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- numpy._core.records.record
- numpy._core.records.recarray
- numpy.ma.mrecords.MaskedRecords
- numpy.matrixlib.defmatrix.matrix
- numpy.lib._index_tricks_impl.nd_grid
- numpy.lib._index_tricks_impl.MGridClass
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- numpy.ma.extras._fromnxfunction
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- numpy._core._internal.dummy_ctype
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  Function list name: All functions
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  - 1426
  - 1491
  - 948
  - 1332
  - 663
  - 1241
  - 1083
  - 604
  - 509
  numpy.lib.recfunctions._append_fields_dispatcher:
  - 659
  - 660
  numpy.lib.recfunctions._common_stride:
  - 930
  - 900
  - 932
  - 934
  - 906
  - 939
  - 910
  - 912
  - 914
  - 918
  - 919
  - 920
  - 922
  - 924
  numpy.lib.recfunctions._fix_defaults:
  - 356
  - 357
  - 350
  numpy.lib.recfunctions._fix_output:
  - 333
  - 337
  - 339
  - 340
  - 341
  - 343
  - 344
  - 345
  numpy.lib.recfunctions._get_fields_and_offsets:
  - 896
  - 880
  - 883
  - 885
  - 886
  - 888
  - 891
  - 892
  - 894
  - 863
  numpy.lib.recfunctions._get_fields_and_offsets.count_elem:
  - 874
  numpy.lib.recfunctions._get_fieldspec:
  - 96
  - 77
  - 103
  numpy.lib.recfunctions._izip_fields:
  - 293
  - 297
  - 298
  - 299
  - 300
  - 301
  - 303
  - 305
  numpy.lib.recfunctions._izip_fields_flat:
  - 289
  - 280
  - 285
  - 286
  - 287
  numpy.lib.recfunctions._izip_records:
  - 328
  - 329
  - 323
  - 309
  numpy.lib.recfunctions._keep_fields:
  - 576
  - 595
  - 596
  - 597
  numpy.lib.recfunctions._rec_append_fields_dispatcher:
  - 736
  - 735
  numpy.lib.recfunctions._zip_descr:
  - 218
  - 228
  numpy.lib.recfunctions._zip_dtype:
  - 203
  - 204
  - 205
  - 207
  - 209
  - 211
  - 213
  - 214
  numpy.lib.recfunctions.append_fields:
  - 666
  - 695
  - 696
  - 699
  - 703
  - 704
  - 705
  - 707
  - 709
  - 710
  - 711
  - 715
  - 716
  - 718
  - 719
  - 720
  - 723
  - 725
  - 726
  - 727
  - 728
  - 729
  - 731
  numpy.lib.recfunctions.apply_along_fields:
  - 1233
  - 1234
  - 1196
  - 1230
  numpy.lib.recfunctions.assign_fields_by_name:
  - 1267
  - 1271
  - 1272
  - 1273
  - 1243
  - 1276
  numpy.lib.recfunctions.drop_fields:
  - 548
  - 551
  - 568
  - 570
  - 571
  - 572
  - 511
  numpy.lib.recfunctions.drop_fields._drop_descr:
  - 556
  - 558
  - 560
  - 561
  - 562
  - 563
  - 565
  numpy.lib.recfunctions.find_duplicates:
  - 1472
  - 1475
  - 1479
  - 1456
  - 1458
  - 1428
  - 1461
  - 1462
  - 1466
  - 1468
  numpy.lib.recfunctions.flatten_descr:
  - 192
  - 194
  - 195
  - 197
  - 198
  - 175
  - 188
  numpy.lib.recfunctions.get_fieldstructure:
  - 258
  - 261
  - 263
  - 232
  - 264
  - 268
  - 270
  - 271
  - 272
  - 273
  numpy.lib.recfunctions.get_names:
  - 132
  - 134
  - 135
  - 137
  - 138
  - 109
  numpy.lib.recfunctions.get_names_flat:
  - 166
  - 167
  - 169
  - 170
  - 171
  - 142
  numpy.lib.recfunctions.join_by:
  - 1666
  - 1667
  - 1668
  - 1543
  - 1549
  - 1553
  - 1554
  - 1556
  - 1557
  - 1559
  - 1563
  - 1564
  - 1567
  - 1571
  - 1572
  - 1580
  - 1581
  - 1584
  - 1585
  - 1589
  - 1594
  - 1595
  - 1597
  - 1599
  - 1600
  - 1601
  - 1602
  - 1604
  - 1605
  - 1611
  - 1614
  - 1615
  - 1616
  - 1619
  - 1494
  - 1622
  - 1624
  - 1627
  - 1631
  - 1633
  - 1642
  - 1645
  - 1647
  - 1649
  - 1651
  - 1655
  - 1657
  - 1659
  - 1663
  numpy.lib.recfunctions.merge_arrays:
  - 418
  - 419
  - 421
  - 424
  - 425
  - 426
  - 428
  - 430
  - 431
  - 435
  - 439
  - 444
  - 446
  - 447
  - 449
  - 454
  - 455
  - 458
  - 459
  - 461
  - 462
  - 463
  - 464
  - 465
  - 468
  - 469
  - 474
  - 475
  - 477
  - 478
  - 479
  - 480
  - 481
  - 484
  - 486
  - 487
  - 488
  - 489
  - 490
  - 491
  - 493
  - 496
  - 497
  - 371
  - 499
  - 500
  numpy.lib.recfunctions.rec_append_fields:
  - 770
  - 741
  numpy.lib.recfunctions.rec_drop_fields:
  - 609
  - 606
  numpy.lib.recfunctions.rec_join:
  - 1680
  - 1690
  - 1688
  numpy.lib.recfunctions.recursive_fill_fields:
  - 64
  - 69
  - 70
  - 38
  - 72
  numpy.lib.recfunctions.rename_fields:
  - 618
  - 653
  - 654
  numpy.lib.recfunctions.rename_fields._recursive_rename_fields:
  - 643
  - 644
  - 646
  - 647
  - 648
  - 651
  numpy.lib.recfunctions.repack_fields:
  - 839
  - 840
  - 841
  - 843
  - 780
  - 847
  - 849
  - 850
  - 854
  - 857
  - 859
  - 860
  numpy.lib.recfunctions.require_fields:
  - 1322
  - 1323
  - 1284
  numpy.lib.recfunctions.stack_arrays:
  - 1409
  - 1410
  - 1412
  - 1414
  - 1415
  - 1417
  - 1335
  - 1374
  - 1376
  - 1378
  - 1379
  - 1384
  - 1386
  - 1387
  - 1388
  - 1389
  - 1390
  - 1392
  - 1394
  - 1395
  - 1396
  - 1400
  - 1401
  - 1404
  - 1405
  - 1407
  numpy.lib.recfunctions.structured_to_unstructured:
  - 1025
  - 1031
  - 1035
  - 1040
  - 1041
  - 1044
  - 1045
  - 1048
  - 1049
  - 1051
  - 1052
  - 1053
  - 1059
  - 1061
  - 1063
  - 1067
  - 1071
  - 1073
  - 1076
  - 950
  - 1008
  - 1011
  - 1012
  - 1013
  - 1015
  - 1019
  - 1020
  - 1022
  - 1023
  numpy.lib.recfunctions.unstructured_to_structured:
  - 1152
  - 1154
  - 1157
  - 1159
  - 1160
  - 1163
  - 1165
  - 1169
  - 1172
  - 1177
  - 1179
  - 1182
  - 1186
  - 1189
  - 1086
  - 1140
  - 1143
  - 1147
  - 1148
  - 1149
  - 1150
  - 1151
  numpy.linalg:
  - 1
  - 91
  - 94
  numpy.linalg._linalg:
  - 1
  - 3459
  - 2443
  - 3472
  - 3096
  - 3356
  - 422
  - 937
  - 3635
  - 3192
  - 320
  - 65
  - 1345
  - 1858
  - 2624
  - 2377
  - 2893
  - 3277
  - 3535
  - 1240
  - 859
  - 1502
  - 746
  - 237
  - 2286
  - 623
  - 499
  - 2163
  - 1141
  - 2037
  - 3446
  - 1912
  - 1659
  numpy.linalg._linalg.LinAlgError:
  - 75
  numpy.linalg._linalg._assert_2d:
  - 187
  - 188
  numpy.linalg._linalg._assert_finite:
  - 205
  - 206
  numpy.linalg._linalg._assert_stacked_2d:
  - 193
  - 194
  numpy.linalg._linalg._assert_stacked_square:
  - 201
  - 199
  numpy.linalg._linalg._commonType:
  - 160
  - 166
  - 152
  - 154
  - 155
  - 157
  - 158
  numpy.linalg._linalg._complexType:
  - 146
  numpy.linalg._linalg._convertarray:
  - 1337
  - 1338
  numpy.linalg._linalg._is_empty_2d:
  - 211
  numpy.linalg._linalg._makearray:
  - 124
  - 125
  numpy.linalg._linalg._multi_dot:
  - 3086
  - 3085
  - 3078
  - 3079
  numpy.linalg._linalg._multi_dot_matrix_chain_order:
  - 3053
