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@pmineiro
Last active July 28, 2022 01:05
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OPE CS with reward range robustness
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{
"cells": [
{
"cell_type": "markdown",
"id": "cd002650",
"metadata": {},
"source": [
"# Reference OPE CS Impl"
]
},
{
"cell_type": "markdown",
"id": "8b34d7f6",
"metadata": {},
"source": [
"An Off-Policy Confidence Sequence suitable for general purposes"
]
},
{
"cell_type": "markdown",
"id": "5352f2d8",
"metadata": {},
"source": [
"## API\n",
"\n",
"The public API is:\n",
" * `Constructor`$(r_\\min, r_\\max, \\text{adjust})$: takes an initial reward range and a boolean saying whether to adjust automatically.\n",
" * `addobs(w_t, r_t)`: Observe an importance weighted reward.\n",
" * `getci`$(\\alpha)$: Return a CI at confidence level $(1 - \\alpha)$."
]
},
{
"cell_type": "markdown",
"id": "9fa2293a",
"metadata": {},
"source": [
"## Coverage Guarantee"
]
},
{
"cell_type": "markdown",
"id": "83f7164c",
"metadata": {},
"source": [
"For the coverage guarantee you must certify the preconditions:\n",
" * $w_t = \\frac{d\\pi_t}{d \\mu_t}(a_t)$ is the correct importance weight:\n",
" * $\\mu_t$ is the logging policy (i.e., the distribution from which the action is drawn):\n",
" * $\\pi_t$ is the policy being evaluated (i.e., the policy whose mean is being estimated).\n",
" * $r_t \\in [ r_{\\min}, r_{\\max} ]$ with probability 1.\n",
" * $r_t = r_t(a_t)$ where $a_t \\sim \\mu_t$.\n",
" \n",
"Then you get the following guarantee $$\n",
"\\mathrm{Pr}\\left( \\forall t: \\frac{1}{t} \\sum_{s=1}^t \\mathbb{E}_{\\substack{t-1 \\\\ a \\sim \\pi_t}}\\left[r_t(a)\\right] \\in \\text{getci}(\\alpha) \\right) \\geq 1 - \\alpha.\n",
"$$\n",
"This guarantee is:\n",
" * time-uniform coverage (simultaneously valid for all sample sizes)\n",
" * of the running mean of the policy sequence being evaluated\n",
" * the environment can [adaptively](https://math.stackexchange.com/questions/1794875/what-is-the-difference-between-an-adapted-process-and-a-predictable-process) change each timestep\n",
" * the policy being evaluated can [predictably](https://math.stackexchange.com/questions/1794875/what-is-the-difference-between-an-adapted-process-and-a-predictable-process) change with each timestep"
]
},
{
"cell_type": "markdown",
"id": "b6006448",
"metadata": {},
"source": [
"### Reward Range Robustness"
]
},
{
"cell_type": "markdown",
"id": "0b32270c",
"metadata": {},
"source": [
"To facilitate unknown reward ranges we have two strategies:\n",
" * `adjust=False`: clips the realized reward to be in the constructor supplied range $[r_{\\min}, r_{\\max}]$ and provides the coverage guarantee on this modified random variable.\n",
" * `adjust=True`: expands the reward range if an observed value exceeds the constructor supplied range.\n",
" * in this case, the coverage guarantee is conditioned on observing the complete range (if initially incorrectly specified), which can cover a value very different than the running mean if extreme reward values are rare."
