sshmm.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import time\n",
    "\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns; sns.set(palette=\"bright\")\n",
    "import tqdm\n",
    "\n",
    "import jax.numpy as np\n",
    "from jax import jit, lax, random\n",
    "from jax.config import config; config.update(\"jax_platform_name\", \"cpu\")\n",
    "from jax.scipy.special import logsumexp\n",
    "\n",
    "import numpyro.distributions as dist\n",
    "from numpyro.handlers import sample\n",
    "from numpyro.hmc_util import initialize_model\n",
    "from numpyro.mcmc import hmc\n",
    "from numpyro.util import fori_collect"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def simulate_data(rng, num_categories, num_words, num_supervised_data, num_unsupervised_data):\n",
    "    rng, rng_transition, rng_emission = random.split(rng, 3)\n",
    "\n",
    "    transition_prior = np.ones(num_categories)\n",
    "    emission_prior = np.repeat(0.1, num_words)\n",
    "\n",
    "    transition_prob = dist.Dirichlet(transition_prior).sample(key=rng_transition,\n",
    "                                                              size=(num_categories,))\n",
    "    emission_prob = dist.Dirichlet(emission_prior).sample(key=rng_emission, size=(num_categories,))\n",
    "\n",
    "    start_prob = np.repeat(1. / num_categories, num_categories)\n",
    "    categories, words = [], []\n",
    "    for t in range(num_supervised_data + num_unsupervised_data):\n",
    "        rng, rng_transition, rng_emission = random.split(rng, 3)\n",
    "        if t == 0 or t == num_supervised_data:\n",
    "            category = dist.Categorical(start_prob).sample(key=rng_transition)\n",
    "        else:\n",
    "            category = dist.Categorical(transition_prob[category]).sample(key=rng_transition)\n",
    "        word = dist.Categorical(emission_prob[category]).sample(key=rng_emission)\n",
    "        categories.append(category)\n",
    "        words.append(word)\n",
    "\n",
    "    # split into supervised data and unsupervised data\n",
    "    categories, words = np.stack(categories), np.stack(words)\n",
    "    supervised_categories = categories[:num_supervised_data]\n",
    "    supervised_words = words[:num_supervised_data]\n",
    "    unsupervised_words = words[num_supervised_data:]\n",
    "    return (transition_prior, emission_prior, transition_prob, emission_prob,\n",
    "            supervised_categories, supervised_words, unsupervised_words)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "(transition_prior, emission_prior,\n",
    " transition_prob, emission_prob,\n",
    " supervised_categories,\n",
    " supervised_words,\n",
    " unsupervised_words) = simulate_data(random.PRNGKey(1),\n",
    "                                     num_categories=3,\n",
    "                                     num_words=10,\n",
    "                                     num_supervised_data=100,\n",
    "                                     num_unsupervised_data=500)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### NumPyro"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def forward_one_step(prev_log_prob, curr_word, transition_log_prob, emission_log_prob):\n",
    "    log_prob_tmp = np.expand_dims(prev_log_prob, axis=1) + transition_log_prob\n",
    "    log_prob = log_prob_tmp + emission_log_prob[:, curr_word]\n",
    "    return logsumexp(log_prob, axis=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "naive implementaion\n",
    "\n",
    "```python\n",
    "def forward_log_prob(init_log_prob, words, transition_lob_prob, emission_log_prob):\n",
    "    log_prob = init_log_prob\n",
    "    for word in words:\n",
    "        log_prob = forward_one_step(log_prob, word, transition_log_prob, emission_log_prob)\n",
    "    return log_prob\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def forward_log_prob(init_log_prob, words, transition_lob_prob, emission_log_prob):\n",
    "    def scan_fn(log_prob, word):\n",
    "        return forward_one_step(log_prob, word, transition_lob_prob, emission_log_prob), np.ones(())\n",
    "\n",
    "    log_prob, _ = lax.scan(scan_fn, init_log_prob, words)\n",
    "    return log_prob"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def semi_supervised_hmm(supervised_categories, supervised_words, unsupervised_words):\n",
    "    num_categories, num_words = transition_prior.shape[0], emission_prior.shape[0]\n",
    "    transition_prob = sample(\"transition_prob\", dist.Dirichlet(\n",
    "        np.broadcast_to(transition_prior, (num_categories, num_categories))))\n",
    "    emission_prob = sample(\"emission_prob\", dist.Dirichlet(\n",
    "        np.broadcast_to(emission_prior, (num_categories, num_words))))\n",
    "\n",
    "    sample(\"supervised_categories\", dist.Categorical(transition_prob[supervised_categories[:-1]]),\n",
    "           obs=supervised_categories[1:])\n",
    "    sample(\"supervised_words\", dist.Categorical(emission_prob[supervised_categories]),\n",
    "           obs=supervised_words)\n",
    "\n",
    "    transition_log_prob = np.log(transition_prob)\n",
    "    emission_log_prob = np.log(emission_prob)\n",
    "    init_log_prob = emission_log_prob[:, unsupervised_words[0]]\n",
    "    log_prob = forward_log_prob(init_log_prob, unsupervised_words[1:],\n",
    "                                transition_log_prob, emission_log_prob)\n",
    "    log_prob = logsumexp(log_prob, axis=0, keepdims=True)\n",
    "    # inject log_prob to potential function\n",
    "    return sample('forward_log_prob', dist.Multinomial(logits=-log_prob), obs=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "init_params, potential_fn, transform_fn = initialize_model(\n",
    "    random.PRNGKey(2), semi_supervised_hmm,\n",
    "    supervised_categories, supervised_words, unsupervised_words)\n",
    "init_kernel, sample_kernel = hmc(potential_fn, algo=\"NUTS\")\n",
    "\n",
    "hmc_state, wa_state, warmup_update = init_kernel(init_params, num_warmup_steps=500,\n",
    "                                                 run_warmup=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "time to compile sample_kernel and wa_update: 20.731277227401733\n"
     ]
    }
   ],
   "source": [
    "start = time.time()\n",
    "warmup_update(0, (hmc_state.update(step_size=10.), wa_state))\n",
    "print(\"time to compile sample_kernel and wa_update:\", time.time() - start)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 500/500 [00:07<00:00, 63.49it/s] \n"
     ]
    }
   ],
   "source": [
    "for t in tqdm.trange(500):\n",
    "    hmc_state, wa_state = warmup_update(t, (hmc_state, wa_state))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 1000/1000 [00:18<00:00, 52.99it/s]\n"
     ]
    }
   ],
   "source": [
    "hmc_states = fori_collect(1000, sample_kernel, hmc_state,\n",
    "                          transform=lambda state: {\n",
    "                              \"transition_prob\": transform_fn(state.z)[\"transition_prob\"],\n",
    "                              \"num_steps\": state.num_steps,\n",
    "                          })"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 127  127  127  127  255  127  127  127  127  127  127  127  127   88\n",
      "   41  127  127   55    4    3   17   31    4    5   19    8   20  263\n",
      "  127  248   63  127  127  127  127  255  127  127  319  335  127  255\n",
      "  528  191   51  610   63   63   63  127   63  194  127  127  127  127\n",
      "  127   63  127  383  127  127  560  255   63  383  127  127  127  511\n",
      "   63  127  127  127   63  127  127  127  337   63  127  123  127  127\n",
      "  332  127  127  127  127  127   74  127  255   63  127  127  127   63\n",
      "  127  127  351  127  403  127   63  127  127  127  127  127  127  127\n",
