
-891,205
-892,169
-893,335
-894,134
-895,471
-896,320
-897,150
-898,194
-899,262
-900,198
-901,234
-902,272
-903,312
-904,205
-905,183
-906,220
-907,290
-908,249
-909,156
-910,107
-911,433
-912,196
-913,140
-914,220
-915,282
-916,249
-917,401
-918,344
-919,153
-920,264
-921,317
-922,299
-923,253
-924,212
-925,196
-926,248
-927,328
-928,190
-929,178
-930,91
-931,137
-932,254
-933,459
-934,323
-935,287
-936,204
-937,78
-938,158
-939,180
-940,257
-941,344
-942,303
-943,257
-944,103
-945,244
-946,165
-947,199
-948,137
-949,160
-950,160
-951,95
-952,142
-953,158
-954,182
-955,127
-956,223
-957,260
-958,247
-959,203
-960,246
-961,234
-962,161
-963,206
-964,225
-965,182
-966,201
-967,241
-968,84
-969,301
-970,414
-971,290
-972,267
-973,104
-974,28
-975,366
-976,300
-977,169
-978,107
-979,143
-980,214
-981,128
-982,293
-983,447
-984,298
-985,243
-986,173
-987,269
-988,187
-989,88
-990,141
-991,183
-992,152
-993,56
-994,57
-995,149
-996,251
-997,166
-998,132
-999,110
-1000,277
-1001,194
-1002,209
-1003,287
-1004,222
-1005,211
-1006,199
-1007,309
-1008,230
-1009,231
-1010,226
-1011,217
-1012,173
-1013,43
-1014,92
-1015,138
-1016,45
-1017,103
-1018,48
-1019,233
-1020,132
-1021,280
-1022,323
-1023,152
-1024,98
-1025,105
-1026,127
-1027,186
-1028,221
-1029,151
-1030,221
-1031,81
-1032,55
-1033,141
-1034,43
-1035,89
-1036,127
-1037,160
-1038,126
-1039,86
-1040,37
-1041,109
-1042,81
-1043,80
-1044,174
-1045,153
-1046,280
-1047,260
-1048,157
-1049,147
-1050,91
-1051,48
-1052,181
-1053,479
-1054,214
-1055,150
-1056,315
-1057,106
-1058,284
-1059,166
-1060,52
-1061,43
-1062,58
-1063,108
-1064,32
-1065,140
-1066,148
-1067,84
-1068,129
-1069,240
-1070,99
-1071,107
-1072,206
-1073,70
-1074,184
-1075,172
-1076,48
-1077,145
-1078,181
-1079,59
-1080,61
-1081,213
-1082,137
-1083,104
-1084,195
-1085,92
-1086,182
-1087,194
-1088,302
-1089,123
-1090,78
-1091,62
-1092,136
-1093,180
-1094,109
-1095,73
-1096,99
-1097,117
-1098,34
-1099,74
-1100,160
-1101,123
-1102,175
-1103,249
-1104,286
-1105,315
-1106,120
-1107,167
-1108,59
-1109,140
-1110,109
-1111,30
-1112,62
-1113,82
-1114,28
-1115,36
-1116,126
-1117,80
-1118,106
-1119,136
-1120,149
-1121,150
-1122,85
-1123,157
-1124,255
-1125,156
-1126,39
-1127,84
-1128,141
-1129,32
-1130,102
-1131,153
-1132,113
-1133,125
-1134,126
-1135,71
-1136,35
-1137,49
-1138,127
-1139,206
-1140,125
-1141,86
-1142,199
-1143,185
-1144,110
-1145,197
-1146,115
-1147,141
-1148,196
-1149,149
-1150,58
-1151,52
-1152,70
-1153,23
-1154,250
-1155,267
-1156,186
-1157,87
-1158,193
-1159,279
-1160,176
-1161,227
-1162,155
-1163,120
-1164,123
-1165,106
-1166,103
-1167,118
-1168,61
-1169,48
-1170,183
-1171,246
-1172,210
-1173,104
-1174,35
-1175,27
-1176,134
-1177,95
-1178,86
-1179,44
-1180,203
-1181,76
-1182,209
-1183,110
-1184,99
-1185,131
-1186,65
-1187,85
-1188,145
-1189,178
-1190,141
-1191,115
-1192,104
-1193,151
-1194,217
-1195,174
-1196,292
-1197,94
-1198,46
-1199,130
-1200,91
-1201,111
-1202,117
-1203,90
-1204,88
-1205,50
-1206,75
-1207,40
-1208,50
-1209,260
-1210,112
-1211,56
-1212,28
-1213,43
-1214,159
-1215,128
-1216,91
-1217,38
-1218,37
-1219,69
-1220,93
-1221,216
-1222,100
-1223,27
-1224,197
-1225,129
-1226,70
-1227,36
-1228,151
-1229,89
-1230,137
-1231,229
-1232,69
-1233,123
-1234,124
-1235,186
-1236,62
-1237,78
-1238,168
-1239,138
-1240,43
-1241,16
-1242,100
-1243,179
-1244,71
-1245,1
-1246,54
-1247,175
-1248,27
-1249,125
-1250,325
-1251,124
-1252,52
-1253,89
-1254,72
-1255,71
-1256,95
-1257,130
-1258,138
-1259,30
-1260,3
-1261,62
-1262,127
-1263,52
-1264,193
-1265,134
-1266,149
-1267,122
-1268,102
-1269,83
-1270,102
-1271,53
-1272,41
-1273,141
-1274,71
-1275,86
-1276,141
-1277,44
-1278,21
-1279,6
-1280,30
-1281,30
-1282,42
-1283,34
-1284,121
-1285,193
-1286,182
-1287,142
-1288,148
-1289,268
-1290,280
-1291,108
-1292,127
-1293,142
-1294,97
-1295,141
-1296,158
-1297,105
-1298,73
-1299,34
-1300,113
-1301,120
-1302,130
-1303,50
-1304,54
-1305,84
-1306,93
-1307,21
-1308,8
-1309,49
-1310,102
-1311,110
-1312,128
-1313,232
-1314,130
-1315,66
-1317,58
-1318,25
-1319,13
-1320,138
-1321,122
-1322,34
-1323,60
-1324,64
-1325,89
-1326,249
-1327,104
-1328,139
-1329,73
-1330,111
-1331,44
-1332,45
-1333,23
-1334,43
-1335,114
-1336,53
-1337,67
-1338,229
-1339,219
-1340,139
-1341,54
-1342,41
-1343,48
-1344,58
-1345,9
-1346,75
-1347,23
-1348,14
-1349,76
-1350,43
-1351,102
-1352,170
-1353,100
-1354,66
-1355,27
-1356,14
-1357,103
-1358,132
-1359,41
-1360,133
-1361,59
-1362,252
-1363,112
-1364,55
-1365,81
-1366,62
-1367,72
-1368,39
-1369,154
-1370,193
-1371,104
-1372,3
-1374,75
-1375,87
-1376,16
-1377,38
-1378,141
-1379,56
-1380,30
-1381,66
-1382,171
-1383,294
-1384,74
-1385,116
-1386,125
-1387,114
-1388,65
-1389,22
-1390,3
-1391,23
-1392,144
-1393,123
-1394,51
-1395,26
-1396,56
-1397,80
-1398,39
-1399,149
-1400,116
-1401,132
-1402,29
-1403,8
-1404,71
-1405,148
-1406,162
-1407,94
-1408,68
-1409,229
-1410,165
-1411,105
-1412,112
-1413,93
-1414,64
-1415,187
-1416,43
-1417,91
-1418,161
-1419,179
-1420,221
-1421,289
-1422,185
-1423,60
-1424,63
-1425,19
-1426,139
-1427,84
-1428,9
-1430,16
-1431,130
-1432,56
-1433,31
-1434,24
-1435,43
-1436,35
-1437,97
-1438,87
-1439,19
-1440,130
-1441,72
-1442,38
-1443,20
-1444,71
-1445,126
-1446,104
-1447,35
-1448,63
-1449,24
-1450,23
-1451,98
-1452,34
-1453,120
-1454,76
-1455,70
-1456,47
-1457,82
-1458,53
-1459,7
-1460,93
-1461,54
-1462,89
-1463,83
-1464,70
-1465,49
-1466,64
-1467,42
-1468,59
-1469,92
-1470,46
-1471,74
-1472,148
-1473,103
-1474,41
-1475,150
-1476,120
-1477,93
-1478,107
-1479,100
-1480,214
-1481,298
-1482,202
-1483,249
-1484,103
-1485,20
-1486,121
-1487,134
-1488,178
-1489,64
-1490,136
-1491,194
-1492,37
-1494,151
-1495,104
-1496,87
-1497,144
-1498,100
-1499,55
-1500,1
-1502,9