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "7da211a7",
"metadata": {
"code_folding": [
0,
31,
55,
83,
103,
121
]
},
"outputs": [],
"source": [
"class IncrementalFsum:\n",
" \"\"\" Incremental version of https://en.wikipedia.org/wiki/Kahan_summation_algorithm \"\"\"\n",
"\n",
" def __init__(self):\n",
" self.partials = []\n",
"\n",
" def __iadd__(self, x):\n",
" i = 0\n",
" for y in self.partials:\n",
" if abs(x) < abs(y):\n",
" x, y = y, x\n",
" hi = x + y\n",
" lo = y - (hi - x)\n",
" if lo:\n",
" self.partials[i] = lo\n",
" i += 1\n",
" x = hi\n",
" self.partials[i:] = [x]\n",
" return self\n",
"\n",
" def __add__(self, other):\n",
" result = IncrementalFsum()\n",
" result.partials = deepcopy(self.partials)\n",
" for y in other.partials:\n",
" result += y\n",
" return result\n",
"\n",
" def __float__(self):\n",
" return sum(self.partials, 0.0)\n",
"\n",
"class EmpBernDynCS(object):\n",
" def __init__(self, rmin=0, rmax=1, adjust=True):\n",
" super().__init__()\n",
" \n",
" assert rmin <= rmax, (rmin, rmax)\n",
" \n",
" self.rho = 1\n",
" self.rmin = rmin\n",
" self.rmax = rmax\n",
" self.adjust = adjust\n",
" \n",
" self.t = 0\n",
"\n",
" self.sumwsqrsq = IncrementalFsum()\n",
" self.sumwsqr = IncrementalFsum()\n",
" self.sumwsq = IncrementalFsum()\n",
" self.sumwr = IncrementalFsum()\n",
" self.sumw = IncrementalFsum()\n",
" self.sumwrxhatlow = IncrementalFsum()\n",
" self.sumwxhatlow = IncrementalFsum()\n",
" self.sumxhatlowsq = IncrementalFsum()\n",
" self.sumwrxhathigh = IncrementalFsum()\n",
" self.sumwxhathigh = IncrementalFsum()\n",
" self.sumxhathighsq = IncrementalFsum()\n",
" \n",
" def addobs(self, w, r):\n",
" assert w >= 0\n",
" \n",
" if not self.adjust:\n",
" r = min(self.rmax, max(self.rmin, r))\n",
" else:\n",
" self.rmin = min(self.rmin, r)\n",
" self.rmax = max(self.rmax, r)\n",
" \n",
" sumXlow = (float(self.sumwr) - float(self.sumw) * self.rmin) / (self.rmax - self.rmin)\n",
" Xhatlow = (sumXlow + 1/2) / (self.t + 1)\n",
" sumXhigh = (float(self.sumw) * self.rmax - float(self.sumwr)) / (self.rmax - self.rmin)\n",
" Xhathigh = (sumXhigh + 1/2) / (self.t + 1)\n",
" \n",
" self.sumwsqrsq += (w * r)**2\n",
" self.sumwsqr += w**2 * r\n",
" self.sumwsq += w**2\n",
" self.sumwr += w * r\n",
" self.sumw += w\n",
" self.sumwrxhatlow += w * r * Xhatlow\n",
" self.sumwxhatlow += w * Xhatlow\n",
" self.sumxhatlowsq += Xhatlow**2\n",
" self.sumwrxhathigh += w * r * Xhathigh\n",
" self.sumwxhathigh += w * Xhathigh\n",
" self.sumxhathighsq += Xhathigh**2\n",
" \n",
" self.t += 1\n",
" \n",
" def getci(self, alpha):\n",
" if self.t == 0 or self.rmin == self.rmax:\n",
" return [self.rmin, self.rmax]\n",
" \n",
" sumvlow = ( (float(self.sumwsqrsq) - 2 * self.rmin * float(self.sumwsqr) + self.rmin**2 * float(self.sumwsq)) / (self.rmax - self.rmin)**2\n",
" - 2 * (float(self.sumwrxhatlow) - self.rmin * float(self.sumwxhatlow)) / (self.rmax - self.rmin)\n",
" + float(self.sumxhatlowsq)\n",
" )\n",
" sumXlow = (float(self.sumwr) - float(self.sumw) * self.rmin) / (self.rmax - self.rmin)\n",
" l = self.__lblogwealth(t=self.t, sumXt=sumXlow, v=sumvlow, rho=self.rho, alpha=alpha/2)\n",
" \n",
" sumvhigh = ( (float(self.sumwsqrsq) - 2 * self.rmax * float(self.sumwsqr) + self.rmax**2 * float(self.sumwsq)) / (self.rmax - self.rmin)**2\n",
" + 2 * (float(self.sumwrxhathigh) - self.rmax * float(self.sumwxhathigh)) / (self.rmax - self.rmin)\n",
" + float(self.sumxhathighsq)\n",
" )\n",
" sumXhigh = (float(self.sumw) * self.rmax - float(self.sumwr)) / (self.rmax - self.rmin)\n",
" u = 1 - self.__lblogwealth(t=self.t, sumXt=sumXhigh, v=sumvhigh, rho=self.rho, alpha=alpha/2)\n",
" \n",
" return self.rmin + l * (self.rmax - self.rmin), self.rmin + u * (self.rmax - self.rmin)\n",
"\n",
" def __logwealth(self, *, s, v, rho):\n",
" from math import log\n",
"\n",
" def loggammalowerinc(*, a, x):\n",
" import scipy.special as sc\n",
"\n",
" return log(sc.gammainc(a, x)) + sc.loggamma(a)\n",
" \n",
" assert s + v + rho > 0\n",
" assert rho > 0\n",
"\n",
" return (s + v\n",
" + rho * log(rho)\n",
" - (v + rho) * log(s + v + rho)\n",
" + loggammalowerinc(a = v + rho, x = s + v + rho)\n",
" - loggammalowerinc(a = rho, x = rho)\n",
" )\n",
"\n",
" def __lblogwealth(self, *, t, sumXt, v, rho, alpha):\n",
" from math import log\n",
" import scipy.optimize as so\n",
"\n",
" assert 0 < alpha < 1, alpha\n",
" thres = -log(alpha)\n",
"\n",
" minmu = 0\n",
" logwealthminmu = self.__logwealth(s=sumXt, v=v, rho=rho)\n",
"\n",
" if logwealthminmu <= thres:\n",
" return minmu\n",
" \n",
" maxmu = min(1, sumXt/t)\n",
" logwealthmaxmu = self.__logwealth(s=sumXt - t * maxmu, v=v, rho=rho)\n",
"\n",
" if logwealthmaxmu >= thres:\n",
" return maxmu\n",
"\n",
" res = so.root_scalar(f = lambda mu: self.__logwealth(s=sumXt - t * mu, v=v, rho=rho) - thres,\n",
" method = 'brentq',\n",
" bracket = [ minmu, maxmu ])\n",
" assert res.converged, res\n",
" return res.root"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "93588099",
"metadata": {
"code_folding": [
1,
6,
48,
54
]
},
"outputs": [
{
"data": {
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\n",
"text/plain": [
"<Figure size 1152x432 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1152x432 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1152x432 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"class DataGen(object):\n",
" def __init__(self, *, wmax, expwsq, truemu, seed, rvals):\n",
" import numpy as np\n",
" import scipy.optimize as so\n",
" import random\n",
" \n",
" if False:\n",
" # { 0, 1, wmax } \\times { 0, 1 } -> 6 values -> we need 6 constraints\n",
" # 1 = sum_i p_i\n",
" # 1 = sum_i w_i p_i\n",
" # E[w^2] = sum_i w_i^2 p_i\n",
" # logging policy value = sum_i r_i p_i\n",
" # evaluated policy value = sum_i w_i r_i p_i\n",
" # we need 1 more constraint to be unique ...\n",
" # SURPRISE: just the above 5 constraints can be infeasible ...\n",
" # instead just minimize the logging policy value subject to other constraints\n",
" # this makes the distribution very difficult to lower bound\n",
" pass\n",
" \n",
" self.gen = random.Random(seed)\n",
" self.wmax = wmax\n",
" self.expwsq = expwsq\n",
" self.truemu = truemu\n",
" self.population = [ (w, r) for w in (0, 1, wmax,) for r in rvals ]\n",
" \n",
" c = [ r for (w, r) in self.population ] \n",
" A_eq = [\n",
