makemore-part1-bigrams.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(('a', 'n'), 5438),\n",
       " (('a', 'r'), 3264),\n",
       " (('e', 'l'), 3248),\n",
       " (('r', 'i'), 3033),\n",
       " (('n', 'a'), 2977),\n",
       " (('l', 'e'), 2921),\n",
       " (('e', 'n'), 2675),\n",
       " (('l', 'a'), 2623),\n",
       " (('m', 'a'), 2590),\n",
       " (('a', 'l'), 2528),\n",
       " (('l', 'i'), 2480),\n",
       " (('i', 'a'), 2445),\n",
       " (('o', 'n'), 2411),\n",
       " (('r', 'a'), 2356),\n",
       " (('a', 'h'), 2332),\n",
       " (('h', 'a'), 2244),\n",
       " (('y', 'a'), 2143),\n",
       " (('i', 'n'), 2126),\n",
       " (('a', 'y'), 2050),\n",
       " (('e', 'r'), 1958),\n",
       " (('n', 'n'), 1906),\n",
       " (('y', 'n'), 1826),\n",
       " (('k', 'a'), 1731),\n",
       " (('n', 'i'), 1725),\n",
       " (('r', 'e'), 1697),\n",
       " (('i', 'e'), 1653),\n",
       " (('a', 'i'), 1650),\n",
       " (('a', 'm'), 1634),\n",
       " (('l', 'y'), 1588),\n",
       " (('j', 'a'), 1473),\n",
       " (('n', 'e'), 1359),\n",
       " (('l', 'l'), 1345),\n",
       " (('i', 'l'), 1345),\n",
       " (('i', 's'), 1316),\n",
       " (('d', 'a'), 1303),\n",
       " (('s', 'h'), 1285),\n",
       " (('d', 'e'), 1283),\n",
       " (('e', 'e'), 1271),\n",
       " (('m', 'i'), 1256),\n",
       " (('s', 'a'), 1201),\n",
       " (('a', 's'), 1118),\n",
       " (('y', 'l'), 1104),\n",
       " (('e', 'y'), 1070),\n",
       " (('o', 'r'), 1059),\n",
       " (('a', 'd'), 1042),\n",
       " (('t', 'a'), 1027),\n",
       " (('v', 'i'), 911),\n",
       " (('k', 'e'), 895),\n",
       " (('s', 'e'), 884),\n",
       " (('r', 'o'), 869),\n",
       " (('e', 's'), 861),\n",
       " (('z', 'a'), 860),\n",
       " (('i', 'r'), 849),\n",
       " (('b', 'r'), 842),\n",
       " (('a', 'v'), 834),\n",
       " (('m', 'e'), 818),\n",
       " (('e', 'i'), 818),\n",
       " (('c', 'a'), 815),\n",
       " (('i', 'y'), 779),\n",
       " (('r', 'y'), 773),\n",
       " (('e', 'm'), 769),\n",
       " (('s', 't'), 765),\n",
       " (('h', 'i'), 729),\n",
       " (('t', 'e'), 716),\n",
       " (('n', 'd'), 704),\n",
       " (('l', 'o'), 692),\n",
       " (('a', 'e'), 692),\n",
       " (('a', 't'), 687),\n",
       " (('s', 'i'), 684),\n",
       " (('e', 'a'), 679),\n",
       " (('d', 'i'), 674),\n",
       " (('h', 'e'), 674),\n",
       " (('t', 'o'), 667),\n",
       " (('c', 'h'), 664),\n",
       " (('b', 'e'), 655),\n",
       " (('t', 'h'), 647),\n",
       " (('v', 'a'), 642),\n",
       " (('o', 'l'), 619),\n",
       " (('i', 'o'), 588),\n",
       " (('e', 't'), 580),\n",
       " (('v', 'e'), 568),\n",
       " (('a', 'k'), 568),\n",
       " (('a', 'a'), 556),\n",
       " (('c', 'e'), 551),\n",
       " (('a', 'b'), 541),\n",
       " (('i', 't'), 541),\n",
       " (('t', 'i'), 532),\n",
       " (('s', 'o'), 531),\n",
       " (('i', 'c'), 509),\n",
       " (('k', 'i'), 509),\n",
       " (('o', 's'), 504),\n",
       " (('n', 'o'), 496),\n",
       " (('j', 'o'), 479),\n",
       " (('u', 's'), 474),\n",
       " (('a', 'c'), 470),\n",
       " (('n', 'y'), 465),\n",
       " (('e', 'v'), 463),\n",
       " (('s', 's'), 461),\n",
       " (('m', 'o'), 452),\n",
       " (('i', 'k'), 445),\n",
       " (('n', 't'), 443),\n",
       " (('i', 'd'), 440),\n",
       " (('j', 'e'), 440),\n",
       " (('a', 'z'), 435),\n",
       " (('i', 'g'), 428),\n",
       " (('i', 'm'), 427),\n",
       " (('r', 'r'), 425),\n",
       " (('d', 'r'), 424),\n",
       " (('u', 'r'), 414),\n",
       " (('r', 'l'), 413),\n",
       " (('y', 's'), 401),\n",
       " (('e', 'd'), 384),\n",
       " (('a', 'u'), 381),\n",
       " (('c', 'o'), 380),\n",
       " (('k', 'y'), 379),\n",
       " (('d', 'o'), 378),\n",
       " (('t', 't'), 374),\n",
       " (('z', 'e'), 373),\n",
       " (('z', 'i'), 364),\n",
       " (('g', 'h'), 360),\n",
       " (('t', 'r'), 352),\n",
       " (('k', 'o'), 344),\n",
       " (('t', 'y'), 341),\n",
       " (('g', 'e'), 334),\n",
       " (('g', 'a'), 330),\n",
       " (('l', 'u'), 324),\n",
       " (('b', 'a'), 321),\n",
       " (('d', 'y'), 317),\n",
       " (('c', 'k'), 316),\n",
       " (('k', 'h'), 307),\n",
       " (('u', 'l'), 301),\n",
       " (('y', 'e'), 301),\n",
       " (('y', 'r'), 291),\n",
       " (('m', 'y'), 287),\n",
       " (('h', 'o'), 287),\n",
       " (('w', 'a'), 280),\n",
       " (('s', 'l'), 279),\n",
       " (('n', 's'), 278),\n",
       " (('i', 'z'), 277),\n",
       " (('u', 'n'), 275),\n",
       " (('o', 'u'), 275),\n",
       " (('n', 'g'), 273),\n",
       " (('y', 'd'), 272),\n",
       " (('c', 'i'), 271),\n",
       " (('y', 'o'), 271),\n",
       " (('i', 'v'), 269),\n",
       " (('e', 'o'), 269),\n",
       " (('o', 'm'), 261),\n",
       " (('r', 'u'), 252),\n",
       " (('f', 'a'), 242),\n",
       " (('b', 'i'), 217),\n",
       " (('s', 'y'), 215),\n",
       " (('n', 'c'), 213),\n",
       " (('h', 'y'), 213),\n",
       " (('p', 'a'), 209),\n",
       " (('r', 't'), 208),\n",
       " (('q', 'u'), 206),\n",
       " (('p', 'h'), 204),\n",
       " (('h', 'r'), 204),\n",
       " (('j', 'u'), 202),\n",
       " (('g', 'r'), 201),\n",
       " (('p', 'e'), 197),\n",
       " (('n', 'l'), 195),\n",
       " (('y', 'i'), 192),\n",
       " (('g', 'i'), 190),\n",
       " (('o', 'd'), 190),\n",
       " (('r', 's'), 190),\n",
       " (('r', 'd'), 187),\n",
       " (('h', 'l'), 185),\n",
       " (('s', 'u'), 185),\n",
       " (('a', 'x'), 182),\n",
       " (('e', 'z'), 181),\n",
       " (('e', 'k'), 178),\n",
       " (('o', 'v'), 176),\n",
       " (('a', 'j'), 175),\n",
       " (('o', 'h'), 171),\n",
       " (('u', 'e'), 169),\n",
       " (('m', 'm'), 168),\n",
       " (('a', 'g'), 168),\n",
       " (('h', 'u'), 166),\n",
       " (('u', 'a'), 163),\n",
       " (('r', 'm'), 162),\n",
       " (('a', 'w'), 161),\n",
       " (('f', 'i'), 160),\n",
       " (('u', 'm'), 154),\n",
       " (('e', 'c'), 153),\n",
       " (('v', 'o'), 153),\n",
       " (('e', 'h'), 152),\n",
       " (('p', 'r'), 151),\n",
       " (('d', 'd'), 149),\n",
       " (('o', 'a'), 149),\n",
       " (('w', 'e'), 149),\n",