-1503,2
-1504,59
-1505,40
-1506,7
-1507,64
-1508,77
-1509,14
-1510,68
-1511,63
-1512,188
-1513,107
-1514,70
-1515,54
-1516,43
-1517,193
-1518,176
-1519,36
-1520,25
-1521,19
-1522,84
-1523,59
-1524,24
-1525,106
-1526,102
-1527,132
-1528,63
-1529,5
-1530,101
-1531,96
-1532,19
-1534,73
-1535,94
-1536,92
-1537,36
-1538,47
-1539,28
-1540,88
-1541,62
-1542,224
-1543,69
-1544,18
-1545,83
-1546,33
-1547,111
-1548,56
-1549,80
-1550,61
-1551,15
-1552,49
-1553,129
-1554,40
-1555,38
-1556,22
-1557,19
-1558,26
-1559,27
-1560,115
-1561,103
-1562,68
-1563,111
-1564,61
-1565,113
-1566,137
-1567,60
-1568,122
-1569,90
-1570,6
-1571,132
-1572,91
-1573,37
-1574,72
-1575,101
-1576,104
-1577,41
-1578,15
-1579,3
-1580,105
-1581,60
-1582,108
-1583,66
-1584,63
-1585,225
-1586,80
-1587,2
-1588,115
-1589,68
-1590,16
-1591,4
-1592,35
-1593,4
-1595,102
-1596,75
-1597,59
-1598,43
-1599,140
-1600,132
-1601,51
-1602,20
-1603,8
-1604,53
-1605,132
-1606,48
-1607,67
-1608,82
-1609,19
-1612,146
-1613,113
-1614,43
-1615,179
-1616,125
-1617,46
-1618,90
-1619,97
-1620,146
-1621,25
-1622,18
-1623,119
-1624,54
-1625,35
-1626,197
-1627,76
-1628,56
-1629,136
-1630,143
-1631,37
-1632,92
-1633,112
-1634,39
-1635,74
-1636,55
-1637,56
-1638,95
-1639,147
-1640,18
-1641,122
-1642,130
-1643,35
-1644,25
-1646,69
-1647,54
-1648,21
-1650,77
-1651,97
-1652,78
-1653,23
-1654,98
-1655,89
-1656,87
-1657,39
-1658,53
-1659,31
-1660,3
-1661,70
-1662,35
-1663,67
-1664,83
-1665,180
-1666,61
-1667,1
-1668,47
-1669,15
-1670,109
-1671,252
-1672,54
-1673,76
-1674,31
-1675,55
-1676,20
-1677,37
-1678,19
-1679,5
-1680,62
-1681,94
-1682,274
-1683,70
-1684,47
-1685,109
-1686,20
-1687,53
-1688,75
-1689,51
-1690,14
-1691,36
-1692,9
-1693,80
-1694,126
-1695,87
-1696,18
-1697,22
-1698,7
-1699,8
-1700,2
-1701,120
-1702,41
-1703,57
-1704,144
-1705,160
-1706,21
-1707,83
-1708,90
-1709,21
-1710,61
-1711,71
-1712,57
-1713,18
-1714,45
-1715,37
-1716,71
-1717,20
-1719,27
-1720,10
-1721,2
-1723,75
-1724,102
-1725,173
-1726,50
-1727,101
-1728,66
-1729,75
-1730,36
-1731,34
-1732,37
-1733,17
-1734,75
-1735,35
-1736,68
-1737,60
-1738,13
-1740,55
-1741,40
-1742,25
-1743,51
-1744,91
-1745,38
-1746,10
-1747,15
-1748,75
-1749,40
-1750,26
-1751,43
-1752,38
-1753,106
-1754,77
-1755,35
-1756,51
-1757,10
-1758,20
-1759,5
-1760,48
-1761,43
-1762,8
-1763,49
-1764,69
-1765,6
-1766,92
-1767,44
-1768,52
-1769,88
-1770,28
-1771,17
-1772,198
-1773,177
-1774,48
-1775,41
-1776,35
-1777,8
-1779,11
-1780,13
-1781,6
-1782,26
-1783,7
-1786,27
-1787,7
-1788,71
-1789,63
-1790,13
-1791,41
-1792,133
-1793,51
-1794,53
-1795,14
-1798,4
-1799,28
-1800,110
-1801,31
-1803,40
-1804,13
-1805,135
-1806,74
-1807,25
-1808,44
-1809,73
-1810,21
-1811,117
-1812,64
-1813,9
-1815,73
-1816,30
-1817,17
-1818,82
-1819,69
-1820,17
-1821,56
-1822,56
-1823,10
-1824,11
-1825,117
-1826,41
-1827,3
-1828,99
-1829,33
-1830,68
-1831,45
-1832,97
-1833,158
-1834,83
-1835,117
-1836,112
-1837,52
-1838,5
-1839,36
-1840,56
-1841,19
-1842,37
-1843,13
-1845,14
-1846,93
-1847,30
-1848,27
-1849,27
-1850,89
-1851,74
-1852,21
-1853,23
-1854,20
-1855,1
-1856,25
-1857,14
-1858,9
-1859,5
-1860,11
-1861,14
-1862,40
-1863,28
-1864,26
-1865,15
-1866,10
-1867,2
-1868,7
-1869,3
-1870,16
-1871,4
-1872,87
-1873,32
-1877,11
-1878,6
-1880,116
-1881,70
-1882,67
-1883,98
-1884,24
-1885,2
-1886,45
-1887,42
-1888,14
-1889,90
-1890,82
-1891,32
-1893,45
-1894,28
-1895,10
-1896,47
-1897,37
-1898,49
-1899,10
-1900,34
-1901,27
-1902,40
-1903,79
-1904,19
-1908,44
-1909,85
-1910,45
-1911,160
-1912,89
-1913,12
-1915,22
-1916,132
-1917,37
-1918,42
-1919,23
-1921,10
-1922,10
-1923,4
-1924,10
-1925,38
-1926,10
-1927,2
-1930,15
-1931,36
-1932,172
-1933,132
-1934,68
-1935,34
-1936,46
-1937,7
-1938,71
-1939,35
-1940,13
-1941,65
-1942,74
-1943,21
-1945,128
-1946,53
-1947,2
-1948,77
-1949,31
-1951,13
-1952,24
-1953,8
-1954,61
-1955,101
-1956,80
-1957,122
-1958,44
-1959,3
-1960,27
-1961,69
-1962,17
-1965,80
-1966,18
-1968,82
-1969,41
-1970,81
-1971,26
-1972,73
-1973,75
-1974,27
-1975,4
-1977,38
-1978,109
-1979,86
-1980,17
-1982,63
-1983,74
-1984,58
-1985,34
-1986,43
-1987,31
-1988,66
-1989,19
-1990,47
-1991,97
-1992,32
-1994,51
-1995,25
-1996,1
-1998,49
-1999,20
-2001,6
-2002,7
-2003,30
-2004,15
-2006,52
-2007,28
-2008,2
-2009,4
-2010,1
-2011,52
-2012,21
-2013,13
-2014,11
-2015,10
-2016,51
-2017,33
-2018,4
-2019,40
-2020,62
-2021,10
-2023,70
-2024,29
-2026,9
-2027,33
-2028,8
-2030,55
-2031,49
-2032,80
-2033,55
-2034,54
-2035,43
-2036,23
-2037,22
-2038,39
-2039,24
-2041,15
-2042,3
-2043,88
-2044,37
-2048,7
-2049,3
-2050,10
-2051,12
-2052,70
-2053,157
-2054,61
-2056,64
-2057,92
-2058,44
-2059,6
-2060,4
-2061,27
-2062,38
-2063,19
-2064,89
-2065,14
-2071,57
-2072,43
-2073,24
-2074,45
-2075,10
-2076,43
-2077,72
-2078,55
-2079,18
-2080,6
-2081,29
-2082,40
-2083,42
-2084,11
-2087,11
-2088,74
-2089,58
-2090,18
-2091,6
-2092,66
-2093,33
-2094,73
-2095,149
-2096,46
-2097,4
-2098,23
-2099,73
-2100,29
-2101,21
-2102,12
-2103,54
-2104,14
-2105,106
-2106,38
-2107,36
-2108,48
-2109,32
-2110,63
-2111,37
-2112,4
-2114,8
-2115,35
-2116,11
-2117,21
-2118,7
-2119,58
-2120,28
-2121,49
-2122,83
-2123,66
-2124,12
-2131,18
-2132,73
-2133,56
-2134,84
-2135,43
-2141,5
-2142,2
-2143,25
-2144,15
-2145,13
-2146,9
-2147,1
-2148,24
-2149,72
-2150,147
-2151,47
-2153,28
-2154,64
-2155,12
-2159,10
-2160,7
-2161,42
-2162,10
-2164,53
-2165,23
-2166,23
-2167,11
-2168,28
-2169,9
-2171,4
-2172,26
-2173,42
-2174,8
-2176,10
-2177,35
-2178,12
-2179,73
-2180,45
-2181,11
-2182,59
-2183,62
-2184,13
-2185,60
-2186,18
-2188,8
-2189,11
-2190,2
-2192,72
-2193,14
-2194,32
-2195,6
-2196,23
-2197,22
-2198,70
-2199,21
-2200,40
-2201,23
-2204,17
-2205,3
-2206,132
-2207,70
-2208,116
-2209,75
-2210,7
-2214,34
-2215,5
-2216,44
