SparseDict representation:

5x_false: Bool[0, 0, 0, 0, 0]
tensor: Tensor(Sparse{Int32}(Element{false, Bool, Int32}(Bool[]), 5, Finch.DictTable{Int32, Int32, Vector{Int32}, Vector{Int32}, Vector{Int32}, Dict{Tuple{Int32, Int32}, Int32}}([1, 1], Int32[], Int32[], Dict{Tuple{Int32, Int32}, Int32}())))
countstored: 0
5x_true: Bool[1, 1, 1, 1, 1]
tensor: Tensor(Sparse{Int32}(Element{false, Bool, Int32}(Bool[1, 1, 1, 1, 1]), 5, Finch.DictTable{Int32, Int32, Vector{Int32}, Vector{Int32}, Vector{Int32}, Dict{Tuple{Int32, Int32}, Int32}}([1, 6], [1, 2, 3, 4, 5], [1, 2, 3, 4, 5], Dict((1, 2) => 2, (1, 4) => 4, (1, 5) => 5, (1, 1) => 1, (1, 3) => 3))))
countstored: 5
6x_bool_mix: Bool[0, 1, 1, 0, 0, 1]
tensor: Tensor(Sparse{Int32}(Element{false, Bool, Int32}(Bool[1, 1, 1]), 6, Finch.DictTable{Int32, Int32, Vector{Int32}, Vector{Int32}, Vector{Int32}, Dict{Tuple{Int32, Int32}, Int32}}([1, 4], [2, 3, 6], [1, 2, 3], Dict((1, 2) => 1, (1, 6) => 3, (1, 3) => 2))))
countstored: 3
6x_one_bool: Bool[0, 0, 1, 0, 0, 0]
tensor: Tensor(Sparse{Int32}(Element{false, Bool, Int32}(Bool[1]), 6, Finch.DictTable{Int32, Int32, Vector{Int32}, Vector{Int32}, Vector{Int32}, Dict{Tuple{Int32, Int32}, Int32}}([1, 2], [3], [1], Dict((1, 3) => 1))))
countstored: 1
1111x_bool_mix: Bool[0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
tensor: Tensor(Sparse{Int32}(Element{false, Bool, Int32}(Bool[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]), 1111, Finch.DictTable{Int32, Int32, Vector{Int32}, Vector{Int32}, Vector{Int32}, Dict{Tuple{Int32, Int32}, Int32}}([1, 449], [2, 3, 555, 556, 557, 558, 559, 560, 561, 562, 563, 564, 565, 566, 567, 568, 569, 570, 571, 572, 573, 574, 575, 576, 577, 578, 579, 580, 581, 582, 583, 584, 585, 586, 587, 588, 589, 590, 591, 592, 593, 594, 595, 596, 597, 598, 599, 600, 601, 602, 603, 604, 605, 606, 607, 608, 609, 610, 611, 612, 613, 614, 615, 616, 617, 618, 619, 620, 621, 622, 623, 624, 625, 626, 627, 628, 629, 630, 631, 632, 633, 634, 635, 636, 637, 638, 639, 640, 641, 642, 643, 644, 645, 646, 647, 648, 649, 650, 651, 652, 653, 654, 655, 656, 657, 658, 659, 660, 661, 662, 663, 664, 665, 666, 667, 668, 669, 670, 671, 672, 673, 674, 675, 676, 677, 678, 679, 680, 681, 682, 683, 684, 685, 686, 687, 688, 689, 690, 691, 692, 693, 694, 695, 696, 697, 698, 699, 700, 701, 702, 703, 704, 705, 706, 707, 708, 709, 710, 711, 712, 713, 714, 715, 716, 717, 718, 719, 720, 721, 722, 723, 724, 725, 726, 727, 728, 729, 730, 731, 732, 733, 734, 735, 736, 737, 738, 739, 740, 741, 742, 743, 744, 745, 746, 747, 748, 749, 750, 751, 752, 753, 754, 755, 756, 757, 758, 759, 760, 761, 762, 763, 764, 765, 766, 767, 768, 769, 770, 771, 772, 773, 774, 775, 776, 777, 778, 779, 780, 781, 782, 783, 784, 785, 786, 787, 788, 789, 790, 791, 792, 793, 794, 795, 796, 797, 798, 799, 800, 801, 802, 803, 804, 805, 806, 807, 808, 809, 810, 811, 812, 813, 814, 815, 816, 817, 818, 819, 820, 821, 822, 823, 824, 825, 826, 827, 828, 829, 830, 831, 832, 833, 