      "  127  127  127  127  127  127  220   93  118  123   63  127  127   63\n",
      "  127  127  255  127  127  127  127  255   63  127  127  255  753  127\n",
      "  127  127  255   63  127  391  110  127  127   63  895   63  511  127\n",
      " 1023  127   63  127  127  511  127   63  191  255  127  127  127  127\n",
      "  127  127  127  127  127  255  255  127   63 1023  127  127  127  127\n",
      "   63  233  255   63  127  127   63  127  127  127  127  127  255   63\n",
      "  127   63   63   85  127  127   63  127   63   63  127  127   63  127\n",
      " 1023 1023  127  639   63  127  127   63  127  191  127   63  127  127\n",
      "  191   63  127  127  127  255  127  127  127  127  127  127  127  341\n",
      "  127  127  127  127  255  127  255  127  127  127  255  127  127  127\n",
      "  127   63  127   63  127  639  127  127  127  127  127  127   97   64\n",
      "   38   45   63   43   30   52   99  429  127  127  127  127  831  127\n",
      "  767  127  127  127   63  127  127  127  127  255  127  767  127  383\n",
      "  127  127  127   63  484  127  127  127  127  127  127 1023   63  284\n",
      "  127  127  255  127  127  127  127  255  639 1023  127  127  127  127\n",
      "   63   63  255  255  127  383  736  127 1023   63  127  255  127  127\n",
      "  127  127  127  127  511  255  127  895  127 1023 1023  127  255  255\n",
      "  127  127  255  127  127  127  127  255   63   63  127  127 1023  127\n",
      "  127   63   63  127 1023  127  127  127  127   63  127  255  383   63\n",
      "  191  127  127  127  207   63  127  127  123   63  191  127   63  127\n",
      "  639  127   63  127  127   84  239  127  255  127  127  511  127  255\n",
      "  127  127   63  127  127  127  127  127  127  319  127   63  255  127\n",
      "  127  127  383  127  127  127  127  127  127   63  805  682  639  255\n",
      "  127  127  127  127  104  464  127  127   63  127  255  127  127   63\n",
      "  127 1023  127  127  127  127  127   63  383   63   63  127  127  127\n",
      "  255  127  127  447  127  191  191  127   63  383  511  394  255  127\n",
      "  127  127  426  127  127  127  127   63  127  255  127  127  127  127\n",
      "  383  119  127  127  127  127  127  255  127  127   63  127  127  127\n",
      "  127  127   97   64  127  263  127  127  144  127  127  127  127  127\n",
      "  127  127  127  127  127  255  127  255  127  127  127  127  127  383\n",
      "   37   53  127  191  573  127  127  127  127  247  127  127   63  127\n",
      "  127  127  585  127  127  127  312  127  383   63  127  127  255  127\n",
      "  127   63  127  127  127   63  127  127  127  127  511  127  383  127\n",
      "  127  127   63  127  127  383  127   63   63  127  127  127  138  219\n",
      "  250  698  127  127  127  127   63  255   63  127  127 1023  127  127\n",
      "  127  127   63  168  127  127  127  127  127  127  127  127   63  127\n",
      "  127  127  127  639  255  127  127   63  127  591  383  127 1023  127\n",
      "   86  255  127  127  127  127  127  127  127  127   63  575  127  127\n",
      "  127  127   63  127  127   63   63  127  255  639  127  241  127  127\n",
      "  127  127  255  127  127  255 1023  127  127  127  383  127  127  127\n",
      "  127  319  831  127  127  127  127  127  127  191 1023   63  127   63\n",
      "  127  511  127  102  127  132  639   63  383   63   63  127   63  127\n",
      "  127  127  127  127  127  127   63  127  127  127  383  127  127   63\n",
      "  127  212  127  127  127  127 1023  127  127  127  255  127  255  255\n",
      "  127  127  127  127  127  127  127  127 1023  127  255  403  127  127\n",
      "  127  127   63  127  127   63  127  127  831  127  127  127  127  127\n",
      "  127   63  127  127  255  739  127  127  319  255  127  127  127  127\n",
      "   63  127  127  127  127   15  255  127  191  127  127   75  127   63\n",
      "  127  127  127  127  127  255  127  127  191  275   63  127  127  127\n",
      "  127  127   63  105  127 1023   63  127  255  127  127  255 1023 1023\n",
      "  901  127  255  127  127  127   63  127  507  127  255  127  127  127\n",
      "  127  127  127  255  127 1023  127  127  127  127   63  639  127  127\n",
      "   63  255  255  127  127  127   63   63  255  127   63  255  127  255\n",
      "  127  127  127  127  127  431  511  127  895  191  127  127  895  127\n",
      "  127  127  127  383  127  127  127   63  127  383  226  127   63   70\n",
      "  127  127  127  127  255  127  127  127  127  127  255   63   63  127\n",
      "  127  127  127  127  127  127  127  127  255 1023  127  383  127  127\n",
      "   63  162  446   63  127  255  127  319  127  127  127  127  127  127\n",
      "  127  767  127 1023   63  127 1023  127 1023 1023 1023  255  127  767\n",
      "  127 1023  127  959  127  127   96  127  127  511  127  639  127  191\n",
      "  255  127  127  127  255  255  127  356  127   63  127  127  127  127\n",
      "  127  127  255  127  127  127  127  127  127   63  127  127  127  127\n",
      "   45   81   65   78  127   63   63  127  191  112  592    7  127  127\n",
      "  127  360  127  255  127 1023]\n"
     ]
    }
   ],
   "source": [
    "print(hmc_states[\"num_steps\"].copy())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Stan"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pystan\n",
    "\n",
    "# Source: https://github.com/stan-dev/example-models/blob/master/misc/hmm/hmm-semisup.stan\n",
    "stan_model = \"\"\"\n",
    "data {\n",
    "  int<lower=1> K;  // num categories\n",
    "  int<lower=1> V;  // num words\n",
    "  int<lower=0> T;  // num supervised items\n",
    "  int<lower=1> T_unsup;  // num unsupervised items\n",
    "  int<lower=1,upper=V> w[T];  // words\n",
    "  int<lower=1,upper=K> z[T];  // categories\n",
    "  int<lower=1,upper=V> u[T_unsup];  // unsup words\n",
    "  vector<lower=0>[K] alpha;   // transit prior\n",
    "  vector<lower=0>[V] beta;    // emit prior\n",
    "}\n",
    "parameters {\n",
    "  simplex[K] theta[K];  // transit probs\n",
    "  simplex[V] phi[K];    // emit probs\n",
    "}\n",
    "model {\n",
    "  for (k in 1:K) \n",
    "    theta[k] ~ dirichlet(alpha);\n",
    "  for (k in 1:K)\n",
    "    phi[k] ~ dirichlet(beta);\n",
    "  for (t in 1:T)\n",
    "    w[t] ~ categorical(phi[z[t]]);\n",
    "  for (t in 2:T)\n",
    "    z[t] ~ categorical(theta[z[t - 1]]);\n",
    "\n",
    "  { \n",
    "    real acc[K];\n",
    "    real gamma[T_unsup, K];\n",
    "    for (k in 1:K)\n",
    "      gamma[1, k] <- log(phi[k, u[1]]);\n",
    "    for (t in 2:T_unsup) {\n",
    "      for (k in 1:K) {\n",
    "        for (j in 1:K)\n",
    "          acc[j] <- gamma[t-1, j] + log(theta[j, k]) + log(phi[k, u[t]]);\n",
    "        gamma[t, k] <- log_sum_exp(acc);\n",
    "      }\n",
    "    }\n",
    "    target += log_sum_exp(gamma[T_unsup]);\n",
    "  }\n",
    "}\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:pystan:COMPILING THE C++ CODE FOR MODEL anon_model_e47c60e83cb8bf11dec4a8d2f9961cba NOW.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 1.05 s, sys: 68.1 ms, total: 1.12 s\n",
      "Wall time: 50.3 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "model = pystan.StanModel(model_code=stan_model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:pystan:82 of 1000 iterations ended with a divergence (8.2 %).\n",
      "WARNING:pystan:Try running with adapt_delta larger than 0.8 to remove the divergences.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 1min 19s, sys: 148 ms, total: 1min 19s\n",
      "Wall time: 1min 19s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "data = {\"K\": transition_prior.shape[0], \"V\": emission_prior.shape[0],\n",
    "        \"T\": supervised_words.shape[0], \"T_unsup\": unsupervised_words.shape[0],\n",
    "        \"alpha\": transition_prior, \"beta\": emission_prior,\n",
    "        \"w\": supervised_words + 1, \"z\": supervised_categories + 1, \"u\": unsupervised_words + 1}\n",
    "fit = model.sampling(data, chains=1, iter=1500, warmup=500)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([127.,  63., 127., 191., 127.,  63.,  63., 127.,  63.,  63., 127.,\n",
       "        63.,  63., 127.,  63.,  63.,  63., 127.,  63.,  63.,  63., 127.,\n",
       "       127., 127.,  63.,  63., 127.,  63., 127., 127.,  63., 127.,  63.,\n",
       "        63.,  63., 127., 127., 127.,  63., 127.,  63.,  87.,  63., 127.,\n",
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       "        63.,  63.,  63., 127.,  63.,  63., 127.,  63., 127.,  63., 127.,\n",
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       "       127.,  63.,  63., 127.,  63., 127., 127.,  63.,  63.,  63.,  63.,\n",
       "       127.,  63.,  63., 127.,  63.,  63.,  63.,  63.,  63.,  63.,  63.,\n",
       "        63., 127., 127.,  63., 127.,  63.,  63., 127.,  63.,  63.,  87.,\n",
       "        63., 127., 127.,  63., 127., 127.,  63.,  63.,  86.,  63., 127.,\n",
       "       127., 127., 127., 127.,  63.,  63., 127.,  19.,  63.,  63.,  63.,\n",
       "        63.,  63., 127.,  63., 127., 127., 127., 127., 127.,  63., 127.,\n",
       "       127., 127., 127.,  63.,  63.,  63.,  63., 127.,  63., 127., 127.,\n",
       "        16.,   2.,  10.,   1.,   1.,  26.,   7.,  25.,   8.,  63., 127.,\n",
       "        63.,  24.,  63., 127.,  63., 127., 127., 127.,  63.,  63.,  63.,\n",
       "       127.,  63.,  63., 127.,  63.,  63.,  63.,  63., 127.,  63.,  63.,\n",
       "        31., 127., 127.,  63., 127.,  63.,  63., 127.,  63., 127., 127.,\n",
       "       127., 127.,  63.,  92.,  63.,  63.,  63., 127.,  63., 127.,  63.,\n",
       "        28.,  63., 127., 127.,  63., 127.,  63.,  63.,  63.,  63., 127.,\n",
       "        63.,  63.,  63.,  44.,  61.,  63.,  63., 127.,  63.,  63.,  63.,\n",
       "       127.,  63.,  58.,  63.,  63.,  63., 127., 127., 127., 127., 127.,\n",
       "        63.,  63.,  47.,  63.,  63., 127., 127.,  63.,  63.,  63., 127.,\n",
       "       127.,  63.,  63., 127., 127., 127., 127.,  63., 127.,  63., 127.,\n",
       "       127.,  63.,  63.,  63.,  63.,  63., 127., 127.,  63., 127.,  63.,\n",
       "       127., 127., 127.,  63., 127., 255., 127., 127.,  63.,  63., 127.,\n",
       "        63., 127.,  63.,  63., 127., 127., 127., 127., 127., 127.,  63.,\n",
       "       127., 127., 127., 127., 127.,  95., 127., 127., 127., 127., 127.,\n",
       "        63., 127.,  63., 127.,  63.,  63., 127., 127., 127.,  63.,  63.,\n",
       "        63.,  63., 127., 127., 127.,  63.,  63.,  63., 127., 127.,  63.,\n",
       "        63.,  63., 127.,  63., 127., 127., 127., 127., 127.,  63.,  63.,\n",
       "        63., 127., 127., 127., 127.,  63.,  63.,  63.,  63., 191., 127.,\n",
       "       127.,  63.,  63.,  63.,  63., 127.,  63.,  63.,  77.,  63., 127.,\n",
       "        63., 191., 127., 127., 191.,  63., 127., 127., 127.,  63.,  63.,\n",
       "       127.,  17., 127., 127.,  13.,  63.,  31., 127.,  63., 127.,  63.,\n",
       "        63.,  63., 127.,  63., 127.,  63.,  63., 127., 127.,  63., 127.,\n",
       "        63., 127.,  52., 127., 127.,  63.,  63.,  63., 127.,  63.,  63.,\n",
       "       127.,  63.,  63.,  63., 127.,  63., 127., 127.,  63., 127., 127.,\n",
       "        63.,  63., 127., 127., 191.,  63.,  63., 127., 127.,  63., 127.,\n",
       "        63., 127., 127.,  63.,  63.,  63., 127.,  63.,   6.,  14.,   3.,\n",
       "       127.,  63.,  51.,  30., 127.,  63., 127., 127., 127., 127., 127.,\n",
       "        63.,  63.,  63.,  63.,  63., 127.,  63.,  63.,  63., 127.,  63.,\n",
       "        63.,  63.,  63.,  44.,  63., 127., 127.,  63., 127., 127.,  63.,\n",
       "       127., 127.,  63.,  63.,  63.,  63., 127., 127., 127., 127.,  63.,\n",
       "       127., 127., 127., 127.,  63.,  63.,  63., 127., 127., 127., 191.,\n",
       "        63.,  63.,  63.,  63.,  63.,  63., 127.,  63.,  63.,  63., 127.,\n",
       "        63., 127.,  63.,  63., 127.,  63.,  63., 127.,  63.,  63.,  63.,\n",
       "       127., 127.,  63.,  63.,  63.,  63., 127.,  63.,  63.,  63.,  63.,\n",
       "        63., 127.,  63., 127.,  39.,  37., 127., 127.,  63.,  63.,  63.,\n",
       "        63.,  63., 127., 127., 127., 127.,  63., 127., 127., 127., 127.,\n",
       "        63., 127.,  63.,  90.,  63., 127., 127., 127., 127., 127.,  56.,\n",
       "        63.,  43.,  29.,  26., 127.,  63.,  63.,  63.,  63., 127.,  63.,\n",
       "        63.,  53.,  47., 127., 127., 127., 127.,   9.,   3.,   8., 127.,\n",
       "       127.,  63.,  63., 127.,  63., 127.,  63.,  54., 127.,  63.,  63.,\n",
       "        63.,  63.,  63., 127., 127.,  63.,  63., 127., 127., 127., 127.,\n",
       "        63.,  63.,  63.,  63.,  63., 127.,  63., 127., 127.,  63., 127.,\n",
       "        63., 127., 127.,  61.,  63.,  63.,  63., 127.,  63., 127.,  63.,\n",
       "        63., 127.,  63., 127., 127.,  63., 127.,  63.,  63.,  63., 127.,\n",
       "       127., 127.,  63., 127., 127.,  63.,  63.,  63.,  63.,  63., 127.,\n",
       "       127.,  24., 127.,  63., 127.,  63.,  63.,  41.,  44., 105.,  63.,\n",
       "        63.,  48.,  70.,  63.,  63., 127., 127.,  63., 127.,  63., 127.,\n",
       "       127., 127., 127.,  63., 127., 127.,  63.,  63., 127., 127., 127.,\n",
       "       127.,  63.,  63., 127., 127.,  63., 127., 127.,  60.,  63.,  63.,\n",
       "       127., 127.,  63.,  63.,  63.,  63., 127.,  58., 127.,  63.,  63.,\n",
       "       127.,  63., 127.,  63., 127.,  63.,  63.,  63.,  63., 127.,  63.,\n",
       "        63.,  63., 127.,  63.,  63.,  63., 127.,  63., 127.,  34.,  16.,\n",
       "        28.,  63.,  63., 127., 127., 127., 127., 127., 127.,  63., 127.,\n",
       "        63.,  63.,  63.,  63.,  63., 127.,  15.,   1.,   9.,  18.,  14.,\n",
       "        38., 127., 127., 127.,  15., 127., 127., 127.,  63., 127.,  63.,\n",
       "        63., 127.,  63., 127., 127., 127., 127., 127., 127.,  63.,  63.,\n",
       "       127.,  63., 127., 127.,  63.,  10., 127., 127.,  63.,  63.,  63.,\n",
       "        63., 127.,  63.,  63.,  63., 127., 127., 127.,  63., 127., 127.,\n",
       "        63., 127.,  63.,  63.,  63., 127., 127.,  63.,  63.,  63.,  63.,\n",
       "       127., 127., 127., 127., 127.,  63.,  63., 127.,  63.,  63.])"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fit.get_sampler_params()[0][\"n_leapfrog__\"][500:]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x864 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def plot(ax, transition_prob_posterior, title):\n",
    "    for i in range(transition_prob.shape[0]):\n",
    "        for j in range(transition_prob.shape[1]):\n",
    "            sns.distplot(transition_prob_posterior[:, i, j], hist=False, kde_kws={\"lw\": 2},\n",
    "                         label=\"transition_prob[{}, {}], true value = {:.2f}\"\n",
    "                         .format(i, j, transition_prob[i, j]), ax=ax)\n",
    "    ax.set(xlabel=\"Probability\", ylabel=\"Frequency\",\n",
    "           title=\"transition probability posterior ({})\".format(title))\n",
    "\n",
    "_, (ax1, ax2) = plt.subplots(2, figsize=(10, 12), sharex=True)\n",
    "plot(ax1, hmc_states[\"transition_prob\"], \"NumPyro\")\n",
    "plot(ax2, np.array(fit.extract(pars=\"theta\")[\"theta\"]), \"Stan\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DeviceArray(193.089, dtype=float32)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hmc_states[\"num_steps\"].sum() / 1000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "90.563"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fit.get_sampler_params()[0][\"n_leapfrog__\"][500:].sum() / 1000"
   ]
  }
 ],
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