-2217,4
-2219,10
-2220,6
-2221,69
-2222,32
-2223,18
-2224,177
-2225,81
-2226,30
-2227,18
-2228,100
-2229,53
-2230,24
-2231,41
-2232,12
-2237,56
-2238,58
-2239,4
-2240,6
-2241,38
-2242,58
-2243,54
-2244,17
-2246,10
-2247,9
-2248,6
-2250,31
-2251,76
-2252,42
-2253,2
-2254,96
-2255,40
-2257,50
-2258,106
-2259,31
-2260,39
-2261,19
-2262,22
-2263,8
-2264,9
-2265,12
-2266,55
-2267,111
-2268,77
-2269,67
-2270,11
-2272,13
-2273,8
-2274,115
-2275,40
-2286,9
-2287,10
-2288,30
-2289,59
-2290,64
-2291,75
-2292,10
-2299,4
-2300,2
-2302,53
-2303,13
-2304,23
-2305,13
-2308,19
-2309,5
-2312,40
-2313,83
-2314,10
-2315,14
-2316,4
-2317,3
-2318,2
-2319,50
-2320,32
-2321,2
-2323,131
-2324,67
-2325,23
-2326,46
-2327,17
-2332,60
-2333,23
-2335,32
-2336,9
-2337,61
-2338,63
-2339,12
-2343,24
-2344,14
-2345,11
-2346,3
-2349,53
-2350,24
-2353,5
-2354,4
-2355,66
-2356,33
-2357,2
-2359,71
-2360,42
-2361,22
-2363,4
-2366,76
-2367,116
-2368,65
-2369,11
-2370,14
-2371,47
-2372,8
-2373,16
-2374,6
-2376,6
-2377,3
-2378,32
-2379,25
-2380,38
-2381,23
-2384,51
-2385,13
-2388,54
-2389,35
-2390,44
-2391,12
-2398,36
-2399,12
-2400,55
-2401,19
-2402,67
-2403,35
-2404,42
-2405,16
-2406,59
-2407,15
-2408,10
-2409,5
-2410,26
-2411,11
-2413,25
-2414,8
-2416,41
-2417,32
-2418,9
-2419,79
-2420,44
-2421,37
-2422,21
-2423,2
-2424,80
-2425,36
-2426,53
-2427,48
-2428,4
-2429,85
-2430,27
-2431,49
-2432,59
-2433,29
-2435,52
-2436,17
-2437,6
-2438,3
-2440,69
-2441,58
-2446,88
-2447,48
-2448,12
-2450,4
-2451,96
-2452,36
-2453,34
-2454,90
-2455,51
-2456,11
-2457,43
-2458,21
-2459,41
-2460,68
-2461,19
-2462,3
-2463,26
-2464,12
-2466,129
-2467,30
-2468,81
-2469,23
-2470,8
-2471,7
-2472,30
-2473,9
-2474,4
-2475,2
-2480,50
-2481,49
-2482,17
-2484,33
-2485,16
-2486,85
-2487,19
-2488,17
-2489,8
-2491,5
-2492,32
-2493,34
-2494,11
-2497,42
-2498,15
-2499,28
-2500,17
-2501,97
-2502,20
-2508,69
-2509,64
-2510,16
-2512,17
-2513,171
-2514,55
-2516,54
-2517,24
-2518,14
-2519,66
-2520,104
-2521,42
-2523,70
-2524,47
-2528,14
-2529,9
-2533,39
-2534,22
-2535,42
-2536,16
-2537,38
-2538,7
-2542,6
-2545,7
-2546,7
-2547,11
-2548,2
-2550,25
-2551,23
-2552,4
-2553,17
-2554,55
-2555,6
-2557,33
-2558,6
-2560,26
-2561,65
-2562,12
-2563,94
-2564,34
-2573,22
-2574,19
-2575,13
-2576,52
-2577,48
-2578,11
-2586,70
-2587,42
-2591,75
-2592,56
-2593,7
-2594,6
-2595,6
-2596,2
-2598,27
-2599,18
-2603,26
-2604,18
-2605,15
-2606,86
-2607,43
-2609,25
-2610,16
-2620,52
-2621,27
-2622,4
-2623,15
-2624,1
-2626,6
-2627,18
-2628,6
-2629,58
-2630,39
-2631,70
-2632,24
-2641,42
-2642,55
-2643,49
-2644,4
-2650,5
-2651,1
-2656,13
-2657,82
-2658,31
-2661,78
-2662,18
-2663,49
-2664,16
-2669,21
-2670,11
-2675,36
-2676,17
-2677,41
-2678,10
-2679,64
-2680,10
-2688,32
-2689,12
-2690,14
-2691,16
-2694,18
-2695,44
-2696,19
-2700,10
-2701,44
-2702,8
-2703,52
-2704,14
-2705,34
-2706,6
-2708,89
-2709,22
-2710,14
-2711,2
-2715,66
-2716,68
-2717,26
-2718,4
-2719,4
-2721,26
-2722,23
-2728,18
-2729,8
-2730,12
-2731,4
-2738,66
-2739,41
-2742,33
-2743,19
-2744,32
-2745,33
-2746,7
-2747,4
-2748,4
-2749,182
-2750,131
-2751,42
-2753,36
-2754,12
-2755,1
-2757,42
-2758,20
-2761,102
-2762,18
-2767,27
-2768,9
-2769,11
-2770,83
-2771,55
-2772,8
-2776,21
-2777,13
-2779,30
-2780,89
-2781,45
-2790,27
-2791,7
-2792,54
-2793,43
-2794,14
-2796,51
-2797,14
-2799,46
-2800,20
-2804,11
-2805,3
-2806,50
-2807,42
-2808,18
-2809,7
-2810,2
-2811,37
-2812,19
-2818,37
-2819,28
-2827,96
-2828,45
-2829,6
-2831,7
-2832,29
-2833,9
-2836,54
-2837,11
-2838,33
-2839,34
-2840,8
-2841,61
-2842,20
-2844,62
-2845,96
-2846,27
-2848,52
-2849,17
-2853,4
-2854,8
-2855,6
-2856,55
-2857,35
-2858,2
-2860,12
-2861,37
-2862,3
-2870,11
-2871,2
-2874,10
-2875,2
-2876,72
-2877,62
-2878,10
-2881,53
-2882,18
-2884,24
-2885,6
-2889,5
-2890,2
-2906,55
-2907,49
-2908,23
-2909,58
-2910,73
-2911,24
-2912,30
-2913,5
-2921,37
-2922,58
-2923,89
-2924,21
-2926,25
-2927,34
-2928,13
-2929,1
-2933,53
-2934,21
-2935,74
-2936,27
-2938,40
-2939,10
-2940,76
-2941,39
-2942,95
-2943,39
-2953,57
-2954,60
-2955,17
-2962,37
-2963,15
-2964,35
-2965,18
-2970,54
-2971,18
-2975,45
-2976,30
-2980,62
-2981,21
-2983,24
-2984,13
-2988,26
-2989,10
-2999,30
-3000,4
-3002,4
-3003,5
-3005,12
-3006,18
-3007,15
-3010,27
-3011,4
-3026,45
-3027,18
-3038,36
-3039,12
-3041,8
-3042,4
-3044,12
-3045,36
-3046,8
-3047,10
-3048,8
-3049,39
-3050,95
-3051,30
-3052,4
-3053,38
-3054,18
-3059,68
-3060,56
-3061,7
-3063,47
-3064,104
-3065,46
-3071,55
-3072,38
-3073,6
-3075,24
-3076,8
-3079,22
-3080,9
-3087,100
-3088,28
-3098,15
-3099,4
-3102,65
-3103,114
-3104,22
-3105,5
-3106,1
-3109,8
-3110,4
-3116,8
-3117,52
-3118,37
-3119,23
-3120,8
-3124,11
-3125,2
-3126,80
-3127,57
-3128,11
-3131,41
-3132,39
-3133,15
-3134,52
-3135,34
-3141,23
-3142,16
-3158,17
-3159,15
-3162,32
-3163,21
-3167,8
-3168,9
-3171,17
-3172,5
-3178,9
-3179,3
-3187,6
-3191,63
-3192,94
-3193,23
-3196,57
-3197,34
-3200,30
-3201,12
-3204,109
-3205,76
-3208,112
-3209,37
-3210,2
-3214,9
-3215,48
-3216,15
-3218,13
-3219,61
-3220,55
-3221,8
-3225,57
-3226,12
-3227,84
-3228,56
-3230,40
-3231,53
-3232,54
-3233,25
-3235,43
-3236,18
-3237,93
-3238,60
-3241,4
-3242,2
-3248,15
-3249,27
-3250,14
-3253,7
-3260,71
-3261,56
-3262,19
-3267,29
-3268,15
-3269,6
-3270,2
-3272,1
-3273,10
-3274,5
-3275,37
-3276,16
-3281,30
-3282,35
-3283,8
-3287,5
-3288,3
-3291,16
-3292,82
-3293,27
-3300,50
-3301,27
-3311,29
-3312,37
-3314,25
-3315,10
-3317,47
-3318,14
-3319,26
-3320,9
-3326,3
-3327,3
-3328,49
-3329,51
-3330,40
-3331,8
-3344,9
-3345,2
-3354,11
-3355,3
-3357,3
-3358,34
-3359,11
-3367,29
-3368,45
-3369,14
-3375,22
-3376,4
-3392,12
-3393,4
-3394,13
-3395,12
-3399,65
-3400,20
-3404,36
-3405,48
-3406,9
-3412,33
-3413,8
-3416,8
-3417,4
-3421,14
-3422,3
-3423,3
-3424,6
-3425,1