834, 835, 836, 837, 838, 839, 840, 841, 842, 843, 844, 845, 846, 847, 848, 849, 850, 851, 852, 853, 854, 855, 856, 857, 858, 859, 860, 861, 862, 863, 864, 865, 866, 867, 868, 869, 870, 871, 872, 873, 874, 875, 876, 877, 878, 879, 880, 881, 882, 883, 884, 885, 886, 887, 888, 889, 890, 891, 892, 893, 894, 895, 896, 897, 898, 899, 900, 901, 902, 903, 904, 905, 906, 907, 908, 909, 910, 911, 912, 913, 914, 915, 916, 917, 918, 919, 920, 921, 922, 923, 924, 925, 926, 927, 928, 929, 930, 931, 932, 933, 934, 935, 936, 937, 938, 939, 940, 941, 942, 943, 944, 945, 946, 947, 948, 949, 950, 951, 952, 953, 954, 955, 956, 957, 958, 959, 960, 961, 962, 963, 964, 965, 966, 967, 968, 969, 970, 971, 972, 973, 974, 975, 976, 977, 978, 979, 980, 981, 982, 983, 984, 985, 986, 987, 988, 989, 990, 991, 992, 993, 994, 995, 996, 997, 998, 999, 1001], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293, 294, 295, 296, 297, 298, 299, 300, 301, 302, 303, 304, 305, 306, 307, 308, 309, 310, 311, 312, 313, 314, 315, 316, 317, 318, 319, 320, 321, 322, 323, 324, 325, 326, 327, 328, 329, 330, 331, 332, 333, 334, 335, 336, 337, 338, 339, 340, 341, 342, 343, 344, 345, 346, 347, 348, 349, 350, 351, 352, 353, 354, 355, 356, 357, 358, 359, 360, 361, 362, 363, 364, 365, 366, 367, 368, 369, 370, 371, 372, 373, 374, 375, 376, 377, 378, 379, 380, 381, 382, 383, 384, 385, 386, 387, 388, 389, 390, 391, 392, 393, 394, 395, 396, 397, 398, 399, 400, 401, 402, 403, 404, 405, 406, 407, 408, 409, 410, 411, 412, 413, 414, 415, 416, 417, 418, 419, 420, 421, 422, 423, 424, 425, 426, 427, 428, 429, 430, 431, 432, 433, 434, 435, 436, 437, 438, 439, 440, 441, 442, 443, 444, 445, 446, 447, 448], Dict((1, 704) => 152, (1, 918) => 366, (1, 986) => 434, (1, 581) => 29, (1, 833) => 281, (1, 597) => 45, (1, 575) => 23, (1, 590) => 38, (1, 595) => 43, (1, 573) => 21, (1, 632) => 80, (1, 698) => 146, (1, 886) => 334, (1, 952) => 400, (1, 750) => 198, (1, 801) => 249, (1, 656) => 104, (1, 572) => 20, (1, 670) => 118, (1, 795) => 243, (1, 808) => 256, (1, 864) => 312, (1, 785) => 233, (1, 614) => 62, (1, 774) => 222, (1, 860) => 308, (1, 927) => 375, (1, 680) => 128, (1, 797) => 245, (1, 813) => 261, (1, 596) => 44, (1, 746) => 194, (1, 966) => 414, (1, 661) => 109, (1, 630) => 78, (1, 888) => 336, (1, 843) => 291, (1, 646) => 94, (1, 904) => 352, (1, 849) => 297, (1, 620) => 68, (1, 722) => 170, (1, 930) => 378, (1, 946) => 394, (1, 606) => 54, (1, 838) => 286, (1, 787) => 235, (1, 856) => 304, (1, 637) => 85, (1, 622) => 70, (1, 644) => 92, (1, 872) => 320, (1, 691) => 139, (1, 861) => 309, (1, 802) => 250, (1, 786) => 234, (1, 668) => 116, (1, 824) => 272, (1, 560) => 8, (1, 822) => 270, (1, 968) => 416, (1, 570) => 18, (1, 613) => 61, (1, 775) => 223, (1, 589) => 37, (1, 965) => 413, (1, 987) => 435, (1, 677) => 125, (1, 812) => 260, (1, 981) => 429, (1, 898) => 346, (1, 584) => 32, (1, 2) => 1, (1, 703) => 151, (1, 953) => 401, (1, 769) => 217, (1, 936) => 384, (1, 917) => 365, (1, 947) => 395, (1, 988) => 436, (1, 831) => 279, (1, 751) => 199, (1, 615) => 63, (1, 850) => 298, (1, 562) => 10, (1, 869) => 317, (1, 792) => 240, (1, 727) => 175, (1, 934) => 382, (1, 702) => 150, (1, 745) => 193, (1, 851) => 299, (1, 994) => 442, (1, 857) => 305, (1, 591) => 39, (1, 726) => 174, (1, 937) => 385, (1, 811) => 259, (1, 883) => 331, (1, 697) => 145, (1, 629) => 77, (1, 779) => 227, (1, 895) => 343, (1, 908) => 356, (1, 821) => 269, (1, 956) => 404, (1, 653) => 101, (1, 901) => 349, (1, 790) => 238, (1, 809) => 257, (1, 840) => 288, (1, 859) => 307, (1, 905) => 353, (1, 899) => 347, (1, 627) => 75, (1, 605) => 53, (1, 949) => 397, (1, 943) => 391, (1, 803) => 251, (1, 603) => 51, (1, 651) => 99, (1, 912) => 360, (1, 892) => 340, (1, 725) => 173, (1, 826) => 274, (1, 909) => 357, (1, 958) => 406, (1, 866) => 314, (1, 749) => 197, (1, 970) => 418, (1, 675) => 123, (1, 854) => 302, (1, 891) => 339, (1, 814) => 262, (1, 897) => 345, (1, 767) => 215, (1, 960) => 408, (1, 910) => 358, (1, 568) => 16, (1, 894) => 342, (1, 982) => 430, (1, 577) => 25, (1, 906) => 354, (1, 818) => 266, (1, 555) => 3, (1, 701) => 149, (1, 929) => 377, (1, 922) => 370, (1, 561) => 9, (1, 587) => 35, (1, 671) => 119, (1, 724) => 172, (1, 844) => 292, (1, 862) => 310, (1, 923) => 371, (1, 569) => 17, (1, 757) => 205, (1, 941) => 389, (1, 945) => 393, (1, 579) => 27, (1, 939) => 387, (1, 611) => 59, (1, 663) => 111, (1, 739) => 187, (1, 748) => 196, (1, 932) => 380, (1, 919) => 367, (1, 635) => 83, (1, 954) => 402, (1, 974) => 422, (1, 925) => 373, (1, 648) => 96, (1, 806) => 254, (1, 881) => 329, (1, 639) => 87, (1, 816) => 264, (1, 942) => 390, (1, 566) => 14, (1, 913) => 361, (1, 772) => 220, (1, 604) => 52, (1, 688) => 136, (1, 672) => 120, (1, 580) => 28, (1, 874) => 322, (1, 893) => 341, (1, 957) => 405, (1, 884) => 332, (1, 967) => 415, (1, 659) => 107, (1, 975) => 423, (1, 940) => 388, (1, 973) => 421, (1, 715) => 163, (1, 798) => 246, (1, 914) => 362, (1, 564) => 12, (1, 585) => 33, (1, 1001) => 448, (1, 980) => 428, (1, 652) => 100, (1, 709) => 157, (1, 633) => 81, (1, 961) => 409, (1, 991) => 439, (1, 763) => 211, (1, 810) => 258, (1, 658) => 106, (1, 599) => 47, (1, 902) => 350, (1, 733) => 181, (1, 556) => 4, (1, 628) => 76, (1, 609) => 57, (1, 950) => 398, (1, 846) => 294, (1, 634) => 82, (1, 841) => 289, (1, 623) => 71, (1, 805) => 253, (1, 796) => 244, (1, 858) => 306, (1, 576) => 24, (1, 885) => 333, (1, 799) => 247, (1, 660) => 108, (1, 783) => 231, (1, 610) => 58, (1, 676) => 124, (1, 717) => 165, (1, 647) => 95, (1, 839) => 287, (1, 567) => 15, (1, 586) => 34, (1, 978) => 426, (1, 996) => 444, (1, 640) => 88, (1, 696) => 144, (1, 674) => 122, (1, 636) => 84, (1, 723) => 171, (1, 601) => 49, (1, 693) => 141, (1, 847) => 295, (1, 921) => 369, (1, 853) => 301, (1, 915) => 363, (1, 964) => 412, (1, 695) => 143, (1, 612) => 60, (1, 616) => 64, (1, 574) => 22, (1, 820) => 268, (1, 626) => 74, (1, 720) => 168, (1, 876) => 324, (1, 765) => 213, (1, 699) => 147, (1, 791) => 239, (1, 933) => 381, (1, 997) => 445, (1, 848) => 296, (1, 719) => 167, (1, 756) => 204, (1, 657) => 105, (1, 588) => 36, (1, 916) => 364, (1, 807) => 255, (1, 963) => 411, (1, 759) => 207, (1, 938) => 386, (1, 877) => 325, (1, 900) => 348, (1, 641) => 89, (1, 650) => 98, (1, 681) => 129, (1, 770) => 218, (1, 969) => 417, (1, 664) => 112, (1, 983) => 431, (1, 741) => 189, (1, 743) => 191, (1, 999) => 447, (1, 735) => 183, (1, 685) => 133, (1, 665) => 113, (1, 793) => 241, (1, 868) => 316, (1, 855) => 303, (1, 773) => 221, (1, 711) => 159, (1, 764) => 212, (1, 926) => 374, (1, 683) => 131, (1, 708) => 156, (1, 602) => 50, (1, 624) => 72, (1, 682) => 130, (1, 710) => 158, (1, 800) => 248, (1, 766) => 214, (1, 836) => 284, (1, 3) => 2, (1, 890) => 338, (1, 959) => 407, (1, 687) => 135, (1, 593) => 41, (1, 732) => 180, (1, 736) => 184, (1, 829) => 277, (1, 837) => 285, (1, 740) => 188, (1, 948) => 396, (1, 995) => 443, (1, 592) => 40, (1, 707) => 155, (1, 712) => 160, (1, 823) => 271, (1, 878) => 326, (1, 911) => 359, (1, 600) => 48, (1, 804) => 252, (1, 758) => 206, (1, 617) => 65, (1, 760) => 208, (1, 686) => 134, (1, 700) => 148, (1, 863) => 311, (1, 976) => 424, (1, 744) => 192, (1, 788) => 236, (1, 673) => 121, (1, 716) => 164, (1, 731) => 179, (1, 817) => 265, (1, 755) => 203, (1, 867) => 315, (1, 873) => 321, (1, 718) => 166, (1, 747) => 195, (1, 896) => 344, (1, 971) => 419, (1, 931) => 379, (1, 889) => 337, (1, 768) => 216, (1, 771) => 219, (1, 985) => 433, (1, 684) => 132, (1, 742) => 190, (1, 776) => 224, (1, 649) => 97, (1, 692) => 140, (1, 734) => 182, (1, 852) => 300, (1, 815) => 263, (1, 944) => 392, (1, 582) => 30, (1, 625) => 73, (1, 865) => 313, (1, 557) => 5, (1, 924) => 372, (1, 558) => 6, (1, 690) => 138, (1, 903) => 351, (1, 880) => 328, (1, 780) => 228, (1, 834) => 282, (1, 979) => 427, (1, 992) => 440, (1, 871) => 319, (1, 714) => 162, (1, 753) => 201, (1, 631) => 79, (1, 669) => 117, (1, 645) => 93, (1, 781) => 229, (1, 870) => 318, (1, 777) => 225, (1, 738) => 186, (1, 972) => 420, (1, 998) => 446, (1, 962) => 410, (1, 571) => 19, (1, 607) => 55, (1, 694) => 142, (1, 721) => 169, (1, 754) => 202, (1, 832) => 280, (1, 762) => 210, (1, 993) => 441, (1, 977) => 425, (1, 935) => 383, (1, 618) => 66, (1, 679) => 127, (1, 778) => 226, (1, 563) => 11, (1, 920) => 368, (1, 737) => 185, (1, 655) => 103, (1, 828) => 276, (1, 594) => 42, (1, 842) => 290, (1, 989) => 437, (1, 907) => 355, (1, 761) => 209, (1, 830) => 278, (1, 730) => 178, (1, 951) => 399, (1, 928) => 376, (1, 583) => 31, (1, 598) => 46, (1, 706) => 154, (1, 643) => 91, (1, 887) => 335, (1, 666) => 114, (1, 729) => 177, (1, 689) => 137, (1, 619) => 67, (1, 782) => 230, (1, 565) => 13, (1, 794) => 242, (1, 559) => 7, (1, 654) => 102, (1, 642) => 90, (1, 705) => 153, (1, 713) => 161, (1, 955) => 403, (1, 638) => 86, (1, 990) => 438, (1, 678) => 126, (1, 667) => 115, (1, 835) => 283, (1, 875) => 323, (1, 752) => 200, (1, 608) => 56, (1, 728) => 176, (1, 789) => 237, (1, 662) => 110, (1, 879) => 327, (1, 621) => 69, (1, 784) => 232, (1, 819) => 267, (1, 578) => 26, (1, 827) => 275, (1, 845) => 293, (1, 825) => 273, (1, 984) => 432, (1, 882) => 330))))