" [ 1 for (w, r) in self.population ],\n",
" [ w for (w, r) in self.population ],\n",
" [ w**2 for (w, r) in self.population ],\n",
" [ w*r for (w, r) in self.population ],\n",
" ]\n",
" b_eq = [ 1, 1, expwsq, truemu, ]\n",
" \n",
" res = so.linprog(np.array(c), A_eq=A_eq, b_eq=b_eq)\n",
" assert res.success, res\n",
" self.probs = res.x\n",
" self.logmu = res.fun\n",
" \n",
" ewwm1r = self.probs.dot([ w * (w - 1) * r for (w, r) in self.population ])\n",
" ewm1sq = self.probs.dot([ (w - 1)**2 for (w, r) in self.population])\n",
" self.kappalowstar = -ewwm1r/ewm1sq if ewm1sq > 0 else 0\n",
" ewwm11mr = self.probs.dot([ w * (w - 1) * (1 - r) for (w, r) in self.population ])\n",
" self.kappahighstar = -ewwm11mr/ewm1sq if ewm1sq > 0 else 0\n",
" \n",
" self._expOp = lambda func: sum(p * func(w) for p, (w, _) in zip(self.probs, self.population))\n",
" self.clippedtruemu = sum(p * w * r for p, (w, r) in zip(self.probs, [ (w, r) for w in (0, 1, wmax) for r in (0, 1)]))\n",
"\n",
" def genobs(self):\n",
" w, r = self.gen.choices(population=self.population,\n",
" weights=self.probs,\n",
" )[0]\n",
" return w, r, self._expOp\n",
"\n",
"def megasim(*, T, datagen, wmax, adjust, dt=1, alpha = 0.05, seed=4545):\n",
" import itertools\n",
" from matplotlib import pyplot as plt \n",
" import numpy as np\n",
" \n",
" cs = EmpBernDynCS(adjust=adjust)\n",
" \n",
" wrz = []\n",
" lbz, ubz = [], []\n",
" \n",
" for t in range(T):\n",
" w, r, expOp = datagen.genobs()\n",
" cs.addobs(w, r)\n",
" if t % dt == 0:\n",
" wrz.append(w*r)\n",
" l, u = cs.getci(alpha=0.05)\n",
" lbz.append(l)\n",
" ubz.append(u)\n",
" \n",
" fig, ax = plt.subplots(1, 2)\n",
" fig.set_size_inches(16, 6)\n",
" ax[0].plot(list(itertools.accumulate(wrz)))\n",
" ax[0].set_ylabel('sum(wr)')\n",
" color = next(ax[1]._get_lines.prop_cycler)['color']\n",
" ax[1].plot(lbz, label='CS', color=color)\n",
" ax[1].plot(ubz, color=color)\n",
" color = next(ax[1]._get_lines.prop_cycler)['color']\n",
" ax[1].plot([datagen.truemu if adjust else datagen.clippedtruemu]*len(lbz), linestyle='dashed', color=color, label=f'{datagen.truemu if adjust else datagen.clippedtruemu:.3g}')\n",
" ax[1].set_xlabel(f'examples (x {dt})')\n",
" ax[1].set_ylabel('raw bounds')\n",
" ax[1].set_xscale('log')\n",
" ax[1].legend()\n",
" \n",
" pstr = ','.join([f'{v:.3g}' for v in datagen.probs])\n",
" fig.suptitle(f'expwsq = {datagen.expwsq} wmax={datagen.wmax} truemu={datagen.truemu} p={pstr}')\n",
" \n",
" return None\n",
"\n",
"def flass(seed):\n",
" dg = DataGen(wmax=10, expwsq=2, truemu=1/2, rvals=(-2, 2), seed=seed)\n",
" megasim(T=10000, wmax=10, dt=10, datagen=dg, adjust=True)\n",
" megasim(T=10000, wmax=10, dt=10, datagen=dg, adjust=False)\n",
" dg = DataGen(wmax=10, expwsq=2, truemu=1/2, rvals=(0, 1), seed=seed)\n",
" megasim(T=10000, wmax=10, dt=10, datagen=dg, adjust=False)\n",
"\n",
"flass(4545)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "8981925a",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"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": "3.8.13"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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