       " (('w', 'i'), 148),\n",
       " (('y', 'm'), 148),\n",
       " (('z', 'y'), 147),\n",
       " (('n', 'z'), 145),\n",
       " (('y', 'u'), 141),\n",
       " (('r', 'n'), 140),\n",
       " (('o', 'b'), 140),\n",
       " (('k', 'l'), 139),\n",
       " (('m', 'u'), 139),\n",
       " (('l', 'd'), 138),\n",
       " (('h', 'n'), 138),\n",
       " (('u', 'd'), 136),\n",
       " (('t', 'l'), 134),\n",
       " (('a', 'f'), 134),\n",
       " (('o', 'e'), 132),\n",
       " (('e', 'x'), 132),\n",
       " (('e', 'g'), 125),\n",
       " (('f', 'e'), 123),\n",
       " (('z', 'l'), 123),\n",
       " (('u', 'i'), 121),\n",
       " (('v', 'y'), 121),\n",
       " (('e', 'b'), 121),\n",
       " (('r', 'h'), 121),\n",
       " (('j', 'i'), 119),\n",
       " (('o', 't'), 118),\n",
       " (('d', 'h'), 118),\n",
       " (('h', 'm'), 117),\n",
       " (('c', 'l'), 116),\n",
       " (('o', 'o'), 115),\n",
       " (('y', 'c'), 115),\n",
       " (('o', 'w'), 114),\n",
       " (('o', 'c'), 114),\n",
       " (('f', 'r'), 114),\n",
       " (('m', 'b'), 112),\n",
       " (('z', 'o'), 110),\n",
       " (('i', 'b'), 110),\n",
       " (('i', 'u'), 109),\n",
       " (('k', 'r'), 109),\n",
       " (('y', 'v'), 106),\n",
       " (('t', 'z'), 105),\n",
       " (('b', 'o'), 105),\n",
       " (('c', 'y'), 104),\n",
       " (('y', 't'), 104),\n",
       " (('u', 'b'), 103),\n",
       " (('u', 'c'), 103),\n",
       " (('x', 'a'), 103),\n",
       " (('b', 'l'), 103),\n",
       " (('o', 'y'), 103),\n",
       " (('x', 'i'), 102),\n",
       " (('i', 'f'), 101),\n",
       " (('r', 'c'), 99),\n",
       " (('m', 'r'), 97),\n",
       " (('n', 'u'), 96),\n",
       " (('o', 'p'), 95),\n",
       " (('i', 'h'), 95),\n",
       " (('k', 's'), 95),\n",
       " (('l', 's'), 94),\n",
       " (('u', 'k'), 93),\n",
       " (('d', 'u'), 92),\n",
       " (('s', 'm'), 90),\n",
       " (('r', 'k'), 90),\n",
       " (('i', 'x'), 89),\n",
       " (('y', 'k'), 86),\n",
       " (('u', 'w'), 86),\n",
       " (('g', 'u'), 85),\n",
       " (('b', 'y'), 83),\n",
       " (('e', 'p'), 83),\n",
       " (('g', 'o'), 83),\n",
       " (('s', 'k'), 82),\n",
       " (('u', 't'), 82),\n",
       " (('a', 'p'), 82),\n",
       " (('e', 'f'), 82),\n",
       " (('i', 'i'), 82),\n",
       " (('r', 'v'), 80),\n",
       " (('t', 'u'), 78),\n",
       " (('y', 'z'), 78),\n",
       " (('l', 't'), 77),\n",
       " (('r', 'g'), 76),\n",
       " (('c', 'r'), 76),\n",
       " (('i', 'j'), 76),\n",
       " (('w', 'y'), 73),\n",
       " (('z', 'u'), 73),\n",
       " (('l', 'v'), 72),\n",
       " (('h', 't'), 71),\n",
       " (('x', 't'), 70),\n",
       " (('o', 'i'), 69),\n",
       " (('e', 'u'), 69),\n",
       " (('o', 'k'), 68),\n",
       " (('b', 'd'), 65),\n",
       " (('a', 'o'), 63),\n",
       " (('p', 'i'), 61),\n",
       " (('s', 'c'), 60),\n",
       " (('d', 'l'), 60),\n",
       " (('l', 'm'), 60),\n",
       " (('a', 'q'), 60),\n",
       " (('f', 'o'), 60),\n",
       " (('p', 'o'), 59),\n",
       " (('n', 'k'), 58),\n",
       " (('w', 'n'), 58),\n",
       " (('u', 'h'), 58),\n",
       " (('e', 'j'), 55),\n",
       " (('n', 'v'), 55),\n",
       " (('s', 'r'), 55),\n",
       " (('o', 'z'), 54),\n",
       " (('i', 'p'), 53),\n",
       " (('l', 'b'), 52),\n",
       " (('i', 'q'), 52),\n",
       " (('m', 'c'), 51),\n",
       " (('s', 'p'), 51),\n",
       " (('e', 'w'), 50),\n",
       " (('k', 'u'), 50),\n",
       " (('v', 'r'), 48),\n",
       " (('u', 'g'), 47),\n",
       " (('o', 'x'), 45),\n",
       " (('u', 'z'), 45),\n",
       " (('z', 'z'), 45),\n",
       " (('j', 'h'), 45),\n",
       " (('b', 'u'), 45),\n",
       " (('o', 'g'), 44),\n",
       " (('n', 'r'), 44),\n",
       " (('f', 'f'), 44),\n",
       " (('n', 'j'), 44),\n",
       " (('z', 'h'), 43),\n",
       " (('c', 'c'), 42),\n",
       " (('r', 'b'), 41),\n",
       " (('x', 'o'), 41),\n",
       " (('b', 'h'), 41),\n",
       " (('p', 'p'), 39),\n",
       " (('x', 'l'), 39),\n",
       " (('h', 'v'), 39),\n",
       " (('b', 'b'), 38),\n",
       " (('m', 'p'), 38),\n",
       " (('x', 'x'), 38),\n",
       " (('u', 'v'), 37),\n",
       " (('x', 'e'), 36),\n",
       " (('w', 'o'), 36),\n",
       " (('c', 't'), 35),\n",
       " (('z', 'm'), 35),\n",
       " (('t', 's'), 35),\n",
       " (('m', 's'), 35),\n",
       " (('c', 'u'), 35),\n",
       " (('o', 'f'), 34),\n",
       " (('u', 'x'), 34),\n",
       " (('k', 'w'), 34),\n",
       " (('g', 'l'), 32),\n",
       " (('z', 'r'), 32),\n",
       " (('d', 'n'), 31),\n",
       " (('g', 't'), 31),\n",
       " (('g', 'y'), 31),\n",
       " (('h', 's'), 31),\n",
       " (('x', 's'), 31),\n",
       " (('g', 's'), 30),\n",
       " (('x', 'y'), 30),\n",
       " (('y', 'g'), 30),\n",
       " (('d', 'm'), 30),\n",
       " (('d', 's'), 29),\n",
       " (('h', 'k'), 29),\n",
       " (('y', 'x'), 28),\n",
       " (('g', 'n'), 27),\n",
       " (('y', 'b'), 27),\n",
       " (('g', 'w'), 26),\n",
       " (('n', 'h'), 26),\n",
       " (('k', 'n'), 26),\n",
       " (('g', 'g'), 25),\n",
       " (('d', 'g'), 25),\n",
       " (('l', 'c'), 25),\n",
       " (('r', 'j'), 25),\n",
       " (('w', 'u'), 25),\n",
       " (('l', 'k'), 24),\n",
       " (('m', 'd'), 24),\n",
       " (('s', 'w'), 24),\n",
       " (('s', 'n'), 24),\n",
       " (('h', 'd'), 24),\n",
       " (('w', 'h'), 23),\n",
       " (('y', 'j'), 23),\n",
       " (('y', 'y'), 23),\n",
       " (('r', 'z'), 23),\n",
       " (('d', 'w'), 23),\n",
       " (('w', 'r'), 22),\n",
       " (('t', 'n'), 22),\n",
       " (('l', 'f'), 22),\n",
       " (('y', 'h'), 22),\n",
       " (('r', 'w'), 21),\n",
       " (('s', 'b'), 21),\n",
       " (('m', 'n'), 20),\n",
       " (('f', 'l'), 20),\n",
       " (('w', 's'), 20),\n",
       " (('k', 'k'), 20),\n",
       " (('h', 'z'), 20),\n",
       " (('g', 'd'), 19),\n",
       " (('l', 'h'), 19),\n",
       " (('n', 'm'), 19),\n",
       " (('x', 'z'), 19),\n",
       " (('u', 'f'), 19),\n",
       " (('f', 't'), 18),\n",
       " (('l', 'r'), 18),\n",
       " (('p', 't'), 17),\n",
       " (('t', 'c'), 17),\n",
       " (('k', 't'), 17),\n",
       " (('d', 'v'), 17),\n",
       " (('u', 'p'), 16),\n",
       " (('p', 'l'), 16),\n",
       " (('l', 'w'), 16),\n",
       " (('p', 's'), 16),\n",
       " (('o', 'j'), 16),\n",
       " (('r', 'q'), 16),\n",
       " (('y', 'p'), 15),\n",
       " (('l', 'p'), 15),\n",
       " (('t', 'v'), 15),\n",
       " (('r', 'p'), 14),\n",
       " (('l', 'n'), 14),\n",
       " (('e', 'q'), 14),\n",
       " (('f', 'y'), 14),\n",
       " (('s', 'v'), 14),\n",
       " (('u', 'j'), 14),\n",
       " (('v', 'l'), 14),\n",
       " (('q', 'a'), 13),\n",
       " (('u', 'y'), 13),\n",
       " (('q', 'i'), 13),\n",
       " (('w', 'l'), 13),\n",
       " (('p', 'y'), 12),\n",
       " (('y', 'f'), 12),\n",
       " (('c', 'q'), 11),\n",
       " (('j', 'r'), 11),\n",
       " (('n', 'w'), 11),\n",
       " (('n', 'f'), 11),\n",
       " (('t', 'w'), 11),\n",
       " (('m', 'z'), 11),\n",
       " (('u', 'o'), 10),\n",
       " (('f', 'u'), 10),\n",
       " (('l', 'z'), 10),\n",
       " (('h', 'w'), 10),\n",
       " (('u', 'q'), 10),\n",
       " (('j', 'y'), 10),\n",
       " (('s', 'z'), 10),\n",
       " (('s', 'd'), 9),\n",
       " (('j', 'l'), 9),\n",
       " (('d', 'j'), 9),\n",
       " (('k', 'm'), 9),\n",
       " (('r', 'f'), 9),\n",
       " (('h', 'j'), 9),\n",
       " (('v', 'n'), 8),\n",
       " (('n', 'b'), 8),\n",
       " (('i', 'w'), 8),\n",
       " (('h', 'b'), 8),\n",
       " (('b', 's'), 8),\n",
       " (('w', 't'), 8),\n",
       " (('w', 'd'), 8),\n",
       " (('v', 'v'), 7),\n",
       " (('v', 'u'), 7),\n",
       " (('j', 's'), 7),\n",
       " (('m', 'j'), 7),\n",
       " (('f', 's'), 6),\n",
       " (('l', 'g'), 6),\n",
       " (('l', 'j'), 6),\n",
       " (('j', 'w'), 6),\n",
       " (('n', 'x'), 6),\n",
       " (('y', 'q'), 6),\n",
       " (('w', 'k'), 6),\n",
       " (('g', 'm'), 6),\n",
       " (('x', 'u'), 5),\n",
       " (('m', 'h'), 5),\n",
       " (('m', 'l'), 5),\n",
       " (('j', 'm'), 5),\n",
       " (('c', 's'), 5),\n",
       " (('j', 'v'), 5),\n",
       " (('n', 'p'), 5),\n",
       " (('d', 'f'), 5),\n",
       " (('x', 'd'), 5),\n",
       " (('z', 'b'), 4),\n",
       " (('f', 'n'), 4),\n",
       " (('x', 'c'), 4),\n",
       " (('m', 't'), 4),\n",
       " (('t', 'm'), 4),\n",
       " (('z', 'n'), 4),\n",
       " (('z', 't'), 4),\n",
       " (('p', 'u'), 4),\n",
       " (('c', 'z'), 4),\n",
       " (('b', 'n'), 4),\n",
       " (('z', 's'), 4),\n",
       " (('f', 'w'), 4),\n",
       " (('d', 't'), 4),\n",
       " (('j', 'd'), 4),\n",
       " (('j', 'c'), 4),\n",
       " (('y', 'w'), 4),\n",
       " (('v', 'k'), 3),\n",
       " (('x', 'w'), 3),\n",
       " (('t', 'j'), 3),\n",
       " (('c', 'j'), 3),\n",
       " (('q', 'w'), 3),\n",
       " (('g', 'b'), 3),\n",
       " (('o', 'q'), 3),\n",
       " (('r', 'x'), 3),\n",
       " (('d', 'c'), 3),\n",
       " (('g', 'j'), 3),\n",
       " (('x', 'f'), 3),\n",
       " (('z', 'w'), 3),\n",
       " (('d', 'k'), 3),\n",
       " (('u', 'u'), 3),\n",
       " (('m', 'v'), 3),\n",
       " (('c', 'x'), 3),\n",
       " (('l', 'q'), 3),\n",
       " (('p', 'b'), 2),\n",
       " (('t', 'g'), 2),\n",
       " (('q', 's'), 2),\n",
       " (('t', 'x'), 2),\n",
       " (('f', 'k'), 2),\n",
       " (('b', 't'), 2),\n",
       " (('j', 'n'), 2),\n",
       " (('k', 'c'), 2),\n",
       " (('z', 'k'), 2),\n",
       " (('s', 'j'), 2),\n",
       " (('s', 'f'), 2),\n",
       " (('z', 'j'), 2),\n",
       " (('n', 'q'), 2),\n",
       " (('f', 'z'), 2),\n",
       " (('h', 'g'), 2),\n",
       " (('w', 'w'), 2),\n",
       " (('k', 'j'), 2),\n",
       " (('j', 'k'), 2),\n",
       " (('w', 'm'), 2),\n",
       " (('z', 'c'), 2),\n",
       " (('z', 'v'), 2),\n",
       " (('w', 'f'), 2),\n",
       " (('q', 'm'), 2),\n",
       " (('k', 'z'), 2),\n",
       " (('j', 'j'), 2),\n",
       " (('z', 'p'), 2),\n",
       " (('j', 't'), 2),\n",
       " (('k', 'b'), 2),\n",
       " (('m', 'w'), 2),\n",
       " (('h', 'f'), 2),\n",
       " (('c', 'g'), 2),\n",
       " (('t', 'f'), 2),\n",
       " (('h', 'c'), 2),\n",
       " (('q', 'o'), 2),\n",
       " (('k', 'd'), 2),\n",
       " (('k', 'v'), 2),\n",
       " (('s', 'g'), 2),\n",
       " (('z', 'd'), 2),\n",
       " (('q', 'r'), 1),\n",
       " (('d', 'z'), 1),\n",
       " (('p', 'j'), 1),\n",
       " (('q', 'l'), 1),\n",
       " (('p', 'f'), 1),\n",
       " (('q', 'e'), 1),\n",
       " (('b', 'c'), 1),\n",
       " (('c', 'd'), 1),\n",
       " (('m', 'f'), 1),\n",
       " (('p', 'n'), 1),\n",
       " (('w', 'b'), 1),\n",
       " (('p', 'c'), 1),\n",
       " (('h', 'p'), 1),\n",
       " (('f', 'h'), 1),\n",
       " (('b', 'j'), 1),\n",
       " (('f', 'g'), 1),\n",
       " (('z', 'g'), 1),\n",
       " (('c', 'p'), 1),\n",
       " (('p', 'k'), 1),\n",
       " (('p', 'm'), 1),\n",
       " (('x', 'n'), 1),\n",
       " (('s', 'q'), 1),\n",
       " (('k', 'f'), 1),\n",
       " (('m', 'k'), 1),\n",
       " (('x', 'h'), 1),\n",
       " (('g', 'f'), 1),\n",
       " (('v', 'b'), 1),\n",
       " (('j', 'p'), 1),\n",
       " (('g', 'z'), 1),\n",
       " (('v', 'd'), 1),\n",
       " (('d', 'b'), 1),\n",
       " (('v', 'h'), 1),\n",
       " (('h', 'h'), 1),\n",
       " (('g', 'v'), 1),\n",
       " (('d', 'q'), 1),\n",
       " (('x', 'b'), 1),\n",
       " (('w', 'z'), 1),\n",
       " (('h', 'q'), 1),\n",
       " (('j', 'b'), 1),\n",
       " (('x', 'm'), 1),\n",
       " (('w', 'g'), 1),\n",
       " (('t', 'b'), 1),\n",
       " (('z', 'x'), 1)]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "words = open(\"names.txt\").read().splitlines()\n",
    "words[:10]\n",
    "len(words)\n",
    "min(len(w) for w in words)\n",
    "max(len(w) for w in words)\n",
    "\n",
    "b = {}\n",
    "for w in words:\n",
    "    # why use list instead of string?\n",
    "    chs = ['<S>'] + list(w) + ['<E>']\n",
    "    for ch1, ch2 in zip(w, w[1:]):\n",
    "        bigram = (ch1, ch2)\n",
    "        b[bigram] = b.get(bigram, 0) + 1\n",
    "\n",
    "sorted(b.items(), key=lambda x: -x[1])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "27"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import torch\n",
    "N = torch.zeros((27, 27), dtype=torch.int32)\n",
    "chars = sorted(list(set(''.join(words))))\n",
    "stoi = {c: i+1 for i, c in enumerate(chars)}\n",
    "stoi['.'] = 0\n",
    "itos = {i: c for c, i in stoi.items()}\n",
    "len(itos)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(('a', 'n'), 5438),\n",
       " (('a', 'r'), 3264),\n",
       " (('e', 'l'), 3248),\n",
       " (('r', 'i'), 3033),\n",
       " (('n', 'a'), 2977),\n",
       " (('l', 'e'), 2921),\n",
       " (('e', 'n'), 2675),\n",
       " (('l', 'a'), 2623),\n",
       " (('m', 'a'), 2590),\n",
       " (('a', 'l'), 2528),\n",
       " (('l', 'i'), 2480),\n",
       " (('i', 'a'), 2445),\n",
       " (('o', 'n'), 2411),\n",
       " (('r', 'a'), 2356),\n",
       " (('a', 'h'), 2332),\n",
       " (('h', 'a'), 2244),\n",
       " (('y', 'a'), 2143),\n",
       " (('i', 'n'), 2126),\n",
       " (('a', 'y'), 2050),\n",
       " (('e', 'r'), 1958),\n",
       " (('n', 'n'), 1906),\n",
       " (('y', 'n'), 1826),\n",
       " (('k', 'a'), 1731),\n",
       " (('n', 'i'), 1725),\n",
       " (('r', 'e'), 1697),\n",
       " (('i', 'e'), 1653),\n",
       " (('a', 'i'), 1650),\n",
       " (('a', 'm'), 1634),\n",
       " (('l', 'y'), 1588),\n",
       " (('j', 'a'), 1473),\n",
       " (('n', 'e'), 1359),\n",
       " (('l', 'l'), 1345),\n",
       " (('i', 'l'), 1345),\n",
       " (('i', 's'), 1316),\n",
       " (('d', 'a'), 1303),\n",
       " (('s', 'h'), 1285),\n",
       " (('d', 'e'), 1283),\n",
       " (('e', 'e'), 1271),\n",
       " (('m', 'i'), 1256),\n",
       " (('s', 'a'), 1201),\n",
       " (('a', 's'), 1118),\n",
       " (('y', 'l'), 1104),\n",
       " (('e', 'y'), 1070),\n",
       " (('o', 'r'), 1059),\n",
       " (('a', 'd'), 1042),\n",
       " (('t', 'a'), 1027),\n",
       " (('v', 'i'), 911),\n",
       " (('k', 'e'), 895),\n",
       " (('s', 'e'), 884),\n",
       " (('r', 'o'), 869),\n",
       " (('e', 's'), 861),\n",
       " (('z', 'a'), 860),\n",
       " (('i', 'r'), 849),\n",
       " (('b', 'r'), 842),\n",
       " (('a', 'v'), 834),\n",
       " (('m', 'e'), 818),\n",
       " (('e', 'i'), 818),\n",
       " (('c', 'a'), 815),\n",
       " (('i', 'y'), 779),\n",
       " (('r', 'y'), 773),\n",
       " (('e', 'm'), 769),\n",
       " (('s', 't'), 765),\n",
       " (('h', 'i'), 729),\n",
       " (('t', 'e'), 716),\n",
       " (('n', 'd'), 704),\n",
       " (('l', 'o'), 692),\n",
       " (('a', 'e'), 692),\n",
       " (('a', 't'), 687),\n",
       " (('s', 'i'), 684),\n",
       " (('e', 'a'), 679),\n",
       " (('d', 'i'), 674),\n",
       " (('h', 'e'), 674),\n",
       " (('t', 'o'), 667),\n",
       " (('c', 'h'), 664),\n",
       " (('b', 'e'), 655),\n",
       " (('t', 'h'), 647),\n",
       " (('v', 'a'), 642),\n",
       " (('o', 'l'), 619),\n",
       " (('i', 'o'), 588),\n",
       " (('e', 't'), 580),\n",
       " (('v', 'e'), 568),\n",
       " (('a', 'k'), 568),\n",
       " (('a', 'a'), 556),\n",
       " (('c', 'e'), 551),\n",
       " (('a', 'b'), 541),\n",
       " (('i', 't'), 541),\n",
       " (('t', 'i'), 532),\n",
       " (('s', 'o'), 531),\n",
       " (('i', 'c'), 509),\n",
       " (('k', 'i'), 509),\n",
       " (('o', 's'), 504),\n",
       " (('n', 'o'), 496),\n",
       " (('j', 'o'), 479),\n",
       " (('u', 's'), 474),\n",
       " (('a', 'c'), 470),\n",
       " (('n', 'y'), 465),\n",
       " (('e', 'v'), 463),\n",
       " (('s', 's'), 461),\n",
       " (('m', 'o'), 452),\n",
       " (('i', 'k'), 445),\n",
       " (('n', 't'), 443),\n",
       " (('i', 'd'), 440),\n",
       " (('j', 'e'), 440),\n",
       " (('a', 'z'), 435),\n",
       " (('i', 'g'), 428),\n",
       " (('i', 'm'), 427),\n",
       " (('r', 'r'), 425),\n",
       " (('d', 'r'), 424),\n",
       " (('u', 'r'), 414),\n",
       " (('r', 'l'), 413),\n",
       " (('y', 's'), 401),\n",
       " (('e', 'd'), 384),\n",
       " (('a', 'u'), 381),\n",
       " (('c', 'o'), 380),\n",
       " (('k', 'y'), 379),\n",
       " (('d', 'o'), 378),\n",
       " (('t', 't'), 374),\n",
       " (('z', 'e'), 373),\n",
       " (('z', 'i'), 364),\n",
       " (('g', 'h'), 360),\n",
       " (('t', 'r'), 352),\n",
       " (('k', 'o'), 344),\n",
       " (('t', 'y'), 341),\n",
       " (('g', 'e'), 334),\n",
       " (('g', 'a'), 330),\n",
       " (('l', 'u'), 324),\n",
       " (('b', 'a'), 321),\n",
       " (('d', 'y'), 317),\n",
       " (('c', 'k'), 316),\n",
       " (('k', 'h'), 307),\n",
       " (('u', 'l'), 301),\n",
       " (('y', 'e'), 301),\n",
       " (('y', 'r'), 291),\n",
       " (('m', 'y'), 287),\n",
       " (('h', 'o'), 287),\n",
       " (('w', 'a'), 280),\n",
       " (('s', 'l'), 279),\n",
       " (('n', 's'), 278),\n",
       " (('i', 'z'), 277),\n",
       " (('u', 'n'), 275),\n",
       " (('o', 'u'), 275),\n",
       " (('n', 'g'), 273),\n",
       " (('y', 'd'), 272),\n",
       " (('c', 'i'), 271),\n",
       " (('y', 'o'), 271),\n",
       " (('i', 'v'), 269),\n",
       " (('e', 'o'), 269),\n",
       " (('o', 'm'), 261),\n",
       " (('r', 'u'), 252),\n",
       " (('f', 'a'), 242),\n",
       " (('b', 'i'), 217),\n",
       " (('s', 'y'), 215),\n",
       " (('n', 'c'), 213),\n",
       " (('h', 'y'), 213),\n",
       " (('p', 'a'), 209),\n",
       " (('r', 't'), 208),\n",
       " (('q', 'u'), 206),\n",
       " (('p', 'h'), 204),\n",
       " (('h', 'r'), 204),\n",
       " (('j', 'u'), 202),\n",
       " (('g', 'r'), 201),\n",
       " (('p', 'e'), 197),\n",
       " (('n', 'l'), 195),\n",
       " (('y', 'i'), 192),\n",
       " (('g', 'i'), 190),\n",
       " (('o', 'd'), 190),\n",
       " (('r', 's'), 190),\n",
       " (('r', 'd'), 187),\n",
       " (('h', 'l'), 185),\n",
       " (('s', 'u'), 185),\n",
       " (('a', 'x'), 182),\n",
       " (('e', 'z'), 181),\n",
       " (('e', 'k'), 178),\n",
       " (('o', 'v'), 176),\n",
       " (('a', 'j'), 175),\n",
       " (('o', 'h'), 171),\n",
       " (('u', 'e'), 169),\n",
       " (('m', 'm'), 168),\n",
       " (('a', 'g'), 168),\n",
       " (('h', 'u'), 166),\n",
       " (('u', 'a'), 163),\n",
       " (('r', 'm'), 162),\n",
       " (('a', 'w'), 161),\n",
       " (('f', 'i'), 160),\n",
       " (('u', 'm'), 154),\n",
       " (('e', 'c'), 153),\n",
       " (('v', 'o'), 153),\n",
       " (('e', 'h'), 152),\n",
       " (('p', 'r'), 151),\n",
       " (('d', 'd'), 149),\n",
       " (('o', 'a'), 149),\n",
       " (('w', 'e'), 149),\n",
       " (('w', 'i'), 148),\n",
       " (('y', 'm'), 148),\n",
       " (('z', 'y'), 147),\n",
       " (('n', 'z'), 145),\n",
       " (('y', 'u'), 141),\n",
       " (('r', 'n'), 140),\n",
       " (('o', 'b'), 140),\n",
       " (('k', 'l'), 139),\n",
       " (('m', 'u'), 139),\n",
       " (('l', 'd'), 138),\n",
       " (('h', 'n'), 138),\n",
       " (('u', 'd'), 136),\n",
       " (('t', 'l'), 134),\n",
       " (('a', 'f'), 134),\n",
       " (('o', 'e'), 132),\n",
       " (('e', 'x'), 132),\n",
       " (('e', 'g'), 125),\n",
       " (('f', 'e'), 123),\n",
       " (('z', 'l'), 123),\n",
       " (('u', 'i'), 121),\n",
       " (('v', 'y'), 121),\n",
       " (('e', 'b'), 121),\n",
       " (('r', 'h'), 121),\n",
       " (('j', 'i'), 119),\n",
       " (('o', 't'), 118),\n",
       " (('d', 'h'), 118),\n",
       " (('h', 'm'), 117),\n",
       " (('c', 'l'), 116),\n",
       " (('o', 'o'), 115),\n",
       " (('y', 'c'), 115),\n",
       " (('o', 'w'), 114),\n",
       " (('o', 'c'), 114),\n",
       " (('f', 'r'), 114),\n",
       " (('m', 'b'), 112),\n",
       " (('z', 'o'), 110),\n",
       " (('i', 'b'), 110),\n",
       " (('i', 'u'), 109),\n",
       " (('k', 'r'), 109),\n",
       " (('y', 'v'), 106),\n",
       " (('t', 'z'), 105),\n",
       " (('b', 'o'), 105),\n",
       " (('c', 'y'), 104),\n",
       " (('y', 't'), 104),\n",
       " (('u', 'b'), 103),\n",
       " (('u', 'c'), 103),\n",
       " (('x', 'a'), 103),\n",
       " (('b', 'l'), 103),\n",
       " (('o', 'y'), 103),\n",
       " (('x', 'i'), 102),\n",
       " (('i', 'f'), 101),\n",
       " (('r', 'c'), 99),\n",
       " (('m', 'r'), 97),\n",
       " (('n', 'u'), 96),\n",
       " (('o', 'p'), 95),\n",
       " (('i', 'h'), 95),\n",
       " (('k', 's'), 95),\n",
       " (('l', 's'), 94),\n",
       " (('u', 'k'), 93),\n",
       " (('d', 'u'), 92),\n",
       " (('s', 'm'), 90),\n",
       " (('r', 'k'), 90),\n",
       " (('i', 'x'), 89),\n",
       " (('y', 'k'), 86),\n",
       " (('u', 'w'), 86),\n",
       " (('g', 'u'), 85),\n",
       " (('b', 'y'), 83),\n",
       " (('e', 'p'), 83),\n",
       " (('g', 'o'), 83),\n",
       " (('s', 'k'), 82),\n",
       " (('u', 't'), 82),\n",
       " (('a', 'p'), 82),\n",
       " (('e', 'f'), 82),\n",
       " (('i', 'i'), 82),\n",
       " (('r', 'v'), 80),\n",
       " (('t', 'u'), 78),\n",
       " (('y', 'z'), 78),\n",
       " (('l', 't'), 77),\n",
       " (('r', 'g'), 76),\n",
       " (('c', 'r'), 76),\n",
       " (('i', 'j'), 76),\n",
       " (('w', 'y'), 73),\n",
       " (('z', 'u'), 73),\n",
       " (('l', 'v'), 72),\n",
       " (('h', 't'), 71),\n",
       " (('x', 't'), 70),\n",
       " (('o', 'i'), 69),\n",
       " (('e', 'u'), 69),\n",
       " (('o', 'k'), 68),\n",
       " (('b', 'd'), 65),\n",
       " (('a', 'o'), 63),\n",
       " (('p', 'i'), 61),\n",
       " (('s', 'c'), 60),\n",
       " (('d', 'l'), 60),\n",
       " (('l', 'm'), 60),\n",
       " (('a', 'q'), 60),\n",
       " (('f', 'o'), 60),\n",
       " (('p', 'o'), 59),\n",
       " (('n', 'k'), 58),\n",
       " (('w', 'n'), 58),\n",
       " (('u', 'h'), 58),\n",
       " (('e', 'j'), 55),\n",
       " (('n', 'v'), 55),\n",
       " (('s', 'r'), 55),\n",
       " (('o', 'z'), 54),\n",
       " (('i', 'p'), 53),\n",
       " (('l', 'b'), 52),\n",
       " (('i', 'q'), 52),\n",
       " (('m', 'c'), 51),\n",
       " (('s', 'p'), 51),\n",
       " (('e', 'w'), 50),\n",
       " (('k', 'u'), 50),\n",
       " (('v', 'r'), 48),\n",
       " (('u', 'g'), 47),\n",
       " (('o', 'x'), 45),\n",
       " (('u', 'z'), 45),\n",
       " (('z', 'z'), 45),\n",
       " (('j', 'h'), 45),\n",
       " (('b', 'u'), 45),\n",
       " (('o', 'g'), 44),\n",
       " (('n', 'r'), 44),\n",
       " (('f', 'f'), 44),\n",
       " (('n', 'j'), 44),\n",
       " (('z', 'h'), 43),\n",
       " (('c', 'c'), 42),\n",
       " (('r', 'b'), 41),\n",
       " (('x', 'o'), 41),\n",
       " (('b', 'h'), 41),\n",
       " (('p', 'p'), 39),\n",
       " (('x', 'l'), 39),\n",
       " (('h', 'v'), 39),\n",
       " (('b', 'b'), 38),\n",
       " (('m', 'p'), 38),\n",
       " (('x', 'x'), 38),\n",
       " (('u', 'v'), 37),\n",
       " (('x', 'e'), 36),\n",
       " (('w', 'o'), 36),\n",
       " (('c', 't'), 35),\n",
       " (('z', 'm'), 35),\n",
       " (('t', 's'), 35),\n",
       " (('m', 's'), 35),\n",
       " (('c', 'u'), 35),\n",
       " (('o', 'f'), 34),\n",
       " (('u', 'x'), 34),\n",
       " (('k', 'w'), 34),\n",
       " (('g', 'l'), 32),\n",
       " (('z', 'r'), 32),\n",
       " (('d', 'n'), 31),\n",
       " (('g', 't'), 31),\n",
       " (('g', 'y'), 31),\n",
       " (('h', 's'), 31),\n",
       " (('x', 's'), 31),\n",
       " (('g', 's'), 30),\n",
       " (('x', 'y'), 30),\n",
       " (('y', 'g'), 30),\n",
       " (('d', 'm'), 30),\n",
       " (('d', 's'), 29),\n",
       " (('h', 'k'), 29),\n",
       " (('y', 'x'), 28),\n",
       " (('g', 'n'), 27),\n",
       " (('y', 'b'), 27),\n",
       " (('g', 'w'), 26),\n",
       " (('n', 'h'), 26),\n",
       " (('k', 'n'), 26),\n",
       " (('g', 'g'), 25),\n",
       " (('d', 'g'), 25),\n",
       " (('l', 'c'), 25),\n",
       " (('r', 'j'), 25),\n",
       " (('w', 'u'), 25),\n",
       " (('l', 'k'), 24),\n",
       " (('m', 'd'), 24),\n",
       " (('s', 'w'), 24),\n",
       " (('s', 'n'), 24),\n",
       " (('h', 'd'), 24),\n",
       " (('w', 'h'), 23),\n",
       " (('y', 'j'), 23),\n",
       " (('y', 'y'), 23),\n",
       " (('r', 'z'), 23),\n",
       " (('d', 'w'), 23),\n",
       " (('w', 'r'), 22),\n",
       " (('t', 'n'), 22),\n",
       " (('l', 'f'), 22),\n",
       " (('y', 'h'), 22),\n",
       " (('r', 'w'), 21),\n",
       " (('s', 'b'), 21),\n",
       " (('m', 'n'), 20),\n",
       " (('f', 'l'), 20),\n",
       " (('w', 's'), 20),\n",
       " (('k', 'k'), 20),\n",
       " (('h', 'z'), 20),\n",
       " (('g', 'd'), 19),\n",
       " (('l', 'h'), 19),\n",
       " (('n', 'm'), 19),\n",
       " (('x', 'z'), 19),\n",
       " (('u', 'f'), 19),\n",
       " (('f', 't'), 18),\n",
       " (('l', 'r'), 18),\n",
       " (('p', 't'), 17),\n",
       " (('t', 'c'), 17),\n",
       " (('k', 't'), 17),\n",
       " (('d', 'v'), 17),\n",
       " (('u', 'p'), 16),\n",
       " (('p', 'l'), 16),\n",
       " (('l', 'w'), 16),\n",
       " (('p', 's'), 16),\n",
       " (('o', 'j'), 16),\n",
       " (('r', 'q'), 16),\n",
       " (('y', 'p'), 15),\n",
       " (('l', 'p'), 15),\n",
       " (('t', 'v'), 15),\n",
       " (('r', 'p'), 14),\n",
       " (('l', 'n'), 14),\n",
       " (('e', 'q'), 14),\n",
       " (('f', 'y'), 14),\n",
       " (('s', 'v'), 14),\n",
       " (('u', 'j'), 14),\n",
       " (('v', 'l'), 14),\n",
       " (('q', 'a'), 13),\n",
       " (('u', 'y'), 13),\n",
       " (('q', 'i'), 13),\n",
       " (('w', 'l'), 13),\n",
       " (('p', 'y'), 12),\n",
       " (('y', 'f'), 12),\n",
       " (('c', 'q'), 11),\n",
       " (('j', 'r'), 11),\n",
       " (('n', 'w'), 11),\n",
       " (('n', 'f'), 11),\n",
       " (('t', 'w'), 11),\n",
       " (('m', 'z'), 11),\n",
       " (('u', 'o'), 10),\n",
       " (('f', 'u'), 10),\n",
       " (('l', 'z'), 10),\n",
       " (('h', 'w'), 10),\n",
       " (('u', 'q'), 10),\n",
       " (('j', 'y'), 10),\n",
       " (('s', 'z'), 10),\n",
       " (('s', 'd'), 9),\n",
       " (('j', 'l'), 9),\n",
       " (('d', 'j'), 9),\n",
       " (('k', 'm'), 9),\n",
       " (('r', 'f'), 9),\n",
       " (('h', 'j'), 9),\n",
       " (('v', 'n'), 8),\n",
       " (('n', 'b'), 8),\n",
       " (('i', 'w'), 8),\n",
       " (('h', 'b'), 8),\n",
       " (('b', 's'), 8),\n",
       " (('w', 't'), 8),\n",
       " (('w', 'd'), 8),\n",
       " (('v', 'v'), 7),\n",
       " (('v', 'u'), 7),\n",
       " (('j', 's'), 7),\n",
       " (('m', 'j'), 7),\n",
       " (('f', 's'), 6),\n",
       " (('l', 'g'), 6),\n",
       " (('l', 'j'), 6),\n",
       " (('j', 'w'), 6),\n",
       " (('n', 'x'), 6),\n",
       " (('y', 'q'), 6),\n",
       " (('w', 'k'), 6),\n",
       " (('g', 'm'), 6),\n",
       " (('x', 'u'), 5),\n",
       " (('m', 'h'), 5),\n",
       " (('m', 'l'), 5),\n",
       " (('j', 'm'), 5),\n",
       " (('c', 's'), 5),\n",
       " (('j', 'v'), 5),\n",
       " (('n', 'p'), 5),\n",
       " (('d', 'f'), 5),\n",
       " (('x', 'd'), 5),\n",
       " (('z', 'b'), 4),\n",
       " (('f', 'n'), 4),\n",
       " (('x', 'c'), 4),\n",
       " (('m', 't'), 4),\n",
       " (('t', 'm'), 4),\n",
       " (('z', 'n'), 4),\n",
       " (('z', 't'), 4),\n",
       " (('p', 'u'), 4),\n",
       " (('c', 'z'), 4),\n",
       " (('b', 'n'), 4),\n",
       " (('z', 's'), 4),\n",
       " (('f', 'w'), 4),\n",
       " (('d', 't'), 4),\n",
       " (('j', 'd'), 4),\n",
       " (('j', 'c'), 4),\n",
       " (('y', 'w'), 4),\n",
       " (('v', 'k'), 3),\n",
       " (('x', 'w'), 3),\n",
       " (('t', 'j'), 3),\n",
       " (('c', 'j'), 3),\n",
       " (('q', 'w'), 3),\n",
       " (('g', 'b'), 3),\n",
       " (('o', 'q'), 3),\n",
       " (('r', 'x'), 3),\n",
       " (('d', 'c'), 3),\n",
       " (('g', 'j'), 3),\n",
       " (('x', 'f'), 3),\n",
       " (('z', 'w'), 3),\n",
       " (('d', 'k'), 3),\n",
       " (('u', 'u'), 3),\n",
       " (('m', 'v'), 3),\n",
       " (('c', 'x'), 3),\n",
       " (('l', 'q'), 3),\n",
       " (('p', 'b'), 2),\n",
       " (('t', 'g'), 2),\n",
       " (('q', 's'), 2),\n",
       " (('t', 'x'), 2),\n",
       " (('f', 'k'), 2),\n",
       " (('b', 't'), 2),\n",
       " (('j', 'n'), 2),\n",
       " (('k', 'c'), 2),\n",
       " (('z', 'k'), 2),\n",
       " (('s', 'j'), 2),\n",
       " (('s', 'f'), 2),\n",
       " (('z', 'j'), 2),\n",
       " (('n', 'q'), 2),\n",
       " (('f', 'z'), 2),\n",
       " (('h', 'g'), 2),\n",
       " (('w', 'w'), 2),\n",
       " (('k', 'j'), 2),\n",
       " (('j', 'k'), 2),\n",
       " (('w', 'm'), 2),\n",
       " (('z', 'c'), 2),\n",
       " (('z', 'v'), 2),\n",
       " (('w', 'f'), 2),\n",
       " (('q', 'm'), 2),\n",
       " (('k', 'z'), 2),\n",
       " (('j', 'j'), 2),\n",
       " (('z', 'p'), 2),\n",
       " (('j', 't'), 2),\n",
       " (('k', 'b'), 2),\n",
       " (('m', 'w'), 2),\n",
       " (('h', 'f'), 2),\n",
       " (('c', 'g'), 2),\n",
       " (('t', 'f'), 2),\n",
       " (('h', 'c'), 2),\n",
       " (('q', 'o'), 2),\n",
       " (('k', 'd'), 2),\n",
       " (('k', 'v'), 2),\n",
       " (('s', 'g'), 2),\n",
       " (('z', 'd'), 2),\n",
       " (('q', 'r'), 1),\n",
       " (('d', 'z'), 1),\n",
       " (('p', 'j'), 1),\n",
       " (('q', 'l'), 1),\n",
       " (('p', 'f'), 1),\n",
       " (('q', 'e'), 1),\n",
       " (('b', 'c'), 1),\n",
       " (('c', 'd'), 1),\n",
       " (('m', 'f'), 1),\n",
       " (('p', 'n'), 1),\n",
       " (('w', 'b'), 1),\n",
       " (('p', 'c'), 1),\n",
       " (('h', 'p'), 1),\n",
       " (('f', 'h'), 1),\n",
       " (('b', 'j'), 1),\n",
       " (('f', 'g'), 1),\n",
       " (('z', 'g'), 1),\n",
       " (('c', 'p'), 1),\n",
       " (('p', 'k'), 1),\n",
       " (('p', 'm'), 1),\n",
       " (('x', 'n'), 1),\n",
       " (('s', 'q'), 1),\n",
       " (('k', 'f'), 1),\n",
       " (('m', 'k'), 1),\n",
       " (('x', 'h'), 1),\n",
       " (('g', 'f'), 1),\n",
       " (('v', 'b'), 1),\n",
       " (('j', 'p'), 1),\n",
       " (('g', 'z'), 1),\n",
       " (('v', 'd'), 1),\n",
       " (('d', 'b'), 1),\n",
       " (('v', 'h'), 1),\n",
       " (('h', 'h'), 1),\n",
       " (('g', 'v'), 1),\n",
       " (('d', 'q'), 1),\n",
       " (('x', 'b'), 1),\n",
       " (('w', 'z'), 1),\n",
       " (('h', 'q'), 1),\n",
       " (('j', 'b'), 1),\n",
       " (('x', 'm'), 1),\n",
       " (('w', 'g'), 1),\n",
       " (('t', 'b'), 1),\n",
       " (('z', 'x'), 1)]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#for biagram, c in b.items():\n",
    "#    ch1 = stoi[biagram[0]]\n",
    "#    ch2 = stoi[biagram[1]]\n",
    "#    N[ch1][ch2] = c\n",
    "\n",
    "for w in words:\n",
    "    # why use list instead of string?\n",
    "    chs = ['.'] + list(w) + ['.']\n",
    "    for ch1, ch2 in zip(chs, chs[1:]):\n",
    "        idx1 = stoi[ch1]\n",
    "        idx2 = stoi[ch2]\n",
    "        N[idx1][idx2] += 1\n",
    "\n",
    "sorted(b.items(), key=lambda x: -x[1])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-0.5, 26.5, 26.5, -0.5)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "%matplotlib  inline\n",
    "plt.imshow(N, cmap='Blues')\n",
    "for i in range(27):\n",
    "    for j in range(27):\n",
    "        chstr = itos[i] + itos[j]\n",
    "        #plt.text(j, i, chstr, ha='center', va='bottom', color='gray')\n",
    "        plt.text(j, i, N[i, j].item(), ha='center', va='top', color='gray')\n",
    "plt.axis('off')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([0.0000, 0.1377, 0.0408, 0.0481, 0.0528, 0.0478, 0.0130, 0.0209, 0.0273,\n",
       "        0.0184, 0.0756, 0.0925, 0.0491, 0.0792, 0.0358, 0.0123, 0.0161, 0.0029,\n",
       "        0.0512, 0.0642, 0.0408, 0.0024, 0.0117, 0.0096, 0.0042, 0.0167, 0.0290])"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "N[0]\n",
    "p = N[0].float()\n",
    "p = p/p.sum()\n",
    "p"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'c'"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "g = torch.Generator().manual_seed(2147483647)\n",
    "ix = torch.multinomial(p, num_samples=1, replacement=True, generator=g).item()\n",
    "itos[ix]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([ 9, 18,  2,  5,  3,  1, 13, 11, 11, 22, 11, 15, 26,  2, 18, 13, 10,  1,\n",
       "        15,  2,  3, 15, 10, 12,  4,  9,  3,  4,  6,  4, 19, 10,  3,  8,  4, 10,\n",
       "        13, 14, 13, 10, 19, 11,  8, 13,  5,  5,  6, 25, 20, 10, 18,  1,  8,  3,\n",
       "         2, 20,  1,  1,  3, 10, 11, 25, 18,  1,  9, 11,  8, 12,  3, 12, 19,  9,\n",
       "        18, 13,  4,  4, 13, 13,  8, 13,  1,  2,  4,  1,  6,  1,  1, 10, 14, 10,\n",
       "        13, 12, 10,  1,  1, 20, 18, 20, 19,  1])"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "torch.multinomial(p, num_samples=100, replacement=True, generator=g)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cexze\n",
      "momasurailezitynn\n",
      "konimittain\n",
      "llayn\n",
      "ka\n"
     ]
    }
   ],
   "source": [
    "P = (N+1).float()\n",
    "P = P/P.sum(1, keepdim=True)\n",
    "\n",
    "g = torch.Generator().manual_seed(2147483647)\n",
    "\n",
    "for i in range(5):\n",
    "    out = []\n",
    "    ix = 0\n",
    "    while True:\n",
    "        p = P[ix]\n",
    "        ix = torch.multinomial(p, num_samples=1, replacement=True, generator=g).item() \n",
    "        if itos[ix] == '.':\n",
    "            break\n",
    "        out.append(itos[ix])\n",
    "    print(''.join(out))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "log_likelihood=tensor(-559951.5625)\n",
      "nll=tensor(559951.5625)\n",
      "2.4543561935424805\n"
     ]
    }
   ],
   "source": [
    "log_likelihood = 0.0\n",
    "n = 0\n",
    "\n",
    "for w in words:\n",
    "    ws = ['.'] + list(w) + ['.']\n",
    "    for ch1, ch2 in zip(ws, ws[1:]):\n",
    "        prob = P[stoi[ch1]][stoi[ch2]]\n",
    "        logprob = torch.log(prob)\n",
    "        log_likelihood += logprob\n",
    "        n += 1\n",
    "\n",
    "print(f'{log_likelihood=}')\n",
    "nll = -log_likelihood\n",
    "print(f'{nll=}')\n",
    "print(f'{nll/n}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      ". e\n",
      "e m\n",
      "m m\n",
      "m a\n",
      "a .\n"
     ]
    }
   ],
   "source": [
    "# create the training set of bigrams (x,y)\n",
    "xs, ys = [], []\n",
    "for w in words[:1]:\n",
    "    chs = ['.'] + list(w) + ['.']\n",
    "    for idx, idy in zip(chs, chs[1:]):\n",
    "        print(idx, idy)\n",
    "        xs.append(stoi[idx])\n",
    "        ys.append(stoi[idy])\n",
    "\n",
    "xs = torch.tensor(xs)\n",
    "ys = torch.tensor(ys)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([ 0,  5, 13, 13,  1])\n",
      "tensor([ 5, 13, 13,  1,  0])\n"
     ]
    }
   ],
   "source": [
    "print(xs)\n",
    "print(ys)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x137f0bb50>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import torch.nn.functional as F\n",
    "xenc = F.one_hot(xs, num_classes=27).float()\n",
    "xenc\n",
    "xenc.shape\n",
    "plt.imshow(xenc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([[0.0117, 0.0148, 0.0783, 0.0309, 0.0084, 0.1647, 0.0228, 0.0145, 0.0567,\n",
       "         0.0164, 0.0169, 0.0174, 0.0674, 0.0255, 0.0039, 0.0533, 0.0791, 0.0102,\n",
       "         0.1096, 0.0245, 0.0425, 0.0055, 0.0505, 0.0186, 0.0213, 0.0183, 0.0162],\n",
       "        [0.1024, 0.0302, 0.0164, 0.0062, 0.0143, 0.0417, 0.0908, 0.0311, 0.0107,\n",
       "         0.0734, 0.0096, 0.1266, 0.0542, 0.0484, 0.0330, 0.0120, 0.0716, 0.0365,\n",
       "         0.0219, 0.0214, 0.0119, 0.0177, 0.0124, 0.0313, 0.0028, 0.0450, 0.0265],\n",
       "        [0.0175, 0.0146, 0.0362, 0.0472, 0.0023, 0.1229, 0.0923, 0.1391, 0.0038,\n",
       "         0.0108, 0.0971, 0.0039, 0.0129, 0.0139, 0.0288, 0.0982, 0.0280, 0.0319,\n",
       "         0.0075, 0.0298, 0.0128, 0.0289, 0.0243, 0.0157, 0.0494, 0.0106, 0.0197],\n",
       "        [0.0175, 0.0146, 0.0362, 0.0472, 0.0023, 0.1229, 0.0923, 0.1391, 0.0038,\n",
       "         0.0108, 0.0971, 0.0039, 0.0129, 0.0139, 0.0288, 0.0982, 0.0280, 0.0319,\n",
       "         0.0075, 0.0298, 0.0128, 0.0289, 0.0243, 0.0157, 0.0494, 0.0106, 0.0197],\n",
       "        [0.0166, 0.0112, 0.0061, 0.0078, 0.0432, 0.1042, 0.1077, 0.0047, 0.0252,\n",
       "         0.0109, 0.2239, 0.0116, 0.0421, 0.0521, 0.0363, 0.0458, 0.0158, 0.0152,\n",
       "         0.0038, 0.0558, 0.0355, 0.0031, 0.0047, 0.0080, 0.0230, 0.0170, 0.0688]])"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "W = torch.randn((27,27))\n",
    "# why log-counts\n",
    "logits = xenc@W # 为什么例子里已经是 (5, 27)\n",
    "counts = logits.exp()\n",
    "probs = counts / counts.sum(1, keepdim=True)\n",
    "probs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor(1.0000)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "probs[0]\n",
    "probs[0].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "# randomly initialize 27 neuron's weights. each neuron receives 27 inputs\n",
    "g = torch.Generator().manual_seed(2147483647)\n",
    "W = torch.randn((27,27), generator=g)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "torch.Size([5, 27])"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 不需要权重？\n",
    "xenc = F.one_hot(xs, num_classes=27).float() # input to the network: one-hot encoding\n",
    "# 为什么还需要乘以 W？\n",
    "logits = xenc@W # predict log-counts\n",
    "# this is called a 'softmax'\n",
    "counts = logits.exp()\n",
    "probs = counts/counts.sum(1, keepdim=True)\n",
    "probs.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--------\n",
      "bigram example 1: .e (indexes 0,5)\n",
      "input to the neural net: 0\n",
      "label (actual next character): 5\n",
      "probs assigned by the net to the correct character: 0.012286253273487091\n",
      "log likelihood: -4.3992743492126465\n",
      "negaive log likelihood: 4.3992743492126465\n",
      "--------\n",
      "bigram example 2: em (indexes 5,13)\n",
      "input to the neural net: 5\n",
      "label (actual next character): 13\n",
      "probs assigned by the net to the correct character: 0.018050702288746834\n",
      "log likelihood: -4.014570713043213\n",
      "negaive log likelihood: 4.014570713043213\n",
      "--------\n",
      "bigram example 3: mm (indexes 13,13)\n",
      "input to the neural net: 13\n",
      "label (actual next character): 13\n",
      "probs assigned by the net to the correct character: 0.026691533625125885\n",
      "log likelihood: -3.623408794403076\n",
      "negaive log likelihood: 3.623408794403076\n",
      "--------\n",
      "bigram example 4: ma (indexes 13,1)\n",
      "input to the neural net: 13\n",
      "label (actual next character): 1\n",
      "probs assigned by the net to the correct character: 0.07367684692144394\n",
      "log likelihood: -2.6080667972564697\n",
      "negaive log likelihood: 2.6080667972564697\n",
      "--------\n",
      "bigram example 5: a. (indexes 1,0)\n",
      "input to the neural net: 1\n",
      "label (actual next character): 0\n",
      "probs assigned by the net to the correct character: 0.0149775305762887\n",
      "log likelihood: -4.201204299926758\n",
      "negaive log likelihood: 4.201204299926758\n",
      "===========\n",
      "average negative log likelihood, i.e., loss = 3.7693049907684326\n"
     ]
    }
   ],
   "source": [
    "nlls = torch.zeros(5)\n",
    "\n",
    "for i in range(5):\n",
    "    # i-th bigram\n",
    "    x = xs[i].item()\n",
    "    y = ys[i].item()\n",
    "    print('--------')\n",
    "    print(f\"bigram example {i+1}: {itos[x]}{itos[y]} (indexes {x},{y})\")\n",
    "    print('input to the neural net:', x)\n",
    "    #print('output probs from the neural net:', probs[i])\n",
    "    print('label (actual next character):', y)\n",
    "    p = probs[i][y]\n",
    "    print('probs assigned by the net to the correct character:', p.item())\n",
    "    logp = torch.log(p)\n",
    "    print('log likelihood:', logp.item())\n",
    "    nll = -logp\n",
    "    print('negaive log likelihood:', nll.item())\n",
    "    nlls[i] = nll\n",
    "\n",
    "print('===========')\n",
    "print('average negative log likelihood, i.e., loss =', nlls.mean().item())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([ 0,  5, 13, 13,  1])"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([ 5, 13, 13,  1,  0])"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ys"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3.7693049907684326\n"
     ]
    }
   ],
   "source": [
    "g = torch.Generator().manual_seed(2147483647)\n",
    "W = torch.randn((27, 27), generator=g, requires_grad=True)\n",
    "# forward pass\n",
    "xenc = F.one_hot(xs, num_classes=27).float() # input to the network: one-hot encoding\n",
    "logits = xenc @ W # predict log-counts\n",
    "counts = logits.exp() # counts, equivalent to N\n",
    "probs = counts / counts.sum(dim=1, keepdim=True) # probabilities for next character\n",
    "loss = -probs[torch.arange(5), ys].log().mean() # .log() 的结果是什么？\n",
    "print(loss.item())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "# backward pass\n",
    "W.grad = None # set to zero the gradient\n",
    "loss.backward()\n",
    "\n",
    "W.data += -0.1*W.grad\n",
    "\n",
    "# -------- !!! optimization !!! yay, but this time actually -------\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "number of examples:  228146\n"
     ]
    }
   ],
   "source": [
    "# create the dataset\n",
    "xs, ys = [], []\n",
    "for w in words:\n",
    "    chs = ['.'] + list(w) + ['.'] \n",
    "    for ch1, ch2 in zip(chs, chs[1:]):\n",
    "        ix1 = stoi[ch1]\n",
    "        ix2 = stoi[ch2]\n",
    "        xs.append(ix1) \n",
    "        ys.append(ix2) \n",
    "\n",
    "xs = torch.tensor(xs)\n",
    "ys = torch.tensor(ys)\n",
    "num = xs.nelement()\n",
    "print('number of examples: ', num)\n",
    "\n",
    "# initialize the 'network'\n",
    "g = torch.Generator().manual_seed(2147483647)\n",
    "W = torch.randn((27, 27), generator=g, requires_grad=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "ename": "",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31mThe Kernel crashed while executing code in the the current cell or a previous cell. Please review the code in the cell(s) to identify a possible cause of the failure. Click <a href='https://aka.ms/vscodeJupyterKernelCrash'>here</a> for more info. View Jupyter <a href='command:jupyter.viewOutput'>log</a> for further details."
     ]
    }
   ],
   "source": [
    "# gradient descent\n",
    "import torch.nn.functional as F\n",
    "for k in range(1):\n",
    "    # forward pass\n",
    "    xenc = F.one_hot(xs, num_classes=27).float() # input to the network\n",
    "    logits = xenc @ W # predict log-counts\n",
    "    print(f\"{logits=}\")\n",
    "    counts = logits.exp() # convert logits to counts\n",
    "    probs = counts/counts.sum(1, keepdim=True) # compute probabilities\n",
    "    print(f\"{probs=}\")\n",
    "    # 只计算第二个的 loss\n",
    "    loss = -probs[:, ys].log().mean() # compute loss\n",
    "\n",
    "    # backward pass\n",
    "    W.grad = None\n",
    "    loss.backward()\n",
    "\n",
    "    # update weights\n",
    "    W.data -= W.grad*0.1\n",
    "    "
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}