From 766b9cab3830ff7a8e0f6c55df3a5707e05746c2 Mon Sep 17 00:00:00 2001 From: Heiko Zimmermann <23041469+zmheiko@users.noreply.github.com> Date: Wed, 27 Mar 2024 22:34:12 +0100 Subject: [PATCH] Add coix tutorials (#18) * Added tutorial notebooks * Fixed typos and bug (changed factor to unit node) in tutorial 2 * fixed formating * fixed indentation and issue with level-one headlines * Changes order of tutorials * . * fixed doc generation * Update README * . * delete empty cell * changes proposed in comments --------- Co-authored-by: Du Phan --- .gitignore | 2 + README.md | 3 +- docs/conf.py | 15 +- docs/index.rst | 3 + notebooks/figures/smcs_nvi.png | Bin 0 -> 81918 bytes notebooks/tutorial_part1_vae.ipynb | 436 +++++++++++ notebooks/tutorial_part2_api.ipynb | 1044 +++++++++++++++++++++++++++ notebooks/tutorial_part3_smcs.ipynb | 593 +++++++++++++++ 8 files changed, 2090 insertions(+), 6 deletions(-) create mode 100644 notebooks/figures/smcs_nvi.png create mode 100644 notebooks/tutorial_part1_vae.ipynb create mode 100644 notebooks/tutorial_part2_api.ipynb create mode 100644 notebooks/tutorial_part3_smcs.ipynb diff --git a/.gitignore b/.gitignore index f2d0743..4f1c393 100644 --- a/.gitignore +++ b/.gitignore @@ -1,3 +1,5 @@ +docs/notebooks + # Compiled python modules. *.pyc diff --git a/README.md b/README.md index 5e7d72e..8b4857d 100644 --- a/README.md +++ b/README.md @@ -4,8 +4,7 @@ [![Documentation Status](https://readthedocs.org/projects/coix/badge/?version=latest)](https://coix.readthedocs.io/en/latest/?badge=latest) [![PyPI version](https://badge.fury.io/py/coix.svg)](https://badge.fury.io/py/coix) -Inference Combinators in JAX (Coix) is a machine learning framework used to -develop inference algorithms that are composed of probabilistic programs. +Coix (COmbinators In jaX) is a flexible and backend-agnostic implementation of inference combinators [(Stites and Zimmermann et al., 2021)](https://arxiv.org/abs/2103.00668), a set of program transformations for compositional inference with probabilistic programs. Coix ships with backends for numpyro and oryx, and a set of pre-implemented losses and utility functions that allows to implement and run a wide variety of inference algorithms out-of-the-box. *This is not an officially supported Google product.* diff --git a/docs/conf.py b/docs/conf.py index 7da7159..ce17515 100644 --- a/docs/conf.py +++ b/docs/conf.py @@ -164,11 +164,18 @@ # -- Copy notebook files -if not os.path.exists("tutorials"): - os.makedirs("tutorials") +if not os.path.exists("notebooks"): + os.makedirs("notebooks") + +if not os.path.exists("notebooks/figures"): + os.makedirs("notebooks/figures") for src_file in glob.glob("../notebooks/*.ipynb"): - shutil.copy(src_file, "tutorials/") + shutil.copy(src_file, "notebooks/") + +for src_file in glob.glob("../notebooks/figures/*"): + shutil.copy(src_file, "notebooks/figures/") + # add index file to `notebooks` path, `:orphan:` is used to # tell sphinx that this rst file needs not to be appeared in toctree @@ -198,7 +205,7 @@ for src_file in glob.glob("../notebooks/*.ipynb") + glob.glob( "../examples/*.py" ): - toctree_path = "tutorials/" if src_file.endswith("ipynb") else "examples/" + toctree_path = "notebooks/" if src_file.endswith("ipynb") else "examples/" filename = os.path.splitext(src_file.split("/")[-1])[0] png_path = "_static/img/" + toctree_path + filename + ".png" # use Coix logo if not exist png file diff --git a/docs/index.rst b/docs/index.rst index 232b1ce..6fa2a7e 100644 --- a/docs/index.rst +++ b/docs/index.rst @@ -25,6 +25,9 @@ Coix Documentation :caption: Tutorials and Examples :name: tutorials + notebooks/tutorial_part1_vae + notebooks/tutorial_part2_api + notebooks/tutorial_part3_smcs examples/anneal examples/anneal_oryx examples/gmm_oryx diff --git a/notebooks/figures/smcs_nvi.png b/notebooks/figures/smcs_nvi.png new file mode 100644 index 0000000000000000000000000000000000000000..0a9481f7c232859a455f708939f850541558bd6e GIT binary patch literal 81918 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prior, likelihood (a.k.a. decoder model), and variational proposal (a.k.a. encoder model), as probabilistic numpyro programs, which we can later compose using inference combinators. \n", + "The encoder program and decoder program depend on an encoder function $f_\\mathrm{enc}$ and decoder function $f_\\mathrm{dev}$, which we implement as neural networks, with learnable parameters $\\phi$ and $\\theta$ respectively." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "cb7b774f-9eca-4a5b-83c4-02fd78108067", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "import numpyro\n", + "import numpyro.distributions as dist\n", + "\n", + "\n", + "def make_programs(f_enc, f_dec):\n", + " # prior_program does not use x argument but needs to pass it on to dec_program\n", + " def prior_program(params, x):\n", + " z = numpyro.sample(\"z\", dist.Normal(0, 1).expand((2,)).to_event(1))\n", + " return (params, z, x)\n", + "\n", + " # arguments matche the output of prior_program\n", + " def dec_program(params, z, x=None):\n", + " _, dec_params = params\n", + " mean_x = f_dec.apply(dec_params, z)\n", + " x = numpyro.sample(\"x\", dist.Normal(mean_x, 1.0).to_event(1), obs=x)\n", + " return (mean_x, x)\n", + "\n", + " def enc_program(params, x):\n", + " enc_params, _ = params\n", + " mean_z = f_enc.apply(enc_params, x)\n", + " z = numpyro.sample(\"z\", dist.Normal(mean_z, 0.01).to_event(1))\n", + " return (mean_z, z)\n", + "\n", + " return prior_program, enc_program, dec_program" + ] + }, + { + "cell_type": "markdown", + "id": "6bda551d-f4b8-4fbc-939c-e60d91aa1047", + "metadata": {}, + "source": [ + "We define the neural networks as simple Multilayer Perceptrons (MLPs) with a single hidden layer and ReLU activation functions" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "7501df92-54c0-46fd-9e53-ab4852c05337", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "import jax\n", + "from flax import linen as nn\n", + "\n", + "\n", + "class MLP(nn.Module):\n", + "\n", + " @nn.compact\n", + " def __call__(self, x):\n", + " x = nn.Dense(features=32)(x)\n", + " x = nn.relu(x)\n", + " x = nn.Dense(features=2)(x)\n", + " return x\n", + "\n", + "\n", + "f_enc = f_dec = MLP()\n", + "enc_key, dec_key = jax.random.split(jax.random.PRNGKey(0))\n", + "enc_params = f_enc.init(enc_key, data_test.shape)\n", + "dec_params = f_dec.init(dec_key, data_test.shape)\n", + "params = (enc_params, dec_params)" + ] + }, + { + "cell_type": "markdown", + "id": "fd527e1b-fc97-4cea-b5bb-872788e8c462", + "metadata": {}, + "source": [ + "### Combining the encoder program and decoder program using inference combinators" + ] + }, + { + "cell_type": "markdown", + "id": "ed93bfef-4eab-4c7c-9a81-baa73af3755b", + "metadata": {}, + "source": [ + "Having defined probabilistic programs for the prior, likelihood, and variational proposal we can combine these models by applying an inference combinator. An inference combinator is a program transformation which transforms the input programs to a new probabilistic program such that weighted samples produced by the output program are still guaranteed to be approximately distributed w.r.t. the correct target density (which is defined by the combinator). Let's have a look at the combinators we are going to use:\n", + "- `compose(program_2, program_1)` outputs a new probabilistic program, whose weighted samples (when executed) are approximately distributed w.r.t. the joint target density of `program_1` and `program_2`.\n", + "- `propose(target_program, proposal_program)` outputs a new probabilistic program, whose weighted samples (when executed) are approximately distributed w.r.t. the target density of `target_program`.\n", + "\n", + "We will use `compose` to combine `prior_program` with the `dec_program` to a new program, which we call `target_program`. When executed, `target_program` first runs `prior_program` and feeds its outputs, including samples from the prior, to `dec_program`, which then decodes the samples and returns the reconstructions and samples from the decoder. We can conceptually think about applying the compose combinator as constructing the joint distribution $p_\\theta(x, z) = p_\\theta(x \\mid z)p(z)$.\n", + "\n", + "Next we apply the `propose` combinator to `target_program` and `enc_program` to obtain our final inference program. When executed, it runs `enc_program` conditioned on the input data, which generates samples from the approximate posterior. It consecutively runs `target_program` in a *substitution context* conditioned on the drawn samples (i.e. `target_program` will not draw new samples from to the prior, but will reuse the samples from `enc_program` instead).\n", + "We can think about this step as construction the density ratio $p_\\theta(x, z)/q_\\phi(z \\mid x)$ given data $x$ and samples $z$ from the variational proposal.\n", + "\n", + "We additionally define a helper function `make_particle_plate` which adds a additional particle dimension to our probabilistic programs. This allows us to execute our program with different number of particles/samples, e.g. to execute the program on a batch of data instead instead of individual data instances." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "fe54c3a1-c682-4713-a6d5-935ae193008d", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "import coix\n", + "\n", + "coix.set_backend(\"coix.numpyro\")\n", + "\n", + "\n", + "def make_particle_plate(num_particles):\n", + " return numpyro.plate(\"particle\", num_particles, dim=-1)\n", + "\n", + "\n", + "def make_target_and_inference_program(\n", + " prior_program, enc_program, dec_program, num_particles, loss_fn=None\n", + "):\n", + " target_program = make_particle_plate(num_particles)(\n", + " coix.compose(dec_program, prior_program, suffix=False)\n", + " )\n", + " proposal_program = make_particle_plate(num_particles)(enc_program)\n", + " inference_program = coix.propose(\n", + " target_program, proposal_program, loss_fn=loss_fn\n", + " )\n", + " return target_program, inference_program\n", + "\n", + "\n", + "programs = make_programs(f_enc, f_dec)\n", + "target_program, inference_program = make_target_and_inference_program(\n", + " *programs, num_particles=n_test\n", + ")\n", + "out, _, _ = coix.traced_evaluate(target_program, seed=0)(params, x=data_test)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "e30c61b4-5ce1-4e08-a67f-7376bfeec0fa", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "

" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "(means, _), _, _ = coix.traced_evaluate(inference_program, seed=0)(\n", + " params, x=data_test\n", + ")\n", + "\n", + "plt.figure(figsize=(10, 3))\n", + "plt.subplot(121)\n", + "plt.title(\"Test Data\")\n", + "plt.scatter(*data_test.T, alpha=0.1)\n", + "plt.subplot(122)\n", + "plt.title(\"Reconstuctions\")\n", + "plt.scatter(*means.T, alpha=0.1);" + ] + }, + { + "cell_type": "markdown", + "id": "02f5b5a6-aed3-48fa-8c78-fd110871c4fc", + "metadata": {}, + "source": [ + "### Training\n", + "\n", + "Unsurprisingly, the reconstructions of the untrained model do not resemble the test data. So let's train our neural networks. \n", + "We first need to re-compose our inference program in a training context by providing a loss function via the `loss_fn` keyword argument (note that we also changed the surrounding particle plate, i.e. the number of samples, to match our batch size). In this context, every time a propose combinator is executed it additionally evaluates the provided loss function (here the ELBO) for the corresponding importance sampling step. The loss is consecutively stored in the metrics dictionary. Once we computed the loss all we have to do is to differentiate it w.r.t. the parameters of the encoder- and decoder- network and run our favorite gradient descent scheme. " + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "993e6f20-61af-4dd6-8d37-42826a068ec9", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Interation 0: Loss 11.594067573547363\n", + "Interation 10: Loss 10.477442741394043\n", + "Interation 20: Loss 10.214530944824219\n", + "Interation 30: Loss 10.08743953704834\n", + "Interation 40: Loss 10.198956489562988\n", + "Interation 50: Loss 10.160752296447754\n", + "Interation 60: Loss 10.008829116821289\n", + "Interation 70: Loss 10.130775451660156\n", + "Interation 80: Loss 10.030146598815918\n", + "Interation 90: Loss 10.185932159423828\n" + ] + } + ], + "source": [ + "import numpy as np\n", + "import optax\n", + "\n", + "n_batch = 300\n", + "_, inference_program = make_target_and_inference_program(\n", + " *programs, num_particles=n_batch, loss_fn=coix.loss.elbo_loss\n", + ")\n", + "\n", + "\n", + "def loss_fn(rng_key, params, data):\n", + " _, _, metrics = coix.traced_evaluate(inference_program, seed=rng_key)(\n", + " params, x=data\n", + " )\n", + " return metrics[\"loss\"]\n", + "\n", + "\n", + "optimizer = optax.adam(1e-2)\n", + "opt_state = optimizer.init(params)\n", + "\n", + "rng_key = jax.random.PRNGKey(0)\n", + "\n", + "\n", + "def step(step, params, opt_state, data):\n", + " step_key = jax.random.fold_in(rng_key, step)\n", + " batch_key, loss_key = jax.random.split(step_key, 2)\n", + " batch = jax.random.choice(batch_key, data, (n_batch,))\n", + " value, grads = jax.value_and_grad(loss_fn, argnums=1)(loss_key, params, batch)\n", + " updates, opt_state = optimizer.update(grads, opt_state)\n", + " params = optax.apply_updates(params, updates)\n", + " return value, params, opt_state\n", + "\n", + "\n", + "losses = []\n", + "for i in range(100):\n", + " loss, params, opt_state = step(i, params, opt_state, data_train)\n", + " losses.append(loss)\n", + " if i % 10 == 0:\n", + " print(f\"Interation {i}: Loss {loss}\")\n", + "losses = np.stack(losses)" + ] + }, + { + "cell_type": "markdown", + "id": "531b4ff4-e74d-4b71-bb61-9d86d7a3bbf2", + "metadata": {}, + "source": [ + "Finally, let's plot the loss and means of our reconstructions and see if it worked. " + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "63e91ada-1666-4754-adbf-e30df8c03bbd", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "_, inference_program = make_target_and_inference_program(\n", + " *programs, num_particles=n_test\n", + ")\n", + "\n", + "plt.figure(figsize=(20, 3))\n", + "plt.subplot(131)\n", + "plt.title(\"ELBO\")\n", + "plt.plot(-losses)\n", + "plt.subplot(132)\n", + "plt.title(\"Test Data\")\n", + "plt.scatter(*data_test.T, alpha=0.1)\n", + "out, trace, metrics = coix.traced_evaluate(inference_program, seed=0)(\n", + " params, x=data_test\n", + ")\n", + "means, _ = out\n", + "plt.subplot(133)\n", + "plt.title(\"Reconstuctions\")\n", + "plt.scatter(*means.T, alpha=0.1);" + ] + }, + { + "cell_type": "markdown", + "id": "4613eb75-79e6-467b-83ed-0539dca55e67", + "metadata": {}, + "source": [ + "While using coix to composing probabilitic programs to train a VAE is great for building some intuition on what inference combinators can be use for, there is not really much of a gain in term of code complexity or readability compared to a standard VAE implementation. The advantages of using coix really start to show once we try to implement more advances inference algorithms, e.g. variational annealing (see [tutorial part 3](./tutorial_part3_smcs.ipynb)). But before we dive into implementing more complex algorithms we are going to cover the coid API and some of the semantics in more details in [tutorial part 2](./tutorial_part2_api.ipynb)." + ] + } + ], + "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": "3.11.4" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/notebooks/tutorial_part2_api.ipynb b/notebooks/tutorial_part2_api.ipynb new file mode 100644 index 0000000..ec2342c --- /dev/null +++ b/notebooks/tutorial_part2_api.ipynb @@ -0,0 +1,1044 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "5d466658-6b2c-4ee0-9f84-0828621df79b", + "metadata": {}, + "source": [ + "# Tutorial Part 2: Coix API\n", + "\n", + "Inference combinators [(Stites and Zimmermann et al., 2021)](https://arxiv.org/abs/2103.00668) are a set of program transformations for compositional inference and a corresponding small domain specific language (DSL), which describes how these transformations can be composed. We refer to this DSL as *inference language*. Applying inference combinators does not alter the model, which can be defined in an independent *modeling language* -- there only needs to be a common interface between modeling and inference language. Hence, in principle infernce combinators can be implemented on top of any probabilistic *modelling language*. In this tutorial we will use python + numpyro as our probabilistic modeling language but coix also implements backend for pyro and oryx. \n", + "\n", + "Inference combinators comprise four basic program transformations (combinators), `extend`, `resample`, `compose` and `propose`, which can be combined according to the following grammar (in [Backus–Naur form](https://en.wikipedia.org/wiki/Backus%E2%80%93Naur_form), non-terminals in bold text):\n", + "\n", + "\\begin{align}\n", + "\\textbf{k} &::= \\mathrm{primitive\\ program\\ without\\ observe\\ statements}\n", + "\\\\\n", + "\\textbf{f} &::= k \\mid \\mathrm{primitive\\ program\\ with\\ observe\\ statements} && (\\text{primitive programs})\n", + "\\\\\n", + "\\textbf{p} &::= \\textbf{f} \\mid \\mathrm{extend}(\\textbf{p}, \\textbf{k}) && (\\text{target programs})\n", + "\\\\\n", + "\\textbf{q} &::= \\textbf{p} \\mid \\mathrm{propose}(\\textbf{p}, \\textbf{q}) \\mid \\mathrm{resample}(\\textbf{q}) \\mid \\mathrm{compose}(\\textbf{q}, \\textbf{q}) && (\\text{inference programs})\n", + "\\end{align}\n", + "\n", + "The grammar defines the following program taxonomy:\n", + "\\begin{align}\n", + "S_\\mathrm{kernel\\ program} \\subset\n", + "S_\\mathrm{primitive\\ program} \\subset\n", + "S_\\mathrm{target\\ program} \\subset\n", + "S_\\mathrm{inference\\ program}\n", + "\\end{align}\n", + "\n", + "Kernel programs (primitive programs without observe statements) are the most specialized programs, followed by primitive programs and target programs, while inference programs are the most general. \n", + "However, as we will see, this generality comes with restriction in the ways we can combined these programs in oder to guarantee the validity of the composed program.\n", + "\n", + "In the following we walk through basic principles underlying infernce combinators, the application of each combinator, and their composition. The emphasis is on understanding and applying the main concepts, for an in depth technical discussion we refer to [Stites and Zimmermann et al.](https://arxiv.org/abs/2103.00668)." + ] + }, + { + "cell_type": "markdown", + "id": "103888b6-5bce-4e61-92dc-42d1d0995b44", + "metadata": {}, + "source": [ + "### Primitive Programs\n", + "A primitive program is any probabilitic program in the modelling language (e.g. pyro, numpyro, or oryx depending on the backend we chose) which is not constructed by an inference combinator. Let's have a look at the following primitive program:" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "6d6d0679-871b-4d34-b37a-46a5c90e088e", + "metadata": {}, + "outputs": [], + "source": [ + "# !pip install numpyro coix" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "1d48bbfd-7991-451d-aed8-aface18fab2f", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "import jax\n", + "import jax.numpy as jnp\n", + "import numpyro\n", + "from numpyro.handlers import seed, trace\n", + "import numpyro.distributions as dist\n", + "import coix\n", + "\n", + "coix.set_backend(\n", + " \"coix.numpyro\"\n", + ") # Setting the backend depending on the modeling language, here python + numpyro\n", + "from coix import traced_evaluate\n", + "\n", + "log_phi = lambda x: -0.5 * ((x - 1.0) / 0.1) ** 2\n", + "\n", + "\n", + "def f():\n", + " x = numpyro.sample(\"x\", dist.Normal(0.0, 1.0))\n", + " numpyro.factor(\"phi_x\", log_phi(x))\n", + " return (x,)" + ] + }, + { + "cell_type": "markdown", + "id": "21e7eb3b-08d8-408f-93b3-278de48a1b6e", + "metadata": {}, + "source": [ + "We can evaluate the program and have a look at it's trace, the data structure that keeps track of all the random choices made by a program." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "cec2a964-5cf8-444d-8154-c33e9cb594e7", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(Array(-1.2515389, dtype=float32),)\n", + "OrderedDict([('x',\n", + " {'args': (),\n", + " 'cond_indep_stack': [],\n", + " 'fn': ,\n", + " 'infer': {},\n", + " 'intermediates': [],\n", + " 'is_observed': False,\n", + " 'kwargs': {'rng_key': Array([1278412471, 2182328957], dtype=uint32),\n", + " 'sample_shape': ()},\n", + " 'name': 'x',\n", + " 'scale': None,\n", + " 'type': 'sample',\n", + " 'value': Array(-0.58665055, dtype=float32)}),\n", + " ('phi_x',\n", + " {'args': (),\n", + " 'cond_indep_stack': [],\n", + " 'fn': ,\n", + " 'infer': {'is_auxiliary': True},\n", + " 'intermediates': [],\n", + " 'is_observed': True,\n", + " 'kwargs': {'rng_key': None, 'sample_shape': ()},\n", + " 'name': 'phi_x',\n", + " 'scale': None,\n", + " 'type': 'sample',\n", + " 'value': Array([], shape=(0,), dtype=float32)})])\n" + ] + } + ], + "source": [ + "from pprint import pprint\n", + "\n", + "f_seeded = seed(rng_seed=0)(f)\n", + "f_out = f_seeded()\n", + "f_trace = trace(f_seeded).get_trace()\n", + "print(f_out)\n", + "pprint(f_trace)" + ] + }, + { + "cell_type": "markdown", + "id": "ef210bb5-54b1-42f4-93b9-652d57b8a2d3", + "metadata": {}, + "source": [ + "We can see that the program trace has two nodes: (1) a node corresponding to the random variable $x$ and (2) a node corresponding to the factor node $\\phi_x$ which are both of type `sample`. The factor node `phi_x` is *observerd* while the random variable node `x` is not.\n", + "We will see that whether a node is *observed* or *unobserved* plays an important role in the semantics of a program, as it changes the density the program denotes. \n", + "As mentioned above, we call a promitive program without any observe statements a *kernel program*.\n", + "In combinators each primitive program denotes two densities:\n", + "1. a **prior density**, which is defined as the joint density over all unobserverd variables in the program\n", + "2. an **unnormalized target density**, which is defined as the joint density over all variables in the program\n", + "\n", + "To get a better understanding of these densities and why their distinction is important, let's visualize these densities for the primitive program `f` that we defined above:\n", + "1. The prior density is given by the denstity of the normal distribution\n", + "2. The unnormalized target denstity given by the product of the densities of the normal distribution and the factor node" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "63cf7717-1089-4094-99db-edbe29cc8ee7", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "\n", + "log_prior_density = lambda x: dist.Normal(0, 1).log_prob(x)\n", + "log_target_density = lambda x: log_prior_density(x) + log_phi(x)\n", + "xrange_prior = np.linspace(-5, 5, 1000)\n", + "\n", + "plt.figure(figsize=(8, 4))\n", + "plt.title(\"Prior and target density of a primitive program\")\n", + "plt.plot(\n", + " xrange_prior, np.exp(log_prior_density(xrange_prior)), label=\"prior density\"\n", + ")\n", + "plt.plot(\n", + " xrange_prior,\n", + " np.exp(log_target_density(xrange_prior)),\n", + " label=\"target density\",\n", + ")\n", + "plt.plot(xrange_prior, np.exp(log_phi(xrange_prior)), label=\"factor density\")\n", + "plt.legend();" + ] + }, + { + "cell_type": "markdown", + "id": "85206456-f6b7-4fd4-a37d-6945478a56f8", + "metadata": {}, + "source": [ + "\n", + "While it is possible to evaluate programs using numpyro effect handlers, coix implements it's own evaluation handler, `traced_evaluate`, which uses numpyro's `seed` and `trace` handlers under the hood. It exposes the return value of the program, a simplified trace, and an additional `metrics` dictionary, which stores different evaluation metrics that are accumulated during the execution of the program.\n", + "Most importantly, the metrics dictionary contains the log-importance weights corresponding to the execution traces of the program. For primitive programs the log weight is defined as the sum of the log probabilities of all observed random variables in the trace. Hence, the log weight is precisely the difference between the log-prior density and the log-target density of a program. Let's verify this for our example program `f`:" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "94f0bba6-2897-481f-8143-ecae9bfa5145", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "_, f_batch_trace, f_batch_metrics = traced_evaluate(\n", + " numpyro.plate(\"particle_plate\", 20)(f), seed=0\n", + ")()\n", + "\n", + "plt.figure(figsize=(10, 6))\n", + "plt.title(\"Prior and target density of a primitive program\")\n", + "plt.plot(\n", + " xrange_prior, np.exp(log_prior_density(xrange_prior)), label=\"prior density\"\n", + ")\n", + "plt.plot(\n", + " xrange_prior,\n", + " np.exp(log_target_density(xrange_prior)),\n", + " label=\"target density\",\n", + ")\n", + "\n", + "plt.scatter(\n", + " f_batch_trace[\"x\"][\"value\"],\n", + " np.exp(f_batch_trace[\"x\"][\"log_prob\"]),\n", + " label=\"prior density\",\n", + ")\n", + "plt.scatter(\n", + " f_batch_trace[\"x\"][\"value\"],\n", + " np.exp(f_batch_trace[\"x\"][\"log_prob\"] + f_batch_metrics[\"log_weight\"]),\n", + " label=\"prior density * weight\",\n", + ")\n", + "plt.legend();" + ] + }, + { + "cell_type": "markdown", + "id": "2b7d82e7-bdbf-47f7-806b-80edf2999be1", + "metadata": {}, + "source": [ + "### Proper Weighting\n", + "\n", + "The above observation suggests that we can use the weighted samples $(x, w)$ produced by a primitive program to approximate expectations w.r.t. its target density up to a normalization constant $Z$. \n", + "We refer to this property as *proper weighting*. We can generalize this notion of proper weighting to programs that define more than one variable, by weighting execution traces $\\tau$ instead, which track all random choices of a particular program evaluation.\n", + "\n", + "\n", + "**Definition (Properly weighted evaluation)**:\n", + "We say *the evaluation of the program $\\tau, w \\leftarrow f$ is properly weighted w.r.t. its unnormalized target density $\\gamma_{target} = Z p_{target}$*, if for all measurable function $h$,\n", + "\n", + "\\begin{align}\n", + "\\mathbb{E}_{\\tau, w}\\left[ w \\cdot h (\\tau) \\right] \n", + "=\n", + "Z \\cdot \\mathbb{E}_{p_{target}} \\left[ h(\\tau) \\right]\n", + ".\n", + "\\end{align}\n", + "\n", + "Indeed, with the definition of the target density and weight of a primitive program above, we can show that all primitive programs are properly weighted w.r.t. their target densities (see [Stites and Zimmermann et al., 2021](https://arxiv.org/abs/2103.00668)). \n", + "\n", + "As this property holds for any measureable function $h$, it must also hold for $h(\\tau) = 1$. In this case the above equation reduces to $\\mathbb{E}_{\\tau, w}\\left[ w \\right] = Z$, meaning that the expected weight must equal the normalizing constant of the target density. \n", + "\n", + "Let's test this for our example program `f`. Fortunately, for our example, we can compute the normalization constant for the target density of `f` analytically by noticing that the factor $\\phi_x$ is just an unnormalized normal density. This allows us to do some math to derive the normalizing constant $Z_{target}$ (for the purpose of this tutorial the math can safely be skipped):\n", + "\n", + "\\begin{align}\n", + "Z_{target} = \\sqrt{2\\pi\\sigma_{target}^2} \\cdot Z_{\\phi}\n", + ",&&\n", + "Z_{\\phi} = \\sqrt{2\\pi\\sigma_{\\phi}^2}\n", + ",&&\n", + "\\sigma^2_{target} = \\frac{1}{\\frac{1}{\\sigma_x^2} + \\frac{1}{\\sigma_{\\phi}^2}}\n", + ".