From 596dd903298371b34543a0bb678ed012e00e65f5 Mon Sep 17 00:00:00 2001 From: adrien Date: Sat, 17 Feb 2024 16:16:17 +0200 Subject: [PATCH 1/6] Plotting BlackJAX with BlackJAX --- ...owto_reproduce_the_blackjax_image.md.ipynb | 361 ++++++++++++++++++ 1 file changed, 361 insertions(+) create mode 100644 docs/examples/howto_reproduce_the_blackjax_image.md.ipynb diff --git a/docs/examples/howto_reproduce_the_blackjax_image.md.ipynb b/docs/examples/howto_reproduce_the_blackjax_image.md.ipynb new file mode 100644 index 000000000..b158f38d8 --- /dev/null +++ b/docs/examples/howto_reproduce_the_blackjax_image.md.ipynb @@ -0,0 +1,361 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "source": [ + "# Reproducing the front page image of the repository\n", + "\n", + "The front page image of the repository is a sampled version of the following image:\n", + "\n", + "![front_page_image](./data/blackjax.png)\n", + "\n", + "Here we show how we can sample from the uniform distribution corresponding to black pixels in the image. " + ], + "metadata": { + "collapsed": false + }, + "id": "f89531d0bfae707c" + }, + { + "cell_type": "markdown", + "source": [ + "## Make the image into a numpy array" + ], + "metadata": { + "collapsed": false + }, + "id": "9bde453da73873d3" + }, + { + "cell_type": "code", + "outputs": [], + "source": [ + "import matplotlib.image as mpimg\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "\n", + "plt.rcParams[\"axes.spines.right\"] = False\n", + "plt.rcParams[\"axes.spines.top\"] = False" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-02-17T13:32:27.285207747Z", + "start_time": "2024-02-17T13:32:24.234424533Z" + } + }, + "id": "3d490f88d558246c", + "execution_count": 1 + }, + { + "cell_type": "code", + "outputs": [ + { + "data": { + "text/plain": "(80, 250)" + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Load the image\n", + "im = mpimg.imread('./data/blackjax.png')\n", + "\n", + "# Convert to mask\n", + "im = np.amax(im[:, :, :2], 2) < 0.5\n", + "\n", + "# Convert back to float\n", + "im = im.astype(float)\n", + "display(im.shape)" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-02-17T13:43:09.549249388Z", + "start_time": "2024-02-17T13:43:09.538282916Z" + } + }, + "id": "d9d1439c4b5b9a9", + "execution_count": 10 + }, + { + "cell_type": "markdown", + "source": [ + "## The sampling procedure\n", + "\n", + "To sample from **BlackJAX**, we form a bridge between the uniform distribution over the full image, corresponding to a 2D domain of size (80, 250) and the uniform distribution over the black pixels.\n", + "\n", + "Formally, this corresponds to a prior distribution $p_0 \\sim U([[0, 79]] \\times [[0, 249]]$ and a target distribution $p_1(x) \\propto \\mathbb{1}_{x \\in \\text{image}}$." + ], + "metadata": { + "collapsed": false + }, + "id": "776d39fa7cf4c3f9" + }, + { + "cell_type": "code", + "outputs": [], + "source": [ + "import jax\n", + "import jax.numpy as jnp\n", + "from datetime import date\n", + "\n", + "rng_key = jax.random.key(int(date.today().strftime(\"%Y%m%d\")))\n" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-02-17T13:43:09.889467386Z", + "start_time": "2024-02-17T13:43:09.865690157Z" + } + }, + "id": "fd1219e9be924e6f", + "execution_count": 11 + }, + { + "cell_type": "code", + "outputs": [ + { + "data": { + "text/plain": "Array(0., dtype=float32, weak_type=True)" + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Sample from the uniform distribution over the domain\n", + "key_init, rng_key = jax.random.split(rng_key)\n", + "n_samples = 1_000\n", + "INF = 1e6 # A large number\n", + "jax_im = jnp.array(im.astype(float))\n", + "\n", + "key_init_xs, key_init_ys = jax.random.split(key_init)\n", + "xs_init = jax.random.uniform(key_init_xs, (n_samples,), minval=0, maxval=80)\n", + "ys_init = jax.random.randint(key_init_ys, (n_samples,), minval=0, maxval=250)\n", + "\n", + "zs_init = np.stack([xs_init, ys_init], axis=1)\n", + "\n", + "\n", + "# Set the prior and likelihood\n", + "def prior_logpdf(z): return 0.0\n", + "\n", + "\n", + "# The pdf is uniform, so the logpdf is constant on the domain and negative infinite outside\n", + "def log_likelihood(z):\n", + " x, y = z\n", + " # The pixel is black if x, y falls within the image, which means that their integer part is a valid index\n", + " floor_x, floor_y = jnp.floor(x), jnp.floor(y)\n", + " floor_x, floor_y = jnp.astype(floor_x, jnp.int32), jnp.astype(floor_y, jnp.int32)\n", + " out_of_bounds = (floor_x < 0) | (floor_x >= 80) | (floor_y < 0) | (floor_y >= 250)\n", + " value = jax.lax.cond(out_of_bounds,\n", + " lambda *_: -INF,\n", + " lambda arg: -INF * (jax_im[arg[0], arg[1]] == 0),\n", + " operand=(floor_x, floor_y))\n", + " return value\n", + "\n" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-02-17T13:45:21.015026796Z", + "start_time": "2024-02-17T13:45:20.922202798Z" + } + }, + "id": "5fad06c9167863da", + "execution_count": 22 + }, + { + "cell_type": "markdown", + "source": [ + "## The sampling procedure\n", + "\n", + "We will a RWMH sampler within SMC routine to sample from the target distribution.\n", + "For more information we refer to the [documentation](https://blackjax-devs.github.io/sampling-book/algorithms/TemperedSMC.html) specific to SMC\n" + ], + "metadata": { + "collapsed": false + }, + "id": "9f4c5105adf6b7df" + }, + { + "cell_type": "code", + "outputs": [], + "source": [ + "import blackjax\n", + "import blackjax.smc.resampling as resampling\n", + "\n", + "# Temperature schedule\n", + "n_temperatures = 25\n", + "lambda_schedule = np.logspace(-8, 0, n_temperatures)\n", + "\n", + "# The proposal distribution is a random walk with a fixed scale\n", + "scale = 0.5 # The scale of the proposal distribution\n", + "normal = blackjax.mcmc.random_walk.normal(scale * jnp.ones((2,)))\n", + "\n", + "rw_kernel = blackjax.additive_step_random_walk.build_kernel()\n", + "rw_init = blackjax.additive_step_random_walk.init\n", + "rw_params = {\"random_step\": normal}\n", + "\n", + "tempered = blackjax.tempered_smc(\n", + " prior_logpdf,\n", + " log_likelihood,\n", + " rw_kernel,\n", + " rw_init,\n", + " rw_params,\n", + " resampling.systematic,\n", + " num_mcmc_steps=5,\n", + ")\n", + "\n", + "initial_smc_state = tempered.init(zs_init)\n" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-02-17T14:15:31.484797433Z", + "start_time": "2024-02-17T14:15:31.437243584Z" + } + }, + "id": "845c7dbe6c1a832", + "execution_count": 51 + }, + { + "cell_type": "markdown", + "source": [ + "## Run the SMC sampler" + ], + "metadata": { + "collapsed": false + }, + "id": "56f93dc3e264290" + }, + { + "cell_type": "code", + "outputs": [], + "source": [ + "# Define the loop\n", + "def smc_inference_loop(loop_key, smc_kernel, init_state, schedule):\n", + " \"\"\"Run the tempered SMC algorithm.\n", + " \"\"\"\n", + "\n", + " def body_fn(carry, lmbda):\n", + " carry_key, state = carry\n", + " carry_key, subkey = jax.random.split(carry_key)\n", + " new_state, info = smc_kernel(subkey, state, lmbda)\n", + " return (rng_key, new_state), (new_state, info)\n", + "\n", + " _, (all_samples, _) = jax.lax.scan(body_fn, (loop_key, init_state), schedule)\n", + "\n", + " return all_samples\n", + "\n", + "\n", + "# Run the SMC sampler\n", + "blackjax_samples = smc_inference_loop(rng_key, tempered.step, initial_smc_state, lambda_schedule)" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-02-17T14:15:33.008019885Z", + "start_time": "2024-02-17T14:15:31.747818125Z" + } + }, + "id": "f2fe6a735b01ac4b", + "execution_count": 52 + }, + { + "cell_type": "markdown", + "source": [ + "## Plot the samples" + ], + "metadata": { + "collapsed": false + }, + "id": "1cb9ffddf6904401" + }, + { + "cell_type": "code", + "outputs": [], + "source": [ + "weights = np.array(blackjax_samples.weights)\n", + "samples = np.array(blackjax_samples.particles)" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-02-17T14:15:33.011708257Z", + "start_time": "2024-02-17T14:15:33.009543139Z" + } + }, + "id": "4a2a65a4d49c1e1f", + "execution_count": 53 + }, + { + "cell_type": "code", + "outputs": [ + { + "data": { + "text/plain": "" + }, + "execution_count": 57, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "text/plain": "
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" + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.xlim(0, 250)\n", + "plt.ylim(0, 80)\n", + "plt.scatter(samples[24, :, 1], samples[24, :, 0], c=weights[0], cmap=\"viridis\", s=10)\n", + "plt.colorbar()" + ], + "metadata": { + "collapsed": false, + "ExecuteTime": { + "end_time": "2024-02-17T14:15:45.634541282Z", + "start_time": "2024-02-17T14:15:45.479144208Z" + } + }, + "id": "44da0c1923e525e0", + "execution_count": 57 + }, + { + "cell_type": "code", + "outputs": [], + "source": [], + "metadata": { + "collapsed": false + }, + "id": "712b7d0f2849e246" + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 2 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython2", + "version": "2.7.6" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} From f2cc7797e732768de7e36652b11fb689c1834bb4 Mon Sep 17 00:00:00 2001 From: adrien Date: Sat, 17 Feb 2024 16:56:33 +0200 Subject: [PATCH 2/6] Plotting BlackJAX with BlackJAX --- ...owto_reproduce_the_blackjax_image.md.ipynb | 361 ------------------ 1 file changed, 361 deletions(-) delete mode 100644 docs/examples/howto_reproduce_the_blackjax_image.md.ipynb diff --git a/docs/examples/howto_reproduce_the_blackjax_image.md.ipynb b/docs/examples/howto_reproduce_the_blackjax_image.md.ipynb deleted file mode 100644 index b158f38d8..000000000 --- a/docs/examples/howto_reproduce_the_blackjax_image.md.ipynb +++ /dev/null @@ -1,361 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "source": [ - "# Reproducing the front page image of the repository\n", - "\n", - "The front page image of the repository is a sampled version of the following image:\n", - "\n", - "![front_page_image](./data/blackjax.png)\n", - "\n", - "Here we show how we can sample from the uniform distribution corresponding to black pixels in the image. " - ], - "metadata": { - "collapsed": false - }, - "id": "f89531d0bfae707c" - }, - { - "cell_type": "markdown", - "source": [ - "## Make the image into a numpy array" - ], - "metadata": { - "collapsed": false - }, - "id": "9bde453da73873d3" - }, - { - "cell_type": "code", - "outputs": [], - "source": [ - "import matplotlib.image as mpimg\n", - "import matplotlib.pyplot as plt\n", - "import numpy as np\n", - "\n", - "plt.rcParams[\"axes.spines.right\"] = False\n", - "plt.rcParams[\"axes.spines.top\"] = False" - ], - "metadata": { - "collapsed": false, - "ExecuteTime": { - "end_time": "2024-02-17T13:32:27.285207747Z", - "start_time": "2024-02-17T13:32:24.234424533Z" - } - }, - "id": "3d490f88d558246c", - "execution_count": 1 - }, - { - "cell_type": "code", - "outputs": [ - { - "data": { - "text/plain": "(80, 250)" - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Load the image\n", - "im = mpimg.imread('./data/blackjax.png')\n", - "\n", - "# Convert to mask\n", - "im = np.amax(im[:, :, :2], 2) < 0.5\n", - "\n", - "# Convert back to float\n", - "im = im.astype(float)\n", - "display(im.shape)" - ], - "metadata": { - "collapsed": false, - "ExecuteTime": { - "end_time": "2024-02-17T13:43:09.549249388Z", - "start_time": "2024-02-17T13:43:09.538282916Z" - } - }, - "id": "d9d1439c4b5b9a9", - "execution_count": 10 - }, - { - "cell_type": "markdown", - "source": [ - "## The sampling procedure\n", - "\n", - "To sample from **BlackJAX**, we form a bridge between the uniform distribution over the full image, corresponding to a 2D domain of size (80, 250) and the uniform distribution over the black pixels.\n", - "\n", - "Formally, this corresponds to a prior distribution $p_0 \\sim U([[0, 79]] \\times [[0, 249]]$ and a target distribution $p_1(x) \\propto \\mathbb{1}_{x \\in \\text{image}}$." - ], - "metadata": { - "collapsed": false - }, - "id": "776d39fa7cf4c3f9" - }, - { - "cell_type": "code", - "outputs": [], - "source": [ - "import jax\n", - "import jax.numpy as jnp\n", - "from datetime import date\n", - "\n", - "rng_key = jax.random.key(int(date.today().strftime(\"%Y%m%d\")))\n" - ], - "metadata": { - "collapsed": false, - "ExecuteTime": { - "end_time": "2024-02-17T13:43:09.889467386Z", - "start_time": "2024-02-17T13:43:09.865690157Z" - } - }, - "id": "fd1219e9be924e6f", - "execution_count": 11 - }, - { - "cell_type": "code", - "outputs": [ - { - "data": { - "text/plain": "Array(0., dtype=float32, weak_type=True)" - }, - "execution_count": 22, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Sample from the uniform distribution over the domain\n", - "key_init, rng_key = jax.random.split(rng_key)\n", - "n_samples = 1_000\n", - "INF = 1e6 # A large number\n", - "jax_im = jnp.array(im.astype(float))\n", - "\n", - "key_init_xs, key_init_ys = jax.random.split(key_init)\n", - "xs_init = jax.random.uniform(key_init_xs, (n_samples,), minval=0, maxval=80)\n", - "ys_init = jax.random.randint(key_init_ys, (n_samples,), minval=0, maxval=250)\n", - "\n", - "zs_init = np.stack([xs_init, ys_init], axis=1)\n", - "\n", - "\n", - "# Set the prior and likelihood\n", - "def prior_logpdf(z): return 0.0\n", - "\n", - "\n", - "# The pdf is uniform, so the logpdf is constant on the domain and negative infinite outside\n", - "def log_likelihood(z):\n", - " x, y = z\n", - " # The pixel is black if x, y falls within the image, which means that their integer part is a valid index\n", - " floor_x, floor_y = jnp.floor(x), jnp.floor(y)\n", - " floor_x, floor_y = jnp.astype(floor_x, jnp.int32), jnp.astype(floor_y, jnp.int32)\n", - " out_of_bounds = (floor_x < 0) | (floor_x >= 80) | (floor_y < 0) | (floor_y >= 250)\n", - " value = jax.lax.cond(out_of_bounds,\n", - " lambda *_: -INF,\n", - " lambda arg: -INF * (jax_im[arg[0], arg[1]] == 0),\n", - " operand=(floor_x, floor_y))\n", - " return value\n", - "\n" - ], - "metadata": { - "collapsed": false, - "ExecuteTime": { - "end_time": "2024-02-17T13:45:21.015026796Z", - "start_time": "2024-02-17T13:45:20.922202798Z" - } - }, - "id": "5fad06c9167863da", - "execution_count": 22 - }, - { - "cell_type": "markdown", - "source": [ - "## The sampling procedure\n", - "\n", - "We will a RWMH sampler within SMC routine to sample from the target distribution.\n", - "For more information we refer to the [documentation](https://blackjax-devs.github.io/sampling-book/algorithms/TemperedSMC.html) specific to SMC\n" - ], - "metadata": { - "collapsed": false - }, - "id": "9f4c5105adf6b7df" - }, - { - "cell_type": "code", - "outputs": [], - "source": [ - "import blackjax\n", - "import blackjax.smc.resampling as resampling\n", - "\n", - "# Temperature schedule\n", - "n_temperatures = 25\n", - "lambda_schedule = np.logspace(-8, 0, n_temperatures)\n", - "\n", - "# The proposal distribution is a random walk with a fixed scale\n", - "scale = 0.5 # The scale of the proposal distribution\n", - "normal = blackjax.mcmc.random_walk.normal(scale * jnp.ones((2,)))\n", - "\n", - "rw_kernel = blackjax.additive_step_random_walk.build_kernel()\n", - "rw_init = blackjax.additive_step_random_walk.init\n", - "rw_params = {\"random_step\": normal}\n", - "\n", - "tempered = blackjax.tempered_smc(\n", - " prior_logpdf,\n", - " log_likelihood,\n", - " rw_kernel,\n", - " rw_init,\n", - " rw_params,\n", - " resampling.systematic,\n", - " num_mcmc_steps=5,\n", - ")\n", - "\n", - "initial_smc_state = tempered.init(zs_init)\n" - ], - "metadata": { - "collapsed": false, - "ExecuteTime": { - "end_time": "2024-02-17T14:15:31.484797433Z", - "start_time": "2024-02-17T14:15:31.437243584Z" - } - }, - "id": "845c7dbe6c1a832", - "execution_count": 51 - }, - { - "cell_type": "markdown", - "source": [ - "## Run the SMC sampler" - ], - "metadata": { - "collapsed": false - }, - "id": "56f93dc3e264290" - }, - { - "cell_type": "code", - "outputs": [], - "source": [ - "# Define the loop\n", - "def smc_inference_loop(loop_key, smc_kernel, init_state, schedule):\n", - " \"\"\"Run the tempered SMC algorithm.\n", - " \"\"\"\n", - "\n", - " def body_fn(carry, lmbda):\n", - " carry_key, state = carry\n", - " carry_key, subkey = jax.random.split(carry_key)\n", - " new_state, info = smc_kernel(subkey, state, lmbda)\n", - " return (rng_key, new_state), (new_state, info)\n", - "\n", - " _, (all_samples, _) = jax.lax.scan(body_fn, (loop_key, init_state), schedule)\n", - "\n", - " return all_samples\n", - "\n", - "\n", - "# Run the SMC sampler\n", - "blackjax_samples = smc_inference_loop(rng_key, tempered.step, initial_smc_state, lambda_schedule)" - ], - "metadata": { - "collapsed": false, - "ExecuteTime": { - "end_time": "2024-02-17T14:15:33.008019885Z", - "start_time": "2024-02-17T14:15:31.747818125Z" - } - }, - "id": "f2fe6a735b01ac4b", - "execution_count": 52 - }, - { - "cell_type": "markdown", - "source": [ - "## Plot the samples" - ], - "metadata": { - "collapsed": false - }, - "id": "1cb9ffddf6904401" - }, - { - "cell_type": "code", - "outputs": [], - "source": [ - "weights = np.array(blackjax_samples.weights)\n", - "samples = np.array(blackjax_samples.particles)" - ], - "metadata": { - "collapsed": false, - "ExecuteTime": { - "end_time": "2024-02-17T14:15:33.011708257Z", - "start_time": "2024-02-17T14:15:33.009543139Z" - } - }, - "id": "4a2a65a4d49c1e1f", - "execution_count": 53 - }, - { - "cell_type": "code", - "outputs": [ - { - "data": { - "text/plain": "" - }, - "execution_count": 57, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "text/plain": "
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" - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plt.xlim(0, 250)\n", - "plt.ylim(0, 80)\n", - "plt.scatter(samples[24, :, 1], samples[24, :, 0], c=weights[0], cmap=\"viridis\", s=10)\n", - "plt.colorbar()" - ], - "metadata": { - "collapsed": false, - "ExecuteTime": { - "end_time": "2024-02-17T14:15:45.634541282Z", - "start_time": "2024-02-17T14:15:45.479144208Z" - } - }, - "id": "44da0c1923e525e0", - "execution_count": 57 - }, - { - "cell_type": "code", - "outputs": [], - "source": [], - "metadata": { - "collapsed": false - }, - "id": "712b7d0f2849e246" - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 2 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython2", - "version": "2.7.6" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} From 13d3395a57062e720416ea521bb11cfd71d79b24 Mon Sep 17 00:00:00 2001 From: Adrien Corenflos Date: Mon, 16 Sep 2024 20:02:18 +0100 Subject: [PATCH 3/6] Update blackjax/mcmc/metrics.py Co-authored-by: Junpeng Lao --- blackjax/mcmc/metrics.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/blackjax/mcmc/metrics.py b/blackjax/mcmc/metrics.py index 4e079714b..58b39deb7 100644 --- a/blackjax/mcmc/metrics.py +++ b/blackjax/mcmc/metrics.py @@ -187,7 +187,7 @@ def is_turning( return turning_at_left | turning_at_right def scale( - position: ArrayLikeTree, element: ArrayLikeTree, inv: ArrayLikeTree + position: ArrayLikeTree, element: ArrayLikeTree, inv: bool ) -> ArrayLikeTree: """Scale elements by the mass matrix. From e1c733070db79e891fa3aea2348adcdc3d15c26a Mon Sep 17 00:00:00 2001 From: Adrien Corenflos Date: Mon, 16 Sep 2024 20:02:37 +0100 Subject: [PATCH 4/6] Update blackjax/mcmc/metrics.py Co-authored-by: Junpeng Lao --- blackjax/mcmc/metrics.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/blackjax/mcmc/metrics.py b/blackjax/mcmc/metrics.py index 58b39deb7..678b5cc37 100644 --- a/blackjax/mcmc/metrics.py +++ b/blackjax/mcmc/metrics.py @@ -279,7 +279,7 @@ def is_turning( # return turning_at_left | turning_at_right def scale( - position: ArrayLikeTree, element: ArrayLikeTree, inv: ArrayLikeTree + position: ArrayLikeTree, element: ArrayLikeTree, inv: bool ) -> ArrayLikeTree: """Scale elements by the mass matrix. From 3755e6b063874dc4a70f4200b44dcb278159965b Mon Sep 17 00:00:00 2001 From: Adrien Corenflos Date: Mon, 16 Sep 2024 20:19:31 +0100 Subject: [PATCH 5/6] Merged comments from Junpeng --- blackjax/mcmc/metrics.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/blackjax/mcmc/metrics.py b/blackjax/mcmc/metrics.py index 678b5cc37..4e079714b 100644 --- a/blackjax/mcmc/metrics.py +++ b/blackjax/mcmc/metrics.py @@ -187,7 +187,7 @@ def is_turning( return turning_at_left | turning_at_right def scale( - position: ArrayLikeTree, element: ArrayLikeTree, inv: bool + position: ArrayLikeTree, element: ArrayLikeTree, inv: ArrayLikeTree ) -> ArrayLikeTree: """Scale elements by the mass matrix. @@ -279,7 +279,7 @@ def is_turning( # return turning_at_left | turning_at_right def scale( - position: ArrayLikeTree, element: ArrayLikeTree, inv: bool + position: ArrayLikeTree, element: ArrayLikeTree, inv: ArrayLikeTree ) -> ArrayLikeTree: """Scale elements by the mass matrix. From 460aba56e0575e3ac90dcf66d59ed81bca4c5117 Mon Sep 17 00:00:00 2001 From: Adrien Corenflos Date: Sun, 22 Sep 2024 18:03:41 +0100 Subject: [PATCH 6/6] Speed up Follmer --- tests/vi/test_schrodinger_follmer.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/vi/test_schrodinger_follmer.py b/tests/vi/test_schrodinger_follmer.py index fd58fed0a..79e7afedd 100644 --- a/tests/vi/test_schrodinger_follmer.py +++ b/tests/vi/test_schrodinger_follmer.py @@ -51,7 +51,7 @@ def logp_unnormalized_posterior(x, observed, prior_mu, prior_prec, true_cov): # Simulate the data observed = jax.random.multivariate_normal( - rng_key_observed, true_mu, true_cov, shape=(10_000,) + rng_key_observed, true_mu, true_cov, shape=(25,) ) logp_model = functools.partial(