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{ | |
"cells": [ | |
{ | |
"cell_type": "markdown", | |
"id": "d875f51f", | |
"metadata": {}, | |
"source": [ | |
"# IGL" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 1, | |
"id": "277b36f3", | |
"metadata": { | |
"code_folding": [ | |
0, | |
21, | |
23, | |
27, | |
42, | |
45, | |
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54, | |
60, | |
79, | |
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] | |
}, | |
"outputs": [], | |
"source": [ | |
"class IncrementalFsum:\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 __float__(self):\n", | |
" return sum(self.partials, 0.0)\n", | |
"\n", | |
"class ExampleBuilder:\n", | |
" class Features:\n", | |
" def __init__(self, categorical={}, numerical={}):\n", | |
" self.categorical = categorical\n", | |
" self.numerical = numerical\n", | |
" \n", | |
" def __str__(self):\n", | |
" import numbers\n", | |
" reserved = set(':=|\\n ')\n", | |
" \n", | |
" exstr = \"\"\n", | |
" for key, value in self.categorical.items():\n", | |
" assert not any(c in reserved for c in key), key\n", | |
" assert not any(c in reserved for c in value), value\n", | |
" exstr += f\"{key}={value} \"\n", | |
" for key, value in self.numerical.items():\n", | |
" assert not any(c in reserved for c in key), key\n", | |
" assert isinstance(value, numbers.Number), value\n", | |
" exstr += f\"{key}:{value} \" \n", | |
" return exstr[:-1]\n", | |
" \n", | |
" def __init__(self, namespaces={}):\n", | |
" self.namespaces = namespaces\n", | |
" \n", | |
" def __str__(self):\n", | |
" reserved = set(':=|\\n ')\n", | |
" exstr = \"\"\n", | |
" for ns, feats in self.namespaces.items():\n", | |
" assert not any(c in reserved for c in ns), ns\n", | |
" exstr += f\"|{ns} {str(feats)}\" \n", | |
" return exstr\n", | |
" \n", | |
"class CB:\n", | |
" def __init__(self, polargs):\n", | |
" from vowpalwabbit import pyvw\n", | |
" \n", | |
" assert '--cb_explore_adf' in polargs, polargs\n", | |
" self.pi = pyvw.vw(polargs)\n", | |
" \n", | |
" def _makePiExample(self, context, actions, chosen_action_index=None, reward=None, prob=None):\n", | |
" import numbers\n", | |
" \n", | |
" assert chosen_action_index is not None or (reward is None and prob is None), (chosen_action_index, reward, prob)\n", | |
" \n", | |
" exarray = []\n", | |
" exarray.append(f\"shared {str(context)}\") \n", | |
" for k, a in enumerate(actions):\n", | |
" label = ''\n", | |
" if chosen_action_index is not None:\n", | |
" if k == chosen_action_index:\n", | |
" assert isinstance(reward, numbers.Number), reward\n", | |
" cost = -reward\n", | |
" label += f\"0:{cost}:{prob}\"\n", | |
" \n", | |
" exarray.append(f\"{label} {str(a)}\")\n", | |
" \n", | |
" return '\\n'.join(exarray)\n", | |
" \n", | |
" def predict(self, context, actions):\n", | |
" return self.pi.predict(self._makePiExample(context, actions))\n", | |
" \n", | |
" def offPolicyLearn(self, context, actions, chosen_action_index, reward, prob): \n", | |
" self.pi.learn(self._makePiExample(context, actions, chosen_action_index, reward, prob))\n", | |
"\n", | |
"class IGL:\n", | |
" def __init__(self, polargs, psiargs, seed):\n", | |
" from vowpalwabbit import pyvw\n", | |
" import random\n", | |
" \n", | |
" assert '--link=logistic' in psiargs, psiargs\n", | |
" assert '--loss_function=logistic' in psiargs, psiargs\n", | |
" assert '--cb_explore_adf' in polargs, polargs\n", | |
" self.pol = pyvw.vw(polargs)\n", | |
" self.psi = pyvw.vw(psiargs)\n", | |
" \n", | |
" def _psipredict(self, *, feedback, context, actions, chosen_action_index):\n", | |
" example = f\" {str(feedback)} {str(context)} {str(actions[chosen_action_index])}\"\n", | |
" return self.psi.predict(example)\n", | |
" \n", | |
" def _psilearn(self, *, feedback, context, actions, chosen_action_index, importance): \n", | |
" exbase = f\" {str(feedback)} {str(context)}\"\n", | |
" for k, a in enumerate(actions):\n", | |
" example = f\"{1 if k == chosen_action_index else -1} {importance} {exbase} {str(a)}\"\n", | |
" self.psi.learn(example)\n", | |
" \n", | |
