Spaces:
Sleeping
Sleeping
File size: 2,393 Bytes
6e124c0 cff7f74 6e124c0 b24b865 6e124c0 cff7f74 6e124c0 |
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 |
{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"id": "9ef7f2cc",
"metadata": {},
"outputs": [],
"source": [
"%load_ext autoreload\n",
"%autoreload 2"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "5c1563c6",
"metadata": {},
"outputs": [],
"source": [
"import copy\n",
"\n",
"import torch"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "6c8f9b12",
"metadata": {},
"outputs": [],
"source": [
"from rubik.cube import Cube\n",
"from rubik.action import build_actions_tensor"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "6b3b066b",
"metadata": {},
"outputs": [],
"source": [
"size = 3\n",
"\n",
"actions = build_actions_tensor(size)\n",
"\n",
"cube = Cube([\"U\", \"L\", \"C\", \"R\", \"B\", \"D\"], size=size)\n",
"print(cube)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "de9308c5",
"metadata": {},
"outputs": [],
"source": [
"cubis = copy.deepcopy(cube)\n",
"cubis.shuffle(2000, seed=0)\n",
"print(cubis)\n",
"print(cubis.history)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "cb29c742",
"metadata": {},
"outputs": [],
"source": [
"cubis.compute_changes(\"X2 X1i Y1i Z1i Y0 Z0i X2 X1i Y1i Z1i Y0 Z0i \")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "63dec5ee",
"metadata": {},
"outputs": [],
"source": [
"cubis = copy.deepcopy(cube)\n",
"cubis.rotate(\"X2 X1i Y1i Z1i Y0 Z0i X2 X1i Y1i Z1i Y0 Z0i \" * 1000)\n",
"print(cubis)\n",
"print(cubis.history)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "a8bc424f",
"metadata": {},
"outputs": [],
"source": [
"(actions[0, 2, 0].type(torch.float32) @ actions[0, 1, 1].type(torch.float32)).type(torch.int8)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Rubik-Tensor",
"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": "3.11.13"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
|