\n", + "\\end{align}\n", + "\n", + "\n", + "If the the samples we obtained from running `f` are propoerly weighted, we should be able to compute an estimate of the normalizing constant of the target density of `f` by simply averaging them." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "f449cbad-00ec-4c73-a723-d0ed0507a367", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Normalizing constant: 0.062520035\n", + "Estimated normalizing constant: 0.06102728\n" + ] + } + ], + "source": [ + "var_prior = 1.0\n", + "var_factor = 0.1**2\n", + "var_target = 1 / (1 / var_prior + 1 / var_factor)\n", + "Z_target = np.sqrt(2 * np.pi * var_target) * jnp.sqrt(2 * jnp.pi * var_factor)\n", + "normalized_log_target_density = lambda x: log_target_density(x) - jnp.log(\n", + " Z_target\n", + ")\n", + "\n", + "_, f_batch_trace, f_batch_metrics = traced_evaluate(\n", + " numpyro.plate(\"particle_plate\", 10000)(f), seed=0\n", + ")()\n", + "approx_target_sampels = f_batch_trace[\"x\"][\"value\"]\n", + "weights = jnp.exp(f_batch_metrics[\"log_weight\"])\n", + "\n", + "print(\"Normalizing constant:\", Z_target)\n", + "print(\"Estimated normalizing constant:\", weights.mean())" + ] + }, + { + "cell_type": "markdown", + "id": "5d94a6f0-9ca4-4760-9b1b-317caf21df8a", + "metadata": {}, + "source": [ + "A convinient way to visially check if the weighted samples we generated approximate out target density well is to simply plot a sample histogram." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "53bfbc5e-b2d1-4fd7-86d0-8b5aa43be13c", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "xrange_target = np.linspace(0, 2, 100)\n", + "plt.plot(\n", + " xrange_target,\n", + " np.exp(normalized_log_target_density(xrange_target)),\n", + " label=\"target density\",\n", + " color=\"C1\",\n", + ")\n", + "_ = plt.hist(\n", + " approx_target_sampels,\n", + " weights=weights,\n", + " density=True,\n", + " bins=100,\n", + " range=(xrange_target[0], xrange_target[-1]),\n", + " color=\"C1\",\n", + " alpha=0.5,\n", + ")\n", + "plt.legend();" + ] + }, + { + "cell_type": "markdown", + "id": "5baa65e8-3c58-41a2-948b-f1d9e18cbb08", + "metadata": {}, + "source": [ + "### Target Programs\n", + "Now that we understand the significance of the densities denoted by a program, as well as the role of the importance weight associated with a program evaluation, we can talk about target programs. The grammar defines a target programs as\n", + "\n", + "\\begin{align}\n", + "p &::= f \\mid \\mathrm{extend}(p, k)\n", + "\\end{align}\n", + "\n", + "In other words, a target program is either\n", + "1. primitive program or \n", + "2. a program produced by an `extend` combinator\n", + "\n", + "We already talked about primitive programs and the prior- and target-density they denote, so let's have a closer look at *extended programs*. The `extend` combinator is used to produce a program that extends the prior and target density of a target program `p` by introducing *auxiliary variables*. When an extended program is executed it first executes the target program `p` and consecutively runs the kernel program `k` on the output of `p`.\n", + "The prior density and of the extended program `extend(p, k)` is defined as the product of the prior densities of the input programs, `p` and `k`. Similarly the target density of `extend(p, k)` is defined as the product the target densities of the input programs.\n", + "\n", + "Importantly, `extend(p, k)` is only valid if `k` is a kernel program. Moreover, it does not check if `k` does contains any illegal observe statements, so it is our responsibility to make use we are passing a kernel program.\n", + "\n", + "Let's see what happens when we extend the primitive program `f` with a kernel program:" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "05a7c937-9b12-49f7-9423-79e8c22ad7a2", + "metadata": {}, + "outputs": [], + "source": [ + "def k(x):\n", + " y = numpyro.sample(\"y\", dist.Normal(2 * x + 3, 0.5))\n", + " return (y,)\n", + "\n", + "\n", + "p_ext = coix.extend(f, k)\n", + "log_extend_density = lambda x, y: dist.Normal(2 * x + 3, 0.5).log_prob(y)\n", + "log_extended_target_density = lambda x, y: log_target_density(\n", + " x\n", + ") + log_extend_density(x, y)\n", + "log_extended_prior_density = lambda x, y: log_prior_density(\n", + " x\n", + ") + log_extend_density(x, y)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "364f722c-2cf3-432f-a3bc-03dc8b3fc20f", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# A bunch of plotting code that can be ignored...\n", + "from matplotlib import colors, lines, gridspec\n", + "\n", + "\n", + "def plot_extended_density_samples(\n", + " p, name_x=\"x\", name_y=\"y\", color1=\"C0\", color2=\"C1\"\n", + "):\n", + " p_batch = numpyro.plate(\"particle_plate\", 10000)(p)\n", + " out, trace, metrics = traced_evaluate(p_batch, seed=0)()\n", + " out_rs, trace_rs, metrics_rs = traced_evaluate(\n", + " coix.resample(p_batch), seed=0\n", + " )()\n", + " xs, ys, ws = (\n", + " trace[name_x][\"value\"],\n", + " trace[name_y][\"value\"],\n", + " jax.nn.softmax(metrics[\"log_weight\"]),\n", + " )\n", + " # xs_rs, ys_rs = trace_rs[name_x][\"value\"], trace_rs[name_y][\"value\"]\n", + "\n", + " fig = plt.figure(figsize=(8, 8))\n", + " gs = gridspec.GridSpec(3, 3, wspace=0, hspace=0)\n", + "\n", + " ax_xy = plt.subplot(gs[1:3, :2])\n", + " cmap_c0 = colors.LinearSegmentedColormap.from_list(\n", + " \"c0_alpha\",\n", + " [\n", + " colors.colorConverter.to_rgba(color1, alpha=0),\n", + " colors.colorConverter.to_rgba(color1, alpha=1),\n", + " ],\n", + " 256,\n", + " )\n", + " cmap_c1 = colors.LinearSegmentedColormap.from_list(\n", + " \"c1_alpha\",\n", + " [\n", + " colors.colorConverter.to_rgba(color2, alpha=0),\n", + " colors.colorConverter.to_rgba(color2, alpha=1),\n", + " ],\n", + " 256,\n", + " )\n", + " ax_xy.hist2d(\n", + " xs,\n", + " ys,\n", + " bins=100,\n", + " density=True,\n", + " cmap=cmap_c0,\n", + " )\n", + " ax_xy.hist2d(\n", + " xs,\n", + " ys,\n", + " bins=100,\n", + " density=True,\n", + " weights=ws,\n", + " cmap=cmap_c1,\n", + " )\n", + " ax_xy.set(xlabel=name_x, ylabel=name_y)\n", + "\n", + " ax_x = plt.subplot(gs[0, :2], sharex=ax_xy)\n", + " ax_x.set(title=f\"{name_x}-marginal densities\")\n", + " ax_x.hist(xs, bins=100, align=\"mid\", density=True, alpha=0.5, color=color1)\n", + " ax_x.hist(\n", + " xs,\n", + " bins=100,\n", + " weights=ws,\n", + " align=\"mid\",\n", + " density=True,\n", + " alpha=0.5,\n", + " color=color2,\n", + " )\n", + "\n", + " ax_y = plt.subplot(gs[1:3, 2], sharey=ax_xy)\n", + " ax_y.set(title=f\"{name_y}-marginal densities\")\n", + " ax_y.hist(\n", + " ys,\n", + " bins=100,\n", + " orientation=\"horizontal\",\n", + " align=\"mid\",\n", + " density=True,\n", + " alpha=0.5,\n", + " color=color1,\n", + " )\n", + " ax_y.hist(\n", + " ys,\n", + " bins=100,\n", + " weights=ws,\n", + " align=\"mid\",\n", + " density=True,\n", + " orientation=\"horizontal\",\n", + " alpha=0.5,\n", + " color=color2,\n", + " )\n", + " return ax_xy, ax_x, ax_y\n", + "\n", + "\n", + "N_x, N_y = 200, 400\n", + "xrange_ext = np.linspace(-4, 4, N_x)\n", + "yrange_ext = np.linspace(-4, 10, N_y)\n", + "m_xy = np.dstack(np.meshgrid(xrange_ext, yrange_ext))\n", + "m_p_target = np.exp(\n", + " log_extended_target_density(*m_xy.reshape(N_x * N_y, 2).T).reshape(N_y, N_x)\n", + ")\n", + "m_p_prior = np.exp(\n", + " log_extended_prior_density(*m_xy.reshape(N_x * N_y, 2).T).reshape(N_y, N_x)\n", + ")\n", + "\n", + "ax_xy, ax_x, ax_y = plot_extended_density_samples(p_ext)\n", + "ax_x.plot(xrange_prior, np.exp(log_prior_density(xrange_prior)), color=\"C0\")\n", + "ax_x.plot(\n", + " xrange_prior,\n", + " np.exp(normalized_log_target_density(xrange_prior)),\n", + " color=\"C1\",\n", + ")\n", + "ax_xy.contour(\n", + " m_xy[..., 0], m_xy[..., 1], m_p_prior, levels=[0.05, 0.3], colors=\"C0\"\n", + ")\n", + "ax_xy.contour(\n", + " m_xy[..., 0], m_xy[..., 1], m_p_target, levels=[0.05, 0.3], colors=\"C1\"\n", + ")\n", + "handles, labels = ax_xy.get_legend_handles_labels()\n", + "handles.extend([\n", + " lines.Line2D(\n", + " [0], [0], label=\"prior density of $extend(f,\\ k)$\", color=\"C0\"\n", + " ),\n", + " lines.Line2D(\n", + " [0], [0], label=\"target denstity of $extend(f,\\ k)$\", color=\"C1\"\n", + " ),\n", + "])\n", + "ax_xy.legend(handles=handles, loc=\"lower left\");" + ] + }, + { + "cell_type": "markdown", + "id": "f35e0f95-f190-43ec-8043-5d1fd67c9c05", + "metadata": {}, + "source": [ + "We see that the prior-density and target-density of `f` on $X$ have been *extended* to densities on $X \\times Y$. \n", + "Note that the marginals (over $X$) of the extended prior- and target-density of `extend(f, k)` correspond exactly to the prior- and target-density of our *unextended* target program `f`.\n", + "\n", + "#### Extending vs combining programs in the modeling language.