  - 3059
  - 3062
  - 3064
  - 3065
  - 3068
  - 3037
  - 3070
  numpy.linalg._linalg._multi_dot_three:
  - 3016
  - 3033
  - 3030
  - 3031
  numpy.linalg._linalg._multi_svd_norm:
  - 2616
  - 2593
  - 2615
  numpy.linalg._linalg._multidot_dispatcher:
  - 2889
  - 2890
  numpy.linalg._linalg._realType:
  - 143
  numpy.linalg._linalg._to_native_byte_order:
  - 175
  - 176
  - 177
  - 179
  - 180
  numpy.linalg._linalg.cholesky:
  - 841
  - 842
  - 843
  - 748
  - 844
  - 845
  - 846
  - 848
  - 849
  numpy.linalg._linalg.cond:
  - 1994
  - 1995
  - 1997
  - 1998
  - 1999
  - 2000
  - 2007
  - 2008
  - 2009
  - 2010
  - 2011
  - 2012
  - 2013
  - 2014
  - 2017
  - 2018
  - 2019
  - 2020
  - 2021
  - 2023
  - 2027
  - 1914
  numpy.linalg._linalg.cross:
  - 3337
  - 3338
  - 3340
  - 3279
  - 3347
  numpy.linalg._linalg.det:
  - 2432
  - 2433
  - 2379
  - 2427
  - 2428
  - 2429
  - 2430
  - 2431
  numpy.linalg._linalg.diagonal:
  - 3098
  - 3183
  numpy.linalg._linalg.eig:
  - 1347
  - 1479
  - 1480
  - 1481
  - 1482
  - 1483
  - 1485
  - 1486
  - 1489
  - 1491
  - 1494
  - 1496
  - 1498
  - 1499
  numpy.linalg._linalg.eigh:
  - 1504
  - 1633
  - 1634
  - 1635
  - 1636
  - 1638
  - 1643
  - 1644
  - 1647
  - 1648
  - 1649
  - 1650
  - 1629
  - 1630
  numpy.linalg._linalg.eigvals:
  - 1216
  - 1217
  - 1218
  - 1220
  - 1221
  - 1224
  - 1226
  - 1227
  - 1229
  - 1231
  - 1233
  - 1143
  - 1214
  - 1215
  numpy.linalg._linalg.eigvalsh:
  - 1316
  - 1317
  - 1320
  - 1325
  - 1326
  - 1327
  - 1328
  - 1329
  - 1330
  - 1333
  - 1334
  - 1242
  numpy.linalg._linalg.inv:
  - 608
  - 609
  - 610
  - 612
  - 613
  - 615
  - 616
  - 501
  - 607
  numpy.linalg._linalg.isComplexType:
  - 129
  numpy.linalg._linalg.lstsq:
  - 2561
  - 2563
  - 2565
  - 2567
  - 2569
  - 2445
  - 2575
  - 2576
  - 2581
  - 2582
  - 2585
  - 2586
  - 2588
  - 2589
  - 2540
  - 2541
  - 2543
  - 2545
  - 2548
  - 2551
  - 2552
  - 2554
  - 2555
  - 2557
  - 2558
  numpy.linalg._linalg.matmul:
  - 3437
  - 3358
  numpy.linalg._linalg.matrix_norm:
  - 3474
  - 3526
  - 3527
  numpy.linalg._linalg.matrix_power:
  - 689
  - 690
  - 691
  - 694
  - 700
  - 702
  - 708
  - 709
  - 710
  - 713
  - 714
  - 715
  - 718
  - 721
  - 722
  - 724
  - 725
  - 732
  - 733
  - 734
  - 735
  - 625
  numpy.linalg._linalg.matrix_rank:
  - 2145
  - 2146
  - 2147
  - 2149
  - 2150
  - 2152
  - 2154
  - 2039
  - 2137
  - 2140
  - 2141
  - 2142
  - 2143
  numpy.linalg._linalg.matrix_transpose:
  - 3461
  numpy.linalg._linalg.multi_dot:
  - 3009
  - 3010
  - 2980
  - 2982
  - 2984
  - 2985
  - 2987
  - 2895
  - 2993
  - 2994
  - 2995
  - 2996
  - 2997
  - 3000
  - 3001
  - 3003
  - 3004
  - 3007
  numpy.linalg._linalg.norm:
  - 2816
  - 2817
  - 2818
  - 2819
  - 2820
  - 2823
  - 2827
  - 2829
  - 2830
  - 2832
  - 2833
  - 2836
  - 2839
  - 2841
  - 2842
  - 2844
  - 2846
  - 2847
  - 2848
  - 2850
  - 2851
  - 2852
  - 2853
  - 2854
  - 2855
  - 2857
  - 2858
  - 2859
  - 2861
  - 2862
  - 2863
  - 2865
  - 2866
  - 2867
  - 2869
  - 2870
  - 2871
  - 2872
  - 2873
  - 2876
  - 2877
  - 2880
  - 2626
  - 2777
  - 2779
  - 2780
  - 2783
  - 2785
  - 2790
  - 2791
  - 2794
  - 2796
  - 2797
  - 2798
  - 2799
  - 2804
  - 2805
  - 2806
  - 2808
  - 2815
  numpy.linalg._linalg.outer:
  - 920
  - 921
  - 922
  - 861
  - 927
  numpy.linalg._linalg.pinv:
  - 2274
  - 2276
  - 2279
  - 2280
  - 2251
  - 2252
  - 2253
  - 2255
  - 2256
  - 2259
  - 2165
  - 2265
  - 2266
  - 2268
  - 2269
  - 2270
  - 2271
  numpy.linalg._linalg.qr:
  - 939
  - 1071
  - 1072
  - 1074
  - 1077
  - 1079
  - 1082
  - 1087
  - 1088
  - 1090
  - 1091
  - 1092
  - 1093
  - 1095
  - 1096
  - 1098
  - 1101
  - 1102
  - 1103
  - 1104
  - 1106
  - 1107
  - 1108
  - 1109
  - 1110
  - 1112
  - 1113
  - 1114
  - 1120
  - 1127
  - 1128
  - 1130
  - 1131
  - 1133
  - 1134
  - 1136
  numpy.linalg._linalg.slogdet:
  - 2368
  - 2369
  - 2370
  - 2371
  - 2372
  - 2373
  - 2374
  - 2288
  - 2365
  - 2366
  - 2367
  numpy.linalg._linalg.solve:
  - 322
  - 397
  - 398
  - 399
  - 400
  - 401
  - 405
  - 410
  - 411
  - 413
  - 415
  numpy.linalg._linalg.svd:
  - 1803
  - 1805
  - 1809
  - 1810
  - 1811
  - 1812
  - 1813
  - 1814
  - 1815
  - 1816
  - 1818
  - 1819
  - 1821
  - 1822
  - 1823
  - 1825
  - 1826
  - 1829
  - 1830
  - 1835
  - 1836
  - 1839
  - 1840
  - 1841
  - 1842
  - 1843
  - 1845
  - 1846
  - 1849
  - 1850
  - 1661
  numpy.linalg._linalg.svdvals:
  - 1905
  - 1860
  numpy.linalg._linalg.tensordot:
  - 3448
  numpy.linalg._linalg.tensorinv:
  - 482
  - 484
  - 424
  - 488
  - 489
  - 490
  - 479
  numpy.linalg._linalg.tensorsolve:
  - 288
  - 291
  - 292
  - 293
  - 294
  - 295
  - 296
  - 300
  - 239
  - 303
  - 309
  - 310
  - 311
  - 287
  numpy.linalg._linalg.trace:
  - 3194
  - 3268
  numpy.linalg._linalg.transpose:
  - 229
  - 215
  numpy.linalg._linalg.vecdot:
  - 3681
  - 3637
  numpy.linalg._linalg.vector_norm:
  - 3617
  - 3620
  - 3621
  - 3623
  - 3593
  - 3594
  - 3595
  - 3625
  - 3597
  - 3599
  - 3537
  - 3602
  - 3603
  - 3605
  - 3607
  - 3615
  numpy.linalg.linalg.__getattr__:
  - 8
  - 4
  - 5
  numpy.ma:
  - 1
  - 53
  numpy.ma.core:
  - 1
  - 7183
  - 7184
  - 8237
  - 8255
  - 8783
  - 80
  - 8785
  - 8789
  - 8791
  - 8795
  - 8797
  - 8801
  - 8806
  - 8811
  - 8816
  - 8818
  - 8822
  - 8824
  - 8828
  - 8830
  - 8834
  - 8839
  - 8841
  - 8845
  - 8847
  - 8851
  - 180
  - 182
  - 183
  - 6839
  - 191
  - 192
  - 194
  - 195
  - 197
  - 198
  - 200
  - 201
  - 203
  - 1235
  - 212
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  - 1236
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  - 216
  - 217
  - 1238
  - 1239
  - 1240
  - 1241
  - 1242
  - 1243
  - 1244
  - 1245
  - 1246
  - 1247
  - 1248
  - 1249
  - 1250
  - 1251
  - 1254
  - 1255
  - 1256
  - 1257
  - 1258
  - 1259
  - 1260
  - 1261
  - 1262
  - 1263
  - 1264
  - 1265
  - 1266
  - 1267
  - 1268
  - 1269
  - 1270
  - 1271
  - 1274
  - 1275
  - 1276
  - 1277
  - 1278
  - 1280
  - 1282
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  - 1286
  - 1288
  - 1290
  - 1291
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  - 1294
  - 1295
  - 1296
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  - 1301
  - 1302
  - 1303
  - 1304
  - 1305
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  - 1307
  - 1308
  - 1309
  - 7069
  - 7070
  - 7071
  - 7072