-3427,6
-3429,30
-3430,77
-3431,52
-3432,23
-3433,5
-3435,4
-3436,56
-3437,69
-3438,12
-3442,25
-3443,17
-3448,38
-3449,9
-3452,11
-3453,9
-3454,48
-3455,35
-3460,13
-3461,3
-3465,44
-3466,16
-3468,27
-3469,16
-3473,49
-3474,50
-3475,19
-3476,1
-3501,39
-3502,22
-3506,11
-3507,16
-3508,1
-3511,39
-3512,16
-3515,84
-3516,28
-3522,101
-3523,42
-3525,41
-3526,17
-3528,41
-3529,48
-3530,8
-3534,26
-3535,6
-3536,50
-3537,22
-3538,1
-3540,39
-3541,19
-3546,16
-3547,10
-3550,9
-3551,3
-3559,20
-3560,3
-3571,45
-3572,19
-3576,6
-3577,3
-3580,7
-3592,27
-3593,9
-3601,10
-3602,5
-3606,44
-3607,13
-3612,8
-3613,1
-3623,24
-3624,89
-3625,15
-3626,6
-3627,3
-3633,11
-3634,25
-3635,9
-3636,51
-3637,23
-3639,17
-3640,9
-3641,29
-3642,7
-3646,23
-3647,13
-3648,28
-3649,7
-3650,6
-3651,28
-3652,63
-3653,7
-3657,46
-3658,12
-3662,58
-3663,15
-3669,33
-3670,11
-3675,26
-3676,7
-3702,9
-3703,1
-3711,32
-3712,12
-3715,7
-3716,3
-3722,45
-3723,54
-3724,15
-3725,104
-3726,30
-3727,21
-3728,16
-3732,28
-3733,16
-3734,5
-3743,23
-3744,19
-3748,4
-3749,2
-3763,10
-3764,1
-3765,34
-3766,11
-3787,7
-3788,3
-3795,65
-3796,11
-3805,10
-3806,62
-3807,25
-3811,38
-3812,38
-3813,11
-3819,6
-3820,7
-3821,57
-3822,11
-3824,37
-3825,17
-3836,100
-3837,48
-3842,99
-3843,38
-3847,61
-3848,21
-3850,9
-3851,14
-3852,3
-3853,13
-3854,11
-3856,61
-3857,6
-3859,32
-3860,2
-3865,26
-3866,15
-3867,13
-3868,4
-3873,5
-3874,72
-3875,52
-3877,15
-3878,10
-3884,33
-3885,12
-3888,11
-3889,2
-3899,29
-3900,14
-3901,59
-3902,17
-3909,4
-3910,3
-3914,49
-3915,20
-3916,1
-3919,29
-3920,10
-3921,43
-3922,15
-3929,3
-3933,18
-3934,4
-3936,15
-3937,11
-3940,8
-3945,37
-3946,42
-3947,11
-3948,25
-3949,15
-3953,46
-3954,7
-3963,30
-3964,7
-3966,30
-3967,18
-3975,10
-3976,3
-3980,4
-3981,23
-3982,7
-3983,25
-3984,9
-3994,49
-3995,37
-4003,37
-4004,20
-4017,55
-4018,10
-4029,26
-4030,9
-4031,36
-4032,16
-4039,9
-4040,4
-4057,52
-4058,20
-4059,2
-4060,1
-4067,32
-4068,154
-4069,47
-4073,6
-4074,1
-4075,14
-4076,17
-4077,5
-4085,4
-4086,20
-4087,12
-4088,1
-4099,21
-4100,6
-4104,92
-4105,25
-4106,9
-4107,3
-4130,39
-4131,17
-4133,15
-4134,3
-4152,90
-4153,55
-4169,27
-4170,16
-4172,18
-4173,15
-4174,11
-4175,5
-4186,57
-4187,6
-4188,13
-4189,26
-4190,11
-4204,52
-4205,45
-4206,20
-4213,44
-4214,14
-4219,80
-4220,34
-4228,27
-4229,4
-4235,25
-4236,10
-4237,41
-4238,18
-4240,8
-4241,7
-4248,37
-4249,7
-4250,28
-4251,8
-4253,27
-4254,9
-4255,57
-4256,12
-4276,23
-4277,8
-4294,7
-4295,4
-4301,27
-4302,19
-4315,26
-4316,68
-4317,64
-4318,7
-4346,8
-4347,2
-4350,39
-4351,21
-4358,2
-4359,1
-4361,8
-4362,4
-4363,35
-4364,13
-4366,2
-4378,34
-4379,19
-4382,43
-4383,19
-4387,19
-4388,59
-4389,20
-4411,19
-4412,11
-4431,7
-4432,22
-4433,13
-4439,14
-4440,10
-4442,66
-4443,30
-4450,61
-4451,56
-4462,29
-4463,15
-4467,19
-4468,59
-4469,25
-4470,17
-4471,9
-4500,64
-4501,31
-4520,38
-4521,77
-4522,85
-4523,34
-4534,11
-4535,4
-4540,14
-4541,3
-4544,49
-4545,22
-4546,2
-4571,35
-4572,18
-4578,10
-4579,11
-4582,32
-4583,12
-4590,63
-4591,32
-4600,83
-4601,23
-4628,8
-4629,4
-4631,52
-4632,19
-4648,24
-4649,11
-4691,43
-4692,31
-4704,10
-4705,4
-4708,31
-4709,10
-4722,4
-4723,15
-4724,40
-4725,8
-4726,5
-4727,1
-4750,29
-4751,12
-4756,32
-4757,7
-4759,3
-4760,72
-4761,16
-4770,50
-4771,26
-4791,46
-4792,22
-4796,21
-4797,12
-4798,2
-4870,25
-4871,11
-4875,94
-4876,39
-4877,83
-4878,22
-4893,24
-4894,10
-4899,8
-4900,3
-4906,12
-4907,3
-4910,24
-4911,13
-4942,29
-4943,10
-4967,25
-4968,5
-4973,69
-4974,35
-4976,26
-4977,47
-4978,9
-4979,104
-4980,76
-4981,5
-4985,29
-4986,13
-4989,24
-4990,11
-5011,32
-5012,11
-5013,40
-5014,15
-5024,13
-5025,5
-5026,38
-5027,21
-5042,50
-5043,21
-5044,16
-5045,4
-5085,52
-5086,35
-5092,9
-5093,2
-5097,50
-5098,35
-5119,51
-5120,39
-5131,35
-5132,24
-5138,23
-5139,18
-5166,29
-5167,16
-5168,9
-5169,1
-5184,53
-5185,29
-5191,23
-5192,10
-5193,5
-5194,1
-5208,27
-5209,2
-5215,26
-5216,8
-5218,32
-5219,7
-5221,25
-5222,18
-5229,54
-5230,17
-5232,19
-5233,9
-5239,4
-5240,5
-5249,37
-5250,15
-5262,33
-5263,90
-5264,23
-5266,33
-5267,9
-5280,47
-5281,8
-5290,36
-5291,9
-5298,70
-5299,27
-5307,21
-5308,13
-5322,41
-5323,26
-5328,37
-5329,12
-5332,37
-5333,29
-5388,20
-5389,50
-5390,18
-5401,8
-5402,7
-5403,110
-5404,31
-5410,50
-5411,17
-5422,8
-5423,6
-5424,19
-5425,13
-5429,6
-5430,2
-5436,17
-5437,7
-5440,14
-5441,11
-5450,23
-5451,15
-5461,43
-5462,9
-5463,1
-5464,11
-5465,4
-5467,2
-5468,2
-5476,12
-5477,4
-5490,63
-5491,21
-5493,21
-5494,10
-5499,9
-5503,16
-5504,8
-5505,33
-5506,11
-5520,37
-5521,35
-5522,3
-5528,21
-5529,9
-5547,10
-5548,7
-5576,21
-5577,10
-5589,91
-5590,35
-5591,9
-5592,4
-5599,46
-5600,2
-5692,3
-5700,44
-5701,36
-5714,29
-5715,5
-5728,35
-5729,21
-5767,46
-5768,14
-5773,12
-5774,5
-5780,17
-5781,16
-5793,8
-5794,4
-5813,29
-5814,14
-5843,17
-5844,2
-5855,8
-5856,1
-5875,13
-5876,3
-5877,49
-5878,20
-5887,75
-5888,28
-5893,24
-5894,11
-5907,39
-5908,17
-5909,16
-5910,4
-5935,58
-5936,12
-5948,9
-5949,4
-5959,28
-5960,8
-5984,21
-5985,11
-6012,36
-6013,12
-6031,29
-6032,6
-6033,5
-6034,1
-6035,115
-6036,19
-6045,38
-6046,8
-6096,55
-6097,12
-6103,41
-6104,16
-6143,47
-6144,9
-6164,54
-6165,13
-6166,40
-6167,24
-6178,17
-6179,6
-6205,27
-6206,10
-6211,8
-6212,4
-6237,94
-6238,33
-6253,15
-6254,6
-6268,19
-6269,4
-6276,7
-6277,3
-6278,5
-6279,3
-6280,46
-6281,5
-6330,41
-6331,18
-6364,75
-6365,25
-6395,3
-6396,3
-6417,11
-6418,4
-6423,50
-6424,13
-6426,14
-6427,4
-6453,18
-6454,6
-6460,24
-6461,8
-6467,215
-6468,80
-6490,22
-6491,9
-6495,97
-6496,44
-6518,34
-6519,5
-6547,11
-6548,1
-6550,38
-6551,13
-6577,52
-6578,24
-6613,73
-6614,18
-6619,3
-6620,1
-6651,18
-6652,8
-6660,38
-6661,9
-6684,3
-6685,1
-6693,85
-6694,27
-6744,107
-6745,41
-6773,6
-6774,4
-6781,7
-6782,2
-6800,38
-6801,19
-6804,23
-6805,2
-6818,32
-6819,44
-6820,24
-6840,44
-6841,30
-6844,67
-6845,24
-6849,5
-6853,98
-6854,38
-6876,14
-6877,5
-6895,33
-6896,9
-6902,38
-6903,9
-6919,60
-6920,26
-6972,10
-6973,7
-7009,10
-7010,5
-7019,63
-7020,15
-7082,20
-7083,8
-7099,12
-7100,4
-7110,41
-7111,6
-7124,28
-7125,10
-7132,9
-7133,4
-7196,7
-7197,5
-7202,28
-7203,11
-7215,20
-7216,11
-7221,13
-7222,6
-7266,20
-7267,7
-7277,19
-7278,2
-7338,5
-7339,2
-7370,48
-7371,22
-7429,70
-7430,40
-7434,117
-7435,31
-7447,12
-7448,5
-7603,11
-7604,7
-7621,26
-7622,12
-7626,50
-7627,24
-7641,33
-7642,9
-7702,32
-7703,7
-7707,77
-7708,62
-7733,84
-7734,39
-7791,38
-7792,18
-7798,28
-7799,6
-7803,52
-7804,6
-7851,35
-7852,7
-7890,5
-7891,2
-7917,34
-7918,14
-7919,93
-7920,19
-7921,26
-7922,16
-7924,4
-7933,47
-7934,17
-7964,60
-7965,19
-8044,8
-8045,1
-8067,45
-8068,17
-8107,44
-8108,11
-8165,36
-8166,13
-8223,36
-8224,20
-8225,4
-8230,55
-8231,24
-8241,93
-8242,30
-8268,28
-8269,8
-8336,52
-8337,30
-8467,38
-8468,14
-8472,46
-8473,18
-8522,58
-8523,25
-8605,35
-8606,12
-8637,33
-8638,8
-8639,22
-8640,12
-8658,9
-8659,4
-8678,23
-8679,6
-8695,38
-8696,12
-8734,57
-8735,45
-8766,6
-8767,2
-8773,40
-8774,15
-8792,24
-8793,4
-8805,23
-8806,10
-8851,57
-8852,24
-8927,38
-8928,12
-8971,22
-8972,12
-8988,27
-8989,15
-9018,3
-9019,2
-9074,11
-9075,27
-9076,11
-9087,23
-9088,16
-9090,17
-9091,9
-9130,10
-9131,3
-9140,38
-9141,12
-9149,13
-9150,8
-9228,13
-9229,5
-9267,17
-9268,10
-9294,10
-9295,2
-9343,4
-9344,1
-9347,5
-9348,1
-9432,6
-9433,4
-9493,33
-9494,10
-9571,5
-9572,2
-9575,19
-9576,4
-9584,38
-9585,16
-9608,23
-9609,18
-9678,6
-9679,1
-9740,72
-9741,33
-9756,5
-9757,6
-9838,10
-9839,3
-9961,13
-9962,11
-9971,23
-9972,14
-10025,45
-10026,12
-10042,3
-10043,1
-10106,45
-10107,12
-10108,34
-10109,19
-10192,31
-10193,14
-10308,8
-10309,9
-10337,7
-10338,3
-10375,36
-10376,12
-10433,28
-10434,16
-10461,12
-10462,4
-10532,43
-10533,10
-10665,24
-10666,12
-10719,29
-10720,14
-10747,31
-10748,10
-10749,94
-10750,32
-10769,27
-10770,2
-10836,24
-10837,10
-10880,42
-10881,14
-10893,7
-10894,5
-10902,75
-10903,31
-10919,54
-10920,32
-10924,8
-10925,3
-11011,9
-11012,10
-11048,43
-11049,13
-11055,21
-11056,4
-11100,2
-11101,3
-11144,10
-11145,5
-11261,116
-11262,46
-11325,12
-11326,5
-11422,51
-11423,11
-11426,24
-11427,5
-11458,66
-11459,30
-11460,28
-11461,13
-11468,17
-11469,15
-11483,23
-11484,12
-11529,25
-11530,2
-11654,57
-11655,27
-11681,63
-11682,28
-11831,19
-11832,9
-11985,8
-11986,4
-12120,21
-12121,10
-12124,39
-12125,13
-12169,7
-12170,3
-12251,27
-12252,10
-12393,55
-12394,18
-12479,50
-12480,15
-12496,18
-12497,5
-12576,38
-12577,14
-12581,39
-12582,18
-12601,50
-12602,11
-12734,10
-12735,2
-12777,6
-12778,1
-12956,29
-12957,12
-12965,37
-12966,9
-12969,31
-12970,8
-12971,23
-12972,12
-13073,7
-13074,3
-13161,20
-13162,11
-13166,91
-13167,21
-13549,54
-13550,35
-14022,11
-14023,15
-14605,89
-14606,26
-14726,14
-14727,9
-14736,5
-14737,3
-15075,4
-15076,3
-15097,31
-15098,6
-15507,8
-15508,3
-15544,45
-15545,15
-15845,5
-15846,1
-16252,26
-16253,6
-16356,2
-16357,2
-16440,3
-16441,1
-16601,17
-16602,6
-16876,2
-16877,1
-16891,86
-16892,38
-17220,55
-17221,39
-17394,56
-17395,15
-17412,46
-17413,13
-17512,74
-17513,28
-17999,35
-18000,5
-18152,17
-18153,12
-18208,14
-18209,6
-19008,61
-19009,25
-19273,7
-19274,3
-19456,86
-19457,37
-19469,8
-19470,2
-19730,47
-19731,20
-19887,43
-19888,9
-20060,46
-20061,29
-20172,39
-20173,28
-20222,77
-20223,22
-20318,42
-20319,15
-20397,85
-20398,42
-20510,29
-20511,8
-21096,41
-21097,13
-21164,91
-21165,28
-21303,32
-21304,7
-21784,27
-21785,14
-22129,69
-22130,18
-22730,82
-22731,28
-24532,68
-24533,28
-25235,55
-25236,30
-25530,67
-25531,33
-25635,22
-25636,12
-27225,12
-27226,7
-27304,38
-27305,11
-27430,17
-27431,4
-27748,38
-27749,4
-28270,28
-28271,12
-28825,20
-28826,20
-30839,49
-30840,19
-33547,27
-33548,11
-34454,23
-34455,17
-35878,26
-35879,8
-36707,53
-36708,16
-40907,14
-40908,11
-42274,22
-42275,6
-42374,22
-42375,8
-43321,76
-43322,25
-46114,15
-46115,6
-51382,16
-51383,5
-52018,24
-52019,5
-59344,45
-59345,12
-64689,40
-64690,46
-75620,16
-75621,5
-80872,65
-80873,19
-94174,40
-94175,15
-124261,22
-124262,10
diff --git a/dtrain/dtrain.cc b/dtrain/dtrain.cc
index 18024bae..cdf95c95 100644
--- a/dtrain/dtrain.cc
+++ b/dtrain/dtrain.cc
@@ -216,6 +216,7 @@ main(int argc, char** argv)
score_t max_score = 0.;
unsigned best_it = 0;
float overall_time = 0.;
+ unsigned pair_count = 0, feature_count = 0;
// output cfg
if (!quiet) {
@@ -400,10 +401,12 @@ main(int argc, char** argv)
if (pair_sampling == "PRO")
PROsampling(samples, pairs);
npairs += pairs.size();
+ pair_count += 2*pairs.size();
for (vector<pair<ScoredHyp,ScoredHyp> >::iterator it = pairs.begin();
it != pairs.end(); it++) {
score_t rank_error = it->second.score - it->first.score;
+ feature_count += it->first.f.size() + it->second.f.size();
if (!gamma) {
// perceptron
if (rank_error > 0) {
@@ -534,9 +537,11 @@ if (false) {
cerr << " avg #rank err: ";
cerr << rank_errors/(float)in_sz << endl;
cerr << " avg #margin viol: ";
- cerr << margin_violations/float(in_sz) << endl;
- cerr << " non0 feature count: ";
+ cerr << margin_violations/(float)in_sz << endl;
+ cerr << " non0 feature count: " << endl;
cerr << nonz << endl;
+ cerr << " avg f count: ";
+ cerr << feature_count/(float)pair_count;
}
if (hstreaming) {
diff --git a/dtrain/dtrain.h b/dtrain/dtrain.h
index 3d76bd7f..14ef410e 100644
--- a/dtrain/dtrain.h
+++ b/dtrain/dtrain.h
@@ -13,7 +13,7 @@
#include "filelib.h"
-//#define DTRAIN_LOCAL
+#define DTRAIN_LOCAL
#define DTRAIN_DOTS 100 // when to display a '.'