\n", + "It is important to understand that we can also create a new *extended* primitive program `f2(*args) = k(*f(*args))` in the modeling language, which denotes the same prior- and target-density as `extend(f, k)`, but has slightly different inference semantics. Extended programs treat the newly created variables as *auxiliary variables*, i.e. variables that are introduces to compute a valid importance weight only, but do not directly influence the computation thereafter. This becomes clear when observing the return values of these programs. While the combined primitive program `f2` outputs the return value of `k` the extended program `extend(f, k)` returns the return value of `f`, i.e. it does not allow the computation down the line to condition on any auxiliary variables (or other outputs) produced by `k`. Let's check this statement:" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "cb272cec-9e5f-4cab-87c2-968370c87967", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Return value of f3 (Array(0.20359698, dtype=float32),) --> This is the value of y (check trace below)\n", + "Return value of p_ext (Array(-1.2515389, dtype=float32),) --> This is the value of x (check trace below)\n", + "\n", + "The traces of f3 and p_ext are identical:\n", + "\n", + "Trace of f2:\n", + "{'phi_x': {'is_observed': True,\n", + " 'log_prob': Array(-253.47131, dtype=float32),\n", + " 'value': Array([], shape=(0,), dtype=float32)},\n", + " 'x': {'log_prob': Array(-1.7021133, dtype=float32),\n", + " 'value': Array(-1.2515389, dtype=float32)},\n", + " 'y': {'log_prob': Array(-0.39787078, dtype=float32),\n", + " 'value': Array(0.20359698, dtype=float32)}}\n", + "\n", + "Trace of p_ext:\n", + "{'phi_x': {'is_observed': True,\n", + " 'log_prob': Array(-253.47131, dtype=float32),\n", + " 'value': Array([], shape=(0,), dtype=float32)},\n", + " 'x': {'log_prob': Array(-1.7021133, dtype=float32),\n", + " 'value': Array(-1.2515389, dtype=float32)},\n", + " 'y': {'log_prob': Array(-0.39787078, dtype=float32),\n", + " 'value': Array(0.20359698, dtype=float32)}}\n" + ] + } + ], + "source": [ + "f2 = lambda *args: k(*f(*args))\n", + "out_f2, trace_f2, _ = traced_evaluate(f2, seed=0)()\n", + "out_ext, trace_ext, _ = traced_evaluate(p_ext, seed=0)()\n", + "print(\n", + " \"Return value of f3\",\n", + " out_f2,\n", + " \"--> This is the value of y (check trace below)\",\n", + ")\n", + "print(\n", + " \"Return value of p_ext\",\n", + " out_ext,\n", + " \"--> This is the value of x (check trace below)\",\n", + ")\n", + "print(\"\\nThe traces of f3 and p_ext are identical:\")\n", + "print(\"\\nTrace of f2:\")\n", + "pprint(trace_f2)\n", + "print(\"\\nTrace of p_ext:\")\n", + "pprint(trace_ext)" + ] + }, + { + "cell_type": "markdown", + "id": "52dd0ede-5036-4483-aad9-1d6db80a55d4", + "metadata": {}, + "source": [ + "While it might not be intuitively clear why an construction like `extend` is needed, it is essential to guarantee the correctness (proper weighting) of auxiliary variable schemes, which will be discuss in a later tutorial. For now it's enough to remember that we should use the modeling language to compose our models and use `extend` only when we explicitly want to describe an auxiliary variable scheme. Or more generally, use the modeling language for modeling and the inference language (coix) for inference! " + ] + }, + { + "cell_type": "markdown", + "id": "7a3807b2-a293-41e5-be19-1aee706d568f", + "metadata": { + "tags": [] + }, + "source": [ + "### Inference Programs\n", + "Inference programs are programs that use properly weighted samples generated from a proposal program to construct properly weighted samples for a target program.\n", + "The grammar degines an inference program as:\n", + "\n", + "\\begin{align}\n", + "\\textbf{q}\n", + "&::= \n", + "\\textbf{p}\n", + "\\mid \n", + "\\mathrm{propose}(\\textbf{p}, \\textbf{q})\n", + "\\mid \n", + "\\mathrm{resample}(\\textbf{q}) \n", + "\\mid \n", + "\\mathrm{compose}(\\textbf{q}, \\textbf{q}) \n", + "\\end{align}\n", + "\n", + "In words, a inference program is either \n", + "1. a target program `p` (including primitive programs)\n", + "2. a program `compose(q, q')`\n", + "3. a program `propose(p, q)`\n", + "4. a program `resample(q)`\n", + "\n", + "Let's discuss each of these options one-by-one and have a look at their importance weights." + ] + }, + { + "cell_type": "markdown", + "id": "a9235dff-2059-4d03-9ddb-faa2f3d2a395", + "metadata": { + "jp-MarkdownHeadingCollapsed": true, + "tags": [] + }, + "source": [ + "#### 1. Target and primitive programs as inference programs\n", + "We already defined the target density of a primitive program and discussed that the weight of a primitive program evaluation corresponds to the product of the probability densities of all observed random variables. We have also seen that this exactly amounts to the difference between the prior- and target-density in log space. Let's make this a bit more formal. Let $\\tau_f = \\mathrm{trace}($ `f` $)$ be the trace of a our primitive program `f`, and explicitly write down the weight:\n", + "\n", + "\\begin{align}\n", + "w_f = \\prod_{x_i \\in \\tau_f} \\phi(x_i) \n", + "= \\prod_{x_i \\in \\tau_f} \\frac{\\phi(x_i) p_x(x_i \\mid x_{0:i-1})}{p_x(x_i \\mid x_{0:i-1})}\n", + "= \\prod_{x_i \\in \\tau_f} \\frac{\\gamma_x(x_i \\mid x_{0:i-1})}{p_x(x_i \\mid x_{0:i-1})}\n", + "= \\frac{\\gamma_{f}(\\tau_f)}{p_{f}(\\tau_f)}\n", + ".\n", + "\\end{align}\n", + "\n", + "We can see that the weight corresponds to an unnormalized importance weight that corrects for using samples generated from the program prior in place of samples form the unnormalized target density of the program. \n", + "In other words, a primitive program can be interpreted as an importance sampler, that implicitly uses the program prior as a proposal to target the unnormalized density of the same program. \n", + "\n", + "Computing the importance weight of a target program that is the output of a extend combinator, e.g. `p_ext := extend(p, f)`, works analogously but is computed on the variables in the combined trace $\\tau_{p_{ext}} = \\mathrm{trace}($ `p_ext` $)$. We can interpret the program as a importance sampler that targets the extended target density and implicitly uses the extended prior density as a proposal. \n", + "\n", + "Importance sampling using the prior as a proposal is also known as *likelihood* weighting, as the weight (after canceling-out the prior density terms) corresponds to the likelihood, i.e. the density of the observed random variables.\n", + "While valid, likelihood weighting often performs very poorly in practice when the prior and target density differ significantly, which often yields high-variance importance weights. \n", + "\n", + "Fortunately we can often do better! Let's see how we can use the propose combinator to construct proposals by means of another probabilistic program." + ] + }, + { + "cell_type": "markdown", + "id": "47c508f1-d25c-4812-b699-ac926a7c61aa", + "metadata": {}, + "source": [ + "#### 2. Propose\n", + "\n", + "An inference program `propose(p, q)` defines the same target density as `p` but uses the program `q` to generate proposals instead of proposing from the program prior of `p`. \n", + "Let's build some intuition by writing a proposal program for out example program `f`. We know the target density of `f`, so it should be quiet easy to construct a proposal that performs better (in terms of weight variance) than naively proposing from the prior:" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "073b5a99-860d-4e38-b5f1-9fa756d38873", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Variance and ess of importance weight using the prior as a proposal: 0.03914084\n", + "Variance and ess of importance weight using the new proposal as a proposal: 0.009500867\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "def q():\n", + " x = numpyro.sample(\"x\", dist.Normal(1, 0.5))\n", + " return (x,)\n", + "\n", + "\n", + "def log_proposal_density(x):\n", + " return dist.Normal(1, 0.5).log_prob(x)\n", + "\n", + "\n", + "log_extended_proposal_density = lambda x, y: log_proposal_density(\n", + " x\n", + ") + log_extend_density(x, y)\n", + "\n", + "\n", + "f_batch = numpyro.plate(\"particle_plate\", 10000)(f)\n", + "q_batch = numpyro.plate(\"particle_plate\", 10000)(q)\n", + "q2 = coix.propose(f_batch, q_batch)\n", + "_, q2_trace, q2_metrics = traced_evaluate(q2, seed=0)()\n", + "_, _, f_batch_metrics = traced_evaluate(f_batch, seed=0)()\n", + "\n", + "approx_target_sampels = q2_trace[\"x\"][\"value\"]\n", + "weights = jnp.exp(q2_metrics[\"log_weight\"])\n", + "weights_prior = np.exp(f_batch_metrics[\"log_weight\"])\n", + "ess = q2_metrics[\"ess\"]\n", + "# ess_prior = jnp.exp(f_batch_metrics[\"ess\"])\n", + "print(\n", + " \"Variance and ess of importance weight using the prior as a proposal:\",\n", + " np.var(weights_prior),\n", + ")\n", + "print(\n", + " \"Variance and ess of importance weight using the new proposal as a\"\n", + " \" proposal:\",\n", + " np.var(weights),\n", + ")\n", + "\n", + "plt.plot(\n", + " xrange_target,\n", + " np.exp(normalized_log_target_density(xrange_target)),\n", + " label=\"target density\",\n", + " color=\"C1\",\n", + ")\n", + "plt.plot(\n", + " xrange_target,\n", + " np.exp(log_prior_density(xrange_target)),\n", + " label=\"prior density\",\n", + " color=\"C0\",\n", + ")\n", + "plt.plot(\n", + " xrange_target,\n", + " np.exp(log_proposal_density(xrange_target)),\n", + " label=\"new proposal density\",\n", + " color=\"C2\",\n", + ")\n", + "_ = plt.hist(\n", + " approx_target_sampels,\n", + " weights=weights,\n", + " density=True,\n", + " bins=100,\n", + " range=(xrange_target[0], xrange_target[-1]),\n", + " color=\"C1\",\n", + " alpha=0.5,\n", + ")\n", + "plt.legend();" + ] + }, + { + "cell_type": "markdown", + "id": "9422778a-4e94-4a80-b98f-a97039cd6fef", + "metadata": {}, + "source": [ + "We see that the weighted samples generated by `propose(p, q)` approximate the same target density as before. However, the variance of the weights is significantly lower compared to proposing from the program prior." + ] + }, + { + "cell_type": "markdown", + "id": "df36750c-a4da-4a20-a52d-551ecd76acda", + "metadata": { + "tags": [] + }, + "source": [ + "#### 3. Resample" + ] + }, + { + "cell_type": "markdown", + "id": "d7b8c6f7-8008-411d-b346-390fe3335088", + "metadata": {}, + "source": [ + "If we want to generate equally-weighted approximate samples from a target density or discard low-weight samples while maintaining proper weighting we can use the resample combinator. `resample(q)` return a program that first evaluates `q` and then resamples the samples generated by `q` according to their importance weights.