  - 7073
  - 7074
  - 7075
  - 7076
  - 7077
  - 7078
  - 7079
  - 7080
  - 7081
  - 7082
  - 2475
  - 7083
  - 7084
  - 7085
  - 7086
  - 7087
  - 7088
  - 7089
  - 7090
  - 7091
  - 7093
  - 7094
  - 7096
  - 2496
  - 2497
  - 2504
  - 2512
  - 2517
  numpy.ma.core.MAError:
  - 147
  numpy.ma.core.MaskError:
  - 155
  numpy.ma.core.MaskedArray:
  - 6240
  - 6241
  - 6242
  - 6243
  - 6244
  - 2757
  - 6245
  - 6246
  - 3407
  - 3773
  - 3774
  - 6239
  numpy.ma.core.MaskedArray.<lambda1>:
  - 6245
  numpy.ma.core.MaskedArray.__add__:
  - 4306
  - 4308
  - 4302
  numpy.ma.core.MaskedArray.__array_finalize__:
  - 3040
  - 3073
  - 3107
  - 3076
  - 3077
  - 3045
  - 3079
  - 3110
  - 3130
  - 3116
  - 3088
  - 3127
  - 3126
  - 3095
  - 3128
  - 3098
  - 3100
  - 3102
  numpy.ma.core.MaskedArray.__array_wrap__:
  - 3170
  - 3139
  - 3173
  - 3142
  - 3143
  - 3145
  - 3146
  - 3180
  - 3150
  - 3152
  - 3153
  - 3155
  - 3156
  - 3158
  - 3133
  numpy.ma.core.MaskedArray.__deepcopy__:
  - 6504
  - 6505
  - 6507
  - 6508
  - 6509
  - 6514
  - 6515
  numpy.ma.core.MaskedArray.__div__:
  - 4355
  - 4357
  - 4351
  numpy.ma.core.MaskedArray.__eq__:
  - 4273
  - 4263
  numpy.ma.core.MaskedArray.__float__:
  - 4545
  - 4546
  - 4548
  - 4538
  - 4542
  numpy.ma.core.MaskedArray.__floordiv__:
  - 4376
  - 4380
  - 4382
  numpy.ma.core.MaskedArray.__ge__:
  - 4296
  numpy.ma.core.MaskedArray.__getitem__:
  - 3328
  - 3332
  - 3335
  - 3337
  - 3341
  - 3344
  - 3345
  - 3348
  - 3349
  - 3355
  - 3361
  - 3363
  - 3365
  - 3366
  - 3371
  - 3381
  - 3382
  - 3384
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  - 580
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  - 706
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  - 713
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  - 745
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  - 82
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  numpy.ma.testutils.approx:
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  numpy.ma.testutils.assert_almost_equal:
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  - 260
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  - 241
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  - 439
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  - 87
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  - 91
  - 92
  - 99
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  - 107
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  - 112
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  - 141
  - 147
  - 123
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  - 151
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  - 157
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  - 163
  - 167
  - 174
  - 175
  - 176
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  - 201
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  - 224
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  - 228
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  - 231
  - 214
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  - 257
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  - 260
  - 263
  - 265
  - 267
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  - 271
  - 273
  - 275
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  - 238
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  - 243
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  - 304
  - 305
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  - 312
  - 316
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  - 333
  - 336
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  - 366
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  - 369
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  - 372
  - 373
  - 374
  - 343
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  - 345
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  - 424
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  - 232
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  numpy.polynomial.chebyshev.Chebyshev:
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  - 2077
  - 2079
  numpy.polynomial.chebyshev.Chebyshev.interpolate.<lambda1>:
  - 2079
  numpy.polynomial.chebyshev._cseries_to_zseries:
  - 153
  - 134
  numpy.polynomial.chebyshev._zseries_der:
  - 302
  - 303
  - 304
  - 305
  - 278
  numpy.polynomial.chebyshev._zseries_div:
  - 256
  - 273
  - 211
  - 244
  - 245
  - 246
  - 243
  - 250
  - 247
  numpy.polynomial.chebyshev._zseries_int:
  - 333
  - 334
  - 335
  - 336
  - 310
  numpy.polynomial.chebyshev._zseries_mul:
  - 184
  - 207
  numpy.polynomial.chebyshev._zseries_to_cseries:
  - 178
  - 159
  numpy.polynomial.chebyshev.cheb2poly:
  - 451
  - 453
  - 454
  - 455
  - 398
  - 443
  - 444
  - 445
  numpy.polynomial.chebyshev.chebadd:
  - 608
  - 570
  numpy.polynomial.chebyshev.chebcompanion:
  - 1705
  - 1706
  - 1708
  - 1709
  - 1679
  - 1711
  - 1712
  - 1713
  - 1714
  - 1715
  - 1716
  numpy.polynomial.chebyshev.chebder:
  - 960
  - 963
  - 967
  - 939
  - 940
  - 941
  - 942
  - 943
  - 880
  - 944
  - 946
  - 948
  - 951
  - 952
  - 953
  - 956
  - 959
  numpy.polynomial.chebyshev.chebdiv:
  - 801
  - 802
  - 806
  - 807
  - 808
  - 810
  - 813
  - 814
  - 815
  - 816
  - 817
  - 755
  numpy.polynomial.chebyshev.chebfit:
  - 1552
  - 1675
  numpy.polynomial.chebyshev.chebfromroots:
  - 515
  - 566
  numpy.polynomial.chebyshev.chebgauss:
  - 1890
  - 1891
  - 1852
  - 1886
  - 1887
  numpy.polynomial.chebyshev.chebgrid2d:
  - 1232
  - 1281
  numpy.polynomial.chebyshev.chebgrid3d:
  - 1336
  - 1388
  numpy.polynomial.chebyshev.chebint:
  - 1056
  - 1057
  - 1058
  - 1059
  - 1061
  - 1062
  - 1063
  - 1065
  - 1067
  - 1069
  - 1071
  - 1073
  - 1076
  - 1077
  - 1078
  - 1079
  - 1081
  - 1084
  - 1087
  - 1089
  - 1092
  - 1094
  - 972
  numpy.polynomial.chebyshev.chebinterpolate:
  - 1832
  - 1835
  - 1837
  - 1841
  - 1842
  - 1843
  - 1844
  - 1785
  numpy.polynomial.chebyshev.chebline:
  - 509
  - 508
  - 477
  - 511
  numpy.polynomial.chebyshev.chebmul:
  - 706
  - 746
  - 747
  - 748
  - 749
  - 750
  - 751
  numpy.polynomial.chebyshev.chebmulx:
  - 656
  - 690
  - 692
  - 695
  - 698
  numpy.polynomial.chebyshev.chebpow:
  - 865
  - 866
  - 867
  - 872
  - 874
  - 875
  - 876
  - 822
  - 859
  - 860
  - 861
  - 863
  numpy.polynomial.chebyshev.chebpts1:
  - 1952
  - 1954
  - 1957
  - 1925
  - 1958
  - 1951
  numpy.polynomial.chebyshev.chebpts2:
  - 1985
  - 1986
  - 1988
  - 1991
  - 1992
  - 1962
  numpy.polynomial.chebyshev.chebroots:
  - 1771
  - 1772
  - 1773
  - 1774
  - 1775
  - 1778
  - 1779
  - 1780
  - 1724
  numpy.polynomial.chebyshev.chebsub:
  - 652
  - 612
  numpy.polynomial.chebyshev.chebval:
  - 1157
  - 1158
  - 1159
  - 1160
  - 1161
  - 1162
  - 1099
  - 1163
  - 1165
  - 1168
  - 1175
  numpy.polynomial.chebyshev.chebval2d:
  - 1228
  - 1183
  numpy.polynomial.chebyshev.chebval3d:
  - 1332
  - 1285
  numpy.polynomial.chebyshev.chebvander:
  - 1441
  - 1392
  - 1426
  - 1427
  - 1430
  - 1433
  - 1436
  - 1439
  numpy.polynomial.chebyshev.chebvander2d:
  - 1445
  - 1494
  numpy.polynomial.chebyshev.chebvander3d:
  - 1498
  - 1548
  numpy.polynomial.chebyshev.chebweight:
  - 1920
  - 1897
  numpy.polynomial.chebyshev.poly2cheb:
  - 389
  - 390
  - 392
  - 393
  - 348
  numpy.polynomial.hermite:
  - 1
  - 206
  - 209
  - 212
  - 215
  numpy.polynomial.hermite.Hermite:
  - 1792
  - 1783
  - 1777
  - 1778
  - 1779
  - 1780
  - 1749
  - 1781
  - 1782
  - 1784
  - 1785
  - 1786
  - 1787
  - 1788
  - 1791
  numpy.polynomial.hermite._normed_hermite_n:
  - 1632
  - 1593
  - 1621
  - 1622
  - 1625
  - 1626
  - 1627
  - 1629
  - 1630
  numpy.polynomial.hermite.herm2poly:
  - 193
  - 195
  - 196
  - 197
  - 143
  - 182
  - 183
  - 184
  - 186
  numpy.polynomial.hermite.hermadd:
  - 315
  - 351
  numpy.polynomial.hermite.hermcompanion:
  - 1477
  - 1510
  - 1511
  - 1513
  - 1514
  - 1516
  - 1517
  - 1518
  - 1519
  - 1520
  - 1521
  - 1522
  numpy.polynomial.hermite.hermder:
  - 673
  - 674
  - 677
  - 653
  - 654
  - 655
  - 656
  - 657
  - 658
  - 660
  - 662
  - 599
  - 665
  - 666
  - 667
  - 670
  numpy.polynomial.hermite.hermdiv:
  - 514
  - 558
  numpy.polynomial.hermite.hermfit:
  - 1473
  - 1343
  numpy.polynomial.hermite.hermfromroots:
  - 259
  - 311
  numpy.polynomial.hermite.hermgauss:
  - 1636
  - 1703
  - 1677
  - 1678
  - 1683
  - 1684
  - 1685
  - 1688
  - 1689
  - 1694
  - 1695
  numpy.polynomial.hermite.hermgrid2d:
  - 1018
  - 958
  numpy.polynomial.hermite.hermgrid3d:
  - 1083
  - 1148
  numpy.polynomial.hermite.hermint:
  - 769
  - 770
  - 771
  - 773
  - 775
  - 777
  - 779
  - 781
  - 784
  - 785
  - 786
  - 787
  - 789
  - 792
  - 795
  - 797
  - 799
  - 682
  - 764
  - 765
  - 766
  - 767
  numpy.polynomial.hermite.hermline:
  - 219
  - 252
  - 253
  - 255
  numpy.polynomial.hermite.hermmul:
  - 448
  - 486
  - 488
  - 495
  - 498
  - 502
  - 505
  - 508
  - 509
  - 510
  numpy.polynomial.hermite.hermmulx:
  - 395
  - 433
  - 435
  - 438
  - 441
  numpy.polynomial.hermite.hermpow:
  - 562
  - 595
  numpy.polynomial.hermite.hermroots:
  - 1579
  - 1580
  - 1581
  - 1582
  - 1583
  - 1586
  - 1587
  - 1588
  - 1529
  numpy.polynomial.hermite.hermsub:
  - 355
  - 391
  numpy.polynomial.hermite.hermval:
  - 804
  - 872
  - 873
  - 874
  - 875
  - 876
  - 877
  - 878
  - 881
  - 884
  - 888
  - 891
  numpy.polynomial.hermite.hermval2d:
  - 954
  - 900
  numpy.polynomial.hermite.hermval3d:
  - 1022
  - 1079
  numpy.polynomial.hermite.hermvander:
  - 1152
  - 1196
  - 1197
  - 1200
  - 1203
  - 1205
  - 1208
  - 1210
  numpy.polynomial.hermite.hermvander2d:
  - 1274
  - 1214
  numpy.polynomial.hermite.hermvander3d:
  - 1339
  - 1278
  numpy.polynomial.hermite.hermweight:
  - 1740
  - 1709
  numpy.polynomial.hermite.poly2herm:
  - 97
  - 134
  - 135
  - 137
  - 138
  numpy.polynomial.hermite_e:
  - 1
  - 207
  - 210
  - 213
  - 216
  numpy.polynomial.hermite_e.HermiteE:
  - 1696
  - 1692
  - 1697
  - 1698
  - 1701
  - 1702
  - 1687
  - 1688
  - 1689
  - 1690
  - 1659
  - 1691
  - 1693
  - 1694
  - 1695
  numpy.polynomial.hermite_e._normed_hermite_e_n:
  - 1546
  - 1547
  - 1518
  - 1551
  - 1550
  - 1552
  - 1554
  - 1555
  numpy.polynomial.hermite_e.herme2poly:
  - 194
  - 196
  - 197
  - 198
  - 145
  - 184
  - 185
  - 186
  - 188
  numpy.polynomial.hermite_e.hermeadd:
  - 315
  - 351
  numpy.polynomial.hermite_e.hermecompanion:
  - 1408
  - 1441
  - 1442
  - 1443
  - 1444
  - 1445
  - 1446
  - 1447
  - 1435
  - 1436
  - 1438
  - 1439
  numpy.polynomial.hermite_e.hermeder:
  - 672
  - 675
  - 651
  - 652
  - 653
  - 654
  - 655
  - 656
  - 658
  - 660
  - 597
  - 663
  - 664
  - 665
  - 668
  - 671
  numpy.polynomial.hermite_e.hermediv:
  - 514
  - 556
  numpy.polynomial.hermite_e.hermefit:
  - 1274
  - 1404
  numpy.polynomial.hermite_e.hermefromroots:
  - 259
  - 311
  numpy.polynomial.hermite_e.hermegauss:
  - 1602
  - 1603
  - 1604
  - 1607
  - 1608
  - 1613
  - 1614
  - 1622
  - 1561
  - 1596
  - 1597
  numpy.polynomial.hermite_e.hermegrid2d:
  - 946
  - 995
  numpy.polynomial.hermite_e.hermegrid3d:
  - 1050
  - 1102
  numpy.polynomial.hermite_e.hermeint:
  - 768
  - 769
  - 771
  - 773
  - 775
  - 777
  - 779
  - 782
  - 783
  - 784
  - 785
  - 787
  - 790
  - 793
  - 795
  - 797
  - 680
  - 762
  - 763
  - 764
  - 765
  - 767
  numpy.polynomial.hermite_e.hermeline:
  - 253
  - 220
  - 252
  - 255
  numpy.polynomial.hermite_e.hermemul:
  - 448
  - 486
  - 488
  - 495
  - 498
  - 502
  - 505
  - 508
  - 509
  - 510
  numpy.polynomial.hermite_e.hermemulx:
  - 395
  - 433
  - 435
  - 438
  - 441
  numpy.polynomial.hermite_e.hermepow:
  - 560
  - 593
  numpy.polynomial.hermite_e.hermeroots:
  - 1504
  - 1505
  - 1506
  - 1507
  - 1508
  - 1511
  - 1512
  - 1513
  - 1454
  numpy.polynomial.hermite_e.hermesub:
  - 355
  - 391
  numpy.polynomial.hermite_e.hermeval:
  - 802
  - 870
  - 871
  - 872
  - 873
  - 874
  - 875
  - 876
  - 878
  - 881
  - 885
  - 888
  numpy.polynomial.hermite_e.hermeval2d:
  - 897
  - 942
  numpy.polynomial.hermite_e.hermeval3d:
  - 1046
  - 999
  numpy.polynomial.hermite_e.hermevander:
  - 1154
  - 1157
  - 1159
  - 1161
  - 1163
  - 1106
  - 1150
  - 1151
  numpy.polynomial.hermite_e.hermevander2d:
  - 1216
  - 1167
  numpy.polynomial.hermite_e.hermevander3d:
  - 1220
  - 1270
  numpy.polynomial.hermite_e.hermeweight:
  - 1650
  - 1628
  numpy.polynomial.hermite_e.poly2herme:
  - 98
  - 136
  - 137
  - 139
  - 140
  numpy.polynomial.laguerre:
  - 1
  - 203
  - 206
  - 209
  - 212
  numpy.polynomial.laguerre.Laguerre:
  - 1719
  - 1710
  - 1711
  - 1712
  - 1713
  - 1682
  - 1714
  - 1715
  - 1716
  - 1717
  - 1718
  - 1720
  - 1721
  - 1724
  - 1725
  numpy.polynomial.laguerre.lag2poly:
  - 192
  - 193
  - 194
  - 143
  - 182
  - 183
  - 184
  - 190
  numpy.polynomial.laguerre.lagadd:
  - 346
  - 310
  numpy.polynomial.laguerre.lagcompanion:
  - 1504
  - 1492
  - 1460
  - 1493
  - 1495
  - 1496
  - 1498
  - 1499
  - 1500
  - 1501
  - 1502
  - 1503
  numpy.polynomial.laguerre.lagder:
  - 674
  - 647
  - 648
  - 649
  - 651
  - 652
  - 653
  - 655
  - 593
  - 657
  - 660
  - 661
  - 662
  - 665
  - 668
  - 669
  numpy.polynomial.laguerre.lagdiv:
  - 552
  - 510
  numpy.polynomial.laguerre.lagfit:
  - 1456
  - 1326
  numpy.polynomial.laguerre.lagfromroots:
  - 306
  - 254
  numpy.polynomial.laguerre.laggauss:
  - 1633
  - 1634
  - 1635
  - 1575
  - 1639
  - 1616
  - 1617
  - 1622
  - 1623
  - 1624
  - 1627
  - 1628
  numpy.polynomial.laguerre.laggrid2d:
  - 953
  - 1010
  numpy.polynomial.laguerre.laggrid3d:
  - 1072
  - 1134
  numpy.polynomial.laguerre.lagint:
  - 768
  - 769
  - 771
  - 773
  - 775
  - 777
  - 779
  - 782
  - 783
  - 784
  - 785
  - 787
  - 790
  - 793
  - 796
  - 798
  - 679
  - 762
  - 763
  - 764
  - 765
  - 767
  numpy.polynomial.laguerre.lagline:
  - 216
  - 248
  - 250
  - 247
  numpy.polynomial.laguerre.lagmul:
  - 482
  - 484
  - 491
  - 494
  - 498
  - 501
  - 504
  - 505
  - 506
  - 444
  numpy.polynomial.laguerre.lagmulx:
  - 390
  - 428
  - 430
  - 433
  - 436
  numpy.polynomial.laguerre.lagpow:
  - 556
  - 589
  numpy.polynomial.laguerre.lagroots:
  - 1568
  - 1569
  - 1570
  - 1511
  - 1561
  - 1562
  - 1563
  - 1564
  - 1565
  numpy.polynomial.laguerre.lagsub:
  - 386
  - 350
  numpy.polynomial.laguerre.lagval:
  - 803
  - 871
  - 872
  - 873
  - 874
  - 875
  - 876
  - 877
  - 879
  - 882
  - 886
  - 889
  numpy.polynomial.laguerre.lagval2d:
  - 898
  - 949
  numpy.polynomial.laguerre.lagval3d:
  - 1068
  - 1014
  numpy.polynomial.laguerre.lagvander:
  - 1186
  - 1189
  - 1191
  - 1193
  - 1195
  - 1138
  - 1182
  - 1183
  numpy.polynomial.laguerre.lagvander2d:
  - 1257
  - 1199
  numpy.polynomial.laguerre.lagvander3d:
  - 1322
  - 1261
  numpy.polynomial.laguerre.lagweight:
  - 1674
  - 1645
  numpy.polynomial.laguerre.poly2lag:
  - 97
  - 137
  - 138
  - 135
  numpy.polynomial.legendre:
  - 1
  - 226
  - 217
  - 220
  - 223
  numpy.polynomial.legendre.Legendre:
  - 1664
  - 1665
  - 1655
  - 1650
  - 1651
  - 1652
  - 1653
  - 1622
  - 1654
  - 1656
  - 1657
  - 1658
  - 1659
  - 1660
  - 1661
  numpy.polynomial.legendre.leg2poly:
  - 196
  - 197
  - 198
  - 204
  - 206
  - 207
  - 208
  - 150
  numpy.polynomial.legendre.legadd:
  - 363
  - 325
  numpy.polynomial.legendre.legcompanion:
  - 1444
  - 1445
  - 1447
  - 1448
  - 1418
  - 1450
  - 1451
  - 1452
  - 1453
  - 1454
  - 1455
  numpy.polynomial.legendre.legder:
  - 674
  - 675
  - 676
  - 677
  - 678
  - 615
  - 679
  - 681
  - 683
  - 686
  - 687
  - 688
  - 691
  - 694
  - 695
  - 698
  - 702
  numpy.polynomial.legendre.legdiv:
  - 580
  - 535
  numpy.polynomial.legendre.legfit:
  - 1289
  - 1414
  numpy.polynomial.legendre.legfromroots:
  - 321
  - 270
  numpy.polynomial.legendre.leggauss:
  - 1569
  - 1570
  - 1575
  - 1576
  - 1577
  - 1585
  - 1523
  - 1558
  - 1559
  - 1564
  - 1565
  - 1566
  numpy.polynomial.legendre.leggrid2d:
  - 969
  - 1018
  numpy.polynomial.legendre.leggrid3d:
  - 1073
  - 1125
  numpy.polynomial.legendre.legint:
  - 791
  - 792
  - 793
  - 794
  - 796
  - 797
  - 798
  - 800
  - 802
  - 804
  - 806
  - 808
  - 811
  - 812
  - 813
  - 814
  - 816
  - 819
  - 822
  - 824
  - 828
  - 830
  - 707
  numpy.polynomial.legendre.legline:
  - 264
  - 266
  - 230
  - 263
  numpy.polynomial.legendre.legmul:
  - 516
  - 519
  - 523
  - 526
  - 529
  - 530
  - 467
  - 531
  - 507
  - 509
  numpy.polynomial.legendre.legmulx:
  - 449
  - 451
  - 454
  - 457
  - 411
  numpy.polynomial.legendre.legpow:
  - 584
  - 611
  numpy.polynomial.legendre.legroots:
  - 1509
  - 1510
  - 1511
  - 1512
  - 1513
  - 1516
  - 1517
  - 1518
  - 1462
  numpy.polynomial.legendre.legsub:
  - 407
  - 367
  numpy.polynomial.legendre.legval:
  - 896
  - 897
  - 898
  - 835
  - 899
  - 901
  - 904
  - 908
  - 911
  - 893
  - 894
  - 895
  numpy.polynomial.legendre.legval2d:
  - 920
  - 965
  numpy.polynomial.legendre.legval3d:
  - 1069
  - 1022
  numpy.polynomial.legendre.legvander:
  - 1129
  - 1163
  - 1164
  - 1167
  - 1170
  - 1174
  - 1176
  - 1178
  numpy.polynomial.legendre.legvander2d:
  - 1182
  - 1231
  numpy.polynomial.legendre.legvander3d:
  - 1235
  - 1285
  numpy.polynomial.legendre.legweight:
  - 1591
  numpy.polynomial.legendre.poly2leg:
  - 101
  - 141
  - 142
  - 144
  - 145
  numpy.polynomial.polynomial:
  - 1
  - 98
  - 101
  - 104
  - 107
  numpy.polynomial.polynomial.Polynomial:
  - 1632
  - 1633
  - 1634
  - 1627
  - 1637
  - 1638
  - 1623
  - 1624
  - 1625
  - 1626
  - 1595
  - 1628
  - 1629
  - 1630
  - 1631
  numpy.polynomial.polynomial.Polynomial._repr_latex_term:
  - 1657
  - 1659
  - 1661
  numpy.polynomial.polynomial.Polynomial._str_term_ascii:
  - 1650
  numpy.polynomial.polynomial.Polynomial._str_term_unicode:
  - 1643
  - 1646
  numpy.polynomial.polynomial.polyadd:
  - 217
  - 249
  numpy.polynomial.polynomial.polycompanion:
  - 1480
  - 1513
  - 1514
  - 1516
  - 1517
  - 1519
  - 1520
  - 1521
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  numpy.testing.print_coercion_tables.GenericObject:
  - 20
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  - 24
  - 25
  - 26
  - 27
  - 28
  - 29
  - 30
  numpy.testing.print_coercion_tables.print_coercion_table:
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  numpy.testing.print_coercion_tables.print_new_cast_table:
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  - 113
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  - 124
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  numpy.testing.print_coercion_tables.print_new_cast_table.print_table:
  - 148
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  - 150
  - 151
  - 152
  - 153
  - 154
  - 155
  - 156
  - 157
  numpy.testing.print_coercion_tables.print_new_cast_table.sorter:
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  - 128
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  - 114
  - 117
  numpy.typing.mypy_plugin._NumpyPlugin:
  - 153
  numpy.typing.mypy_plugin._NumpyPlugin.get_additional_deps:
  - 168
  - 178
  - 179
  - 183
  - 184
  numpy.typing.mypy_plugin._NumpyPlugin.get_type_analyze_hook:
  - 161
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  numpy.typing.mypy_plugin._get_c_intp_name:
  - 98
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  - 101
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  numpy.typing.mypy_plugin._get_extended_precision_list:
  - 93
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  - 72
  - 73
  numpy.typing.mypy_plugin._hook:
  - 121
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  numpy.typing.mypy_plugin._index:
  - 130
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  numpy.typing.mypy_plugin._override_imports:
  - 144
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  - 142
  numpy.typing.mypy_plugin.plugin:
  - 196
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  - 2
  - 11
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  - 1
  - 28
  - 29
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  - 7
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  - 1
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  - 1
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  - 20
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  - 23
  opt_einsum.backends.cupy.evaluate_constants:
  - 32
  - 29
  opt_einsum.backends.cupy.to_cupy:
  - 13
  - 14
  opt_einsum.backends.dispatch:
  - 1
  opt_einsum.backends.dispatch._import_func:
  - 44
  - 45
  - 38
  opt_einsum.backends.dispatch.build_expression:
  - 144
  - 141
  opt_einsum.backends.dispatch.evaluate_constants:
  - 148
  - 151
  opt_einsum.backends.dispatch.get_func:
  - 81
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  opt_einsum.backends.dispatch.has_backend:
  - 155
  - 156
  opt_einsum.backends.dispatch.has_einsum:
  - 96
  - 91
  opt_einsum.backends.dispatch.has_tensordot:
  - 113
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  opt_einsum.backends.jax:
  - 1
  opt_einsum.backends.jax._get_jax_and_to_jax:
  - 12
  opt_einsum.backends.jax.build_expression:
  - 26
  - 27
  - 29
  opt_einsum.backends.jax.build_expression.jax_contract:
  - 34
  opt_einsum.backends.jax.evaluate_constants:
  - 40
  - 43
  - 45
  opt_einsum.backends.object_arrays:
  - 1
  opt_einsum.backends.object_arrays.object_einsum:
  - 33
  - 34
  - 37
  - 38
  - 41
  - 10
  - 42
  - 44
  - 45
  - 47
  - 48
  - 57
  opt_einsum.backends.object_arrays.object_einsum.gen_inner_sum:
  - 51
  - 52
  - 53
  - 54
  - 55
  opt_einsum.backends.tensorflow:
  - 1
  - 34
  opt_einsum.backends.tensorflow._get_tensorflow_and_device:
  - 14
  - 18
  - 21
  - 25
  - 26
  opt_einsum.backends.tensorflow.build_expression:
  - 115
  - 117
  opt_einsum.backends.tensorflow.build_expression_eager:
  - 96
  opt_einsum.backends.tensorflow.build_expression_eager.tensorflow_eager_contract:
  - 99
  opt_einsum.backends.tensorflow.build_expression_graph:
  - 59
  - 60
  - 62
  - 63
  opt_einsum.backends.tensorflow.build_expression_graph.tensorflow_contract:
  - 66
  - 68
  - 69
  opt_einsum.backends.tensorflow.evaluate_constants:
  - 121
  - 123
  opt_einsum.backends.tensorflow.evaluate_constants_eager:
  - 105
  - 108
  opt_einsum.backends.tensorflow.evaluate_constants_graph:
  - 75
  - 78
  - 81
  - 82
  - 85
  - 86
  - 87
  opt_einsum.backends.tensorflow.to_tensorflow:
  - 36
  - 37
  - 39
  - 40
  - 41
  - 42
  - 46
  - 47
  - 48
  - 50
  opt_einsum.backends.theano:
  - 1
  - 9
  opt_einsum.backends.theano.build_expression:
  - 32
  - 24
  - 27
  - 28
  - 31
  opt_einsum.backends.theano.build_expression.theano_contract:
  - 35
  opt_einsum.backends.theano.evaluate_constants:
  - 42
  - 43
  - 46
  opt_einsum.backends.theano.to_theano:
  - 11
  - 14
  - 15
  - 16
  - 18
  opt_einsum.backends.torch:
  - 1
  opt_einsum.backends.torch._get_torch_and_device:
  - 26
  - 29
  - 31
  opt_einsum.backends.torch.build_expression:
  - 111
  opt_einsum.backends.torch.build_expression.torch_contract:
  - 114
  - 115
  - 117
  - 118
  - 120
  opt_einsum.backends.torch.einsum:
  - 48
  - 42
  - 45
  - 47
  opt_einsum.backends.torch.evaluate_constants:
  - 129
  - 130
  - 126
  opt_einsum.backends.torch.tensordot:
  - 52
  - 53
  - 55
  - 56
  - 58
  - 59
  - 62
  - 63
  - 66
  - 68
  - 77
  - 78
  - 79
  - 84
  - 85
  - 86
  - 88
  - 89
  - 90
  - 91
  - 93
  - 96
  - 97
  opt_einsum.backends.torch.to_torch:
  - 104
  - 105
  - 102
  opt_einsum.backends.torch.transpose:
  - 37
  - 38
  opt_einsum.blas:
  - 1
  opt_einsum.blas.can_blas:
  - 16
  - 57
  - 62
  - 64
  - 65
  - 71
  - 76
  - 77
  - 78
  - 83
  - 87
  - 90
  - 93
  - 97
  - 101
  - 105
  - 109
  - 113
  - 117
  opt_einsum.contract:
  - 1
  - 606
  opt_einsum.contract.ContractExpression:
  - 741
  opt_einsum.contract.ContractExpression.__call__:
  - 898
  - 872
  - 876
  - 882
  - 884
  - 885
  - 859
  - 892
  - 893
  - 895
  opt_einsum.contract.ContractExpression.__init__:
  - 752
  - 757
  - 758
  opt_einsum.contract.ContractExpression.__repr__:
  - 908
  - 909
  opt_einsum.contract.ContractExpression.__str__:
  - 915
  - 916
  - 917
  - 918
  - 919
  - 920
  opt_einsum.contract.ContractExpression._contract:
  - 816
  - 817
  - 813
  opt_einsum.contract.ContractExpression._contract_with_conversion:
  - 832
  - 841
  - 842
  - 844
  - 846
  opt_einsum.contract.ContractExpression._get_backend_expression:
  - 802
  opt_einsum.contract.ContractExpression._get_evaluated_constants:
  - 795
  - 788
  opt_einsum.contract.ContractExpression.evaluate_constants:
  - 768
  - 775
  - 776
  - 780
  - 782
  opt_einsum.contract.PathInfo:
  - 33
  opt_einsum.contract.PathInfo.__init__:
  - 54
  - 55
  - 56
  - 60
  - 62
  opt_einsum.contract.PathInfo.__repr__:
  - 97
  - 99
  - 70
  - 71
  - 77
  - 81
  - 84
  - 85
  - 88
  opt_einsum.contract._choose_memory_arg:
  - 103
  - 104
  - 106
  - 109
  - 112
  - 113
  - 118
  opt_einsum.contract._core_contract:
  - 645
  - 646
  - 649
  - 652
  - 657
  - 660
  - 663
  - 666
  - 668
  - 669
  - 671
  - 673
  - 676
  - 677
  - 678
  - 681
  - 687
  - 690
  - 691
  - 692
  - 694
  - 700
  - 702
  - 705
  - 708
  - 639
  opt_einsum.contract._default_transpose:
  - 456
  opt_einsum.contract._einsum:
  - 448
  - 450
  - 451
  - 434
  - 435
  - 437
  - 438
  - 443
  - 445
  - 446
  opt_einsum.contract._filter_einsum_defaults:
  - 128
  - 131
  - 134
  - 137
  - 140
  - 125
  - 126
  opt_einsum.contract._infer_backend_class_cached:
  - 608
  opt_einsum.contract._tensordot:
  - 468
