From f1ed0822867a702105cdd2bc91ebed569f008e75 Mon Sep 17 00:00:00 2001
From: georgematheos <georgematheos@gmail.com>
Date: Tue, 10 Sep 2024 17:39:59 -0400
Subject: [PATCH] Gm/gen3d/inference3 (#156)

---
 notebooks/bayes3d_paper/tester.ipynb          | 1442 ++++++++++++++++-
 src/b3d/chisight/gen3d/inference.py           |   18 +-
 src/b3d/chisight/gen3d/inference_moves.py     |  222 ++-
 src/b3d/chisight/gen3d/projection.py          |    1 +
 .../test_depth_nonreturn_prob_inference.py    |   32 +
 5 files changed, 1619 insertions(+), 96 deletions(-)
 create mode 100644 tests/gen3d/inference/test_depth_nonreturn_prob_inference.py

diff --git a/notebooks/bayes3d_paper/tester.ipynb b/notebooks/bayes3d_paper/tester.ipynb
index 6c582ebe..0c9560c0 100644
--- a/notebooks/bayes3d_paper/tester.ipynb
+++ b/notebooks/bayes3d_paper/tester.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -16,7 +16,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import genjax\n",
+    "genjax.pretty()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -25,7 +35,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
@@ -46,7 +56,10 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "100%|██████████| 49/49 [00:03<00:00, 14.41it/s]\n"
+      "100%|██████████| 49/49 [00:03<00:00, 12.99it/s]\n",
+      "/home/georgematheos/b3d/.pixi/envs/gpu/lib/python3.12/site-packages/torch/utils/cpp_extension.py:1967: UserWarning: TORCH_CUDA_ARCH_LIST is not set, all archs for visible cards are included for compilation. \n",
+      "If this is not desired, please set os.environ['TORCH_CUDA_ARCH_LIST'].\n",
+      "  warnings.warn(\n"
      ]
     },
     {
@@ -57,7 +70,7 @@
        "<PIL.Image.Image image mode=RGB size=640x480>"
       ]
      },
-     "execution_count": 32,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -92,7 +105,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -120,7 +133,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -129,7 +142,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -151,7 +164,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -162,7 +175,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -196,7 +209,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -210,7 +223,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -229,7 +242,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -250,16 +263,43 @@
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   {
    "cell_type": "code",
-   "execution_count": 41,
+   "execution_count": 36,
    "metadata": {},
    "outputs": [
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@@ -272,16 +312,43 @@
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+   "execution_count": 14,
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      "data": {
+      "text/html": [
+       "<script> (()=>{ if (customElements.get('treescope-container') === undefined) { class TreescopeContainer extends HTMLElement { constructor() { super(); this.attachShadow({mode: \"open\"}); this.defns = {}; this.state = {}; } } customElements.define(\"treescope-container\", TreescopeContainer); } if (customElements.get('treescope-run-here') === undefined) { class RunHere extends HTMLElement { constructor() { super() } connectedCallback() { const run = child => { const fn = new Function(child.textContent); child.textContent = \"\"; fn.call(this); this.remove(); }; const child = this.querySelector(\"script\"); if (child) { run(child); } else { new MutationObserver(()=>{ run(this.querySelector(\"script\")); }).observe(this, {childList: true}); } } } customElements.define(\"treescope-run-here\", RunHere); } })(); </script> <treescope-container class=\"treescope_out_6fd5bb1f04994266adc348d04d831344\" ></treescope-container> <treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_6fd5bb1f04994266adc348d04d831344\")) .filter((elt) => !elt.dataset.setup) )[0]; root.dataset.setup = 1; const msg = document.createElement(\"span\"); msg.style = \"color: #aaaaaa; font-family: monospace; transition: opacity 0.2s; opacity: 0.0;\"; msg.textContent = \"(Loading...)\"; root.state.loadingMsg = msg; root.shadowRoot.appendChild(msg); root.state.chain = new Promise((resolve, reject) => { const observer = new IntersectionObserver((entries) => { for (const entry of entries) { if (entry.isIntersecting) { resolve(); observer.disconnect(); return; } } }, {rootMargin: \"1000px\"}); window.setTimeout(() => { if (root.loadingMsg) { root.loadingMsg.style.opacity = \"1.0\"; } observer.observe(root); }, 0); }); root.state.deferring = false; const _insertNode = (node) => { for (let oldScript of node.querySelectorAll(\"script\")) { let newScript = document.createElement(\"script\"); newScript.type = oldScript.type; newScript.textContent = oldScript.textContent; oldScript.parentNode.replaceChild(newScript, oldScript); } if (root.state.loadingMsg) { root.state.loadingMsg.remove(); root.state.loadingMsg = null; } root.shadowRoot.appendChild(node); }; root.defns.insertContent = ((contentNode, compressed) => { if (compressed) { root.state.deferring = true; } if (root.state.deferring) { root.state.chain = (async () => { await root.state.chain; if (compressed) { const encoded = contentNode.textContent; const blob = new Blob([ Uint8Array.from(atob(encoded), (m) => m.codePointAt(0)) ]); const reader = blob.stream().pipeThrough( new DecompressionStream(\"deflate\") ).pipeThrough( new TextDecoderStream(\"utf-8\") ).getReader(); const parts = []; while (true) { const step = await reader.read(); if (step.done) { break; } parts.push(step.value); } const tpl = document.createElement('template'); tpl.innerHTML = parts.join(\"\"); _insertNode(tpl.content); } else { _insertNode(contentNode.content); } })(); } else { _insertNode(contentNode.content); } }); </script></treescope-run-here><div style=\"display:none\"> <script type=\"application/octet-stream\" >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</script> <treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_6fd5bb1f04994266adc348d04d831344\")) .filter((elt) => !elt.dataset['step0']) )[0]; root.dataset['step0'] = 1; root.defns.insertContent( this.parentNode.querySelector('script[type=\"application/octet-stream\"]'), true ); this.parentNode.remove(); </script></treescope-run-here> </div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div style=\"display:none\"> <script type=\"application/octet-stream\" >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</script> <treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_6fd5bb1f04994266adc348d04d831344\")) .filter((elt) => !elt.dataset['step1']) )[0]; root.dataset['step1'] = 1; root.defns.insertContent( this.parentNode.querySelector('script[type=\"application/octet-stream\"]'), true ); this.parentNode.remove(); </script></treescope-run-here> </div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_6fd5bb1f04994266adc348d04d831344\")) .filter((elt) => !elt.dataset.stolen) )[0]; root.dataset.stolen = 1; this.parentNode.replaceChild(root, this); </script></treescope-run-here>"
+      ],
       "text/plain": [
-       "Array(82541.78, dtype=float32)"
+       "<jax.Array(82541.78, dtype=float32)>"
       ]
      },
-     "execution_count": 42,
+     "execution_count": 14,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -292,7 +359,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 86,
+   "execution_count": 30,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -304,31 +371,59 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 87,
+   "execution_count": 31,
    "metadata": {},
    "outputs": [
     {
      "data": {
+      "text/html": [
+       "<script> (()=>{ if (customElements.get('treescope-container') === undefined) { class TreescopeContainer extends HTMLElement { constructor() { super(); this.attachShadow({mode: \"open\"}); this.defns = {}; this.state = {}; } } customElements.define(\"treescope-container\", TreescopeContainer); } if (customElements.get('treescope-run-here') === undefined) { class RunHere extends HTMLElement { constructor() { super() } connectedCallback() { const run = child => { const fn = new Function(child.textContent); child.textContent = \"\"; fn.call(this); this.remove(); }; const child = this.querySelector(\"script\"); if (child) { run(child); } else { new MutationObserver(()=>{ run(this.querySelector(\"script\")); }).observe(this, {childList: true}); } } } customElements.define(\"treescope-run-here\", RunHere); } })(); </script> <treescope-container class=\"treescope_out_9bbd2c7d46a84ad49fe8d1e72ef56359\" ></treescope-container> <treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_9bbd2c7d46a84ad49fe8d1e72ef56359\")) .filter((elt) => !elt.dataset.setup) )[0]; root.dataset.setup = 1; const msg = document.createElement(\"span\"); msg.style = \"color: #aaaaaa; font-family: monospace; transition: opacity 0.2s; opacity: 0.0;\"; msg.textContent = \"(Loading...)\"; root.state.loadingMsg = msg; root.shadowRoot.appendChild(msg); root.state.chain = new Promise((resolve, reject) => { const observer = new IntersectionObserver((entries) => { for (const entry of entries) { if (entry.isIntersecting) { resolve(); observer.disconnect(); return; } } }, {rootMargin: \"1000px\"}); window.setTimeout(() => { if (root.loadingMsg) { root.loadingMsg.style.opacity = \"1.0\"; } observer.observe(root); }, 0); }); root.state.deferring = false; const _insertNode = (node) => { for (let oldScript of node.querySelectorAll(\"script\")) { let newScript = document.createElement(\"script\"); newScript.type = oldScript.type; newScript.textContent = oldScript.textContent; oldScript.parentNode.replaceChild(newScript, oldScript); } if (root.state.loadingMsg) { root.state.loadingMsg.remove(); root.state.loadingMsg = null; } root.shadowRoot.appendChild(node); }; root.defns.insertContent = ((contentNode, compressed) => { if (compressed) { root.state.deferring = true; } if (root.state.deferring) { root.state.chain = (async () => { await root.state.chain; if (compressed) { const encoded = contentNode.textContent; const blob = new Blob([ Uint8Array.from(atob(encoded), (m) => m.codePointAt(0)) ]); const reader = blob.stream().pipeThrough( new DecompressionStream(\"deflate\") ).pipeThrough( new TextDecoderStream(\"utf-8\") ).getReader(); const parts = []; while (true) { const step = await reader.read(); if (step.done) { break; } parts.push(step.value); } const tpl = document.createElement('template'); tpl.innerHTML = parts.join(\"\"); _insertNode(tpl.content); } else { _insertNode(contentNode.content); } })(); } else { _insertNode(contentNode.content); } }); </script></treescope-run-here><div style=\"display:none\"> <script type=\"application/octet-stream\" >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</script> <treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_9bbd2c7d46a84ad49fe8d1e72ef56359\")) .filter((elt) => !elt.dataset['step0']) )[0]; root.dataset['step0'] = 1; root.defns.insertContent( this.parentNode.querySelector('script[type=\"application/octet-stream\"]'), true ); this.parentNode.remove(); </script></treescope-run-here> </div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
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+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_9bbd2c7d46a84ad49fe8d1e72ef56359\")) .filter((elt) => !elt.dataset.stolen) )[0]; root.dataset.stolen = 1; this.parentNode.replaceChild(root, this); </script></treescope-run-here>"
+      ],
       "text/plain": [
-       "Array(35023.812, dtype=float32)"
+       "<jax.Array(50898.457, dtype=float32)>"
       ]
      },
-     "execution_count": 87,
+     "execution_count": 31,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "inference_hyperparams = InferenceHyperparams(\n",
-    "    n_poses=10000,\n",
+    "inference_hyperparams = i.InferenceHyperparams(\n",
+    "    n_poses=6000,\n",
     "    pose_proposal_std=0.04,\n",
     "    pose_proposal_conc=1000.,\n",
+    "    color_proposal_params=None\n",
     ")\n",
     "\n",
     "stepped_trace, step_weight, metadata = i.inference_step(\n",
     "    jax.random.PRNGKey(21),\n",
     "    trace,\n",
-    "    all_data[1][\"rgbd\"],\n",
+    "    all_data[0][\"rgbd\"],\n",
     "    inference_hyperparams\n",
     ")\n",
     "step_weight"
@@ -336,30 +431,1315 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 89,
+   "execution_count": 32,
    "metadata": {},
    "outputs": [],
    "source": [
-    "T = 1\n",
+    "T = 0\n",
     "b3d.chisight.gen3d.model.viz_trace(stepped_trace, T, ground_truth_vertices=meshes[OBJECT_INDEX].vertices, ground_truth_pose=all_data[T][\"camera_pose\"].inv() @ all_data[T][\"object_poses\"][OBJECT_INDEX])"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 62,
+   "execution_count": 37,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "[2024-09-10T18:07:03Z WARN  re_log_types::path::parse_path] When parsing the entity path \"proposed positions\": Unescaped whitespace. The path will be interpreted as /proposed\\ positions\n"
+      "100%|██████████| 49/49 [00:59<00:00,  1.21s/it]\n"
      ]
     }
    ],
    "source": [
     "import rerun as rr\n",
-    "rr.log(\"proposed positions\", rr.Points3D(metadata[\"proposed_poses\"].position))"
+    "\n",
+    "### Run inference ###\n",
+    "for T in tqdm(range(len(all_data))):\n",
+    "    key = b3d.split_key(key)\n",
+    "    trace, wt, _ = i.inference_step(\n",
+    "        key,\n",
+    "        trace,\n",
+    "        all_data[T][\"rgbd\"],\n",
+    "        inference_hyperparams\n",
+    "    )\n",
+    "    b3d.chisight.gen3d.model.viz_trace(trace, T, ground_truth_vertices=meshes[OBJECT_INDEX].vertices, ground_truth_pose=all_data[T][\"camera_pose\"].inv() @ all_data[T][\"object_poses\"][OBJECT_INDEX])\n",
+    "    rr.log(\"importance_weight\", rr.Scalar(wt))\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 97,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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<treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_d3d1d986794541c88ef5f85fc7bc350f\")) .filter((elt) => !elt.dataset['step0']) )[0]; root.dataset['step0'] = 1; root.defns.insertContent( this.parentNode.querySelector('script[type=\"application/octet-stream\"]'), true ); this.parentNode.remove(); </script></treescope-run-here> </div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_d3d1d986794541c88ef5f85fc7bc350f\")) .filter((elt) => !elt.dataset.stolen) )[0]; root.dataset.stolen = 1; this.parentNode.replaceChild(root, this); </script></treescope-run-here>"
+      ],
+      "text/plain": [
+       "dict_keys(['chosen_pose_index', 'log_q_nonpose_latents', 'log_q_poses', 'other_latents_metadata', 'p_scores', 'proposed_poses'])"
+      ]
+     },
+     "execution_count": 97,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "metadata.keys()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 108,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<script> (()=>{ if (customElements.get('treescope-container') === undefined) { class TreescopeContainer extends HTMLElement { constructor() { super(); this.attachShadow({mode: \"open\"}); this.defns = {}; this.state = {}; } } customElements.define(\"treescope-container\", TreescopeContainer); } if (customElements.get('treescope-run-here') === undefined) { class RunHere extends HTMLElement { constructor() { super() } connectedCallback() { const run = child => { const fn = new Function(child.textContent); child.textContent = \"\"; fn.call(this); this.remove(); }; const child = this.querySelector(\"script\"); if (child) { run(child); } else { new MutationObserver(()=>{ run(this.querySelector(\"script\")); }).observe(this, {childList: true}); } } } customElements.define(\"treescope-run-here\", RunHere); } })(); </script> <treescope-container class=\"treescope_out_ee8c40aed98f4861aaab355388b38d4b\" ></treescope-container> <treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_ee8c40aed98f4861aaab355388b38d4b\")) .filter((elt) => !elt.dataset.setup) )[0]; 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root.state.loadingMsg = null; } root.shadowRoot.appendChild(node); }; root.defns.insertContent = ((contentNode, compressed) => { if (compressed) { root.state.deferring = true; } if (root.state.deferring) { root.state.chain = (async () => { await root.state.chain; if (compressed) { const encoded = contentNode.textContent; const blob = new Blob([ Uint8Array.from(atob(encoded), (m) => m.codePointAt(0)) ]); const reader = blob.stream().pipeThrough( new DecompressionStream(\"deflate\") ).pipeThrough( new TextDecoderStream(\"utf-8\") ).getReader(); const parts = []; while (true) { const step = await reader.read(); if (step.done) { break; } parts.push(step.value); } const tpl = document.createElement('template'); tpl.innerHTML = parts.join(\"\"); _insertNode(tpl.content); } else { _insertNode(contentNode.content); } })(); } else { _insertNode(contentNode.content); } }); </script></treescope-run-here><div style=\"display:none\"> <script type=\"application/octet-stream\" >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</script> <treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_ee8c40aed98f4861aaab355388b38d4b\")) .filter((elt) => !elt.dataset['step0']) )[0]; root.dataset['step0'] = 1; root.defns.insertContent( this.parentNode.querySelector('script[type=\"application/octet-stream\"]'), true ); this.parentNode.remove(); </script></treescope-run-here> </div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
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</script> <treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_ee8c40aed98f4861aaab355388b38d4b\")) .filter((elt) => !elt.dataset['step1']) )[0]; root.dataset['step1'] = 1; root.defns.insertContent( this.parentNode.querySelector('script[type=\"application/octet-stream\"]'), true ); this.parentNode.remove(); </script></treescope-run-here> </div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_ee8c40aed98f4861aaab355388b38d4b\")) .filter((elt) => !elt.dataset.stolen) )[0]; root.dataset.stolen = 1; this.parentNode.replaceChild(root, this); </script></treescope-run-here>"
+      ],
+      "text/plain": [
+       "<Array([nan, nan], dtype=float32)\n",
+       "  <Arrayviz rendering>\n",
+       ">"
+      ]
+     },
+     "execution_count": 108,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "jax.nn.softmax(jnp.array([-jnp.inf, -jnp.inf]))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 107,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<script> (()=>{ if (customElements.get('treescope-container') === undefined) { class TreescopeContainer extends HTMLElement { constructor() { super(); this.attachShadow({mode: \"open\"}); this.defns = {}; this.state = {}; } } customElements.define(\"treescope-container\", TreescopeContainer); } if (customElements.get('treescope-run-here') === undefined) { class RunHere extends HTMLElement { constructor() { super() } connectedCallback() { const run = child => { const fn = new Function(child.textContent); child.textContent = \"\"; fn.call(this); this.remove(); }; const child = this.querySelector(\"script\"); if (child) { run(child); } else { new MutationObserver(()=>{ run(this.querySelector(\"script\")); }).observe(this, {childList: true}); } } } customElements.define(\"treescope-run-here\", RunHere); } })(); </script> <treescope-container class=\"treescope_out_0aab8e3b5cbc4dd4ba6547c7cac6e3e9\" ></treescope-container> <treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_0aab8e3b5cbc4dd4ba6547c7cac6e3e9\")) .filter((elt) => !elt.dataset.setup) )[0]; 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</script> <treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_0aab8e3b5cbc4dd4ba6547c7cac6e3e9\")) .filter((elt) => !elt.dataset['step1']) )[0]; root.dataset['step1'] = 1; root.defns.insertContent( this.parentNode.querySelector('script[type=\"application/octet-stream\"]'), true ); this.parentNode.remove(); </script></treescope-run-here> </div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_0aab8e3b5cbc4dd4ba6547c7cac6e3e9\")) .filter((elt) => !elt.dataset.stolen) )[0]; root.dataset.stolen = 1; this.parentNode.replaceChild(root, this); </script></treescope-run-here>"
+      ],
+      "text/plain": [
+       "<jax.Array float32(5071, 2) ≈-5.4 ±1.2 [≥-inf, ≤-2.1] nonzero:10_142 -inf:1_390\n",
+       "  <Arrayviz rendering>\n",
+       ">"
+      ]
+     },
+     "execution_count": 107,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "metadata[\"other_latents_metadata\"][\"depth_nonreturn_proposal\"][\"log_normalized_scores\"]\n",
+    "metadata[\"other_latents_metadata\"][\"depth_nonreturn_proposal\"][\"likelihood_score\"][4]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 77,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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</script> <treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_4537891baa154be6bcbf905e9bbe20d0\")) .filter((elt) => !elt.dataset['step1']) )[0]; root.dataset['step1'] = 1; root.defns.insertContent( this.parentNode.querySelector('script[type=\"application/octet-stream\"]'), true ); this.parentNode.remove(); </script></treescope-run-here> </div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_4537891baa154be6bcbf905e9bbe20d0\")) .filter((elt) => !elt.dataset.stolen) )[0]; root.dataset.stolen = 1; this.parentNode.replaceChild(root, this); </script></treescope-run-here>"
+      ],
+      "text/plain": [
+       "<jax.Array float32(6,) ≈-2.8e+04 ±2.9e+04 [≥-6.3e+04, ≤3e+04] nonzero:6\n",
+       "  <Arrayviz rendering>\n",
+       ">"
+      ]
+     },
+     "execution_count": 77,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "i = jnp.argmax(metadata[\"p_scores\"])\n",
+    "metadata[\"p_scores\"][i-3:i+3]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 84,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<script> (()=>{ if (customElements.get('treescope-container') === undefined) { class TreescopeContainer extends HTMLElement { constructor() { super(); this.attachShadow({mode: \"open\"}); this.defns = {}; this.state = {}; } } customElements.define(\"treescope-container\", TreescopeContainer); } if (customElements.get('treescope-run-here') === undefined) { class RunHere extends HTMLElement { constructor() { super() } connectedCallback() { const run = child => { const fn = new Function(child.textContent); child.textContent = \"\"; fn.call(this); this.remove(); }; const child = this.querySelector(\"script\"); if (child) { run(child); } else { new MutationObserver(()=>{ run(this.querySelector(\"script\")); }).observe(this, {childList: true}); } } } customElements.define(\"treescope-run-here\", RunHere); } })(); </script> <treescope-container class=\"treescope_out_109d85518ae2425992e77e3c0f646724\" ></treescope-container> <treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_109d85518ae2425992e77e3c0f646724\")) .filter((elt) => !elt.dataset.setup) )[0]; 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</script> <treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_109d85518ae2425992e77e3c0f646724\")) .filter((elt) => !elt.dataset['step1']) )[0]; root.dataset['step1'] = 1; root.defns.insertContent( this.parentNode.querySelector('script[type=\"application/octet-stream\"]'), true ); this.parentNode.remove(); </script></treescope-run-here> </div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_109d85518ae2425992e77e3c0f646724\")) .filter((elt) => !elt.dataset.stolen) )[0]; root.dataset.stolen = 1; this.parentNode.replaceChild(root, this); </script></treescope-run-here>"
+      ],
+      "text/plain": [
+       "<jax.Array float32(10,) ≈1.5e+04 ±5.9e+03 [≥8.1e+03, ≤3e+04] nonzero:10\n",
+       "  <Arrayviz rendering>\n",
+       ">"
+      ]
+     },
+     "execution_count": 84,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# get the 10 largest values in p_scores\n",
+    "jnp.sort(metadata[\"p_scores\"])[-10:]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 80,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_d2b345b1bb29456699b2dedca502cbab\")) .filter((elt) => !elt.dataset.stolen) )[0]; root.dataset.stolen = 1; this.parentNode.replaceChild(root, this); </script></treescope-run-here>"
+      ],
+      "text/plain": [
+       "<jax.Array(14.426146, dtype=float32)>"
+      ]
+     },
+     "execution_count": 80,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "jnp.max(metadata[\"log_q_poses\"])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 91,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<script> (()=>{ if (customElements.get('treescope-container') === undefined) { class TreescopeContainer extends HTMLElement { constructor() { super(); this.attachShadow({mode: \"open\"}); this.defns = {}; this.state = {}; } } customElements.define(\"treescope-container\", TreescopeContainer); } if (customElements.get('treescope-run-here') === undefined) { class RunHere extends HTMLElement { constructor() { super() } connectedCallback() { const run = child => { const fn = new Function(child.textContent); child.textContent = \"\"; fn.call(this); this.remove(); }; const child = this.querySelector(\"script\"); if (child) { run(child); } else { new MutationObserver(()=>{ run(this.querySelector(\"script\")); }).observe(this, {childList: true}); } } } customElements.define(\"treescope-run-here\", RunHere); } })(); </script> <treescope-container class=\"treescope_out_d38a57f14e7d423fb5ed5dd866c4a531\" ></treescope-container> <treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_d38a57f14e7d423fb5ed5dd866c4a531\")) .filter((elt) => !elt.dataset.setup) )[0]; root.dataset.setup = 1; const msg = document.createElement(\"span\"); msg.style = \"color: #aaaaaa; font-family: monospace; transition: opacity 0.2s; opacity: 0.0;\"; msg.textContent = \"(Loading...)\"; root.state.loadingMsg = msg; root.shadowRoot.appendChild(msg); root.state.chain = new Promise((resolve, reject) => { const observer = new IntersectionObserver((entries) => { for (const entry of entries) { if (entry.isIntersecting) { resolve(); observer.disconnect(); return; } } }, {rootMargin: \"1000px\"}); window.setTimeout(() => { if (root.loadingMsg) { root.loadingMsg.style.opacity = \"1.0\"; } observer.observe(root); }, 0); }); root.state.deferring = false; const _insertNode = (node) => { for (let oldScript of node.querySelectorAll(\"script\")) { let newScript = document.createElement(\"script\"); newScript.type = oldScript.type; newScript.textContent = oldScript.textContent; oldScript.parentNode.replaceChild(newScript, oldScript); } if (root.state.loadingMsg) { root.state.loadingMsg.remove(); root.state.loadingMsg = null; } root.shadowRoot.appendChild(node); }; root.defns.insertContent = ((contentNode, compressed) => { if (compressed) { root.state.deferring = true; } if (root.state.deferring) { root.state.chain = (async () => { await root.state.chain; if (compressed) { const encoded = contentNode.textContent; const blob = new Blob([ Uint8Array.from(atob(encoded), (m) => m.codePointAt(0)) ]); const reader = blob.stream().pipeThrough( new DecompressionStream(\"deflate\") ).pipeThrough( new TextDecoderStream(\"utf-8\") ).getReader(); const parts = []; while (true) { const step = await reader.read(); if (step.done) { break; } parts.push(step.value); } const tpl = document.createElement('template'); tpl.innerHTML = parts.join(\"\"); _insertNode(tpl.content); } else { _insertNode(contentNode.content); } })(); } else { _insertNode(contentNode.content); } }); </script></treescope-run-here><div style=\"display:none\"> <script type=\"application/octet-stream\" >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</script> <treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_d38a57f14e7d423fb5ed5dd866c4a531\")) .filter((elt) => !elt.dataset['step0']) )[0]; root.dataset['step0'] = 1; root.defns.insertContent( this.parentNode.querySelector('script[type=\"application/octet-stream\"]'), true ); this.parentNode.remove(); </script></treescope-run-here> </div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
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+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_d38a57f14e7d423fb5ed5dd866c4a531\")) .filter((elt) => !elt.dataset.stolen) )[0]; root.dataset.stolen = 1; this.parentNode.replaceChild(root, this); </script></treescope-run-here>"
+      ],
+      "text/plain": [
+       "<jax.Array(-1609.5681, dtype=float32)>"
+      ]
+     },
+     "execution_count": 91,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "jnp.min(jnp.nan_to_num(metadata[\"log_q_nonpose_latents\"], -jnp.inf))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_031342aa8966447896f349bf16d6649a\")) .filter((elt) => !elt.dataset.stolen) )[0]; root.dataset.stolen = 1; this.parentNode.replaceChild(root, this); </script></treescope-run-here>"
+      ],
+      "text/plain": [
+       "dict_keys(['chosen_pose_index', 'other_latents_metadata', 'proposed_poses'])"
+      ]
+     },
+     "execution_count": 41,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "metadata.keys()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+      "text/plain": [
+       "<IPython.core.display.HTML object>"
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+     "metadata": {},
+     "output_type": "display_data"
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</script> <treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_b14ca1b0f17b43b88deb45efcb85d100\")) .filter((elt) => !elt.dataset['step1']) )[0]; root.dataset['step1'] = 1; root.defns.insertContent( this.parentNode.querySelector('script[type=\"application/octet-stream\"]'), true ); this.parentNode.remove(); </script></treescope-run-here> </div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_b14ca1b0f17b43b88deb45efcb85d100\")) .filter((elt) => !elt.dataset.stolen) )[0]; root.dataset.stolen = 1; this.parentNode.replaceChild(root, this); </script></treescope-run-here>"
+      ],
+      "text/plain": [
+       "{'depth_nonreturn_proposal': {'index': <jax.Array(1, dtype=int32)>,\n",
+       "  'latent_depth': <jax.Array(0.9522158, dtype=float32)>,\n",
+       "  'likelihood_score': <Array([-4.2057743 , -0.69624233], dtype=float32)\n",
+       "    <Arrayviz rendering>\n",
+       "  >,\n",
+       "  'log_normalized_scores': <Array([-1.01509   , -0.44999695], dtype=float32)\n",
+       "    <Arrayviz rendering>\n",
+       "  >,\n",
+       "  'observed_depth': <jax.Array(0.95300007, dtype=float32, weak_type=True)>,\n",
+       "  'prev_dnrp': <jax.Array(0.01, dtype=float32)>,\n",
+       "  'support': <Array([0.01, 0.99], dtype=float32)\n",
+       "    <Arrayviz rendering>\n",
+       "  >,\n",
+       "  'transition_score': <Array([-0.05129331, -2.9957323 ], dtype=float32, weak_type=True)\n",
+       "    <Arrayviz rendering>\n",
+       "  >},\n",
+       " 'dnrps': <jax.Array(0.99, dtype=float32)>}"
+      ]
+     },
+     "execution_count": 51,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "md = jax.tree.map(lambda x: x[metadata['chosen_pose_index']], metadata['other_latents_metadata'])\n",
+    "jax.tree.map(lambda x: x[0], md)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<script> (()=>{ if (customElements.get('treescope-container') === undefined) { class TreescopeContainer extends HTMLElement { constructor() { super(); this.attachShadow({mode: \"open\"}); this.defns = {}; this.state = {}; } } customElements.define(\"treescope-container\", TreescopeContainer); } if (customElements.get('treescope-run-here') === undefined) { class RunHere extends HTMLElement { constructor() { super() } connectedCallback() { const run = child => { const fn = new Function(child.textContent); child.textContent = \"\"; fn.call(this); this.remove(); }; const child = this.querySelector(\"script\"); if (child) { run(child); } else { new MutationObserver(()=>{ run(this.querySelector(\"script\")); }).observe(this, {childList: true}); } } } customElements.define(\"treescope-run-here\", RunHere); } })(); </script> <treescope-container class=\"treescope_out_c3f4ba3e107845bd96fea5ae95d36d29\" ></treescope-container> <treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_c3f4ba3e107845bd96fea5ae95d36d29\")) .filter((elt) => !elt.dataset.setup) )[0]; 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root.state.loadingMsg = null; } root.shadowRoot.appendChild(node); }; root.defns.insertContent = ((contentNode, compressed) => { if (compressed) { root.state.deferring = true; } if (root.state.deferring) { root.state.chain = (async () => { await root.state.chain; if (compressed) { const encoded = contentNode.textContent; const blob = new Blob([ Uint8Array.from(atob(encoded), (m) => m.codePointAt(0)) ]); const reader = blob.stream().pipeThrough( new DecompressionStream(\"deflate\") ).pipeThrough( new TextDecoderStream(\"utf-8\") ).getReader(); const parts = []; while (true) { const step = await reader.read(); if (step.done) { break; } parts.push(step.value); } const tpl = document.createElement('template'); tpl.innerHTML = parts.join(\"\"); _insertNode(tpl.content); } else { _insertNode(contentNode.content); } })(); } else { _insertNode(contentNode.content); } }); </script></treescope-run-here><div style=\"display:none\"> <script type=\"application/octet-stream\" >eNrlVktv4zYQ/iuEFtjIxUqxHcfryA8gl6KHoocWaA9tYVDkyGJDkypJJ/YW+e8dUnIc2bKbokF7qHyQNRzO982TnFm3k7BInQGwTFewNFo78geptBVOaJURA5I68QhTUmjlkoKuhdxlZK2VthVlKH8qhYMkfGSkMiiRwrokmE7crkKp0grFOWUPK6M3iidMS22yeuuUNF+5RAW0J7grM1IIh2rKgXJTUlHOhVolEgqXkSErPYiCpASxKlEySG+9GeWoQM4v25o/yaOwIhdSOGRON06/6CZCOSOUFSyx4gvUqw3d59l1HZ7ZS3gSs1GIaVBmmRGVI96/+RWtKikY9RG71syB994AXV8t4rg3X2BAEc86wqFQlsyJK4VNV+C+x2h/pznEvbTU1qVhHV0DR5YVKO/yPfNW/aaff+1a+YYqLgGX1UbKaY2QIs0ftFYojZ+0eeiR1xz0TyjySy2xE8wLKzCFNmuqGKRKP8W9kF8EiE9WSFJvmpGbYQ/tiILER6xTCWrlSjKfk75XuUjdgNsYhXEnIC0ciJUb5Zkdm7alKJznFxT8n2f8nUGIsaoU10+pgd83YN29EuuQrq8NXUNcx6TnbUxPgKqNLeswTjt83EPMazcuePl2Dp5FnUinVytZd+UydA5Wa+VteQlI94nAIxZ4k0nPLnynD7DzQY9M5Ak1yimT1NpvsTkbu3H0YnO5xjKM9uDPPYwnln+o8cXsuqsBuHgkweA8ao+PiDiao6ewnUf9iGiFZNBthXqXyr7b19jv2XsZYdvVAytMjCXT6zXKQ6mECfKBhsd7caRCM6VdnJX6EUyvQ99zAGOALyucQlBqycG8NvzZ/5ohGEhkRDiKXe83F6hOcySv0Ksz4xMptdSWtb+ozYVF0N1+TB4rkgWRNAeZZTlgB8IrViw80068elQmAz8rm5Hanx6whAoDNJfaz9yzmCFgp8icmgcLdIWJV6e7Q6yPRCW18SLYXHTGoc4PK4E9AO/1yFe9Awe/tXvTXr/FMMz8jFz9MrzN2dV/Sa+96SzJ8b9A0ufRA2+M9QmsNJ58YDpwhX0/2NAKASgJHWzP1fj7oB7cc7B1pyipsMtCGOuWWi19+Xe01qVWSoe3vps6U0X+Mf0648cUvVdralZ4V6lphIZ+Tp9KUDjdpKSVBf7XU+RvE7qAUM+OgBGUYFvhIXdW5z14dEE0jtYKh9OxKxTtEyptH3vkgoVjV1XrIO5WfAvYWTvHd0+8V6v9OdumGTWLgs+jl9OL34z6k3wwgIL1R/n4bpIPPw9v79j4jrN+f1JEbYvtoX9ce6hcJ2omVLVpLrtRSE2ut1GnkSaLuFhnEG8PYTO+G1uv8btO3WjxUbrpb3Sb3htDdxhZdzOMB/3+JyyGNCUfV87fTdDKovt1ErJWsDvDNhqOJnzCoCjGfDQZD/KCD25uaZ+NJnfFcHzzvwzbvueit1Rhs9i6dUULQj6QH4Xd4EXpS7jrklJwDhh9RQ7l7/viDDW8ZS7+BCZjNDk=</script> <treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_c3f4ba3e107845bd96fea5ae95d36d29\")) .filter((elt) => !elt.dataset['step0']) )[0]; root.dataset['step0'] = 1; root.defns.insertContent( this.parentNode.querySelector('script[type=\"application/octet-stream\"]'), true ); this.parentNode.remove(); </script></treescope-run-here> </div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
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</script> <treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_c3f4ba3e107845bd96fea5ae95d36d29\")) .filter((elt) => !elt.dataset['step1']) )[0]; root.dataset['step1'] = 1; root.defns.insertContent( this.parentNode.querySelector('script[type=\"application/octet-stream\"]'), true ); this.parentNode.remove(); </script></treescope-run-here> </div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_c3f4ba3e107845bd96fea5ae95d36d29\")) .filter((elt) => !elt.dataset.stolen) )[0]; root.dataset.stolen = 1; this.parentNode.replaceChild(root, this); </script></treescope-run-here>"
+      ],
+      "text/plain": [
+       "<jax.Array int32(100,) [≥0, ≤1] zero:30 nonzero:70\n",
+       "  <Arrayviz rendering>\n",
+       ">"
+      ]
+     },
+     "execution_count": 45,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "def sample(key):\n",
+    "    return jax.random.categorical(key, jnp.array([-1.01509   , -0.44999695]))\n",
+    "\n",
+    "key = jax.random.PRNGKey(0)\n",
+    "jax.vmap(sample)(jax.random.split(key, 100))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<script> (()=>{ if (customElements.get('treescope-container') === undefined) { class TreescopeContainer extends HTMLElement { constructor() { super(); this.attachShadow({mode: \"open\"}); this.defns = {}; this.state = {}; } } customElements.define(\"treescope-container\", TreescopeContainer); } if (customElements.get('treescope-run-here') === undefined) { class RunHere extends HTMLElement { constructor() { super() } connectedCallback() { const run = child => { const fn = new Function(child.textContent); child.textContent = \"\"; fn.call(this); this.remove(); }; const child = this.querySelector(\"script\"); if (child) { run(child); } else { new MutationObserver(()=>{ run(this.querySelector(\"script\")); }).observe(this, {childList: true}); } } } customElements.define(\"treescope-run-here\", RunHere); } })(); </script> <treescope-container class=\"treescope_out_c0db601401054dbdad3d1103d8e2e90f\" ></treescope-container> <treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_c0db601401054dbdad3d1103d8e2e90f\")) .filter((elt) => !elt.dataset.setup) )[0]; 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</script> <treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_c0db601401054dbdad3d1103d8e2e90f\")) .filter((elt) => !elt.dataset['step1']) )[0]; root.dataset['step1'] = 1; root.defns.insertContent( this.parentNode.querySelector('script[type=\"application/octet-stream\"]'), true ); this.parentNode.remove(); </script></treescope-run-here> </div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_c0db601401054dbdad3d1103d8e2e90f\")) .filter((elt) => !elt.dataset.stolen) )[0]; root.dataset.stolen = 1; this.parentNode.replaceChild(root, this); </script></treescope-run-here>"
+      ],
+      "text/plain": [
+       "<Array([0.36236984, 0.6376301 ], dtype=float32)\n",
+       "  <Arrayviz rendering>\n",
+       ">"
+      ]
+     },
+     "execution_count": 47,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "jnp.exp(jnp.array([-1.01509   , -0.44999695]))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
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+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_19528859f6ec4c7ca101464a87289550\")) .filter((elt) => !elt.dataset.stolen) )[0]; root.dataset.stolen = 1; this.parentNode.replaceChild(root, this); </script></treescope-run-here>"
+      ],
+      "text/plain": [
+       "<jax.Array(False, dtype=bool)>"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "b3d.reload(b3d.chisight.gen3d.projection)\n",
+    "from b3d.chisight.gen3d.projection import PixelsPointsAssociation\n",
+    "import b3d.chisight.gen3d.model as m\n",
+    "\n",
+    "obs_point_depths = PixelsPointsAssociation.from_hyperparams_and_pose(\n",
+    "    m.get_hypers(trace), m.get_new_state(trace)[\"pose\"]\n",
+    ").get_point_depths(m.get_observed_rgbd(trace))\n",
+    "\n",
+    "true_point_depths = template_pose.apply(hyperparams[\"vertices\"])[:, 2]\n",
+    "\n",
+    "jnp.all(jnp.abs(obs_point_depths - true_point_depths) < 1e-3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<script> (()=>{ if (customElements.get('treescope-container') === undefined) { class TreescopeContainer extends HTMLElement { constructor() { super(); this.attachShadow({mode: \"open\"}); this.defns = {}; this.state = {}; } } customElements.define(\"treescope-container\", TreescopeContainer); } if (customElements.get('treescope-run-here') === undefined) { class RunHere extends HTMLElement { constructor() { super() } connectedCallback() { const run = child => { const fn = new Function(child.textContent); child.textContent = \"\"; fn.call(this); this.remove(); }; const child = this.querySelector(\"script\"); if (child) { run(child); } else { new MutationObserver(()=>{ run(this.querySelector(\"script\")); }).observe(this, {childList: true}); } } } customElements.define(\"treescope-run-here\", RunHere); } })(); </script> <treescope-container class=\"treescope_out_fcff3321216f4d619126241dd51c1099\" ></treescope-container> <treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_fcff3321216f4d619126241dd51c1099\")) .filter((elt) => !elt.dataset.setup) )[0]; root.dataset.setup = 1; const msg = document.createElement(\"span\"); msg.style = \"color: #aaaaaa; font-family: monospace; transition: opacity 0.2s; opacity: 0.0;\"; msg.textContent = \"(Loading...)\"; root.state.loadingMsg = msg; root.shadowRoot.appendChild(msg); root.state.chain = new Promise((resolve, reject) => { const observer = new IntersectionObserver((entries) => { for (const entry of entries) { if (entry.isIntersecting) { resolve(); observer.disconnect(); return; } } }, {rootMargin: \"1000px\"}); window.setTimeout(() => { if (root.loadingMsg) { root.loadingMsg.style.opacity = \"1.0\"; } observer.observe(root); }, 0); }); root.state.deferring = false; const _insertNode = (node) => { for (let oldScript of node.querySelectorAll(\"script\")) { let newScript = document.createElement(\"script\"); newScript.type = oldScript.type; newScript.textContent = oldScript.textContent; oldScript.parentNode.replaceChild(newScript, oldScript); } if (root.state.loadingMsg) { root.state.loadingMsg.remove(); root.state.loadingMsg = null; } root.shadowRoot.appendChild(node); }; root.defns.insertContent = ((contentNode, compressed) => { if (compressed) { root.state.deferring = true; } if (root.state.deferring) { root.state.chain = (async () => { await root.state.chain; if (compressed) { const encoded = contentNode.textContent; const blob = new Blob([ Uint8Array.from(atob(encoded), (m) => m.codePointAt(0)) ]); const reader = blob.stream().pipeThrough( new DecompressionStream(\"deflate\") ).pipeThrough( new TextDecoderStream(\"utf-8\") ).getReader(); const parts = []; while (true) { const step = await reader.read(); if (step.done) { break; } parts.push(step.value); } const tpl = document.createElement('template'); tpl.innerHTML = parts.join(\"\"); _insertNode(tpl.content); } else { _insertNode(contentNode.content); } })(); } else { _insertNode(contentNode.content); } }); </script></treescope-run-here><div style=\"display:none\"> <script type=\"application/octet-stream\" >eNrFVk2P8zQQ/itWkN5NEcnudj9ebdpG2gvigDjAgQOgynEmialrB3vS3YL2vzN20nbbpiskXkFzaDKemeeZz2TucKsgT9ECOGFaWFpjkP3FWuMkSqMzZkFxlBuYscpoTCq+lmqbsbXRxrVckPylkQhJeMhYa0mipMMkuE5w25JUG03igotVbU2ny0QYZWzWm87Y8FQoUiB/ssQmY5VEUtMIGmes5WUpdZ0oqDBjU9F4EA1JA7JuSHKbPng3Grkkznuz4SbZSCcLqSQSc96h2esmUqOV2kmROPkn9KcD3bf5dZ+e+T49ie00YVqSOWFli8zHt7jibauk4D5j10Yg+Ogt8PVVHseTRU4JJTyHrIRKO7Zg2EiX1oA/UrZ/MCXEk7QxDtNwTqEBsmUL2of8LLxXb/TLb2Mn33FdKqBj3Sk16xFSovmTMZqk8Yuxqwl7z8H8TCJ/dCRGKbywBVsZu+ZaQKrNSzwJ9SWA+OyEJb3RnN1NJ+RHViw+YZ0q0DU2bLFgN17lQ+oWsLOa8s5AOTgQazrtmZ26do2s0PMLCv7mja4LCDF1lS7NS2rhjw4cPmu5DuX61vI1xH1OJt7H7Ayo7VzTp3E2EuMOYtGH8UGU/5yDZ9EXEk1dq34ql2FyqFtb78tLQOE3DDbU4EMlPbvwnK5g65Me2cgTGpRTobhz39NwDn7jaO9zuaY2jHbgbxPKJ7V/6PF8fj02AKXcsOBwER2vj4ghLyhSeF1ENxEzmshQ2Jr0Pmr78Vhjb7OLMqKx6xcWWYC1UC5b2hnQGFWCDR0TFslX/LO/hpUVTDImkdOMUmxpReq8IChNHC4suzd2rLbs2ZF2KR2BbndL7VSR5UzxAlSWFUDzAu9YifCbjeL1iy259ZttWIA3swOW1GHdFcr4DXkRszEbsOfIJbcrB7ymMulz60wbjE9EDXdxHnzmo3kINploQKygnEzY15MDB286brTTP2IYNnTGrn6dPhTi6v+kd2x0keTjf0DS19EDd9b5AraG3lNgR3Cl+3KwYRQCUBLmzV3q8S+DeggP4RXPUVLplpW0DpdGL337j4zWR6OUTh/8NI2Wiv1r+n3FTyn6qNbc1vRl0dMIA334kqCvJM1kuYj2C+weprx6mt7yO3i854/w9HR/JypxU3wWhb+NBqNh1R7P/Sk8KfdBzKVuu+HrJAq0C/MajToZIqTDPjpa98GY/gdf7/HHFm+Uf1I4+52/ps/W8i0rjFH0eZCmKftUo3+PkIP89I/eH/nfQEq2Xw==</script> <treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_fcff3321216f4d619126241dd51c1099\")) .filter((elt) => !elt.dataset['step0']) )[0]; root.dataset['step0'] = 1; root.defns.insertContent( this.parentNode.querySelector('script[type=\"application/octet-stream\"]'), true ); this.parentNode.remove(); </script></treescope-run-here> </div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
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+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_fcff3321216f4d619126241dd51c1099\")) .filter((elt) => !elt.dataset.stolen) )[0]; root.dataset.stolen = 1; this.parentNode.replaceChild(root, this); </script></treescope-run-here>"
+      ],
+      "text/plain": [
+       "<jax.Array(False, dtype=bool)>"
+      ]
+     },
+     "execution_count": 31,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "jnp.any(jnp.abs(obs_point_depths - true_point_depths[0]) < 1e-6)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<script> (()=>{ if (customElements.get('treescope-container') === undefined) { class TreescopeContainer extends HTMLElement { constructor() { super(); this.attachShadow({mode: \"open\"}); this.defns = {}; this.state = {}; } } customElements.define(\"treescope-container\", TreescopeContainer); } if (customElements.get('treescope-run-here') === undefined) { class RunHere extends HTMLElement { constructor() { super() } connectedCallback() { const run = child => { const fn = new Function(child.textContent); child.textContent = \"\"; fn.call(this); this.remove(); }; const child = this.querySelector(\"script\"); if (child) { run(child); } else { new MutationObserver(()=>{ run(this.querySelector(\"script\")); }).observe(this, {childList: true}); } } } customElements.define(\"treescope-run-here\", RunHere); } })(); </script> <treescope-container class=\"treescope_out_47b5be30cc7747e2a2bc1ec5a5394dbf\" ></treescope-container> <treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_47b5be30cc7747e2a2bc1ec5a5394dbf\")) .filter((elt) => !elt.dataset.setup) )[0]; root.dataset.setup = 1; const msg = document.createElement(\"span\"); msg.style = \"color: #aaaaaa; font-family: monospace; transition: opacity 0.2s; opacity: 0.0;\"; msg.textContent = \"(Loading...)\"; root.state.loadingMsg = msg; root.shadowRoot.appendChild(msg); root.state.chain = new Promise((resolve, reject) => { const observer = new IntersectionObserver((entries) => { for (const entry of entries) { if (entry.isIntersecting) { resolve(); observer.disconnect(); return; } } }, {rootMargin: \"1000px\"}); window.setTimeout(() => { if (root.loadingMsg) { root.loadingMsg.style.opacity = \"1.0\"; } observer.observe(root); }, 0); }); root.state.deferring = false; const _insertNode = (node) => { for (let oldScript of node.querySelectorAll(\"script\")) { let newScript = document.createElement(\"script\"); newScript.type = oldScript.type; newScript.textContent = oldScript.textContent; oldScript.parentNode.replaceChild(newScript, oldScript); } if (root.state.loadingMsg) { root.state.loadingMsg.remove(); root.state.loadingMsg = null; } root.shadowRoot.appendChild(node); }; root.defns.insertContent = ((contentNode, compressed) => { if (compressed) { root.state.deferring = true; } if (root.state.deferring) { root.state.chain = (async () => { await root.state.chain; if (compressed) { const encoded = contentNode.textContent; const blob = new Blob([ Uint8Array.from(atob(encoded), (m) => m.codePointAt(0)) ]); const reader = blob.stream().pipeThrough( new DecompressionStream(\"deflate\") ).pipeThrough( new TextDecoderStream(\"utf-8\") ).getReader(); const parts = []; while (true) { const step = await reader.read(); if (step.done) { break; } parts.push(step.value); } const tpl = document.createElement('template'); tpl.innerHTML = parts.join(\"\"); _insertNode(tpl.content); } else { _insertNode(contentNode.content); } })(); } else { _insertNode(contentNode.content); } }); </script></treescope-run-here><div style=\"display:none\"> <script type=\"application/octet-stream\" >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</script> <treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_47b5be30cc7747e2a2bc1ec5a5394dbf\")) .filter((elt) => !elt.dataset['step0']) )[0]; root.dataset['step0'] = 1; root.defns.insertContent( this.parentNode.querySelector('script[type=\"application/octet-stream\"]'), true ); this.parentNode.remove(); </script></treescope-run-here> </div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
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+       "<div style=\"display:none\"> <script type=\"application/octet-stream\" 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</script> <treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_47b5be30cc7747e2a2bc1ec5a5394dbf\")) .filter((elt) => !elt.dataset['step1']) )[0]; root.dataset['step1'] = 1; root.defns.insertContent( this.parentNode.querySelector('script[type=\"application/octet-stream\"]'), true ); this.parentNode.remove(); </script></treescope-run-here> </div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_47b5be30cc7747e2a2bc1ec5a5394dbf\")) .filter((elt) => !elt.dataset.stolen) )[0]; root.dataset.stolen = 1; this.parentNode.replaceChild(root, this); </script></treescope-run-here>"
+      ],
+      "text/plain": [
+       "<jax.Array float32(5071, 3) ≈0.0 ±0.0 [≥0.0, ≤0.0] zero:15_213\n",
+       "  <Arrayviz rendering>\n",
+       ">"
+      ]
+     },
+     "execution_count": 26,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "true_point_colors = m.get_prev_state(trace)[\"colors\"]\n",
+    "obs_point_colors = PixelsPointsAssociation.from_hyperparams_and_pose(\n",
+    "    m.get_hypers(trace), m.get_new_state(trace)[\"pose\"]\n",
+    ").get_point_rgbds(m.get_observed_rgbd(trace))[..., :3]\n",
+    "\n",
+    "true_point_colors - obs_point_colors"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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<treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_7a16b4c8e1094b7db3e9ad04c489d791\")) .filter((elt) => !elt.dataset['step0']) )[0]; root.dataset['step0'] = 1; root.defns.insertContent( this.parentNode.querySelector('script[type=\"application/octet-stream\"]'), true ); this.parentNode.remove(); </script></treescope-run-here> </div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_7a16b4c8e1094b7db3e9ad04c489d791\")) .filter((elt) => !elt.dataset.stolen) )[0]; root.dataset.stolen = 1; this.parentNode.replaceChild(root, this); </script></treescope-run-here>"
+      ],
+      "text/plain": [
+       "dict_keys(['chosen_pose_index', 'other_latents_metadata', 'proposed_poses'])"
+      ]
+     },
+     "execution_count": 33,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "metadata.keys()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<script> (()=>{ if (customElements.get('treescope-container') === undefined) { class TreescopeContainer extends HTMLElement { constructor() { super(); this.attachShadow({mode: \"open\"}); this.defns = {}; this.state = {}; } } customElements.define(\"treescope-container\", TreescopeContainer); } if (customElements.get('treescope-run-here') === undefined) { class RunHere extends HTMLElement { constructor() { super() } connectedCallback() { const run = child => { const fn = new Function(child.textContent); child.textContent = \"\"; fn.call(this); this.remove(); }; const child = this.querySelector(\"script\"); if (child) { run(child); } else { new MutationObserver(()=>{ run(this.querySelector(\"script\")); }).observe(this, {childList: true}); } } } customElements.define(\"treescope-run-here\", RunHere); } })(); </script> <treescope-container class=\"treescope_out_472a510544b54dd3bb11d8eebf96e5a1\" ></treescope-container> <treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_472a510544b54dd3bb11d8eebf96e5a1\")) .filter((elt) => !elt.dataset.setup) )[0]; root.dataset.setup = 1; const msg = document.createElement(\"span\"); msg.style = \"color: #aaaaaa; font-family: monospace; transition: opacity 0.2s; opacity: 0.0;\"; msg.textContent = \"(Loading...)\"; root.state.loadingMsg = msg; root.shadowRoot.appendChild(msg); root.state.chain = new Promise((resolve, reject) => { const observer = new IntersectionObserver((entries) => { for (const entry of entries) { if (entry.isIntersecting) { resolve(); observer.disconnect(); return; } } }, {rootMargin: \"1000px\"}); window.setTimeout(() => { if (root.loadingMsg) { root.loadingMsg.style.opacity = \"1.0\"; } observer.observe(root); }, 0); }); root.state.deferring = false; const _insertNode = (node) => { for (let oldScript of node.querySelectorAll(\"script\")) { let newScript = document.createElement(\"script\"); newScript.type = oldScript.type; newScript.textContent = oldScript.textContent; oldScript.parentNode.replaceChild(newScript, oldScript); } if (root.state.loadingMsg) { root.state.loadingMsg.remove(); root.state.loadingMsg = null; } root.shadowRoot.appendChild(node); }; root.defns.insertContent = ((contentNode, compressed) => { if (compressed) { root.state.deferring = true; } if (root.state.deferring) { root.state.chain = (async () => { await root.state.chain; if (compressed) { const encoded = contentNode.textContent; const blob = new Blob([ Uint8Array.from(atob(encoded), (m) => m.codePointAt(0)) ]); const reader = blob.stream().pipeThrough( new DecompressionStream(\"deflate\") ).pipeThrough( new TextDecoderStream(\"utf-8\") ).getReader(); const parts = []; while (true) { const step = await reader.read(); if (step.done) { break; } parts.push(step.value); } const tpl = document.createElement('template'); tpl.innerHTML = parts.join(\"\"); _insertNode(tpl.content); } else { _insertNode(contentNode.content); } })(); } else { _insertNode(contentNode.content); } }); </script></treescope-run-here><div style=\"display:none\"> <script type=\"application/octet-stream\" >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</script> <treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_472a510544b54dd3bb11d8eebf96e5a1\")) .filter((elt) => !elt.dataset['step0']) )[0]; root.dataset['step0'] = 1; root.defns.insertContent( this.parentNode.querySelector('script[type=\"application/octet-stream\"]'), true ); this.parentNode.remove(); </script></treescope-run-here> </div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
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+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_472a510544b54dd3bb11d8eebf96e5a1\")) .filter((elt) => !elt.dataset.stolen) )[0]; root.dataset.stolen = 1; this.parentNode.replaceChild(root, this); </script></treescope-run-here>"
+      ],
+      "text/plain": [
+       "<jax.Array(True, dtype=bool)>"
+      ]
+     },
+     "execution_count": 35,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "jnp.all(stepped_trace.get_retval()[\"new_state\"][\"depth_nonreturn_prob\"] == metadata[\"other_latents_metadata\"][\"dnrps\"][metadata[\"chosen_pose_index\"]])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<script> (()=>{ if (customElements.get('treescope-container') === undefined) { class TreescopeContainer extends HTMLElement { constructor() { super(); this.attachShadow({mode: \"open\"}); this.defns = {}; this.state = {}; } } customElements.define(\"treescope-container\", TreescopeContainer); } if (customElements.get('treescope-run-here') === undefined) { class RunHere extends HTMLElement { constructor() { super() } connectedCallback() { const run = child => { const fn = new Function(child.textContent); child.textContent = \"\"; fn.call(this); this.remove(); }; const child = this.querySelector(\"script\"); if (child) { run(child); } else { new MutationObserver(()=>{ run(this.querySelector(\"script\")); }).observe(this, {childList: true}); } } } customElements.define(\"treescope-run-here\", RunHere); } })(); </script> <treescope-container class=\"treescope_out_cf9f3be257204ee78c9f3b8955124ba0\" ></treescope-container> <treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_cf9f3be257204ee78c9f3b8955124ba0\")) .filter((elt) => !elt.dataset.setup) )[0]; root.dataset.setup = 1; const msg = document.createElement(\"span\"); msg.style = \"color: #aaaaaa; font-family: monospace; transition: opacity 0.2s; opacity: 0.0;\"; msg.textContent = \"(Loading...)\"; root.state.loadingMsg = msg; root.shadowRoot.appendChild(msg); root.state.chain = new Promise((resolve, reject) => { const observer = new IntersectionObserver((entries) => { for (const entry of entries) { if (entry.isIntersecting) { resolve(); observer.disconnect(); return; } } }, {rootMargin: \"1000px\"}); window.setTimeout(() => { if (root.loadingMsg) { root.loadingMsg.style.opacity = \"1.0\"; } observer.observe(root); }, 0); }); root.state.deferring = false; const _insertNode = (node) => { for (let oldScript of node.querySelectorAll(\"script\")) { let newScript = document.createElement(\"script\"); newScript.type = oldScript.type; newScript.textContent = oldScript.textContent; oldScript.parentNode.replaceChild(newScript, oldScript); } if (root.state.loadingMsg) { root.state.loadingMsg.remove(); root.state.loadingMsg = null; } root.shadowRoot.appendChild(node); }; root.defns.insertContent = ((contentNode, compressed) => { if (compressed) { root.state.deferring = true; } if (root.state.deferring) { root.state.chain = (async () => { await root.state.chain; if (compressed) { const encoded = contentNode.textContent; const blob = new Blob([ Uint8Array.from(atob(encoded), (m) => m.codePointAt(0)) ]); const reader = blob.stream().pipeThrough( new DecompressionStream(\"deflate\") ).pipeThrough( new TextDecoderStream(\"utf-8\") ).getReader(); const parts = []; while (true) { const step = await reader.read(); if (step.done) { break; } parts.push(step.value); } const tpl = document.createElement('template'); tpl.innerHTML = parts.join(\"\"); _insertNode(tpl.content); } else { _insertNode(contentNode.content); } })(); } else { _insertNode(contentNode.content); } }); </script></treescope-run-here><div style=\"display:none\"> <script type=\"application/octet-stream\" >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</script> <treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_cf9f3be257204ee78c9f3b8955124ba0\")) .filter((elt) => !elt.dataset['step0']) )[0]; root.dataset['step0'] = 1; root.defns.insertContent( this.parentNode.querySelector('script[type=\"application/octet-stream\"]'), true ); this.parentNode.remove(); </script></treescope-run-here> </div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
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+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_cf9f3be257204ee78c9f3b8955124ba0\")) .filter((elt) => !elt.dataset.stolen) )[0]; root.dataset.stolen = 1; this.parentNode.replaceChild(root, this); </script></treescope-run-here>"
+      ],
+      "text/plain": [
+       "# jax.Array float32(100,) ≈0.68 ±0.46 [≥0.01, ≤0.99] nonzero:100\n",
+       "  Array([0.99, 0.99, 0.99, 0.99, 0.99, 0.99, 0.01, 0.01, 0.99, 0.99, 0.01,\n",
+       "         0.99, 0.99, 0.99, 0.99, 0.01, 0.99, 0.99, 0.99, 0.01, 0.99, 0.99,\n",
+       "         0.01, 0.01, 0.99, 0.01, 0.99, 0.99, 0.01, 0.01, 0.99, 0.99, 0.01,\n",
+       "         0.99, 0.99, 0.99, 0.99, 0.01, 0.99, 0.01, 0.01, 0.01, 0.99, 0.99,\n",
+       "         0.99, 0.99, 0.99, 0.01, 0.01, 0.99, 0.99, 0.99, 0.99, 0.99, 0.99,\n",
+       "         0.99, 0.99, 0.99, 0.99, 0.99, 0.99, 0.01, 0.99, 0.01, 0.99, 0.01,\n",
+       "         0.99, 0.99, 0.01, 0.01, 0.99, 0.99, 0.01, 0.99, 0.99, 0.01, 0.99,\n",
+       "         0.99, 0.01, 0.99, 0.01, 0.99, 0.99, 0.99, 0.99, 0.99, 0.01, 0.99,\n",
+       "         0.99, 0.99, 0.99, 0.01, 0.99, 0.01, 0.01, 0.99, 0.01, 0.99, 0.99,\n",
+       "         0.01], dtype=float32)\n"
+      ]
+     },
+     "execution_count": 36,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "stepped_trace.get_retval()[\"new_state\"][\"depth_nonreturn_prob\"][:100]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "T = 0\n",
+    "b3d.chisight.gen3d.model.viz_trace(stepped_trace, T, ground_truth_vertices=meshes[OBJECT_INDEX].vertices, ground_truth_pose=all_data[T][\"camera_pose\"].inv() @ all_data[T][\"object_poses\"][OBJECT_INDEX])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 75,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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<treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_78b23d2725fd4cf79264280248235914\")) .filter((elt) => !elt.dataset['step0']) )[0]; root.dataset['step0'] = 1; root.defns.insertContent( this.parentNode.querySelector('script[type=\"application/octet-stream\"]'), true ); this.parentNode.remove(); </script></treescope-run-here> </div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
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</script> <treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_78b23d2725fd4cf79264280248235914\")) .filter((elt) => !elt.dataset['step1']) )[0]; root.dataset['step1'] = 1; root.defns.insertContent( this.parentNode.querySelector('script[type=\"application/octet-stream\"]'), true ); this.parentNode.remove(); </script></treescope-run-here> </div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_78b23d2725fd4cf79264280248235914\")) .filter((elt) => !elt.dataset.stolen) )[0]; root.dataset.stolen = 1; this.parentNode.replaceChild(root, this); </script></treescope-run-here>"
+      ],
+      "text/plain": [
+       "{'depth_nonreturn_proposal': {'index': <jax.Array int32(5071,) [≥0, ≤1] zero:1_963 nonzero:3_108\n",
+       "    <Arrayviz rendering>\n",
+       "  >,\n",
+       "  'log_normalized_scores': <jax.Array float32(5071, 2) ≈-0.77 ±0.44 [≥-3.0, ≤-0.051] nonzero:10_142\n",
+       "    <Arrayviz rendering>\n",
+       "  >,\n",
+       "  'support': <jax.Array float32(5071, 2) ≈0.5 ±0.49 [≥0.01, ≤0.99] nonzero:10_142\n",
+       "    <Arrayviz rendering>\n",
+       "  >}}"
+      ]
+     },
+     "execution_count": 75,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "jax.tree.map(\n",
+    "    lambda x: x[closest_pose_idx], metadata[\"other_latents_metadata\"]\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 65,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "gt_pose = all_data[T][\"camera_pose\"].inv() @ all_data[T][\"object_poses\"][OBJECT_INDEX]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 66,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<script> (()=>{ if (customElements.get('treescope-container') === undefined) { class TreescopeContainer extends HTMLElement { constructor() { super(); this.attachShadow({mode: \"open\"}); this.defns = {}; this.state = {}; } } customElements.define(\"treescope-container\", TreescopeContainer); } if (customElements.get('treescope-run-here') === undefined) { class RunHere extends HTMLElement { constructor() { super() } connectedCallback() { const run = child => { const fn = new Function(child.textContent); child.textContent = \"\"; fn.call(this); this.remove(); }; const child = this.querySelector(\"script\"); if (child) { run(child); } else { new MutationObserver(()=>{ run(this.querySelector(\"script\")); }).observe(this, {childList: true}); } } } customElements.define(\"treescope-run-here\", RunHere); } })(); </script> <treescope-container class=\"treescope_out_1ce626eb8b5b4dbc80ce1713f20183c6\" ></treescope-container> <treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_1ce626eb8b5b4dbc80ce1713f20183c6\")) .filter((elt) => !elt.dataset.setup) )[0]; root.dataset.setup = 1; const msg = document.createElement(\"span\"); msg.style = \"color: #aaaaaa; font-family: monospace; transition: opacity 0.2s; opacity: 0.0;\"; msg.textContent = \"(Loading...)\"; root.state.loadingMsg = msg; root.shadowRoot.appendChild(msg); root.state.chain = new Promise((resolve, reject) => { const observer = new IntersectionObserver((entries) => { for (const entry of entries) { if (entry.isIntersecting) { resolve(); observer.disconnect(); return; } } }, {rootMargin: \"1000px\"}); window.setTimeout(() => { if (root.loadingMsg) { root.loadingMsg.style.opacity = \"1.0\"; } observer.observe(root); }, 0); }); root.state.deferring = false; const _insertNode = (node) => { for (let oldScript of node.querySelectorAll(\"script\")) { let newScript = document.createElement(\"script\"); newScript.type = oldScript.type; newScript.textContent = oldScript.textContent; oldScript.parentNode.replaceChild(newScript, oldScript); } if (root.state.loadingMsg) { root.state.loadingMsg.remove(); root.state.loadingMsg = null; } root.shadowRoot.appendChild(node); }; root.defns.insertContent = ((contentNode, compressed) => { if (compressed) { root.state.deferring = true; } if (root.state.deferring) { root.state.chain = (async () => { await root.state.chain; if (compressed) { const encoded = contentNode.textContent; const blob = new Blob([ Uint8Array.from(atob(encoded), (m) => m.codePointAt(0)) ]); const reader = blob.stream().pipeThrough( new DecompressionStream(\"deflate\") ).pipeThrough( new TextDecoderStream(\"utf-8\") ).getReader(); const parts = []; while (true) { const step = await reader.read(); if (step.done) { break; } parts.push(step.value); } const tpl = document.createElement('template'); tpl.innerHTML = parts.join(\"\"); _insertNode(tpl.content); } else { _insertNode(contentNode.content); } })(); } else { _insertNode(contentNode.content); } }); </script></treescope-run-here><div style=\"display:none\"> <script type=\"application/octet-stream\" >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</script> <treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_1ce626eb8b5b4dbc80ce1713f20183c6\")) .filter((elt) => !elt.dataset['step0']) )[0]; root.dataset['step0'] = 1; root.defns.insertContent( this.parentNode.querySelector('script[type=\"application/octet-stream\"]'), true ); this.parentNode.remove(); </script></treescope-run-here> </div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
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</script> <treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_1ce626eb8b5b4dbc80ce1713f20183c6\")) .filter((elt) => !elt.dataset['step1']) )[0]; root.dataset['step1'] = 1; root.defns.insertContent( this.parentNode.querySelector('script[type=\"application/octet-stream\"]'), true ); this.parentNode.remove(); </script></treescope-run-here> </div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_1ce626eb8b5b4dbc80ce1713f20183c6\")) .filter((elt) => !elt.dataset.stolen) )[0]; root.dataset.stolen = 1; this.parentNode.replaceChild(root, this); </script></treescope-run-here>"
+      ],
+      "text/plain": [
+       "<jax.Array float32(10000, 3) ≈0.33 ±0.44 [≥-0.25, ≤1.1] nonzero:30_000\n",
+       "  <Arrayviz rendering>\n",
+       ">"
+      ]
+     },
+     "execution_count": 66,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "metadata[\"proposed_poses\"].position"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 74,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div style=\"display:none\"> <script type=\"application/octet-stream\" >eNrtGoly2kj2VzpK7ViMjSwwhwGbWoG5nGDHxokdz04xjdSS2uiy1IDxVP59X7fEjYlzzOzW1pIUIOnd92t8YtAxitjUIaeSQaPAwdMy8nyPSIgap5Lph32DmCQMidHPqzibLR6pekbN57JGHhP4j0nRzB+rOKdiqXoSBdiDd06vqgx8xnzXoR4pez6TFdN3DDxwSN/zDVK2cSRXHTwgTnX1SZ/5luXEOGXdJvqQGKkU+jWF/kQBNgzqWWnmB2WkKpk8cSuIc0jbhFo2K6OMIu49p6lnkCe4rqDAjyijvldGIXEwo2NSQV8U3XdAOTwYhGQMlMVlGb0tHGexqi4AdN91icf6E5t4ffIE+hnE+Gn6zLhi8Vpw9UbugIRLAGrpOJMvLAAiFoIdlikcZfKZ/BwA3MXNsgAYOFgfVtAA3q3QH3lGOnkwxqGcTg8cXx/Gt1IA5YcGCWMrZ4InFPkONXZBxq7+GvAXpNjTgIQg2bAfEtdnpG/7Y1B0XehNMf2ho9vyce4f3O25PMqopZjiBEf9SA99xwF05ismDSPWZ1QfvppqKadkOF21hDJHBaW4lbDw3052qQ2GLMTeLPbWmaNMhAiOCARq2h+xA2T6HktPRBivPeNe/bFgA8GC6WAETvJArJVEF7ouHpfLAwJZH0eOxyD0y0hC0hoUqiKe6luB/0UyOQMQhD4mdqkDnPa6mJGQYgf1pu7AdyJ0OWLcSgaqx5jwGUz3KghMMBhSwOTokev7zIZILyPsMUCnYBWjMo96ovJ/cD0KI34j8CkQCxPmEX0mvEyUeEVY1TIOuy1aCLoGDocRwVZIiLeGKQJAdyg37Bwfm2wlW3Xx2s1zDWeV5bLpk1QyMMNp7IFjMQ+o1PJtzgSCdjnctsXYt6kylwAcQ4nxZlUSwRK9oW7ghwx8s057EPpDqJj8TqL4q6y7hLZkz5mbvyi2bvdBUJ30HWKypY7AL7mv87q9CheKhFoAhnGfmEPyPgGqGn3dpo4REi9RHlNhRWEFIeUq4E9rAfNkFLWyglwcWuCuWB8dO7qc1W2U5qU1rksRwxx/Lu9fJklS22NJDKjwECa8wC+543GEHQ+7pB+ExKRPQGQl8Y5F4m1I/JKF1+Hm5TSWBGJ0FeRv94Gq5HQ79RpZ/x6nxK1WSLW14a6MS0IPCHvHRr8iOQPqLKMkdCOAIqlUam6DBWr69bgzvrOxQGDOSc7uppPbf6M1F4ONsGA6xAYdRYmCGeKCdi8rJiT9wT78tRD/c2X2iv3Lc+4Vs9du4C8KUPxLZvGFk39kHBfzNQjr4AA6/NYh5QdN/zIH6nGZ46Fvecx/AeZnyLGNRaJoDCAmRRjyg62mYNA7I2iS0N5gQFLmwH0XGKMdFNZVBeG+CvgaZi/SSUQ+OYyXwpM5sXQ48iBMQrgH8zQNGGKwG5zu4QDCVBczzqGvMwLdBHCwu1elJpLRGy0M8VQxQ9+VDV8f8eVM4U0nUsbYGZFITqWUyHeJLFoROq2KTyUeRNHp6WtHUWkPBvp4R/MihiKbEKCGPDJB9V6vx7Xp8XsyJJd4qIQEVNZJb+rp8h//TMZfncya4rePwnEv5Zy4HUMXO5XlLaGMcnxTjUK9jEahI/O5rMyfH05808xWBjD5FXIHhlpqdS2tpolX50rTfPGtdj2B93ZT0xrarlfN1TRr6L8zOo1affJZ024+18+1bqdW15rWU6f93mZRrUuJddQ8u8u+7xQ+j3vBiH7o5m8y53ed60/d8W33mX2YNpv1/VtreENrZ6pNz65G5w2j9aC2B4fmuGMEj+8K9uMtpVejrtey2+ZHpn0s1C7CnNbseMNGQf84Gnn71/lHPRpOxmbTOXx8shr+sTU4n7SOM23t0NOu8+/D8DxzvW89q9eGqp2bGeuiWJ+0HrKW6k9H18Wi28gUJu270qVlBeRmOM2RzuA5rw/CyxbDmnXVuZic4WgaXY06nbvbRnOifbgKOp+Nj4eH+1bxpnh3xFTz3YdHbZwHmu+1i6LWnWiu9Xzd2x/d90jj7ilrFvTni9x1e5of1bR3z7WHoBkc0fZVvaHejz7kekXPrL1vtJtdV6P7x+NG1vYydnF/8Gly9zBph+Oz1se692A2Ghbbv9TvHaeYL9XPJ7Vju5Trdlu9o9a9Zrmd/EPtqsRuWqRdatRqndbRmZW7PvysTwdaC3z66d2hdtXCGunWHa393Li07plVqH2wLi87Z7UhvcqTZu2uXmvqVA3s0A88iI3gvnGWec4Me2bdZPb0ndc2cDNqm+qF22pcFGqG9vjpU4BZ1Lt3DQPTUtZ8LuU+0ofHQuCGhUv/c71Hw5Y7Pm8d9W57R81GVq9dmTf7bccPWrlmNMlj67FwTO9J78IJbr1au0OMbkhGt4+tupu5bYbDXu8pny3c3kYTDSRKQcxD7DN5T4T1Hm9mf8DbPPux4Qcwmy5SMoI8/U1RlB0QB3HO/g60YL+MFIuwayhuF1DR5JRi+xFTDGJ6kWJDmYaCzheSeFcC2hAeno7keGVJ8RIzqxI8BW98nr4Alqw0/F4E5YGT4DsaX2zwBFOGPDymFmZ+qADlYODj0FAmIWXkhjwxeUGL9/qYlu7gKHpPI66SIUtLC5zEyxBhN9QlsOnJciLWBh4/dhmTDdQvByirqqqYcaD4wjwpk9Q2fMF3aUuTFsIxkHpWwU6hVEvoLWpi6kBhYz7iwG9EZYM50IO9AaoxBZsRbPAlc3/ZdkKMLxVoGqIzVE8Ot7YNaKFISHYqrXa85CRydrC5MgvBOmkMjnN5XNk25cEYU5FWSa80dUSjfnzk43vilAeA4+Z/Qr1glDQxSbT7gf8kbSWSTAaAeiiQVvktjsgYzMuEScIy6SGZQtrZp9KaeCtHTsmMh1bXZOk1tkoerm10UjUg3jOmiyFAxHGAwXF9E5zIj7UUcJQ4+I0/LnzIpYR6wJWWV5+fHCYWW+a7sSOuDsbSDugNUB92fOphpw8dOTz9JuMqK7jbTJ0cvUrVX94+ZYsVMY7IWfWoeIAM4XzqsaNsKn66qvjBphvm86hURTPgDaDZsLgqzt7i2GQP+V6dJ/Pp3jdWM5nDp/bQ/EznVJId7A4MjPiwVxbvq0ZJSYu8mqPBWPNVPH64t36MBXgi47n14fv8J4TDHR/fEQjU+N4woMbWIIgP6KVqKXd8VMzkSqXscVHN/a+5mxrf42zA+g+6WuTgdzqb4+6q/j+/2O/4kUnaGRpvt8bPRvV+wE+z6iwq1a4SvIv7xinpzudS9ec5YPl3Oii6DquIBygusFw/oVh8+YvFKjtC6L8svbi235NgAu9npdhr02/Ndgf/t+832ffFkW3xKzla+9FCqqa+zTsrhzBfTaN56mybXjbzaPZh0PHXT3Gkl05xpGq8KMWFoGOIVU16/Z8Y/F5JFi1f5z4D7M0QqiTLGBcyAUrAlccRCac94hAdti5ZWjvakuaoZogtN95j5kukDvIzcpZcNhOITXZ1xwdfns5pKGAL4hl1XhjlGRBsVAAl5GXhSBwuw5aLZIcwRAFZrcDHycJMikM8i9lwd3+f72UcLn64zAkuGw7hX2vTDjCbYf9GfwcGHCfyR6FOzuj4ZaO85X/0wReyNfT4cnbKdUuZLc+pxT+DJ7yFpnwdnT9Nlk6x1s0tsExoxXapryx+/wZ+IjZw</script> <treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_021a300eec504b5a8f83986873a29005\")) .filter((elt) => !elt.dataset['step1']) )[0]; root.dataset['step1'] = 1; root.defns.insertContent( this.parentNode.querySelector('script[type=\"application/octet-stream\"]'), true ); this.parentNode.remove(); </script></treescope-run-here> </div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_021a300eec504b5a8f83986873a29005\")) .filter((elt) => !elt.dataset.stolen) )[0]; root.dataset.stolen = 1; this.parentNode.replaceChild(root, this); </script></treescope-run-here>"
+      ],
+      "text/plain": [
+       "<jax.Array(2037, dtype=int32)>"
+      ]
+     },
+     "execution_count": 74,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "closest_pose_idx"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 72,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<script> (()=>{ if (customElements.get('treescope-container') === undefined) { class TreescopeContainer extends HTMLElement { constructor() { super(); this.attachShadow({mode: \"open\"}); this.defns = {}; this.state = {}; } } customElements.define(\"treescope-container\", TreescopeContainer); } if (customElements.get('treescope-run-here') === undefined) { class RunHere extends HTMLElement { constructor() { super() } connectedCallback() { const run = child => { const fn = new Function(child.textContent); child.textContent = \"\"; fn.call(this); this.remove(); }; const child = this.querySelector(\"script\"); if (child) { run(child); } else { new MutationObserver(()=>{ run(this.querySelector(\"script\")); }).observe(this, {childList: true}); } } } customElements.define(\"treescope-run-here\", RunHere); } })(); </script> <treescope-container class=\"treescope_out_234455d1be0941dcaf66c26199e5a336\" ></treescope-container> <treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_234455d1be0941dcaf66c26199e5a336\")) .filter((elt) => !elt.dataset.setup) )[0]; root.dataset.setup = 1; const msg = document.createElement(\"span\"); msg.style = \"color: #aaaaaa; font-family: monospace; transition: opacity 0.2s; opacity: 0.0;\"; msg.textContent = \"(Loading...)\"; root.state.loadingMsg = msg; root.shadowRoot.appendChild(msg); root.state.chain = new Promise((resolve, reject) => { const observer = new IntersectionObserver((entries) => { for (const entry of entries) { if (entry.isIntersecting) { resolve(); observer.disconnect(); return; } } }, {rootMargin: \"1000px\"}); window.setTimeout(() => { if (root.loadingMsg) { root.loadingMsg.style.opacity = \"1.0\"; } observer.observe(root); }, 0); }); root.state.deferring = false; const _insertNode = (node) => { for (let oldScript of node.querySelectorAll(\"script\")) { let newScript = document.createElement(\"script\"); newScript.type = oldScript.type; newScript.textContent = oldScript.textContent; oldScript.parentNode.replaceChild(newScript, oldScript); } if (root.state.loadingMsg) { root.state.loadingMsg.remove(); root.state.loadingMsg = null; } root.shadowRoot.appendChild(node); }; root.defns.insertContent = ((contentNode, compressed) => { if (compressed) { root.state.deferring = true; } if (root.state.deferring) { root.state.chain = (async () => { await root.state.chain; if (compressed) { const encoded = contentNode.textContent; const blob = new Blob([ Uint8Array.from(atob(encoded), (m) => m.codePointAt(0)) ]); const reader = blob.stream().pipeThrough( new DecompressionStream(\"deflate\") ).pipeThrough( new TextDecoderStream(\"utf-8\") ).getReader(); const parts = []; while (true) { const step = await reader.read(); if (step.done) { break; } parts.push(step.value); } const tpl = document.createElement('template'); tpl.innerHTML = parts.join(\"\"); _insertNode(tpl.content); } else { _insertNode(contentNode.content); } })(); } else { _insertNode(contentNode.content); } }); </script></treescope-run-here><div style=\"display:none\"> <script type=\"application/octet-stream\" >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</script> <treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_234455d1be0941dcaf66c26199e5a336\")) .filter((elt) => !elt.dataset['step0']) )[0]; root.dataset['step0'] = 1; root.defns.insertContent( this.parentNode.querySelector('script[type=\"application/octet-stream\"]'), true ); this.parentNode.remove(); </script></treescope-run-here> </div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
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</script> <treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_234455d1be0941dcaf66c26199e5a336\")) .filter((elt) => !elt.dataset['step1']) )[0]; root.dataset['step1'] = 1; root.defns.insertContent( this.parentNode.querySelector('script[type=\"application/octet-stream\"]'), true ); this.parentNode.remove(); </script></treescope-run-here> </div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_234455d1be0941dcaf66c26199e5a336\")) .filter((elt) => !elt.dataset.stolen) )[0]; root.dataset.stolen = 1; this.parentNode.replaceChild(root, this); </script></treescope-run-here>"
+      ],
+      "text/plain": [
+       "<Array([ 0.37760454,  0.06509134,  0.42540824, -0.8198816 ], dtype=float32)\n",
+       "  <Arrayviz rendering>\n",
+       ">"
+      ]
+     },
+     "execution_count": 72,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "closest_pose_idx = jnp.argmin(\n",
+    "    jnp.linalg.norm(\n",
+    "        metadata[\"proposed_poses\"].position - gt_pose.position, axis=-1\n",
+    "    )\n",
+    ")\n",
+    "metadata[\"proposed_poses\"].quaternion[closest_pose_idx]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 73,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<script> (()=>{ if (customElements.get('treescope-container') === undefined) { class TreescopeContainer extends HTMLElement { constructor() { super(); this.attachShadow({mode: \"open\"}); this.defns = {}; this.state = {}; } } customElements.define(\"treescope-container\", TreescopeContainer); } if (customElements.get('treescope-run-here') === undefined) { class RunHere extends HTMLElement { constructor() { super() } connectedCallback() { const run = child => { const fn = new Function(child.textContent); child.textContent = \"\"; fn.call(this); this.remove(); }; const child = this.querySelector(\"script\"); if (child) { run(child); } else { new MutationObserver(()=>{ run(this.querySelector(\"script\")); }).observe(this, {childList: true}); } } } customElements.define(\"treescope-run-here\", RunHere); } })(); </script> <treescope-container class=\"treescope_out_19f21d8f7950428c9bc22af1c3e78dbb\" ></treescope-container> <treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_19f21d8f7950428c9bc22af1c3e78dbb\")) .filter((elt) => !elt.dataset.setup) )[0]; 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</script> <treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_19f21d8f7950428c9bc22af1c3e78dbb\")) .filter((elt) => !elt.dataset['step1']) )[0]; root.dataset['step1'] = 1; root.defns.insertContent( this.parentNode.querySelector('script[type=\"application/octet-stream\"]'), true ); this.parentNode.remove(); </script></treescope-run-here> </div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_19f21d8f7950428c9bc22af1c3e78dbb\")) .filter((elt) => !elt.dataset.stolen) )[0]; root.dataset.stolen = 1; this.parentNode.replaceChild(root, this); </script></treescope-run-here>"
+      ],
+      "text/plain": [
+       "<Array([ 0.40868163,  0.11557679,  0.42380893, -0.80000466], dtype=float32)\n",
+       "  <Arrayviz rendering>\n",
+       ">"
+      ]
+     },
+     "execution_count": 73,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "gt_pose.quaternion"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 77,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "T = 1\n",
+    "b3d.chisight.gen3d.model.viz_trace(stepped_trace, T, ground_truth_vertices=meshes[OBJECT_INDEX].vertices, ground_truth_pose=all_data[T][\"camera_pose\"].inv() @ all_data[T][\"object_poses\"][OBJECT_INDEX])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "[2024-09-10T18:07:03Z WARN  re_log_types::path::parse_path] When parsing the entity path \"proposed positions\": Unescaped whitespace. The path will be interpreted as /proposed\\ positions\n"
+     ]
+    }
+   ],
+   "source": [
+    "import rerun as rr\n",
+    "rr.log(\"proposed positions\", rr.Points3D(metadata[\"proposed_poses\"].position))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+      ],
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+       "<IPython.core.display.HTML object>"
+      ]
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+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<treescope-run-here><script type=\"application/octet-stream\"> const root = ( Array.from(document.getElementsByClassName( \"treescope_out_3dbe35883b1a441fb57d2e97a0ddc99e\")) .filter((elt) => !elt.dataset.stolen) )[0]; root.dataset.stolen = 1; this.parentNode.replaceChild(root, this); </script></treescope-run-here>"
+      ],
+      "text/plain": [
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+      ]
+     },
+     "execution_count": 57,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
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+   "source": [
+    "jax.scipy.special.logsumexp(jnp.array([-jnp.inf, -.2, -1.]))"
    ]
   },
   {
diff --git a/src/b3d/chisight/gen3d/inference.py b/src/b3d/chisight/gen3d/inference.py
index 7db9ddbe..611911fe 100644
--- a/src/b3d/chisight/gen3d/inference.py
+++ b/src/b3d/chisight/gen3d/inference.py
@@ -20,7 +20,8 @@
 
 # Use namedtuple rather than dict so we can hash this, and use it as a static arg to a jitted function.
 InferenceHyperparams = namedtuple(
-    "InferenceHyperparams", ["n_poses", "pose_proposal_std", "pose_proposal_conc"]
+    "InferenceHyperparams",
+    ["n_poses", "pose_proposal_std", "pose_proposal_conc", "color_proposal_params"],
 )
 
 
@@ -66,7 +67,7 @@ def inference_step(key, old_trace, observed_rgbd, inference_hyperparams):
     )
 
     param_generation_keys = split(k3, inference_hyperparams.n_poses)
-    proposed_traces, log_q_nonpose_latents = jax.vmap(
+    proposed_traces, log_q_nonpose_latents, other_latents_metadata = jax.vmap(
         propose_other_latents_given_pose, in_axes=(0, None, 0, None)
     )(param_generation_keys, trace, proposed_poses, inference_hyperparams)
     p_scores = jax.vmap(lambda tr: tr.get_score())(proposed_traces)
@@ -75,7 +76,18 @@ def inference_step(key, old_trace, observed_rgbd, inference_hyperparams):
     chosen_index = jax.random.categorical(k4, scores)
     new_trace = jax.tree.map(lambda x: x[chosen_index], proposed_traces)
 
-    return new_trace, logmeanexp(scores), {"proposed_poses": proposed_poses}
+    return (
+        new_trace,
+        logmeanexp(scores),
+        {
+            "proposed_poses": proposed_poses,
+            "chosen_pose_index": chosen_index,
+            "p_scores": p_scores,
+            "log_q_poses": log_q_poses,
+            "log_q_nonpose_latents": log_q_nonpose_latents,
+            "other_latents_metadata": other_latents_metadata,
+        },
+    )
 
 
 def inference_step_noweight(*args):
diff --git a/src/b3d/chisight/gen3d/inference_moves.py b/src/b3d/chisight/gen3d/inference_moves.py
index 539f3dd4..f8842ed3 100644
--- a/src/b3d/chisight/gen3d/inference_moves.py
+++ b/src/b3d/chisight/gen3d/inference_moves.py
@@ -19,6 +19,18 @@
 from .projection import PixelsPointsAssociation
 
 
+def normalize_log_scores(scores):
+    """
+    Util for constructing log resampling distributions, avoiding NaN issues.
+
+    (Conversely, since there will be no NaNs, this could make it harder to debug.)
+    """
+    val = scores - jax.scipy.special.logsumexp(scores)
+    return jnp.where(
+        jnp.any(jnp.isnan(val)), -jnp.log(len(val)) * jnp.ones_like(val), val
+    )
+
+
 def propose_pose(key, advanced_trace, inference_hyperparams):
     """
     Propose a random pose near the previous timestep's pose.
@@ -43,35 +55,41 @@ def propose_other_latents_given_pose(key, advanced_trace, pose, inference_hyperp
     proposed latents (and the same pose and observed rgbd as in the given trace).
     `log_q` is (a fair estimate of) the log proposal density.
     """
-    k1, k2, k3, k4, k5, k6 = split(key, 6)
+    k1, k2, k3, k4, k5 = split(key, 5)
 
-    trace_with_pose = update_field(k1, advanced_trace, "pose", pose)
+    trace = update_field(k1, advanced_trace, "pose", pose)
 
-    depth_nonreturn_probs, log_q_dnrps = propose_depth_nonreturn_probs(
-        k2, trace_with_pose
+    k2a, k2b = split(k2)
+    depth_nonreturn_probs, log_q_dnrps, dnrp_metadata = propose_depth_nonreturn_probs(
+        k2a, trace
+    )
+    trace = update_vmapped_field(
+        k2b, trace, "depth_nonreturn_prob", depth_nonreturn_probs
     )
+
+    k3a, k3b = split(k3)
     colors, visibility_probs, log_q_cvp = propose_colors_and_visibility_probs(
-        k3, trace_with_pose
+        k3a, trace, inference_hyperparams
+    )
+    trace = update_vmapped_fields(
+        k3b, trace, ["colors", "visibility_prob"], [colors, visibility_probs]
     )
     log_q_cvp = 0.0
-    depth_scale, log_q_ds = propose_depth_scale(k4, trace_with_pose)
-    color_scale, log_q_cs = propose_color_scale(k5, trace_with_pose)
 
-    proposed_trace = update_fields(
-        k6,
-        trace_with_pose,
-        [
-            "depth_nonreturn_prob",
-            "colors",
-            "visibility_prob",
-            "depth_scale",
-            "color_scale",
-        ],
-        [depth_nonreturn_probs, colors, visibility_probs, depth_scale, color_scale],
-    )
-    log_q = log_q_dnrps + log_q_cvp + log_q_ds + log_q_cs
+    k4a, k4b = split(k4)
+    depth_scale, log_q_ds = propose_depth_scale(k4a, trace)
+    trace = update_field(k4b, trace, "depth_scale", depth_scale)
+
+    k5a, k5b = split(k5)
+    color_scale, log_q_cs = propose_color_scale(k5a, trace)
+    trace = update_field(k5b, trace, "color_scale", color_scale)
 
-    return proposed_trace, log_q
+    log_q = log_q_dnrps + log_q_cvp + log_q_ds + log_q_cs
+    return (
+        trace,
+        log_q,
+        {"depth_nonreturn_proposal": dnrp_metadata, "dnrps": depth_nonreturn_probs},
+    )
 
 
 def propose_depth_nonreturn_probs(key, trace):
@@ -86,7 +104,7 @@ def propose_depth_nonreturn_probs(key, trace):
         get_hypers(trace), get_new_state(trace)["pose"]
     ).get_point_depths(get_observed_rgbd(trace))
 
-    depth_nonreturn_probs, per_vertex_log_qs = jax.vmap(
+    depth_nonreturn_probs, per_vertex_log_qs, metadata = jax.vmap(
         propose_vertex_depth_nonreturn_prob, in_axes=(0, 0, 0, None, None, None)
     )(
         split(key, get_n_vertices(trace)),
@@ -97,10 +115,10 @@ def propose_depth_nonreturn_probs(key, trace):
         get_hypers(trace),
     )
 
-    return depth_nonreturn_probs, per_vertex_log_qs.sum()
+    return depth_nonreturn_probs, per_vertex_log_qs.sum(), metadata
 
 
-def propose_colors_and_visibility_probs(key, trace):
+def propose_colors_and_visibility_probs(key, trace, inference_hyperparams):
     """
     Propose a new color and visibility probability for every vertex, conditioned
     upon the other values in `trace`.
@@ -114,7 +132,8 @@ def propose_colors_and_visibility_probs(key, trace):
     ).get_point_rgbds(get_observed_rgbd(trace))
 
     colors, visibility_probs, per_vertex_log_qs = jax.vmap(
-        propose_vertex_color_and_visibility_prob, in_axes=(0, 0, 0, None, None, None)
+        propose_vertex_color_and_visibility_prob,
+        in_axes=(0, 0, 0, None, None, None, None),
     )(
         split(key, get_n_vertices(trace)),
         jnp.arange(get_n_vertices(trace)),
@@ -122,6 +141,7 @@ def propose_colors_and_visibility_probs(key, trace):
         get_prev_state(trace),
         get_new_state(trace),
         get_hypers(trace),
+        inference_hyperparams,
     )
 
     return colors, visibility_probs, per_vertex_log_qs.sum()
@@ -136,35 +156,78 @@ def propose_vertex_depth_nonreturn_prob(
     Returns (depth_nonreturn_prob, log_q) where `depth_nonreturn_prob` is
     the proposed value and `log_q` is (a fair estimate of) the log proposal density.
     """
-
-    # TODO: could factor into a sub-function that just receives the values
-    # we pull out of the previous and new state here, if that facilitates
-    # unit testing.
-
     previous_dnrp = previous_state["depth_nonreturn_prob"][vertex_index]
     visibility_prob = new_state["visibility_prob"][vertex_index]
     latent_depth = new_state["pose"].apply(hyperparams["vertices"][vertex_index])[2]
-    depth_scale = new_state["depth_scale"]
-    obs_depth_kernel = hyperparams["image_kernel"].get_depth_vertex_kernel()
+    return _propose_vertex_depth_nonreturn_prob(
+        key,
+        observed_depth,
+        latent_depth,
+        visibility_prob,
+        new_state["depth_scale"],
+        previous_dnrp,
+        hyperparams["depth_nonreturn_prob_kernel"],
+        hyperparams["image_kernel"].get_depth_vertex_kernel(),
+    )
+
 
+def _propose_vertex_depth_nonreturn_prob(
+    key,
+    observed_depth,
+    latent_depth,
+    visibility_prob,
+    depth_scale,
+    previous_dnrp,
+    dnrp_transition_kernel,
+    obs_depth_kernel,
+    return_metadata=True,
+):
     def score_dnrp_value(dnrp_value):
-        transition_score = hyperparams["depth_nonreturn_prob_kernel"].logpdf(
-            dnrp_value, previous_dnrp
-        )
+        transition_score = dnrp_transition_kernel.logpdf(dnrp_value, previous_dnrp)
         likelihood_score = obs_depth_kernel.logpdf(
-            observed_depth, latent_depth, visibility_prob, dnrp_value, depth_scale
+            observed_depth=observed_depth,
+            latent_depth=latent_depth,
+            depth_scale=depth_scale,
+            visibility_prob=visibility_prob,
+            depth_nonreturn_prob=dnrp_value,
         )
         return transition_score + likelihood_score
 
-    support = hyperparams["depth_nonreturn_prob_kernel"].support
+    support = dnrp_transition_kernel.support
     log_pscores = jax.vmap(score_dnrp_value)(support)
-    log_normalized_scores = log_pscores - jax.scipy.special.logsumexp(log_pscores)
+    log_normalized_scores = normalize_log_scores(log_pscores)
     index = jax.random.categorical(key, log_normalized_scores)
     # ^ since we are enumerating over every value in the domain, it is unnecessary
     # to add a 1/q score when resampling.  (Equivalently, we could include
     # q = 1/len(support), which does not change the resampling distribuiton at all.)
 
-    return support[index], log_normalized_scores[index]
+    if return_metadata:
+        metadata = {
+            "support": support,
+            "log_normalized_scores": log_normalized_scores,
+            "index": index,
+            "observed_depth": observed_depth,
+            "latent_depth": latent_depth,
+            "prev_dnrp": previous_dnrp,
+            "transition_score": jax.vmap(
+                lambda dnrp_value: dnrp_transition_kernel.logpdf(
+                    dnrp_value, previous_dnrp
+                )
+            )(support),
+            "likelihood_score": jax.vmap(
+                lambda dnrp_value: obs_depth_kernel.logpdf(
+                    observed_depth,
+                    latent_depth,
+                    visibility_prob,
+                    dnrp_value,
+                    depth_scale,
+                )
+            )(support),
+        }
+    else:
+        metadata = {}
+
+    return support[index], log_normalized_scores[index], metadata
 
 
 def propose_vertex_color_and_visibility_prob(
@@ -174,6 +237,7 @@ def propose_vertex_color_and_visibility_prob(
     previous_state,
     new_state,
     hyperparams,
+    inference_hyperparams,
 ):
     """
     Propose a new color and visibility probability for the single vertex
@@ -199,12 +263,12 @@ def score_visprob_rgb(visprob, rgb):
             hyperparams["image_kernel"]
             .get_rgbd_vertex_kernel()
             .logpdf(
-                observed_rgbd_for_this_vertex,
-                jnp.append(rgb, latent_depth),
-                new_state["color_scale"],
-                new_state["depth_scale"],
-                visprob,
-                new_state["depth_nonreturn_prob"][vertex_index],
+                observed_rgbd=observed_rgbd_for_this_vertex,
+                latent_rgbd=jnp.append(rgb, latent_depth),
+                rgb_scale=new_state["color_scale"],
+                depth_scale=new_state["depth_scale"],
+                visibility_prob=visprob,
+                depth_nonreturn_prob=new_state["depth_nonreturn_prob"][vertex_index],
             )
         )
         return rgb_transition_score + visprob_transition_score + likelihood_score
@@ -231,7 +295,7 @@ def score_visprob_rgb(visprob, rgb):
     # we are enumerating over every value in the domain.  (Equivalently,
     # we could subtract a log q score of log(1/len(support)) for each value.)
     log_weights = log_pscores - log_qs_rgb
-    log_normalized_scores = log_weights - jax.scipy.special.logsumexp(log_weights)
+    log_normalized_scores = normalize_log_scores(log_weights)
     index = jax.random.categorical(k2, log_normalized_scores)
 
     rgb = rgbs[index]
@@ -288,21 +352,21 @@ def propose_vertex_color_given_visibility(
     (k1, k2, k3) = split(key, 3)
 
     ## Proposal 1: near the previous value.
-    min_rgbs1 = previous_rgb - diffs / 10 - 2 * d
-    max_rgbs1 = previous_rgb + diffs / 10 + 2 * d
+    min_rgbs1 = jnp.maximum(0.0, previous_rgb - diffs / 10 - 2 * d)
+    max_rgbs1 = jnp.minimum(1.0, previous_rgb + diffs / 10 + 2 * d)
     proposed_rgb_1 = uniform.sample(k1, min_rgbs1, max_rgbs1)
     log_q_rgb_1 = uniform.logpdf(proposed_rgb_1, min_rgbs1, max_rgbs1)
 
     ## Proposal 2: near the observed value.
-    min_rgbs2 = observed_rgb - diffs / 10 - 2 * d
-    max_rgbs2 = observed_rgb + diffs / 10 + 2 * d
+    min_rgbs2 = jnp.maximum(0.0, observed_rgb - diffs / 10 - 2 * d)
+    max_rgbs2 = jnp.minimum(1.0, observed_rgb + diffs / 10 + 2 * d)
     proposed_rgb_2 = uniform.sample(k2, min_rgbs2, max_rgbs2)
     log_q_rgb_2 = uniform.logpdf(proposed_rgb_2, min_rgbs2, max_rgbs2)
 
     ## Proposal 3: somewhere in the middle
     mean_rgb = (previous_rgb + observed_rgb) / 2
-    min_rgbs3 = mean_rgb - 8 / 10 * diffs - 2 * d
-    max_rgbs3 = mean_rgb + 8 / 10 * diffs + 2 * d
+    min_rgbs3 = jnp.maximum(0.0, mean_rgb - 8 / 10 * diffs - 2 * d)
+    max_rgbs3 = jnp.minimum(1.0, mean_rgb + 8 / 10 * diffs + 2 * d)
     proposed_rgb_3 = uniform.sample(k3, min_rgbs3, max_rgbs3)
     log_q_rgb_3 = uniform.logpdf(proposed_rgb_3, min_rgbs3, max_rgbs3)
 
@@ -315,13 +379,16 @@ def propose_vertex_color_given_visibility(
         jax.vmap(lambda rgb: score_visprob_and_rgb(visprob, rgb))(proposed_rgbs)
         - log_qs
     )
-    normalized_scores = scores - jax.scipy.special.logsumexp(scores)
+    normalized_scores = normalize_log_scores(scores)
     sampled_index = jax.random.categorical(key, normalized_scores)
     sampled_rgb = proposed_rgbs[sampled_index]
     log_K_score = log_qs.sum() + normalized_scores[sampled_index]
 
-    ## "L proposal": given the sampled rgb, estimate the probability that
-    # it came from the one of the 3 proposals that actually was used.
+    ## "L proposal": given the sampled rgb, the L proposal proposes
+    # an index for which of the 3 proposals may have produced this sample RGB,
+    # and also proposes the other two RGB values.
+    # Here, we need to compute the logpdf of this L proposal having produced
+    # the values we sampled out of the K proposal.
     log_qs_for_this_rgb = jnp.array(
         [
             uniform.logpdf(sampled_rgb, min_rgbs1, max_rgbs1),
@@ -329,18 +396,19 @@ def propose_vertex_color_given_visibility(
             uniform.logpdf(sampled_rgb, min_rgbs3, max_rgbs3),
         ]
     )
-    normalized_L_logprobs = log_qs_for_this_rgb - jax.scipy.special.logsumexp(
-        log_qs_for_this_rgb
-    )
+    normalized_L_logprobs = normalize_log_scores(log_qs_for_this_rgb)
 
     # L score for proposing the index
-    log_L_score = normalized_L_logprobs[sampled_index]
+    log_L_score_for_index = normalized_L_logprobs[sampled_index]
 
     # Also add in the L score for proposing the other two RGB values.
     # The L proposal over these values will just generate them from their prior.
-    log_L_score += jnp.sum(log_qs) - log_qs[sampled_index]
+    log_L_score_for_unused_values = jnp.sum(log_qs) - log_qs[sampled_index]
+
+    # full L score
+    log_L_score = log_L_score_for_index + log_L_score_for_unused_values
 
-    ## Compute the overall score.
+    ## Compute the overall estimate of the marginal density of proposing `sampled_rgb`.
     overall_score = log_K_score - log_L_score
 
     ## Return
@@ -385,8 +453,38 @@ def update_fields(key, trace, fieldnames, values):
     trace, _, _, _ = trace.update(
         key,
         U.g(
-            (Diff.no_change(hyperparams), Diff.unknown_change(previous_state)),
+            (Diff.no_change(hyperparams), Diff.no_change(previous_state)),
             C.kw(**dict(zip(fieldnames, values))),
         ),
     )
     return trace
+
+
+def update_vmapped_fields(key, trace, fieldnames, values):
+    """
+    For each `fieldname` in fieldnames, and each array `arr` in the
+    corresponding slot in `values`, updates `trace` at addresses
+    (0, fieldname) through (len(arr) - 1, fieldname) to the corresponding
+    values in `arr`.
+    (That is, this assumes for each fieldname, there is a vmap combinator
+    sampled at that address in the trace.)
+    """
+    c = C.n()
+    for addr, val in zip(fieldnames, values):
+        c = c ^ jax.vmap(lambda idx: C[addr, idx].set(val[idx]))(
+            jnp.arange(val.shape[0])
+        )
+
+    hyperparams, previous_state = trace.get_args()
+    trace, _, _, _ = trace.update(
+        key,
+        U.g((Diff.no_change(hyperparams), Diff.no_change(previous_state)), c),
+    )
+    return trace
+
+
+def update_vmapped_field(key, trace, fieldname, value):
+    """
+    For information, see `update_vmapped_fields`.
+    """
+    return update_vmapped_fields(key, trace, [fieldname], [value])
diff --git a/src/b3d/chisight/gen3d/projection.py b/src/b3d/chisight/gen3d/projection.py
index 09e00947..e2b011c9 100644
--- a/src/b3d/chisight/gen3d/projection.py
+++ b/src/b3d/chisight/gen3d/projection.py
@@ -56,6 +56,7 @@ def from_points_and_intrinsics(
                 intrinsics["cx"],
                 intrinsics["cy"],
             )
+            - 0.5
         )
         # handle NaN before converting to int (otherwise NaN will be converted
         # to 0)
diff --git a/tests/gen3d/inference/test_depth_nonreturn_prob_inference.py b/tests/gen3d/inference/test_depth_nonreturn_prob_inference.py
new file mode 100644
index 00000000..4af3e1db
--- /dev/null
+++ b/tests/gen3d/inference/test_depth_nonreturn_prob_inference.py
@@ -0,0 +1,32 @@
+import b3d.chisight.gen3d.inference_moves as im
+import b3d.chisight.gen3d.transition_kernels as transition_kernels
+import jax
+import jax.numpy as jnp
+import jax.random as r
+from b3d.chisight.gen3d.pixel_kernels.pixel_depth_kernels import (
+    FullPixelDepthDistribution,
+)
+
+near, far = 0.001, 1.0
+
+dnrp_transition_kernel = transition_kernels.DiscreteFlipKernel(
+    resample_probability=0.05, support=jnp.array([0.01, 0.99])
+)
+
+
+def propose_val(k):
+    return im._propose_vertex_depth_nonreturn_prob(
+        k,
+        observed_depth=0.8,
+        latent_depth=1.0,
+        visibility_prob=1.0,
+        depth_scale=0.00001,
+        previous_dnrp=0.01,
+        dnrp_transition_kernel=dnrp_transition_kernel,
+        obs_depth_kernel=FullPixelDepthDistribution(near, far),
+    )
+
+
+values, log_qs, _ = jax.vmap(propose_val)(r.split(r.PRNGKey(0), 1000))
+n_01 = jnp.sum((values == 0.01).astype(jnp.int32))
+assert n_01 >= 950