\n", + "\n", + "Resampling can be a useful tool that allows us to reallocate particles from low-density regions to high-density regions while maintaining proper weighting and thus to make better use of our overall sampling budget. However, resampling also reduces the sample diversity, as high-weight samples are likely to be reproduced multiple times, which can lead to sample degeneracy. **Hence, resampling should be used with care and it's generably to double-check if the resulting samples suffers from path degeneracy!**\n", + "\n", + "Let's resample our priviouse inference program `q2`:" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "98fa48d5-86a5-48fe-8f68-27e1f93d42fd", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The log weights after resampling are all equal: [0.06132786 0.06132786 0.06132786 ... 0.06132786 0.06132786 0.06132786]\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "q3 = coix.resample(q2)\n", + "_, q3_trace, q3_metrics = traced_evaluate(q3, seed=0)()\n", + "approx_target_sampels = q3_trace[\"x\"][\"value\"]\n", + "weights = jnp.exp(q3_metrics[\"log_weight\"])\n", + "print(\"The log weights after resampling are all equal:\", weights)\n", + "\n", + "plt.plot(\n", + " xrange_target,\n", + " np.exp(normalized_log_target_density(xrange_target)),\n", + " label=\"target density\",\n", + " color=\"C1\",\n", + ")\n", + "_ = plt.hist(\n", + " approx_target_sampels,\n", + " weights=weights,\n", + " density=True,\n", + " bins=100,\n", + " range=(xrange_target[0], xrange_target[-1]),\n", + " color=\"C1\",\n", + " alpha=0.5,\n", + ")\n", + "plt.legend();" + ] + }, + { + "cell_type": "markdown", + "id": "997c06ba-bbc1-4d16-b95e-c9a2e8c59009", + "metadata": {}, + "source": [ + "#### 4. Compose\n", + "\n", + "We discussed that we can combine primitive programs via function composition in the modeling language or by using `extend` to construct a target programs that make use of auxiliary variables, but there is yet another construct to combine inference programs, `compose`. `compose(q, q')` constructs a new inference program by combining two inference programs, `q` and `q'`. The resulting inference program targets joint target density of both program, while proposing from the joint prior density. \n", + "Similar to function composition, `compose(q, q')` allows arbitrary observe statements in both input programs, `q` and `q'`, and returns the output of the *extending program* `q'` (note that the extending program is the 2nd argument here). \n", + "\n", + "Let's revisit the extended space example form above, but this time we extend the inference program `q2` instead of `f`. Note that `q2` and `f` have the same target density, but different inference semantics, i.e. they differ in how they generate proposals and compute the corresponding importance weights." + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "45e2f335-b2d5-4099-bbff-1579e8708574", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Variance of importance weight of $extend(f, k)$: 0.03914084\n", + "Variance of importance weight of $compose(k, q2)$: 0.009500865\n" + ] + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "q_com = coix.compose(k, q2)\n", + "\n", + "m_xy = np.dstack(np.meshgrid(xrange_ext, yrange_ext))\n", + "m_p_target = np.exp(\n", + " log_extended_target_density(*m_xy.reshape(N_x * N_y, 2).T).reshape(N_y, N_x)\n", + ")\n", + "m_p_prior = np.exp(\n", + " log_extended_prior_density(*m_xy.reshape(N_x * N_y, 2).T).reshape(N_y, N_x)\n", + ")\n", + "m_p_proposal = np.exp(\n", + " log_extended_proposal_density(*m_xy.reshape(N_x * N_y, 2).T).reshape(\n", + " N_y, N_x\n", + " )\n", + ")\n", + "\n", + "ax_xy, ax_x, ax_y = plot_extended_density_samples(q_com, color1=\"C2\")\n", + "ax_x.plot(xrange_prior, np.exp(log_prior_density(xrange_prior)), color=\"C0\")\n", + "ax_x.plot(xrange_prior, np.exp(log_proposal_density(xrange_prior)), color=\"C2\")\n", + "ax_x.plot(\n", + " xrange_prior,\n", + " np.exp(normalized_log_target_density(xrange_prior)),\n", + " color=\"C1\",\n", + ")\n", + "ax_xy.contour(\n", + " m_xy[..., 0], m_xy[..., 1], m_p_prior, levels=[0.05, 0.3], colors=\"C0\"\n", + ")\n", + "ax_xy.contour(\n", + " m_xy[..., 0], m_xy[..., 1], m_p_proposal, levels=[0.05, 0.3], colors=\"C2\"\n", + ")\n", + "ax_xy.contour(\n", + " m_xy[..., 0], m_xy[..., 1], m_p_target, levels=[0.05, 0.3], colors=\"C1\"\n", + ")\n", + "handles, labels = ax_xy.get_legend_handles_labels()\n", + "handles.extend([\n", + " lines.Line2D(\n", + " [0], [0], label=\"prior density of $extend(f,\\ k)$\", color=\"C0\"\n", + " ),\n", + " lines.Line2D(\n", + " [0], [0], label=\"proposal denstity $compose(k,\\ q2)$\", color=\"C2\"\n", + " ),\n", + " lines.Line2D(\n", + " [0],\n", + " [0],\n", + " label=\"target denstity $extend(f, k)$ and $compose(k,\\ q2)$\",\n", + " color=\"C1\",\n", + " ),\n", + "])\n", + "ax_xy.legend(handles=handles, loc=\"lower left\")\n", + "\n", + "_, f_ext_trace, f_ext_metrics = traced_evaluate(\n", + " numpyro.plate(\"particle_plate\", 10000)(p_ext), seed=0\n", + ")()\n", + "_, _, q_com_metrics = traced_evaluate(q_com, seed=0)()\n", + "w_ext = np.exp(f_ext_metrics[\"log_weight\"])\n", + "w_com = np.exp(q_com_metrics[\"log_weight\"])\n", + "print(\"Variance of importance weight of $extend(f, k)$:\", np.var(w_ext))\n", + "print(\"Variance of importance weight of $compose(k, q2)$:\", np.var(w_com))" + ] + }, + { + "cell_type": "markdown", + "id": "01c1c434-c009-4418-b8ca-e27416c6d93a", + "metadata": {}, + "source": [ + "Extending the inference program `q2` instead of the primitive program `f`, results in better coverage of the extended target density, as `q1` uses `q` as a proposal instead of the program prior of `f`. This is again reflected in the variance of the importance weights. Note that the variances are exactly the same as for the non-extended example above. This is because we extended/composed our programs with a kernel program `k`, which does not have any observe statements (and we use the same random seed). As a consequence the prior and target density of the kernel program are the same and cancel out of the final importance weight.\n", + "\n", + "##### Why not always use `propose`? Isn't it just a more flexible version of `extend`?\n", + "The answer is yes, but this flexibility comes with a caveat. We are not allowed to use programs constructed by a compose combinator as target programs in later computations. The same is true for any other inference program that is not itself a target program. On a high level, this is because inference programs might represent empirical densities, i.e. degenerate densities that are represented by a set of weighted particles only. As a result we need to be careful how we compose such programs. This is why it's important to follow the rules of the grammar (unless we know exatcly what you are doing)!\n" + ] + }, + { + "cell_type": "markdown", + "id": "73e55c54-02f0-4572-8b8e-82d7c8bea086", + "metadata": {}, + "source": [ + "### Takeaway\n", + "\n", + "We are now ready to start combining programs using inference combinators and as long as we follow the rules of the grammar the resulting programs are valid, in the sense that they produce propoerly weighted sampels for the target densities they define.\n", + "\n", + "To ensure that all evaluations are properly weighted, more general programs are more restricted in the ways they can be combined with other programs. If in doubt, check the grammar!\n", + "\n", + "As we have seen in the [first tutorial](./tutorial_part1_vae.ipynb), programs can also depend on additional parameter, which can be optimized via stochastic gradient descent. To this end the propose combinator provides a convinient option to compute a loss at every importance sampling step by passing the `loss_fn` argument to the propose combinator.