countstored: 448
11x_bool_mix: Bool[0, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1]
tensor: Tensor(Sparse{Int32}(Element{false, Bool, Int32}(Bool[1, 1, 1, 1, 1, 1, 1, 1]), 11, Finch.DictTable{Int32, Int32, Vector{Int32}, Vector{Int32}, Vector{Int32}, Dict{Tuple{Int32, Int32}, Int32}}([1, 9], [2, 3, 5, 6, 7, 8, 9, 11], [1, 2, 3, 4, 5, 6, 7, 8], Dict((1, 2) => 1, (1, 9) => 7, (1, 7) => 5, (1, 6) => 4, (1, 11) => 8, (1, 5) => 3, (1, 3) => 2, (1, 8) => 6))))
countstored: 8
6x_float_mix: [0.0, 2.0, 2.0, 0.0, 3.0, 3.0]
tensor: Tensor(Sparse{Int32}(Element{0.0, Float64, Int32}([2.0, 2.0, 3.0, 3.0]), 6, Finch.DictTable{Int32, Int32, Vector{Int32}, Vector{Int32}, Vector{Int32}, Dict{Tuple{Int32, Int32}, Int32}}([1, 5], [2, 3, 5, 6], [1, 2, 3, 4], Dict((1, 2) => 1, (1, 6) => 4, (1, 5) => 3, (1, 3) => 2))))
countstored: 4
4x_zeros: [0.0, 0.0, 0.0, 0.0]
tensor: Tensor(Sparse{Int32}(Element{0.0, Float64, Int32}(Float64[]), 4, Finch.DictTable{Int32, Int32, Vector{Int32}, Vector{Int32}, Vector{Int32}, Dict{Tuple{Int32, Int32}, Int32}}([1, 1], Int32[], Int32[], Dict{Tuple{Int32, Int32}, Int32}())))
countstored: 0
5x_zeros: [0.0, 0.0, 0.0, 0.0, 0.0]
tensor: Tensor(Sparse{Int32}(Element{0.0, Float64, Int32}(Float64[]), 5, Finch.DictTable{Int32, Int32, Vector{Int32}, Vector{Int32}, Vector{Int32}, Dict{Tuple{Int32, Int32}, Int32}}([1, 1], Int32[], Int32[], Dict{Tuple{Int32, Int32}, Int32}())))
countstored: 0
5x_ones: [1.0, 1.0, 1.0, 1.0, 1.0]
tensor: Tensor(Sparse{Int32}(Element{0.0, Float64, Int32}([1.0, 1.0, 1.0, 1.0, 1.0]), 5, Finch.DictTable{Int32, Int32, Vector{Int32}, Vector{Int32}, Vector{Int32}, Dict{Tuple{Int32, Int32}, Int32}}([1, 6], [1, 2, 3, 4, 5], [1, 2, 3, 4, 5], Dict((1, 2) => 2, (1, 4) => 4, (1, 5) => 5, (1, 1) => 1, (1, 3) => 3))))
countstored: 5
9x_float_mix: [0.0, 1.0, 1.0, 2.0, 2.0, 0.0, 0.0, 3.0, 0.0]
tensor: Tensor(Sparse{Int32}(Element{0.0, Float64, Int32}([1.0, 1.0, 2.0, 2.0, 3.0]), 9, Finch.DictTable{Int32, Int32, Vector{Int32}, Vector{Int32}, Vector{Int32}, Dict{Tuple{Int32, Int32}, Int32}}([1, 6], [2, 3, 4, 5, 8], [1, 2, 3, 4, 5], Dict((1, 2) => 1, (1, 4) => 3, (1, 5) => 4, (1, 3) => 2, (1, 8) => 5))))
countstored: 5
1111x_float_mix: [0.0, 20.0, 30.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 5550.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 6660.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
tensor: Tensor(Sparse{Int32}(Element{0.0, Float64, Int32}([20.0, 30.0, 5550.0, 6660.0]), 1111, Finch.DictTable{Int32, Int32, Vector{Int32}, Vector{Int32}, Vector{Int32}, Dict{Tuple{Int32, Int32}, Int32}}([1, 5], [2, 3, 555, 666], [1, 2, 3, 4], Dict((1, 2) => 1, (1, 666) => 4, (1, 3) => 2, (1, 555) => 3))))
countstored: 4