" def _makePiExample(self, *, context, actions, chosen_action_index=None, reward=None, prob=None):\n", | |
" import numbers\n", | |
" \n", | |
" assert chosen_action_index is not None or (reward is None and prob is None), (chosen_action_index, reward, prob)\n", | |
" \n", | |
" exarray = []\n", | |
" exarray.append(f\"shared {str(context)}\") \n", | |
" for k, a in enumerate(actions):\n", | |
" label = ''\n", | |
" if chosen_action_index is not None:\n", | |
" if k == chosen_action_index:\n", | |
" assert isinstance(reward, numbers.Number), reward\n", | |
" cost = -reward\n", | |
" label += f\"0:{cost}:{prob} \"\n", | |
" \n", | |
" exarray.append(f\"{label}{str(a)}\")\n", | |
" \n", | |
" return '\\n'.join(exarray)\n", | |
" \n", | |
" def predict(self, context, actions): \n", | |
" return self.pol.predict(self._makePiExample(context=context, actions=actions))\n", | |
" \n", | |
" def offPolicyLearn(self, context, actions, chosen_action_index, feedback, prob):\n", | |
" polpredict = self.predict(context, actions)\n", | |
" psipredict = self._psipredict(feedback=feedback, context=context, \n", | |
" actions=actions, chosen_action_index=chosen_action_index)\n", | |
" \n", | |
" self._psilearn(feedback=feedback, context=context, actions=actions,\n", | |
" chosen_action_index=chosen_action_index, \n", | |
" importance = 1/(len(actions)*prob))\n", | |
" \n", | |
" self.pol.learn(self._makePiExample(context=context, \n", | |
" actions=actions, \n", | |
" chosen_action_index=chosen_action_index,\n", | |
" reward=psipredict,\n", | |
" prob=prob))\n" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"id": "14341edc", | |
"metadata": {}, | |
"source": [ | |
"# NTP Style Sim" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 2, | |
"id": "841ca07f", | |
"metadata": { | |
"code_folding": [ | |
0, | |
1 | |
] | |
}, | |
"outputs": [], | |
"source": [ | |
"class Simulator:\n", | |
" def __init__(self, nusers, nactions, seed):\n", | |
" import numpy as np\n", | |
" \n", | |
" self.random = np.random.RandomState(seed)\n", | |
" self.nusers = nusers\n", | |
" self.nactions = nactions\n", | |
" self.actions = [ ExampleBuilder(namespaces = { 'a': ExampleBuilder.Features(categorical = { 'action': str(k) }) }) for k in range(nactions) ]\n", | |
" self.prefs = {}\n", | |
" \n", | |
" for n in range(nusers):\n", | |
" self.prefs[n] = self.random.randint(low=0, high=nactions)\n", | |
" \n", | |
" def trueReward(self, context, action):\n", | |
" user = int(context.namespaces['c'].categorical['user'])\n", | |
" return self.prefs[user] == action\n", | |
" \n", | |
" def expectedTrueReward(self, context, paction):\n", | |
" return sum(p * self.trueReward(context, action) for action, p in enumerate(paction))\n", | |
" \n", | |
" def sampleFeedback(self, context, action):\n", | |
" user = int(context.namespaces['c'].categorical['user'])\n", | |
" what = [ 'click', 'like', 'dislike', 'none']\n", | |
" noise = 0.05\n", | |
" if self.trueReward(context, action):\n", | |
" probs = [ 0.2 + noise, 0.3 + noise, noise, 0.5 - 3 * noise ]\n", | |
" else:\n", | |
" probs = [ noise, noise, 0.1 + noise, 0.9 - 3 * noise ]\n", | |
" \n", | |
" return ExampleBuilder(namespaces = { 'f' : ExampleBuilder.Features(numerical = { what[self.random.choice(len(what), p=probs)] : 1 }) })\n", | |
" \n", | |
" def sampleContext(self):\n", | |
" return ExampleBuilder(namespaces = { 'c': ExampleBuilder.Features(categorical = { 'user': str(self.random.randint(low=0, high=self.nusers)) }) })\n", | |
" \n", | |
" def sampleInstance(self):\n", | |
" context = self.sampleContext()\n", | |
" return (context, self.actions) " | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 4, | |
"id": "08389514", | |
"metadata": { | |
"code_folding": [ | |
0, | |
35, | |
48 | |
] | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
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\n", | |
"text/plain": [ | |
"<Figure size 1152x432 with 3 Axes>" | |
] | |
}, | |
"metadata": { | |
"needs_background": "light" | |
}, | |
"output_type": "display_data" | |
}, | |
{ | |
"data": { | |
"image/png": 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\n", | |
