Public
Edited
Sep 3, 2024
function test(fn, args){
const t = Date.now()
fn(...args)
return Date.now()-t
}
results = {
let trials = []
for(let n=1; n<100;n++){
const A = math.random([n,n])
const x = math.random([n,1])
const At = tf.tensor(A)
const xt = tf.tensor(x)
for(let trial = 1; trial <= 50;trial++){
const timeMath = test(math.multiply, [A,x])
const timeTF = test(tf.matMul, [At,xt])
if(trial > 5)
trials.push({n, timeMath, timeTF})
}
}
return trials
}
n = 100
A = math.random([n, n])
B = math.random([n,1])
cMath = math.multiply(A,B)
cTF = tf.matMul(Atensor,Btensor).array()
Atensor = tf.tensor(A)
Btensor = tf.tensor(B)
math.smaller(math.max(math.subtract(cMath, cTF)), 1e-5) ? 'equal results' : 'unequal results'
math = import("https://cdn.jsdelivr.net/npm/mathjs@latest/+esm")
tf = require('@tensorflow/tfjs@latest')
Purpose-built for displays of data
Observable is your go-to platform for exploring data and creating expressive data visualizations. Use reactive JavaScript notebooks for prototyping and a collaborative canvas for visual data exploration and dashboard creation.