\n", + "\n", + "We demonstrate how inference combinators can be used to compose and train a complex model using a SMC-sampler that samples along a geometric annealing path in the [third tutorial](./tutorial_part3_smcs.ipynb). " + ] + } + ], + "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": "3.11.4" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/notebooks/tutorial_part3_smcs.ipynb b/notebooks/tutorial_part3_smcs.ipynb new file mode 100644 index 0000000..34eeac1 --- /dev/null +++ b/notebooks/tutorial_part3_smcs.ipynb @@ -0,0 +1,593 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "915e3035-fc65-4020-a0ac-48657d952f65", + "metadata": {}, + "source": [ + "## Tutorial Part 3: Annealed Sequential-Monte-Carlo Sampler" + ] + }, + { + "cell_type": "markdown", + "id": "5d466658-6b2c-4ee0-9f84-0828621df79b", + "metadata": { + "tags": [] + }, + "source": [ + "![](figures/smcs_nvi.png)\n", + "\n", + "### Introduction\n", + "\n", + "In this tutorial we using inference combinators to implement a Sequential Monte Carlo Sampler [(Del Moral et al., 2006)](https://rss.onlinelibrary.wiley.com/doi/abs/10.1111/j.1467-9868.2006.00553.x) that generates samples along a geometric annealing path \n", + "\n", + "\\begin{align}\n", + "\\gamma_k(x; \\beta_k) := q_1(x)^{(1-\\beta_k)}\\gamma(x)^{\\beta_k}\n", + ",&&\n", + "\\beta_1 = 0\n", + ",&&\n", + "\\beta_k \\in [0, 1]\n", + ",&&\n", + "\\beta_K = 1,\n", + "\\end{align}\n", + "\n", + "as outlined in [Zimmermann et al.](https://proceedings.neurips.cc/paper/2021/file/ab49b208848abe14418090d95df0d590-Paper.pdf). \n", + "At each step $k$ we are given approximate samples $x_{k-1}$ from the last target $\\gamma_{k-1}$ and use a variational proposals $q_k(\\cdot \\mid x_{k-1})$ to generate proposals $x_k$ for the next target density $\\gamma_k$. We use these proposals to compute an importance weights\n", + "\n", + "\\begin{align}\n", + "w_1 = 1\n", + ",&& \n", + "w_k = \\frac{r_{k-1}(x_{k-1} \\mid x_k)\\gamma_k(x_k)}{\\gamma_{k-1}(x_{k-1})q_k(x_k \\mid x_{k-1})}\n", + "&& \\text{for}\\ 1 < k\\leq K\n", + ",\n", + "\\end{align}\n", + "\n", + "which we can use to resample our particles in order to get approximate samples for the next target distribution $\\gamma_k$. \n", + "\n", + "While this sampling strategy is always valid, the quality of the sampler crucially depends on the variance of the importance weight above. The variance of the importance weights $w_k$ is minimized when \n", + "\n", + "\\begin{align}\n", + "\\check \\gamma_k(x_{k-1}, x_k)\n", + ":= r_{k-1}(x_{k-1} \\mid x_k)\\gamma_k(x_k) && \\text{and}\\ && \\hat \\gamma_k(x_{k-1}, x_k)\n", + ":= \\gamma_{k-1}(x_{k-1})q_k(x_k \\mid x_{k-1})\n", + "\\end{align}\n", + "\n", + "are equal. To make $\\hat \\gamma_k$ as similar as possible to $\\check\\gamma_k$, we model the variational proposals $q_k$ and reverse kernels $r_k$ as variational distribution with parameters $\\phi$ and $\\theta$ respectively and minimize a KL-divergence\n", + "\n", + "\\begin{align}\n", + "\\mathcal{D}_{\\mathrm{KL}}(\\hat\\gamma_{k} \\mid \\check \\gamma_{k})\n", + "=\n", + "\\mathbb{E}_{\\hat\\gamma_{k}(x_{k-1}, x_{k}; \\phi, \\beta_{k-1})}\n", + "\\left[\n", + "\\log \\frac{\\hat \\gamma_k(x_{k-1}, x_k; \\phi, \\beta_{k-1})}{\\check\\gamma_k(x_{k-1}, x_k; \\theta, \\beta_{k})}\n", + "\\right]\n", + "\\end{align}\n", + "\n", + "at each step. We additionally learn the parameters of the schedule of the annealing path $\\beta_k$ (for $1" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "import jax.numpy as jnp\n", + "import flax\n", + "import flax.linen as nn\n", + "import numpyro.distributions as dist\n", + "import numpyro\n", + "\n", + "numpyro.set_platform(\"cpu\")\n", + "\n", + "\n", + "def ring_gmm_log_density(x, M):\n", + " angles = 2 * jnp.arange(1, M + 1) * jnp.pi / M\n", + " mu = 10 * jnp.stack([jnp.sin(angles), jnp.cos(angles)], -1)\n", + " sigma = jnp.sqrt(0.5)\n", + " return nn.logsumexp(\n", + " dist.Normal(mu, sigma).log_prob(x[..., None, :]).sum(-1), -1\n", + " )\n", + "\n", + "\n", + "def proposal_log_density(x):\n", + " return dist.Normal(0, 5).log_prob(x).sum(-1)\n", + "\n", + "\n", + "xrange = np.linspace(-12, 12, 100)\n", + "m_xy = np.dstack(np.meshgrid(xrange, xrange))\n", + "m_target = np.exp(ring_gmm_log_density(m_xy, M=8))\n", + "m_proposal = np.exp(proposal_log_density(m_xy))\n", + "\n", + "fig, (ax1, ax2) = plt.subplots(nrows=1, ncols=2)\n", + "ax1.set_title(\"Proposal Density\")\n", + "ax1.imshow(m_proposal)\n", + "xax1, yax1 = ax1.axes.get_xaxis(), ax1.axes.get_yaxis()\n", + "xax1.set_visible(False)\n", + "yax1.set_visible(False)\n", + "ax2.set_title(\"Target Density\")\n", + "ax2.imshow(m_target)\n", + "xax2, yax2 = ax2.axes.get_xaxis(), ax2.axes.get_yaxis()\n", + "xax2.set_visible(False)\n", + "yax2.set_visible(False)" + ] + }, + { + "cell_type": "markdown", + "id": "b2c37eb8-a6ac-4a60-9256-cb031f188c16", + "metadata": {}, + "source": [ + "### Defining a Sequence of annealed intermediate densities\n", + "\n", + "Given the proposal and target densities defined above, we can define our intermediate annealed densities using flax. Note that we are defining the tunable parameters `beta_raw` in log space and normalize them appropriately to be in the interval $[0, 1]$." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "85cd547d-ba52-4635-978f-d7fd710fce63", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "class AnnealedDensity(nn.Module):\n", + " M = 8\n", + "\n", + " @nn.compact\n", + " def __call__(self, x, index=0):\n", + " beta_raw = self.param(\"beta_raw\", lambda _: -jnp.ones(self.M - 2))\n", + " beta = nn.sigmoid(\n", + " beta_raw[0] + jnp.pad(jnp.cumsum(nn.softplus(beta_raw[1:])), (1, 0))\n", + " )\n", + " beta = jnp.pad(beta, (1, 1), constant_values=(0, 1))\n", + " beta_k = beta[index]\n", + "\n", + " target_density = ring_gmm_log_density(x, self.M)\n", + " init_proposal = proposal_log_density(x)\n", + " return beta_k * target_density + (1 - beta_k) * init_proposal" + ] + }, + { + "cell_type": "markdown", + "id": "e965b054-9eea-4881-ae32-8a8431835d7b", + "metadata": {}, + "source": [ + "### Network\n", + "\n", + "We now define our variational kernels, which each consist of a two-layer MLP with ReLU activations. We additionally define a helper class `VariationalKernelList`, which gives us convenient access to the individual variational kernels (automatically selecting the correct set of parameters), by providing the corresponding index. Lastly we define a `Network` class which wraps around the annealed target, forward kernels, and reverse kernels. This is convenient as it lets us pass around a single object which gives us access to the network of our individual model components." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "8e36102f-6061-4776-b85f-7165e731ecd3", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "class VariationalKernelNetwork(nn.Module):\n", + "\n", + " @nn.compact\n", + " def __call__(self, x):\n", + " h = nn.Dense(50)(x)\n", + " h = nn.relu(h)\n", + " loc = nn.Dense(2, kernel_init=nn.initializers.zeros)(h) + x\n", + " scale_raw = nn.Dense(2, kernel_init=nn.initializers.zeros)(h)\n", + " return loc, nn.softplus(scale_raw)\n", + "\n", + "\n", + "class VariationalKernelNetworks(nn.Module):\n", + " M = 8\n", + "\n", + " @nn.compact\n", + " def __call__(self, x, index=0):\n", + " if self.is_mutable_collection('params'):\n", + " vmap_net = nn.vmap(\n", + " VariationalKernelNetwork,\n", + " variable_axes={'params': 0},\n", + " split_rngs={'params': True},\n", + " )\n", + " out = vmap_net(name='kernel')(\n", + " jnp.broadcast_to(x, (self.M - 1,) + x.shape)\n", + " )\n", + " return jax.tree_util.tree_map(lambda x: x[index], out)\n", + " params = self.scope.get_variable('params', 'kernel')\n", + " params_i = jax.tree_util.tree_map(lambda x: x[index], params)\n", + " return VariationalKernelNetwork(name='kernel').apply(\n", + " flax.core.freeze({'params': params_i}), x\n", + " )\n", + "\n", + "\n", + "class Networks(nn.Module):\n", + "\n", + " def setup(self):\n", + " self.forward_kernel_params = VariationalKernelNetworks()\n", + " self.reverse_kernel_params = VariationalKernelNetworks()\n", + " self.anneal_density = AnnealedDensity()\n", + "\n", + " def __call__(self, x):\n", + " self.reverse_kernel_params(x)\n", + " self.anneal_density(x)\n", + " return self.forward_kernel_params(x)" + ] + }, + { + "cell_type": "markdown", + "id": "000158d9-a7ed-44f1-805c-03b5e4d22b52", + "metadata": {}, + "source": [ + "### Defining the model components\n", + "\n", + "With all of our network definitions in place we can now define our model components as probabilistic programs in numpyro." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "cd7857c9-2f05-4681-92e5-a880dc73bcc2", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "def anneal_target(network, k=0):\n", + " x = numpyro.sample(\"x\", dist.Normal(0, 5).expand([2]).mask(False).to_event())\n", + " # numpyro.factor(\"anneal_density\", network.anneal_density(x, index=k))\n", + " numpyro.sample(\n", + " \"anneal_density\", dist.Unit(network.anneal_density(x, index=k))\n", + " )\n", + " return ({\"x\": x},)\n", + "\n", + "\n", + "def anneal_forward(network, inputs, k=0):\n", + " mu, sigma = network.forward_kernel_params(inputs[\"x\"], index=k)\n", + " return numpyro.sample(\"x\", dist.Normal(mu, sigma).to_event(1))\n", + "\n", + "\n", + "def anneal_reverse(network, inputs, k=0):\n", + " mu, sigma = network.reverse_kernel_params(inputs[\"x\"], index=k)\n", + " return numpyro.sample(\"x\", dist.Normal(mu, sigma).to_event(1))" + ] + }, + { + "cell_type": "markdown", + "id": "7a7c1c6e-89b7-4229-bfdf-0d0dd3c9b242", + "metadata": {}, + "source": [ + "### Using predefined inference algorithms in coix\n", + "\n", + "Coix already implements a selection of inference algorithms including Nested Variational Inference (NVI). All we need to do is to instantiate our model components and pass it to the method that composes the inference program for us. " + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "3f5c1c7c-b67c-459f-b6b8-85ee734d0730", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "from functools import partial\n", + "import jax\n", + "from jax import random\n", + "import coix\n", + "\n", + "coix.set_backend(\"coix.numpyro\")\n", + "\n", + "\n", + "def make_anneal(params, unroll=False, num_particles=10, num_targets=8):\n", + " network = coix.util.BindModule(Networks(), params)\n", + " # Add particle dimension and construct a program.\n", + " make_particle_plate = lambda: numpyro.plate(\"particle\", num_particles, dim=-1)\n", + " targets = lambda k: make_particle_plate()(\n", + " partial(anneal_target, network, k=k)\n", + " )\n", + " forwards = lambda k: make_particle_plate()(\n", + " partial(anneal_forward, network, k=k)\n", + " )\n", + " reverses = lambda k: make_particle_plate()(\n", + " partial(anneal_reverse, network, k=k)\n", + " )\n", + " if unroll: # to unroll the algorithm, we provide a list of programs\n", + " targets = [targets(k) for k in range(num_targets)]\n", + " forwards = [forwards(k) for k in range(num_targets - 1)]\n", + " reverses = [reverses(k) for k in range(num_targets - 1)]\n", + " program = coix.algo.nvi_rkl(\n", + " targets, forwards, reverses, num_targets=num_targets\n", + " )\n", + " return program" + ] + }, + { + "cell_type": "markdown", + "id": "acecd0e3-fa29-45db-bd6e-15dac146e714", + "metadata": { + "tags": [] + }, + "source": [ + "### Evaluating the untrained model\n", + "\n", + "As mentioned before, while our sampler might not be very efficient before we train it, it is still valid. So let's see how our sampler performs pre-training first." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "83372a7c-1803-4373-9943-1fec013defcb", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{'ess': 16678.6855, 'log_Z': 2.0389, 'log_density': -3.656, 'loss': 12.3431}\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from matplotlib.animation import FuncAnimation\n", + "from matplotlib.patches import Ellipse, Rectangle\n", + "\n", + "\n", + "def eval_program(seed, params, num_particles):\n", + " with numpyro.handlers.seed(rng_seed=seed):\n", + " p = make_anneal(params, unroll=True, num_particles=num_particles)\n", + " out, trace, metrics = coix.traced_evaluate(p)()\n", + " return out, trace, metrics\n", + "\n", + "\n", + "anneal_net = Networks()\n", + "init_params = anneal_net.init(random.PRNGKey(0), jnp.zeros(2))\n", + "_, trace, metrics = eval_program(\n", + " random.PRNGKey(1), init_params, num_particles=100000\n", + ")\n", + "\n", + "metrics.pop(\"log_weight\")\n", + "anneal_metrics = jax.tree_util.tree_map(\n", + " lambda x: round(float(jnp.mean(x)), 4), metrics\n", + ")\n", + "print(anneal_metrics)\n", + "\n", + "fig, (ax1, ax2) = plt.subplots(nrows=1, ncols=2)\n", + "x = trace[\"x\"][\"value\"].reshape((-1, 2))\n", + "H, xedges, yedges = np.histogram2d(\n", + " x[:, 0], x[:, 1], range=[[-12, 12], [-12, 12]], bins=100\n", + ")\n", + "ax1.set_title(\"Untrained Proposal Density\")\n", + "ax1.imshow(H.T)\n", + "xax1, yax1 = ax1.axes.get_xaxis(), ax1.axes.get_yaxis()\n", + "xax1.set_visible(False)\n", + "yax1.set_visible(False)\n", + "ax2.set_title(\"Target Density\")\n", + "ax2.imshow(m_target)\n", + "xax2, yax2 = ax2.axes.get_xaxis(), ax2.axes.get_yaxis()\n", + "xax2.set_visible(False)\n", + "yax2.set_visible(False)" + ] + }, + { + "cell_type": "markdown", + "id": "6c4a6e2c-c5f7-434c-9e56-2b236f366245", + "metadata": {}, + "source": [ + "While visually the samples loosely approximate the target density we can clearly see that the modes are too wide and not tightly enough peaked. This is also reflected in the statistics that we can access in the metics dictionary returned by the evaluation effect handler. We can see that the ess is around $300$ when taking $1000$ samples." + ] + }, + { + "cell_type": "markdown", + "id": "5e214589-58e9-45f5-8057-042cc2f9bb89", + "metadata": {}, + "source": [ + "### Training\n", + "\n", + "So let's see if we can do better by training our model with NVI. All we need to do is to repeatedly run our inference program, differentiate the resulting loss, and take a gradient step. `coix.util.train` provides a convenient wrapper for such a training loop and optionally compiles the training procedure." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "5ef69930-2758-4464-a04a-349ca52afe47", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Compiling the first train step...\n", + "Time to compile a train step: 6.4172139167785645\n", + "=====\n", + "Step 2500 | ess 25.2412 | log_Z 1.2350 | log_density -3.7176 | loss 0.9471 | squared_grad_norm 8029.2070\n", + "Step 5000 | ess 31.7915 | log_Z 2.5552 | log_density -2.5793 | loss 0.6548 | squared_grad_norm 3195.3689\n", + "Step 7500 | ess 31.3730 | log_Z 1.9925 | log_density -2.5403 | loss 0.8958 | squared_grad_norm 1125.2384\n", + "Step 10000 | ess 31.2693 | log_Z 1.4725 | log_density -3.0077 | loss 0.8856 | squared_grad_norm 252.5485\n", + "Step 12500 | ess 32.1133 | log_Z 2.1890 | log_density -2.0786 | loss 1.3447 | squared_grad_norm 435.7955\n", + "Step 15000 | ess 33.2006 | log_Z 1.8315 | log_density -2.8067 | loss 0.7987 | squared_grad_norm 306.8722\n", + "Step 17500 | ess 34.6039 | log_Z 2.0502 | log_density -2.1592 | loss 1.7737 | squared_grad_norm 120.0838\n", + "Step 20000 | ess 34.3501 | log_Z 2.1727 | log_density -2.1159 | loss 1.5451 | squared_grad_norm 58.9659\n", + "Step 22500 | ess 34.5807 | log_Z 2.2028 | log_density -2.1809 | loss 1.5018 | squared_grad_norm 90.4855\n", + "Step 25000 | ess 35.5768 | log_Z 2.3687 | log_density -2.0594 | loss 1.4789 | squared_grad_norm 87.8662\n", + "Step 27500 | ess 34.8928 | log_Z 2.0132 | log_density -2.9821 | loss 0.7715 | squared_grad_norm 112.2418\n", + "Step 30000 | ess 34.8616 | log_Z 1.6396 | log_density -2.2300 | loss 1.7796 | squared_grad_norm 53.1720\n", + "Step 32500 | ess 35.5625 | log_Z 1.9240 | log_density -2.1137 | loss 0.8976 | squared_grad_norm 66.0242\n", + "Step 35000 | ess 35.5778 | log_Z 2.0557 | log_density -2.2012 | loss 2.4074 | squared_grad_norm 68.5943\n", + "Step 37500 | ess 35.5934 | log_Z 2.1605 | log_density -2.0528 | loss 1.3179 | squared_grad_norm 50.1874\n", + "Step 40000 | ess 35.2403 | log_Z 2.2516 | log_density -2.2726 | loss 1.4254 | squared_grad_norm 53.3538\n", + "Step 42500 | ess 35.2561 | log_Z 2.3036 | log_density -2.1802 | loss 1.9746 | squared_grad_norm 85.2577\n", + "Step 45000 | ess 35.8931 | log_Z 2.1175 | log_density -1.8413 | loss 1.7932 | squared_grad_norm 71.1966\n", + "Step 47500 | ess 35.5040 | log_Z 2.0723 | log_density -2.4489 | loss 1.2341 | squared_grad_norm 33.0538\n", + "Step 50000 | ess 35.1216 | log_Z 2.0225 | log_density -2.3940 | loss 1.6225 | squared_grad_norm 82.7994\n" + ] + } + ], + "source": [ + "import optax\n", + "\n", + "\n", + "def loss_fn(params, key, num_particles, unroll=False):\n", + " # Run the program and get metrics.\n", + " program = make_anneal(params, num_particles=num_particles, unroll=unroll)\n", + " with numpyro.handlers.seed(rng_seed=key):\n", + " _, _, metrics = coix.traced_evaluate(program)()\n", + " return metrics[\"loss\"], metrics\n", + "\n", + "\n", + "optimizer = optax.adam(1e-3)\n", + "num_steps = 50000\n", + "num_particles = 36\n", + "unroll = True\n", + "\n", + "trained_params, metrics = coix.util.train(\n", + " partial(loss_fn, num_particles=num_particles, unroll=unroll),\n", + " init_params,\n", + " optimizer,\n", + " num_steps,\n", + " jit_compile=True,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "9fcfdd89-9b63-4bbc-b124-572336a5c6cb", + "metadata": {}, + "source": [ + "While the training loss with only 36 particles is not very informative to assess convergence, we can see that the ess goes up to about $34$ which is a good indicator that we learned a good proposal." + ] + }, + { + "cell_type": "markdown", + "id": "a603dc86-bb81-4038-b668-1145be14e0e9", + "metadata": {}, + "source": [ + "### Evaluate trained model\n", + "We already implemented an evaluation wrapped, so let's evaluate the model again but this time with the optimized parameters." + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "2723e40f-9708-4c83-a2dc-f3dd15719dd0", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{'ess': 97606.4062, 'log_Z': 2.0777, 'log_density': -2.1979, 'log_weight': 2.0639, 'loss': 1.5816}\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "_, trace, metrics = eval_program(\n", + " random.PRNGKey(1), trained_params, num_particles=100000\n", + ")\n", + "\n", + "anneal_metrics = jax.tree_util.tree_map(\n", + " lambda x: round(float(jnp.mean(x)), 4), metrics\n", + ")\n", + "print(anneal_metrics)\n", + "\n", + "fig, (ax1, ax2) = plt.subplots(nrows=1, ncols=2)\n", + "x = trace[\"x\"][\"value\"].reshape((-1, 2))\n", + "m_proposal, _, _ = np.histogram2d(\n", + " x[:, 0], x[:, 1], range=[[-12, 12], [-12, 12]], bins=100\n", + ")\n", + "ax1.set_title(\"Trained Proposal Density\")\n", + "ax1.imshow(m_proposal.T)\n", + "xax1, yax1 = ax1.axes.get_xaxis(), ax1.axes.get_yaxis()\n", + "xax1.set_visible(False)\n", + "yax1.set_visible(False)\n", + "ax2.set_title(\"Target Density\")\n", + "ax2.imshow(m_target)\n", + "xax2, yax2 = ax2.axes.get_xaxis(), ax2.axes.get_yaxis()\n", + "xax2.set_visible(False)\n", + "yax2.set_visible(False)" + ] + } + ], + "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": "3.11.4" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +}