function randu(a, b) { return a + (b - a) * Math.random(); }

function sigmoid(x) { return 1 / (1 + Math.exp(-x)); }

function dsigmoid(y) { return y * (1 - y); }

function relu(x) { return x > 0 ? x : 0; }

function reluGrad(x) { return x > 0 ? 1 : 0; }

​

function matvec(W, v) {

  const out = new Array(W.length).fill(0);

  for (let r = 0; r < W.length; r++) {

    let s = 0;

    for (let c = 0; c < v.length; c++) s += W[r][c] * v[c];

    out[r] = s;

  }

  return out;

}

function addv(a, b) { return a.map((x, i) => x + b[i]); }

​

function trainXOR(epochs = 5000, lr = 0.1, hidden = 4) {

  // XOR dataset

  const X = [[0,0],[0,1],[1,0],[1,1]];

  const Y = [0,1,1,0];

​

  // Params

  const inputDim = 2;

  let W1 = Array.from({length: hidden}, () => Array.from({length: inputDim}, () => randu(-1,1)));

  let b1 = Array.from({length: hidden}, () => 0);

  let W2 = Array.from({length: hidden}, () => randu(-1,1));

  let b2 = 0;

​