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zhRj{z@6!Tb=%Y|%fMR*Qw%=6bLIa}1;ZgFkt)GG=QJe17sIEO=i$l|%{iuo>v|jlG zdR1fo3{Zmpg@^-NxwA!)YeUHL(Pd`}>m!&8!G`+ddsvWy^ar5i-izowI}o{X+&{a_ zuUGiHcmoUeU8p5`%^@Pc23T@}`EvD}A+)m#(flAwi=H^vRS2#N@ruE?V#zxhtNIbs z^Smw;kpK2Tj`sza20>QQC=ePKM0k+0KLUd)AEa1-YWfR_>;y)7oJ_ll|E?NW1h4>l z)Nux)yMid+4IDdEE4^0xlR?syW;F{fcR;8PU%Y>U&hP=r6&4<5EjhDv2AMOjC@GMu4 z*L@4-n$_&fm|1>$>Bhcgv)ph`*yAR;s5x|}3!AY{yu=FL! zAHeN{IW88=oP@1xSCzVxBzZ zUmON#w}o-2tJqIfgT&fiyQ;bYY>(J9Ub*}=tpx7??H~X@=nXn@6Vi}&H(wy>;s2aU{_TwEc+&XH|Mm}XJO2*{>)%5<=*$0~ c&%E|x)@^*6i}C~u1^g%dQeL7^Oz+eG0%o#^82|tP diff --git a/docs/source/explainable_categorical.ipynb b/docs/source/explainable_categorical.ipynb index eee6cddf1..f12d638e3 100644 --- a/docs/source/explainable_categorical.ipynb +++ b/docs/source/explainable_categorical.ipynb @@ -461,7 +461,7 @@ "source": [ "query = SearchForExplanation(\n", " supports=forest_fire_supports,\n", - " antecedents={\"smile\": torch.tensor(1.0)},\n", + " antecedents={\"match_dropped\": torch.tensor(1.0)},\n", " consequents={\"forest_fire\": torch.tensor(1.0)},\n", " witnesses={}, \n", " alternatives={\"match_dropped\": torch.tensor(0.0)},\n", diff --git a/docs/source/inference.ipynb b/docs/source/inference.ipynb deleted file mode 100644 index d4b99e30c..000000000 --- a/docs/source/inference.ipynb +++ /dev/null @@ -1,120 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 31, - "metadata": {}, - "outputs": [], - "source": [ - "from typing import Optional, Callable\n", - "import math\n", - "\n", - "import pyro.distributions as dist\n", - "import torch\n", - "\n", - "import pyro\n", - "from chirho.counterfactual.handlers.counterfactual import \\\n", - " MultiWorldCounterfactual\n", - "from chirho.explainable.handlers import SearchForExplanation\n", - "from chirho.explainable.handlers.components import ExtractSupports\n" - ] - }, - { - "cell_type": "code", - "execution_count": 32, - "metadata": {}, - "outputs": [], - "source": [ - "def model():\n", - " a = pyro.sample(\"a\", dist.Normal(loc=torch.tensor(0.0), scale=torch.tensor(1.0)))\n", - " b = pyro.sample(\"b\", dist.Normal(loc=torch.tensor(0.0), scale=torch.tensor(1.0)))" - ] - }, - { - "cell_type": "code", - "execution_count": 33, - "metadata": {}, - "outputs": [], - "source": [ - "with ExtractSupports() as s:\n", - " model()\n", - "\n", - "query = SearchForExplanation(\n", - " supports=s.supports,\n", - " alternatives={\"a\": torch.tensor(0.5)},\n", - " antecedents={\"a\": torch.tensor(-0.5)},\n", - " antecedent_bias=0.0,\n", - " witnesses={},\n", - " consequents={\"b\": torch.tensor(0.0)},\n", - " consequent_scale=1e-8,\n", - " )(model)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "How can I compute the probability that `a=-0.5` is a sufficienct and necessary cause of `b=0` using `SearchForExplanation`?" - ] - }, - { - "cell_type": "code", - "execution_count": 34, - "metadata": {}, - "outputs": [], - "source": [ - "def importance_infer(\n", - " model: Optional[Callable] = None, *, num_samples: int\n", - "):\n", - " \n", - " if model is None:\n", - " return lambda m: importance_infer(m, num_samples=num_samples)\n", - "\n", - " def _wrapped_model(\n", - " *args,\n", - " **kwargs\n", - " ):\n", - "\n", - " guide = pyro.poutine.block(hide_fn=lambda msg: msg[\"is_observed\"])(model)\n", - "\n", - " max_plate_nesting = 9 # TODO guess\n", - "\n", - " with pyro.poutine.block(), MultiWorldCounterfactual() as mwc_imp:\n", - " log_weights, importance_tr, _ = pyro.infer.importance.vectorized_importance_weights(\n", - " model,\n", - " guide,\n", - " *args,\n", - " num_samples=num_samples,\n", - " max_plate_nesting=max_plate_nesting,\n", - " normalized=False,\n", - " **kwargs\n", - " )\n", - "\n", - " return torch.logsumexp(log_weights, dim=0) - math.log(num_samples), importance_tr, mwc_imp, log_weights\n", - "\n", - " return _wrapped_model" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": ".venv", - "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": "3.10.14" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -}