Brunobkr/llama.cpp_AlgMor24_github
ΩFFFΣLLIa • llama.cpp • AlgMor24 ██████╗ ███████╗███████╗███████╗██╗ ██╗ ██╗ █████╗ ██╔═══██╗██╔════╝██╔════╝██╔════╝██║ ██║ ██║██╔══██╗ ██║ ██║█████╗ █████╗ █████╗ ██║ ██║ ██║███████║ ██║ ██║██╔══╝ ██╔══╝ ██╔══╝ ██║ ██║ ██║██╔══██║ ╚██████╔╝██║ ██║ ███████╗███████╗███████╗██║██║ ██║ ╚═════╝ ╚═╝ ╚═╝ ╚══════╝╚══════╝╚══════╝╚═╝╚═╝ ╚═╝ High-Performance LLM / VLM Inference & Autonomous Agentic Ecosystem… See the full description on the dataset page: https://huggingface.co/datasets/Brunobkr/llama.cpp_AlgMor24_github.
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1import {quadtree} from "d3-quadtree";2import constant from "./constant.js";3import jiggle from "./jiggle.js";4import {x, y} from "./simulation.js";5 6export default function() {7 var nodes,8 node,9 random,10 alpha,11 strength = constant(-30),12 strengths,13 distanceMin2 = 1,14 distanceMax2 = Infinity,15 theta2 = 0.81;16 17 function force(_) {18 var i, n = nodes.length, tree = quadtree(nodes, x, y).visitAfter(accumulate);19 for (alpha = _, i = 0; i < n; ++i) node = nodes[i], tree.visit(apply);20 }21 22 function initialize() {23 if (!nodes) return;24 var i, n = nodes.length, node;25 strengths = new Array(n);26 for (i = 0; i < n; ++i) node = nodes[i], strengths[node.index] = +strength(node, i, nodes);27 }28 29 function accumulate(quad) {30 var strength = 0, q, c, weight = 0, x, y, i;31 32 // For internal nodes, accumulate forces from child quadrants.33 if (quad.length) {34 for (x = y = i = 0; i < 4; ++i) {35 if ((q = quad[i]) && (c = Math.abs(q.value))) {36 strength += q.value, weight += c, x += c * q.x, y += c * q.y;37 }38 }39 quad.x = x / weight;40 quad.y = y / weight;41 }42 43 // For leaf nodes, accumulate forces from coincident quadrants.44 else {45 q = quad;46 q.x = q.data.x;47 q.y = q.data.y;48 do strength += strengths[q.data.index];49 while (q = q.next);50 }51 52 quad.value = strength;53 }54 55 function apply(quad, x1, _, x2) {56 if (!quad.value) return true;57 58 var x = quad.x - node.x,59 y = quad.y - node.y,60 w = x2 - x1,61 l = x * x + y * y;62 63 // Apply the Barnes-Hut approximation if possible.64 // Limit forces for very close nodes; randomize direction if coincident.65 if (w * w / theta2 < l) {66 if (l < distanceMax2) {67 if (x === 0) x = jiggle(random), l += x * x;68 if (y === 0) y = jiggle(random), l += y * y;69 if (l < distanceMin2) l = Math.sqrt(distanceMin2 * l);70 node.vx += x * quad.value * alpha / l;71 node.vy += y * quad.value * alpha / l;72 }73 return true;74 }75 76 // Otherwise, process points directly.77 else if (quad.length || l >= distanceMax2) return;78 79 // Limit forces for very close nodes; randomize direction if coincident.80 if (quad.data !== node || quad.next) {81 if (x === 0) x = jiggle(random), l += x * x;82 if (y === 0) y = jiggle(random), l += y * y;83 if (l < distanceMin2) l = Math.sqrt(distanceMin2 * l);84 }85 86 do if (quad.data !== node) {87 w = strengths[quad.data.index] * alpha / l;88 node.vx += x * w;89 node.vy += y * w;90 } while (quad = quad.next);91 }92 93 force.initialize = function(_nodes, _random) {94 nodes = _nodes;95 random = _random;96 initialize();97 };98 99 force.strength = function(_) {100 return arguments.length ? (strength = typeof _ === "function" ? _ : constant(+_), initialize(), force) : strength;101 };102 103 force.distanceMin = function(_) {104 return arguments.length ? (distanceMin2 = _ * _, force) : Math.sqrt(distanceMin2);105 };106 107 force.distanceMax = function(_) {108 return arguments.length ? (distanceMax2 = _ * _, force) : Math.sqrt(distanceMax2);109 };110 111 force.theta = function(_) {112 return arguments.length ? (theta2 = _ * _, force) : Math.sqrt(theta2);113 };114 115 return force;116}117 