  - 469
  - 470
  opt_einsum.contract._transpose:
  - 461
  - 462
  - 463
  opt_einsum.contract.contract:
  - 512
  - 577
  - 580
  - 486
  - 583
  - 584
  - 587
  - 588
  - 590
  - 499
  - 595
  - 600
  - 601
  - 603
  opt_einsum.contract.contract_expression:
  - 1028
  - 965
  - 1029
  - 940
  - 1039
  - 1041
  - 953
  - 1019
  - 1022
  - 1023
  opt_einsum.contract.contract_path:
  - 387
  - 391
  - 392
  - 394
  - 396
  - 397
  - 399
  - 403
  - 404
  - 409
  - 154
  - 411
  - 284
  - 413
  - 288
  - 289
  - 416
  - 293
  - 294
  - 167
  - 297
  - 298
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  - 300
  - 302
  - 303
  - 304
  - 179
  - 308
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  - 316
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  - 340
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  - 344
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  - 356
  - 357
  - 365
  - 367
  - 369
  - 373
  - 374
  - 375
  - 376
  - 378
  - 379
  - 381
  - 382
  opt_einsum.contract.format_const_einsum_str:
  - 736
  - 715
  - 722
  - 725
  - 726
  - 731
  - 733
  opt_einsum.contract.infer_backend:
  - 612
  opt_einsum.contract.parse_backend:
  - 616
  - 625
  - 619
  - 621
  opt_einsum.contract.shape_only:
  - 924
  - 927
  opt_einsum.helpers:
  - 1
  - 11
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  - 19
  - 23
  - 45
  - 15
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  - 96
  - 97
  - 101
  - 55
  - 94
  - 95
  opt_einsum.helpers.flop_count:
  - 112
  - 139
  - 140
  - 141
  opt_einsum.helpers.has_array_interface:
  - 148
  opt_einsum.parser:
  - 1
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  - 129
  - 130
  - 132
  - 133
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  - 118
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  - 257
  - 258
  - 259
  - 261
  - 267
  - 270
  - 273
  - 281
  - 282
  - 284
  - 253
  - 254
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  opt_einsum.parser.convert_subscripts:
  - 233
  - 243
  - 244
  opt_einsum.parser.convert_to_valid_einsum_chars:
  - 112
  - 113
  - 114
  - 103
  opt_einsum.parser.find_output_shape:
  - 169
  - 157
  opt_einsum.parser.find_output_str:
  - 152
  - 153
  - 138
  opt_einsum.parser.gen_unused_symbols:
  - 96
  - 98
  - 84
  - 94
  opt_einsum.parser.get_shape:
  - 176
  - 181
  - 183
  - 185
  - 187
  - 188
  - 190
  opt_einsum.parser.get_symbol:
  - 74
  - 76
  - 78
  - 80
  - 58
  opt_einsum.parser.has_valid_einsum_chars_only:
  - 42
  - 54
  opt_einsum.parser.is_valid_einsum_char:
  - 26
  opt_einsum.parser.parse_einsum_input:
  - 386
  - 387
  - 390
  - 391
  - 396
  - 397
  - 399
  - 402
  - 403
  - 405
  - 409
  - 290
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  - 322
  - 329
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  - 337
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  - 363
  - 366
  - 368
  - 371
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  - 374
  - 376
  - 378
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  opt_einsum.parser.possibly_convert_to_numpy:
  - 219
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  - 227
  opt_einsum.path_random:
  - 1
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  opt_einsum.path_random.RandomGreedy.__init__:
  - 357
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  opt_einsum.path_random.RandomGreedy.choose_fn:
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  - 365
  opt_einsum.path_random.RandomOptimizer:
  - 20
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  - 170
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  - 176
  - 179
  - 180
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  - 185
  - 187
  - 188
  - 191
  opt_einsum.path_random.RandomOptimizer.__del__:
  - 208
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  opt_einsum.path_random.RandomOptimizer.__init__:
  - 73
  - 86
  - 79
  opt_einsum.path_random.RandomOptimizer._cancel_futures:
  - 147
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  opt_einsum.path_random.RandomOptimizer._gen_results_parallel:
  - 132
  - 133
  - 137
  - 138
  - 139
  - 141
  - 144
  opt_einsum.path_random.RandomOptimizer.parallel:
  - 104
  - 105
  - 110
  - 114
  - 117
  - 121
  - 124
  opt_einsum.path_random.RandomOptimizer.path:
  - 94
  - 95
  opt_einsum.path_random._trial_greedy_ssa_path_and_cost:
  - 320
  - 321
  - 313
  - 314
  - 318
  opt_einsum.path_random.random_greedy:
  - 393
  - 394
  - 395
  opt_einsum.path_random.ssa_path_compute_cost:
  - 288
  - 289
  - 293
  - 294
  - 295
  - 296
  - 297
  - 298
  - 300
  - 286
  - 287
  opt_einsum.path_random.thermal_chooser:
  - 259
  - 260
  - 263
  - 267
  - 270
  - 271
  - 274
  - 275
  - 212
  - 245
  - 244
  - 247
  - 250
  - 252
  opt_einsum.paths:
  - 1344
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  - 513
  - 1346
  - 1321
  - 1035
  - 1323
  - 1325
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  - 29
  opt_einsum.paths.BranchBound.__call__:
  - 492
  - 397
  - 399
  - 400
  - 402
  - 380
  opt_einsum.paths.BranchBound.__call__._branch_iterate:
  - 471
  - 482
  - 483
  - 486
  - 456
  - 457
  - 462
  - 465
  - 466
  - 467
  - 470
  - 407
  - 472
  - 475
  - 476
  - 477
  opt_einsum.paths.BranchBound.__call__._branch_iterate._assess_candidate:
  - 418
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  - 423
  - 426
  - 429
  - 433
  - 434
  - 436
  - 440
  - 442
  - 443
  - 445
  opt_einsum.paths.BranchBound.__init__:
  - 357
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  - 365
  - 366
  - 367
  - 338
  opt_einsum.paths.BranchBound.__init__.<lambda1>:
  - 367
  opt_einsum.paths.BranchBound.path:
  - 371
  opt_einsum.paths.DynamicProgramming:
  - 1109
  opt_einsum.paths.DynamicProgramming.__call__:
  - 1155
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  - 1244
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  - 1249
  - 1250
  - 1254
  - 1255
  - 1256
  - 1259
  - 1263
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  opt_einsum.paths.PathOptimizer:
  - 33
  opt_einsum.paths.PathOptimizer._check_args_against_first_call:
  - 66
  - 59
  - 63
  opt_einsum.paths._bitmap_select:
  - 880
  - 873
  opt_einsum.paths._compute_oversize_flops:
  - 192
  - 195
  - 197
  - 198
  opt_einsum.paths._dp_calc_legs:
  - 890
  - 891
  - 884
  - 893
  opt_einsum.paths._dp_compare_combo:
  - 1025
  - 1026
  - 1027
  - 1028
  - 1029
  - 1030
  - 1031
  - 1021
  opt_einsum.paths._dp_compare_flops:
  - 928
  - 930
  - 931
  - 932
  - 933
  - 916
  - 927
  opt_einsum.paths._dp_compare_size:
  - 960
  - 961
  - 962
  - 963
  - 964
  - 954
  - 959
  opt_einsum.paths._dp_compare_write:
  - 993
  - 994
  - 995
  - 985
  - 990
  - 991
  opt_einsum.paths._dp_parse_out_single_term_ops:
  - 1091
  - 1095
  - 1097
  - 1099
  - 1102
  - 1103
  - 1084
  opt_einsum.paths._find_disconnected_subgraphs:
  - 864
  - 865
  - 867
  - 869
  - 852
  - 854
  - 863
  - 856
  - 857
  - 858
  - 859
  - 860
  - 861
  - 831
  opt_einsum.paths._get_candidate:
  - 536
  - 545
  - 535
  opt_einsum.paths._parse_minimize:
  - 1056
  - 1059
  - 1060
  - 1061
  - 1062
  - 1063
  - 1064
  - 1040
  - 1043
  - 1045
  - 1047
  - 1049
  - 1052
  - 1055
  opt_einsum.paths._push_candidate:
  - 563
  - 564
  - 566
  - 567
  - 569
  opt_einsum.paths._simple_chooser:
  - 592
  - 593
  - 591
  opt_einsum.paths._tree_to_sequence:
  - 808
  - 778
  - 815
  - 816
  - 817
  - 819
  - 820
  - 821
  - 823
  - 824
  - 825
  opt_einsum.paths._update_ref_counts:
  - 577
  - 578
  - 579
  - 580
  - 581
  - 582
  - 583
  - 584
  - 586
  - 587
  opt_einsum.paths.auto:
  - 1337
  - 1340
  opt_einsum.paths.auto_hq:
  - 1362
  - 1356
  opt_einsum.paths.branch:
  - 507
  - 510
  opt_einsum.paths.calc_k12_flops:
  - 178
  - 181
  - 158
  opt_einsum.paths.cost_memory_removed:
  - 311
  opt_einsum.paths.cost_memory_removed_jitter:
  - 321
  - 318
  opt_einsum.paths.dynamic_programming:
  - 1316
  - 1317
  opt_einsum.paths.get_path_fn:
  - 1389
  - 1390
  - 1391
  opt_einsum.paths.greedy:
  - 770
  - 771
  - 773
  - 741
  - 774
  opt_einsum.paths.linear_to_ssa:
  - 129
  - 138
  - 139
  - 140
  - 142
  - 143
  - 144
  - 146
  opt_einsum.paths.optimal:
  - 228
  - 229
  - 231
  - 232
  - 207
  - 281
  - 283
  opt_einsum.paths.optimal._optimal_iterate:
  - 259
  - 263
  - 266
  - 267
  - 268
  - 238
  - 270
  - 274
  - 244
  - 245
  - 277
  - 251
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  numpy.lib._arraysetops_impl.UniqueCountsResult:
  - NamedTuple
  numpy.lib._arraysetops_impl.UniqueInverseResult:
  - NamedTuple
  numpy.lib._arrayterator_impl.Arrayterator: []
  numpy.lib._datasource.DataSource: []
  numpy.lib._datasource.Repository:
  - DataSource
  numpy.lib._datasource._FileOpeners: []
  numpy.lib._function_base_impl.vectorize: []
  numpy.lib._index_tricks_impl.AxisConcatenator: []
  numpy.lib._index_tricks_impl.CClass:
  - AxisConcatenator
  numpy.lib._index_tricks_impl.IndexExpression: []
  numpy.lib._index_tricks_impl.MGridClass:
  - nd_grid
  numpy.lib._index_tricks_impl.OGridClass:
  - nd_grid
  numpy.lib._index_tricks_impl.RClass:
  - AxisConcatenator
  numpy.lib._index_tricks_impl.nd_grid: []
  numpy.lib._index_tricks_impl.ndenumerate: []
  numpy.lib._index_tricks_impl.ndindex: []
  numpy.lib._iotools.ConversionWarning:
  - UserWarning
  numpy.lib._iotools.ConverterError:
  - Exception
  numpy.lib._iotools.ConverterLockError:
  - ConverterError
  numpy.lib._iotools.LineSplitter: []
  numpy.lib._iotools.NameValidator: []
  numpy.lib._iotools.StringConverter: []
  numpy.lib._npyio_impl.BagObj: []
  numpy.lib._npyio_impl.NpzFile:
  - Mapping
  numpy.lib._npyio_impl.savetxt.WriteWrap: []
  numpy.lib._polynomial_impl.poly1d: []
  numpy.lib._stride_tricks_impl.DummyArray: []
  numpy.lib._user_array_impl.container: []
  numpy.lib._utils_impl._Deprecate: []
  numpy.lib._version.NumpyVersion: []
  numpy.lib.mixins.NDArrayOperatorsMixin: []
  numpy.linalg._linalg.EigResult:
  - NamedTuple
  numpy.linalg._linalg.EighResult:
  - NamedTuple
  numpy.linalg._linalg.LinAlgError:
  - ValueError
  numpy.linalg._linalg.QRResult:
  - NamedTuple
  numpy.linalg._linalg.SVDResult:
  - NamedTuple
  numpy.linalg._linalg.SlogdetResult:
  - NamedTuple
  numpy.ma.core.MAError:
  - Exception
  numpy.ma.core.MaskError:
  - MAError
  numpy.ma.core.MaskedArray:
  - ndarray
  numpy.ma.core.MaskedArrayFutureWarning:
  - FutureWarning
  numpy.ma.core.MaskedConstant:
  - MaskedArray
  numpy.ma.core.MaskedIterator: []
  numpy.ma.core._DomainCheckInterval: []
  numpy.ma.core._DomainGreater: []
  numpy.ma.core._DomainGreaterEqual: []
  numpy.ma.core._DomainSafeDivide: []
  numpy.ma.core._DomainTan: []
  numpy.ma.core._DomainedBinaryOperation:
  - _MaskedUFunc
  numpy.ma.core._MaskedBinaryOperation:
  - _MaskedUFunc
  numpy.ma.core._MaskedPrintOption: []
  numpy.ma.core._MaskedUFunc: []
  numpy.ma.core._MaskedUnaryOperation:
  - _MaskedUFunc
  numpy.ma.core._convert2ma: []
  numpy.ma.core._extrema_operation:
  - _MaskedUFunc
  numpy.ma.core._frommethod: []
  numpy.ma.core.mvoid:
  - MaskedArray
  numpy.ma.extras.MAxisConcatenator:
  - AxisConcatenator
  numpy.ma.extras._fromnxfunction: []
  numpy.ma.extras._fromnxfunction_allargs:
  - _fromnxfunction
  numpy.ma.extras._fromnxfunction_args:
  - _fromnxfunction
  numpy.ma.extras._fromnxfunction_seq:
  - _fromnxfunction
  numpy.ma.extras._fromnxfunction_single:
  - _fromnxfunction
  numpy.ma.extras.mr_class:
  - MAxisConcatenator
  numpy.ma.mrecords.MaskedRecords:
  - MaskedArray
  numpy.ma.timer_comparison.ModuleTester: []
  numpy.matrixlib.defmatrix.matrix: []
  numpy.polynomial._polybase.ABCPolyBase: []
  numpy.polynomial.chebyshev.Chebyshev:
  - ABCPolyBase
  numpy.polynomial.hermite.Hermite:
  - ABCPolyBase
  numpy.polynomial.hermite_e.HermiteE:
  - ABCPolyBase
  numpy.polynomial.laguerre.Laguerre:
  - ABCPolyBase
  numpy.polynomial.legendre.Legendre:
  - ABCPolyBase
  numpy.polynomial.polynomial.Polynomial:
  - ABCPolyBase
  numpy.testing._private.utils.IgnoreException:
  - Exception
  numpy.testing._private.utils.KnownFailureException:
  - Exception
  numpy.testing._private.utils._Dummy: []
  numpy.testing._private.utils.clear_and_catch_warnings: []
  numpy.testing._private.utils.suppress_warnings: []
  numpy.testing.print_coercion_tables.GenericObject: []
  numpy.typing.mypy_plugin._NumpyPlugin:
  - Plugin
  opt_einsum.contract.ContractExpression: []
  opt_einsum.contract.PathInfo: []
  opt_einsum.path_random.RandomGreedy:
  - RandomOptimizer
  opt_einsum.path_random.RandomOptimizer: []
  opt_einsum.paths.BranchBound:
  - PathOptimizer
  opt_einsum.paths.DynamicProgramming:
  - PathOptimizer
  opt_einsum.paths.PathOptimizer: []
ep:
  func_name: TestOneInput
  module: '...fuzz_parser'