"text/plain": [ | |
"<Figure size 1152x432 with 3 Axes>" | |
] | |
}, | |
"metadata": { | |
"needs_background": "light" | |
}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"def run_sim(T, *, nusers, nactions, useunif, seed):\n", | |
" import numpy as np\n", | |
" \n", | |
" rstate = np.random.RandomState(seed=seed); seed += 1\n", | |
" s = Simulator(nusers=nusers, nactions=nactions, seed=seed); seed += 1\n", | |
" igl = IGL(polargs=f\"--quiet -b 24 -q ca --ignore_linear c --coin --cb_explore_adf --epsilon 0.2 --cb_type mtr\", \n", | |
" psiargs=f\"--quiet -b 24 --cubic cfa --ignore_linear c --ignore_linear f --ignore_linear a --loss_function=logistic --link=logistic --coin --min_prediction -100 --max_prediction 100\",\n", | |
" seed=seed); seed += 1\n", | |
" iglrewards = []\n", | |
" cb = CB(polargs=\"--quiet -b 24 -q ca --ignore_linear c --coin --cb_explore_adf --epsilon 0.2 --cb_type mtr\")\n", | |
" cbrewards = []\n", | |
"\n", | |
" for t in range(T):\n", | |
" context, actions = s.sampleInstance()\n", | |
" if useunif:\n", | |
" logged_action = rstate.randint(low=0, high=len(actions))\n", | |
"\n", | |
" iglpred = igl.predict(context, actions)\n", | |
" iglpred /= np.sum(iglpred)\n", | |
" iglrewards.append(s.expectedTrueReward(context, iglpred))\n", | |
" if not useunif:\n", | |
" logged_action = rstate.choice(len(actions), p=iglpred)\n", | |
" feedback = s.sampleFeedback(context, logged_action)\n", | |
" igl.offPolicyLearn(context, actions, logged_action, feedback, prob=1/len(actions) if useunif else iglpred[logged_action]) \n", | |
" \n", | |
" cbpred = cb.predict(context, actions)\n", | |
" cbpred /= np.sum(cbpred)\n", | |
" cbrewards.append(s.expectedTrueReward(context, cbpred))\n", | |
" if not useunif:\n", | |
" logged_action = rstate.choice(len(actions), p=cbpred)\n", | |
" reward = s.trueReward(context, logged_action)\n", | |
" cb.offPolicyLearn(context, actions, logged_action, reward, prob=1/len(actions) if useunif else cbpred[logged_action])\n", | |
" \n", | |
" return iglrewards, cbrewards\n", | |
"\n", | |
"def run_and_plot_sim(T, *, ax, useunif, seed=2112):\n", | |
" import numpy as np\n", | |
" import pandas as pd\n", | |
" \n", | |
" nusers = 20\n", | |
" nactions = 6\n", | |
" iglrewards, cbrewards = run_sim(T, nusers=nusers, nactions=nactions, useunif=useunif, seed=seed)\n", | |
" \n", | |
" ax.set_title(f'seed = {seed}')\n", | |
" ax.plot(pd.Series(cbrewards).rolling(50).mean(), label='cb')\n", | |
" ax.plot(pd.Series(iglrewards).rolling(50).mean(), label='igl')\n", | |
" ax.legend()\n", | |
" \n", | |
"def mega():\n", | |
" from matplotlib import pyplot as plt\n", | |
" \n", | |
" N = 16000\n", | |
"\n", | |
" fig, ax = plt.subplots(1, 3)\n", | |
" fig.suptitle('uniform logging policy')\n", | |
" fig.set_size_inches(16, 6)\n", | |
" run_and_plot_sim(N, useunif=True, seed=888, ax=ax[0])\n", | |
" run_and_plot_sim(N, useunif=True, seed=2128971964, ax=ax[1])\n", | |
" run_and_plot_sim(N, useunif=True, seed=8675309, ax=ax[2])\n", | |
" plt.show()\n", | |
" \n", | |
" fig, ax = plt.subplots(1, 3)\n", | |
" fig.suptitle('epsilon-greedy on-policy')\n", | |
" fig.set_size_inches(16, 6)\n", | |
" run_and_plot_sim(N, useunif=False, seed=888, ax=ax[0])\n", | |
" run_and_plot_sim(N, useunif=False, seed=2128971964, ax=ax[1])\n", | |
" run_and_plot_sim(N, useunif=False, seed=8675309, ax=ax[2])\n", | |
" plt.show()\n", | |
" \n", | |
"mega()" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": null, | |
"id": "e1419405", | |
"metadata": {}, | |
"outputs": [], | |
"source": [] | |
} | |
], | |
"metadata": { | |
"kernelspec": { | |
"display_name": "Python [conda env:igl4control]", | |
"language": "python", | |
"name": "conda-env-igl4control-py" | |
}, | |
"language_info": { | |
"codemirror_mode": { | |
"name": "ipython", | |
"version": 3 | |
}, | |
"file_extension": ".py", | |
"mimetype": "text/x-python", | |
"name": "python", | |
"nbconvert_exporter": "python", | |
"pygments_lexer": "ipython3", | |
"version": "3.8.12" | |
} | |
}, | |
"nbformat": 4, | |
"nbformat_minor": 5 | |
} |
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