#define DTRAIN_GRAMMAR_DELIM "########EOS########"
diff --git a/dtrain/test/mira_update/Hildreth.cpp b/dtrain/test/mira_update/Hildreth.cpp
new file mode 100644
index 00000000..0e67eb15
--- /dev/null
+++ b/dtrain/test/mira_update/Hildreth.cpp
@@ -0,0 +1,187 @@
+#include "Hildreth.h"
+#include "sparse_vector.h"
+
+using namespace std;
+
+namespace Mira {
+ vector<double> Hildreth::optimise (vector< SparseVector<double> >& a, vector<double>& b) {
+
+ size_t i;
+ int max_iter = 10000;
+ double eps = 0.00000001;
+ double zero = 0.000000000001;
+
+ vector<double> alpha ( b.size() );
+ vector<double> F ( b.size() );
+ vector<double> kkt ( b.size() );
+
+ double max_kkt = -1e100;
+
+ size_t K = b.size();
+
+ double A[K][K];
+ bool is_computed[K];
+ for ( i = 0; i < K; i++ )
+ {
+ A[i][i] = a[i].dot(a[i]);
+ is_computed[i] = false;
+ }
+
+ int max_kkt_i = -1;
+
+
+ for ( i = 0; i < b.size(); i++ )
+ {
+ F[i] = b[i];
+ kkt[i] = F[i];
+ if ( kkt[i] > max_kkt )
+ {
+ max_kkt = kkt[i];
+ max_kkt_i = i;
+ }
+ }
+
+ int iter = 0;
+ double diff_alpha;
+ double try_alpha;
+ double add_alpha;
+
+ while ( max_kkt >= eps && iter < max_iter )
+ {
+
+ diff_alpha = A[max_kkt_i][max_kkt_i] <= zero ? 0.0 : F[max_kkt_i]/A[max_kkt_i][max_kkt_i];
+ try_alpha = alpha[max_kkt_i] + diff_alpha;
+ add_alpha = 0.0;
+
+ if ( try_alpha < 0.0 )
+ add_alpha = -1.0 * alpha[max_kkt_i];
+ else
+ add_alpha = diff_alpha;
+
+ alpha[max_kkt_i] = alpha[max_kkt_i] + add_alpha;
+
+ if ( !is_computed[max_kkt_i] )
+ {
+ for ( i = 0; i < K; i++ )
+ {
+ A[i][max_kkt_i] = a[i].dot(a[max_kkt_i] ); // for version 1
+ //A[i][max_kkt_i] = 0; // for version 1
+ is_computed[max_kkt_i] = true;
+ }
+ }
+
+ for ( i = 0; i < F.size(); i++ )
+ {
+ F[i] -= add_alpha * A[i][max_kkt_i];
+ kkt[i] = F[i];
+ if ( alpha[i] > zero )
+ kkt[i] = abs ( F[i] );
+ }
+ max_kkt = -1e100;
+ max_kkt_i = -1;
+ for ( i = 0; i < F.size(); i++ )
+ if ( kkt[i] > max_kkt )
+ {
+ max_kkt = kkt[i];
+ max_kkt_i = i;
+ }
+
+ iter++;
+ }
+
+ return alpha;
+ }
+
+ vector<double> Hildreth::optimise (vector< SparseVector<double> >& a, vector<double>& b, double C) {
+
+ size_t i;
+ int max_iter = 10000;
+ double eps = 0.00000001;
+ double zero = 0.000000000001;
+
+ vector<double> alpha ( b.size() );
+ vector<double> F ( b.size() );
+ vector<double> kkt ( b.size() );
+
+ double max_kkt = -1e100;
+
+ size_t K = b.size();
+
+ double A[K][K];
+ bool is_computed[K];
+ for ( i = 0; i < K; i++ )
+ {
+ A[i][i] = a[i].dot(a[i]);
+ is_computed[i] = false;
+ }
+
+ int max_kkt_i = -1;
+
+
+ for ( i = 0; i < b.size(); i++ )
+ {
+ F[i] = b[i];
+ kkt[i] = F[i];
+ if ( kkt[i] > max_kkt )
+ {
+ max_kkt = kkt[i];
+ max_kkt_i = i;
+ }
+ }
+
+ int iter = 0;
+ double diff_alpha;
+ double try_alpha;
+ double add_alpha;
+
+ while ( max_kkt >= eps && iter < max_iter )
+ {
+
+ diff_alpha = A[max_kkt_i][max_kkt_i] <= zero ? 0.0 : F[max_kkt_i]/A[max_kkt_i][max_kkt_i];
+ try_alpha = alpha[max_kkt_i] + diff_alpha;
+ add_alpha = 0.0;
+
+ if ( try_alpha < 0.0 )
+ add_alpha = -1.0 * alpha[max_kkt_i];
+ else if (try_alpha > C)
+ add_alpha = C - alpha[max_kkt_i];
+ else
+ add_alpha = diff_alpha;
+
+ alpha[max_kkt_i] = alpha[max_kkt_i] + add_alpha;
+
+ if ( !is_computed[max_kkt_i] )
+ {
+ for ( i = 0; i < K; i++ )
+ {
+ A[i][max_kkt_i] = a[i].dot(a[max_kkt_i] ); // for version 1
+ //A[i][max_kkt_i] = 0; // for version 1
+ is_computed[max_kkt_i] = true;
+ }
+ }
+
+ for ( i = 0; i < F.size(); i++ )
+ {
+ F[i] -= add_alpha * A[i][max_kkt_i];
+ kkt[i] = F[i];
+ if (alpha[i] > C - zero)
+ kkt[i]=-kkt[i];
+ else if (alpha[i] > zero)
+ kkt[i] = abs(F[i]);
+
+ }
+ max_kkt = -1e100;
+ max_kkt_i = -1;
+ for ( i = 0; i < F.size(); i++ )
+ if ( kkt[i] > max_kkt )
+ {
+ max_kkt = kkt[i];
+ max_kkt_i = i;
+ }
+
+ iter++;
+ }
+
+ return alpha;
+ }
+}
diff --git a/dtrain/test/mira_update/Hildreth.h b/dtrain/test/mira_update/Hildreth.h
new file mode 100644
index 00000000..8d791085
--- /dev/null
+++ b/dtrain/test/mira_update/Hildreth.h
@@ -0,0 +1,10 @@
+#include "sparse_vector.h"
+
+namespace Mira {
+ class Hildreth {
+ public :
+ static std::vector<double> optimise(std::vector< SparseVector<double> >& a, std::vector<double>& b);
+ static std::vector<double> optimise(std::vector< SparseVector<double> >& a, std::vector<double>& b, double C);
+ };
+}
+
diff --git a/dtrain/test/mira_update/dtrain.cc b/dtrain/test/mira_update/dtrain.cc
new file mode 100644
index 00000000..933417a4
--- /dev/null
+++ b/dtrain/test/mira_update/dtrain.cc
@@ -0,0 +1,532 @@
+#include "common.h"
+#include "kbestget.h"
+#include "util.h"
+#include "sample.h"
+#include "Hildreth.h"
+
+#include "ksampler.h"
+
+// boost compression
+#include <boost/iostreams/device/file.hpp>
+#include <boost/iostreams/filtering_stream.hpp>
+#include <boost/iostreams/filter/gzip.hpp>
+//#include <boost/iostreams/filter/zlib.hpp>
+//#include <boost/iostreams/filter/bzip2.hpp>
+using namespace boost::iostreams;
+
+
+#ifdef DTRAIN_DEBUG
+#include "tests.h"
+#endif
+
+
+/*
+ * init
+ *
+ */
+bool
+init(int argc, char** argv, po::variables_map* cfg)
+{
+ po::options_description conff( "Configuration File Options" );
+ size_t k, N, T, stop, n_pairs;
+ string s, f, update_type;
+ conff.add_options()
+ ( "decoder_config", po::value<string>(), "configuration file for cdec" )
+ ( "kbest", po::value<size_t>(&k)->default_value(DTRAIN_DEFAULT_K), "k for kbest" )
+ ( "ngrams", po::value<size_t>(&N)->default_value(DTRAIN_DEFAULT_N), "N for Ngrams" )
+ ( "filter", po::value<string>(&f)->default_value("unique"), "filter kbest list" )
+ ( "epochs", po::value<size_t>(&T)->default_value(DTRAIN_DEFAULT_T), "# of iterations T" )
+ ( "input", po::value<string>(), "input file" )
+ ( "scorer", po::value<string>(&s)->default_value(DTRAIN_DEFAULT_SCORER), "scoring metric" )
+ ( "output", po::value<string>(), "output weights file" )
+ ( "stop_after", po::value<size_t>(&stop)->default_value(0), "stop after X input sentences" )
+ ( "weights_file", po::value<string>(), "input weights file (e.g. from previous iteration)" )
+ ( "wprint", po::value<string>(), "weights to print on each iteration" )
+ ( "noup", po::value<bool>()->zero_tokens(), "do not update weights" );
+
+ po::options_description clo("Command Line Options");
+ clo.add_options()
+ ( "config,c", po::value<string>(), "dtrain config file" )
+ ( "quiet,q", po::value<bool>()->zero_tokens(), "be quiet" )
+ ( "update-type", po::value<string>(&update_type)->default_value("mira"), "perceptron or mira" )
+ ( "n-pairs", po::value<size_t>(&n_pairs)->default_value(10), "number of pairs used to compute update" )
+ ( "verbose,v", po::value<bool>()->zero_tokens(), "be verbose" )
+#ifndef DTRAIN_DEBUG
+ ;
+#else
+ ( "test", "run tests and exit");
+#endif
+ po::options_description config_options, cmdline_options;
+
+ config_options.add(conff);
+ cmdline_options.add(clo);
+ cmdline_options.add(conff);
+
+ po::store( parse_command_line(argc, argv, cmdline_options), *cfg );
+ if ( cfg->count("config") ) {
+ ifstream config( (*cfg)["config"].as<string>().c_str() );
+ po::store( po::parse_config_file(config, config_options), *cfg );
+ }
+ po::notify(*cfg);
+
+ if ( !cfg->count("decoder_config") || !cfg->count("input") ) {
+ cerr << cmdline_options << endl;
+ return false;
+ }
+ if ( cfg->count("noup") && cfg->count("decode") ) {
+ cerr << "You can't use 'noup' and 'decode' at once." << endl;
+ return false;
+ }
+ if ( cfg->count("filter") && (*cfg)["filter"].as<string>() != "unique"
+ && (*cfg)["filter"].as<string>() != "no" ) {
+ cerr << "Wrong 'filter' type: '" << (*cfg)["filter"].as<string>() << "'." << endl;
+ }
+ #ifdef DTRAIN_DEBUG
+ if ( !cfg->count("test") ) {
+ cerr << cmdline_options << endl;
+ return false;
+ }
+ #endif
+ return true;
+}
+
+
+// output formatting
+ostream& _nopos( ostream& out ) { return out << resetiosflags( ios::showpos ); }
+ostream& _pos( ostream& out ) { return out << setiosflags( ios::showpos ); }
+ostream& _prec2( ostream& out ) { return out << setprecision(2); }
+ostream& _prec5( ostream& out ) { return out << setprecision(5); }
+
+
+
+
+/*
+ * dtrain
+ *
+ */
+int
+main( int argc, char** argv )
+{
+ cout << setprecision( 5 );
+ // handle most parameters
+ po::variables_map cfg;
+ if ( ! init(argc, argv, &cfg) ) exit(1); // something is wrong
+#ifdef DTRAIN_DEBUG
+ if ( cfg.count("test") ) run_tests(); // run tests and exit
+#endif
+ bool quiet = false;
+ if ( cfg.count("quiet") ) quiet = true;
+ bool verbose = false;
+ if ( cfg.count("verbose") ) verbose = true;
+ bool noup = false;
+ if ( cfg.count("noup") ) noup = true;
+ const size_t k = cfg["kbest"].as<size_t>();
+ const size_t N = cfg["ngrams"].as<size_t>();
+ const size_t T = cfg["epochs"].as<size_t>();
+ const size_t stop_after = cfg["stop_after"].as<size_t>();
+ const string filter_type = cfg["filter"].as<string>();
+ const string update_type = cfg["update-type"].as<string>();
+ const size_t n_pairs = cfg["n-pairs"].as<size_t>();
+ const string output_file = cfg["output"].as<string>();
+ if ( !quiet ) {
+ cout << endl << "dtrain" << endl << "Parameters:" << endl;
+ cout << setw(25) << "k " << k << endl;
+ cout << setw(25) << "N " << N << endl;
+ cout << setw(25) << "T " << T << endl;
+ if ( cfg.count("stop-after") )
+ cout << setw(25) << "stop_after " << stop_after << endl;
+ if ( cfg.count("weights") )
+ cout << setw(25) << "weights " << cfg["weights"].as<string>() << endl;
+ cout << setw(25) << "input " << "'" << cfg["input"].as<string>() << "'" << endl;
+ cout << setw(25) << "filter " << "'" << filter_type << "'" << endl;
+ }
+
+ vector<string> wprint;
+ if ( cfg.count("wprint") ) {
+ boost::split( wprint, cfg["wprint"].as<string>(), boost::is_any_of(" ") );
+ }
+
+ // setup decoder, observer
+ register_feature_functions();
+ SetSilent(true);
+ ReadFile ini_rf( cfg["decoder_config"].as<string>() );
+ if ( !quiet )
+ cout << setw(25) << "cdec cfg " << "'" << cfg["decoder_config"].as<string>() << "'" << endl;
+ Decoder decoder( ini_rf.stream() );
+ //KBestGetter observer( k, filter_type );
+ MT19937 rng;
+ KSampler observer( k, &rng );
+
+ // scoring metric/scorer
+ string scorer_str = cfg["scorer"].as<string>();
+ double (*scorer)( NgramCounts&, const size_t, const size_t, size_t, vector<float> );
+ if ( scorer_str == "bleu" ) {
+ scorer = &bleu;
+ } else if ( scorer_str == "stupid_bleu" ) {
+ scorer = &stupid_bleu;
+ } else if ( scorer_str == "smooth_bleu" ) {
+ scorer = &smooth_bleu;
+ } else if ( scorer_str == "approx_bleu" ) {
+ scorer = &approx_bleu;
+ } else {
+ cerr << "Don't know scoring metric: '" << scorer_str << "', exiting." << endl;
+ exit(1);
+ }
+ // for approx_bleu
+ NgramCounts global_counts( N ); // counts for 1 best translations
+ size_t global_hyp_len = 0; // sum hypothesis lengths
+ size_t global_ref_len = 0; // sum reference lengths
+ // this is all BLEU implmentations
+ vector<float> bleu_weights; // we leave this empty -> 1/N; TODO?
+ if ( !quiet ) cout << setw(26) << "scorer '" << scorer_str << "'" << endl << endl;
+
+ // init weights
+ Weights weights;
+ if ( cfg.count("weights") ) weights.InitFromFile( cfg["weights"].as<string>() );
+ SparseVector<double> lambdas;
+ weights.InitSparseVector( &lambdas );
+ vector<double> dense_weights;
+
+ // input
+ if ( !quiet && !verbose )
+ cout << "(a dot represents " << DTRAIN_DOTS << " lines of input)" << endl;
+ string input_fn = cfg["input"].as<string>();
+ ifstream input;
+ if ( input_fn != "-" ) input.open( input_fn.c_str() );
+ string in;
+ vector<string> in_split; // input: src\tref\tpsg
+ vector<string> ref_tok; // tokenized reference
+ vector<WordID> ref_ids; // reference as vector of WordID
+ string grammar_str;
+
+ // buffer input for t > 0
+ vector<string> src_str_buf; // source strings, TODO? memory
+ vector<vector<WordID> > ref_ids_buf; // references as WordID vecs
+ filtering_ostream grammar_buf; // written to compressed file in /tmp
+ // this is for writing the grammar buffer file
+ grammar_buf.push( gzip_compressor() );
+ char grammar_buf_tmp_fn[] = DTRAIN_TMP_DIR"/dtrain-grammars-XXXXXX";
+ mkstemp( grammar_buf_tmp_fn );
+ grammar_buf.push( file_sink(grammar_buf_tmp_fn, ios::binary | ios::trunc) );
+
+ size_t sid = 0, in_sz = 99999999; // sentence id, input size
+ double acc_1best_score = 0., acc_1best_model = 0.;
+ vector<vector<double> > scores_per_iter;
+ double max_score = 0.;
+ size_t best_t = 0;
+ bool next = false, stop = false;
+ double score = 0.;
+ size_t cand_len = 0;
+ double overall_time = 0.;
+
+ // for the perceptron/SVM; TODO as params
+ double eta = 0.0005;
+ double gamma = 0.;//01; // -> SVM
+ lambdas.add_value( FD::Convert("__bias"), 0 );
+
+ // for random sampling
+ srand ( time(NULL) );
+
+
+ for ( size_t t = 0; t < T; t++ ) // T epochs
+ {
+
+ time_t start, end;
+ time( &start );
+
+ // actually, we need only need this if t > 0 FIXME
+ ifstream grammar_file( grammar_buf_tmp_fn, ios_base::in | ios_base::binary );
+ filtering_istream grammar_buf_in;
+ grammar_buf_in.push( gzip_decompressor() );
+ grammar_buf_in.push( grammar_file );
+
+ // reset average scores
+ acc_1best_score = acc_1best_model = 0.;
+
+ // reset sentence counter
+ sid = 0;
+
+ if ( !quiet ) cout << "Iteration #" << t+1 << " of " << T << "." << endl;
+
+ while( true )
+ {
+
+ // get input from stdin or file
+ in.clear();
+ next = stop = false; // next iteration, premature stop
+ if ( t == 0 ) {
+ if ( input_fn == "-" ) {
+ if ( !getline(cin, in) ) next = true;
+ } else {
+ if ( !getline(input, in) ) next = true;
+ }
+ } else {
+ if ( sid == in_sz ) next = true; // stop if we reach the end of our input
+ }
+ // stop after X sentences (but still iterate for those)
+ if ( stop_after > 0 && stop_after == sid && !next ) stop = true;
+
+ // produce some pretty output
+ if ( !quiet && !verbose ) {
+ if ( sid == 0 ) cout << " ";
+ if ( (sid+1) % (DTRAIN_DOTS) == 0 ) {
+ cout << ".";
+ cout.flush();
+ }
+ if ( (sid+1) % (20*DTRAIN_DOTS) == 0) {
+ cout << " " << sid+1 << endl;
+ if ( !next && !stop ) cout << " ";
+ }
+ if ( stop ) {
+ if ( sid % (20*DTRAIN_DOTS) != 0 ) cout << " " << sid << endl;
+ cout << "Stopping after " << stop_after << " input sentences." << endl;
+ } else {
+ if ( next ) {
+ if ( sid % (20*DTRAIN_DOTS) != 0 ) {
+ cout << " " << sid << endl;
+ }
+ }
+ }
+ }
+
+ // next iteration
+ if ( next || stop ) break;
+
+ // weights
+ dense_weights.clear();
+ weights.InitFromVector( lambdas );
+ weights.InitVector( &dense_weights );
+ decoder.SetWeights( dense_weights );
+
+ if ( t == 0 ) {
+ // handling input
+ in_split.clear();
+ boost::split( in_split, in, boost::is_any_of("\t") ); // in_split[0] is id
+ // getting reference
+ ref_tok.clear(); ref_ids.clear();
+ boost::split( ref_tok, in_split[2], boost::is_any_of(" ") );
+ register_and_convert( ref_tok, ref_ids );
+ ref_ids_buf.push_back( ref_ids );
+ // process and set grammar
+ bool broken_grammar = true;
+ for ( string::iterator ti = in_split[3].begin(); ti != in_split[3].end(); ti++ ) {
+ if ( !isspace(*ti) ) {
+ broken_grammar = false;
+ break;
+ }
+ }
+ if ( broken_grammar ) continue;
+ grammar_str = boost::replace_all_copy( in_split[3], " __NEXT__RULE__ ", "\n" ) + "\n"; // FIXME copy, __
+ grammar_buf << grammar_str << DTRAIN_GRAMMAR_DELIM << endl;
+ decoder.SetSentenceGrammarFromString( grammar_str );
+ // decode, kbest
+ src_str_buf.push_back( in_split[1] );
+ decoder.Decode( in_split[1], &observer );
+ } else {
+ // get buffered grammar
+ grammar_str.clear();
+ int i = 1;
+ while ( true ) {
+ string g;
+ getline( grammar_buf_in, g );
+ if ( g == DTRAIN_GRAMMAR_DELIM ) break;
+ grammar_str += g+"\n";
+ i += 1;
+ }
+ decoder.SetSentenceGrammarFromString( grammar_str );
+ // decode, kbest
+ decoder.Decode( src_str_buf[sid], &observer );
+ }
+
+ // get kbest list
+ KBestList* kb;
+ //if ( ) { // TODO get from forest
+ kb = observer.GetKBest();
+ //}
+
+ // scoring kbest
+ if ( t > 0 ) ref_ids = ref_ids_buf[sid];
+ for ( size_t i = 0; i < kb->GetSize(); i++ ) {
+ NgramCounts counts = make_ngram_counts( ref_ids, kb->sents[i], N );
+ // this is for approx bleu
+ if ( scorer_str == "approx_bleu" ) {
+ if ( i == 0 ) { // 'context of 1best translations'
+ global_counts += counts;
+ global_hyp_len += kb->sents[i].size();
+ global_ref_len += ref_ids.size();
+ counts.reset();
+ cand_len = 0;
+ } else {
+ cand_len = kb->sents[i].size();
+ }
+ NgramCounts counts_tmp = global_counts + counts;
+ // TODO as param
+ score = 0.9 * scorer( counts_tmp,
+ global_ref_len,
+ global_hyp_len + cand_len, N, bleu_weights );
+ } else {
+ // other scorers
+ cand_len = kb->sents[i].size();
+ score = scorer( counts,
+ ref_ids.size(),
+ kb->sents[i].size(), N, bleu_weights );
+ }
+
+ kb->scores.push_back( score );
+
+ if ( i == 0 ) {
+ acc_1best_score += score;
+ acc_1best_model += kb->model_scores[i];
+ }
+
+ if ( verbose ) {
+ if ( i == 0 ) cout << "'" << TD::GetString( ref_ids ) << "' [ref]" << endl;
+ cout << _prec5 << _nopos << "[hyp " << i << "] " << "'" << TD::GetString( kb->sents[i] ) << "'";
+ cout << " [SCORE=" << score << ",model="<< kb->model_scores[i] << "]" << endl;
+ cout << kb->feats[i] << endl; // this is maybe too verbose
+ }
+ } // Nbest loop
+
+ if ( verbose ) cout << endl;
+
+
+ // UPDATE WEIGHTS
+ if ( !noup ) {
+
+ TrainingInstances pairs;
+ sample_all( kb, pairs, n_pairs );
+
+ vector< SparseVector<double> > featureValueDiffs;
+ vector<double> lossMinusModelScoreDiffs;
+ for ( TrainingInstances::iterator ti = pairs.begin();
+ ti != pairs.end(); ti++ ) {
+
+ SparseVector<double> dv;
+ if ( ti->first_score - ti->second_score < 0 ) {
+ dv = ti->second - ti->first;
+ dv.add_value( FD::Convert("__bias"), -1 );
+
+ featureValueDiffs.push_back(dv);
+ double lossMinusModelScoreDiff = ti->loss_diff - ti->model_score_diff;
+ lossMinusModelScoreDiffs.push_back(lossMinusModelScoreDiff);
+
+ if (update_type == "perceptron") {
+ lambdas += dv * eta;
+ cerr << "after perceptron update: " << lambdas << endl << endl;
+ }
+
+ if ( verbose ) {
+ cout << "{{ f("<< ti->first_rank <<") > f(" << ti->second_rank << ") but g(i)="<< ti->first_score <<" < g(j)="<< ti->second_score << " so update" << endl;
+ cout << " i " << TD::GetString(kb->sents[ti->first_rank]) << endl;
+ cout << " " << kb->feats[ti->first_rank] << endl;
+ cout << " j " << TD::GetString(kb->sents[ti->second_rank]) << endl;
+ cout << " " << kb->feats[ti->second_rank] << endl;
+ cout << " diff vec: " << dv << endl;
+ cout << " lambdas after update: " << lambdas << endl;
+ cout << "}}" << endl;
+ }
+ } else {
+ //SparseVector<double> reg;
+ //reg = lambdas * ( 2 * gamma );
+ //lambdas += reg * ( -eta );
+ }
+ }
+ cerr << "Collected " << featureValueDiffs.size() << " constraints." << endl;
+
+ double slack = 0.01;
+ if (update_type == "mira") {
+ if (featureValueDiffs.size() > 0) {
+ vector<double> alphas;
+ if (slack != 0) {
+ alphas = Mira::Hildreth::optimise(featureValueDiffs, lossMinusModelScoreDiffs, slack);
+ } else {
+ alphas = Mira::Hildreth::optimise(featureValueDiffs, lossMinusModelScoreDiffs);
+ }
+
+ for (size_t k = 0; k < featureValueDiffs.size(); ++k) {
+ lambdas += featureValueDiffs[k] * alphas[k];
+ }
+ // cerr << "after mira update: " << lambdas << endl << endl;
+ }
+ }
+ }
+
+ ++sid;
+
+ } // input loop
+
+ if ( t == 0 ) in_sz = sid; // remember size (lines) of input
+
+ // print some stats
+ double avg_1best_score = acc_1best_score/(double)in_sz;
+ double avg_1best_model = acc_1best_model/(double)in_sz;
+ double avg_1best_score_diff, avg_1best_model_diff;
+ if ( t > 0 ) {
+ avg_1best_score_diff = avg_1best_score - scores_per_iter[t-1][0];
+ avg_1best_model_diff = avg_1best_model - scores_per_iter[t-1][1];
+ } else {
+ avg_1best_score_diff = avg_1best_score;
+ avg_1best_model_diff = avg_1best_model;
+ }
+ cout << _prec5 << _pos << "WEIGHTS" << endl;
+ for (vector<string>::iterator it = wprint.begin(); it != wprint.end(); it++) {
+ cout << setw(16) << *it << " = " << dense_weights[FD::Convert( *it )] << endl;
+ }
+
+ cout << " ---" << endl;
+ cout << _nopos << " avg score: " << avg_1best_score;
+ cout << _pos << " (" << avg_1best_score_diff << ")" << endl;
+ cout << _nopos << "avg model score: " << avg_1best_model;
+ cout << _pos << " (" << avg_1best_model_diff << ")" << endl;
+ vector<double> remember_scores;
+ remember_scores.push_back( avg_1best_score );
+ remember_scores.push_back( avg_1best_model );
+ scores_per_iter.push_back( remember_scores );
+ if ( avg_1best_score > max_score ) {
+ max_score = avg_1best_score;
+ best_t = t;
+ }
+
+ // close open files
+ if ( input_fn != "-" ) input.close();
+ close( grammar_buf );
+ grammar_file.close();
+
+ time ( &end );
+ double time_dif = difftime( end, start );
+ overall_time += time_dif;
+ if ( !quiet ) {
+ cout << _prec2 << _nopos << "(time " << time_dif/60. << " min, ";
+ cout << time_dif/(double)in_sz<< " s/S)" << endl;
+ }
+
+ if ( t+1 != T ) cout << endl;
+
+ if ( noup ) break;
+
+ // write weights after every epoch
+ std::string s;
+ std::stringstream out;
+ out << t;
+ s = out.str();
+ string weights_file = output_file + "." + s;
+ weights.WriteToFile(weights_file, true );
+
+ } // outer loop
+
+ unlink( grammar_buf_tmp_fn );
+ if ( !noup ) {
+ if ( !quiet ) cout << endl << "writing weights file '" << cfg["output"].as<string>() << "' ...";
+ weights.WriteToFile( cfg["output"].as<string>(), true );
+ if ( !quiet ) cout << "done" << endl;
+ }
+
+ if ( !quiet ) {
+ cout << _prec5 << _nopos << endl << "---" << endl << "Best iteration: ";
+ cout << best_t+1 << " [SCORE '" << scorer_str << "'=" << max_score << "]." << endl;
+ cout << _prec2 << "This took " << overall_time/60. << " min." << endl;
+ }
+
+ return 0;
+}
+
diff --git a/dtrain/test/mira_update/sample.h b/dtrain/test/mira_update/sample.h
new file mode 100644
index 00000000..5c331bba
--- /dev/null
+++ b/dtrain/test/mira_update/sample.h
@@ -0,0 +1,101 @@
+#ifndef _DTRAIN_SAMPLE_H_
+#define _DTRAIN_SAMPLE_H_
+
+
+#include "kbestget.h"
+
+
+namespace dtrain
+{
+
+
+struct TPair
+{
+ SparseVector<double> first, second;
+ size_t first_rank, second_rank;
+ double first_score, second_score;
+ double model_score_diff;
+ double loss_diff;
+};
+
+typedef vector<TPair> TrainingInstances;
+
+
+void
+ sample_all( KBestList* kb, TrainingInstances &training, size_t n_pairs )
+{
+ std::vector<double> loss_diffs;
+ TrainingInstances training_tmp;
+ for ( size_t i = 0; i < kb->GetSize()-1; i++ ) {
+ for ( size_t j = i+1; j < kb->GetSize(); j++ ) {
+ TPair p;
+ p.first = kb->feats[i];
+ p.second = kb->feats[j];
+ p.first_rank = i;
+ p.second_rank = j;
+ p.first_score = kb->scores[i];
+ p.second_score = kb->scores[j];
+
+ bool conservative = 1;
+ if ( kb->scores[i] - kb->scores[j] < 0 ) {
+ // j=hope, i=fear
+ p.model_score_diff = kb->model_scores[j] - kb->model_scores[i];
+ p.loss_diff = kb->scores[j] - kb->scores[i];
+ training_tmp.push_back(p);
+ loss_diffs.push_back(p.loss_diff);
+ }
+ else if (!conservative) {
+ // i=hope, j=fear
+ p.model_score_diff = kb->model_scores[i] - kb->model_scores[j];
+ p.loss_diff = kb->scores[i] - kb->scores[j];
+ training_tmp.push_back(p);
+ loss_diffs.push_back(p.loss_diff);
+ }
+ }
+ }
+
+ if (training_tmp.size() > 0) {
+ double threshold;
+ std::sort(loss_diffs.begin(), loss_diffs.end());
+ std::reverse(loss_diffs.begin(), loss_diffs.end());
+ threshold = loss_diffs.size() >= n_pairs ? loss_diffs[n_pairs-1] : loss_diffs[loss_diffs.size()-1];
+ cerr << "threshold: " << threshold << endl;
+ size_t constraints = 0;
+ for (size_t i = 0; (i < training_tmp.size() && constraints < n_pairs); ++i) {
+ if (training_tmp[i].loss_diff >= threshold) {
+ training.push_back(training_tmp[i]);
+ constraints++;
+ }
+ }
+ }
+ else {
+ cerr << "No pairs selected." << endl;
+ }
+}
+
+void
+sample_rand( KBestList* kb, TrainingInstances &training )
+{
+ srand( time(NULL) );
+ for ( size_t i = 0; i < kb->GetSize()-1; i++ ) {
+ for ( size_t j = i+1; j < kb->GetSize(); j++ ) {
+ if ( rand() % 2 ) {
+ TPair p;
+ p.first = kb->feats[i];
+ p.second = kb->feats[j];
+ p.first_rank = i;
+ p.second_rank = j;
+ p.first_score = kb->scores[i];
+ p.second_score = kb->scores[j];
+ training.push_back( p );
+ }
+ }
+ }
+}
+
+
+} // namespace
+
+
+#endif
+
generated by cgit v1.2.3 (git 2.39.1) at 2024-12-26 21:05:14 +0000