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mixture_tfp.ipynb
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{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.3"
},
"colab": {
"name": "mixture_tfp.ipynb",
"provenance": [],
"collapsed_sections": [],
"include_colab_link": true
},
"accelerator": "GPU"
},
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"<a href=\"https://colab.research.google.com/gist/junpenglao/f2f9b641f1fa80da78e2dc0b380e59a3/mixture_tfp.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "3249BThsjL58",
"colab_type": "text"
},
"source": [
"TFP port of https://gist.github.com/dfm/5250dd2f17daf60cbe582ceeeb2fd12f"
]
},
{
"cell_type": "code",
"metadata": {
"id": "IVUf-En1zda6",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 100
},
"outputId": "fdd5b54f-9b63-4597-88ae-10c9009cfe69"
},
"source": [
"!pip3 install -q --upgrade tf-nightly-gpu tfp-nightly\n",
"!pip3 install -q --upgrade git+git://github.com/arviz-devs/arviz.git\n",
"!pip3 install -q --upgrade git+git://github.com/pymc-devs/pymc3.git"
],
"execution_count": 1,
"outputs": [
{
"output_type": "stream",
"text": [
" Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
" Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n",
" Preparing wheel metadata ... \u001b[?25l\u001b[?25hdone\n",
" Building wheel for arviz (PEP 517) ... \u001b[?25l\u001b[?25hdone\n",
" Building wheel for pymc3 (setup.py) ... \u001b[?25l\u001b[?25hdone\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "N77X1lEIjJuE",
"colab_type": "code",
"colab": {}
},
"source": [
"import numpy as np\n",
"import pandas as pd\n",
"\n",
"import arviz as az\n",
"\n",
"import matplotlib.pyplot as plt\n",
"\n",
"%matplotlib inline"
],
"execution_count": 2,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "bNMPlvp6jJuU",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 226
},
"outputId": "b4b215eb-4bdf-404f-8770-e7f3070dcbfa"
},
"source": [
"# cut & pasted directly from the fetch_hogg2010test() function\n",
"# identical to the original dataset as hardcoded in the Hogg 2010 paper\n",
"\n",
"dfhogg = pd.DataFrame(\n",
" np.array([[1, 201, 592, 61, 9, -0.84],\n",
" [2, 244, 401, 25, 4, 0.31],\n",
" [3, 47, 583, 38, 11, 0.64],\n",
" [4, 287, 402, 15, 7, -0.27],\n",
" [5, 203, 495, 21, 5, -0.33],\n",
" [6, 58, 173, 15, 9, 0.67],\n",
" [7, 210, 479, 27, 4, -0.02],\n",
" [8, 202, 504, 14, 4, -0.05],\n",
" [9, 198, 510, 30, 11, -0.84],\n",
" [10, 158, 416, 16, 7, -0.69],\n",
" [11, 165, 393, 14, 5, 0.30],\n",
" [12, 201, 442, 25, 5, -0.46],\n",
" [13, 157, 317, 52, 5, -0.03],\n",
" [14, 131, 311, 16, 6, 0.50],\n",
" [15, 166, 400, 34, 6, 0.73],\n",
" [16, 160, 337, 31, 5, -0.52],\n",
" [17, 186, 423, 42, 9, 0.90],\n",
" [18, 125, 334, 26, 8, 0.40],\n",
" [19, 218, 533, 16, 6, -0.78],\n",
" [20, 146, 344, 22, 5, -0.56]]),\n",
" columns=['id','x','y','sigma_y','sigma_x','rho_xy'])\n",
"\n",
"dfhogg['id'] = dfhogg['id'].apply(lambda x: 'p{}'.format(int(x)))\n",
"dfhogg.set_index('id', inplace=True)\n",
"dfhogg.head()"
],
"execution_count": 3,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>x</th>\n",
" <th>y</th>\n",
" <th>sigma_y</th>\n",
" <th>sigma_x</th>\n",
" <th>rho_xy</th>\n",
" </tr>\n",
" <tr>\n",
" <th>id</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>p1</th>\n",
" <td>201.0</td>\n",
" <td>592.0</td>\n",
" <td>61.0</td>\n",
" <td>9.0</td>\n",
" <td>-0.84</td>\n",
" </tr>\n",
" <tr>\n",
" <th>p2</th>\n",
" <td>244.0</td>\n",
" <td>401.0</td>\n",
" <td>25.0</td>\n",
" <td>4.0</td>\n",
" <td>0.31</td>\n",
" </tr>\n",
" <tr>\n",
" <th>p3</th>\n",
" <td>47.0</td>\n",
" <td>583.0</td>\n",
" <td>38.0</td>\n",
" <td>11.0</td>\n",
" <td>0.64</td>\n",
" </tr>\n",
" <tr>\n",
" <th>p4</th>\n",
" <td>287.0</td>\n",
" <td>402.0</td>\n",
" <td>15.0</td>\n",
" <td>7.0</td>\n",
" <td>-0.27</td>\n",
" </tr>\n",
" <tr>\n",
" <th>p5</th>\n",
" <td>203.0</td>\n",
" <td>495.0</td>\n",
" <td>21.0</td>\n",
" <td>5.0</td>\n",
" <td>-0.33</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" x y sigma_y sigma_x rho_xy\n",
"id \n",
"p1 201.0 592.0 61.0 9.0 -0.84\n",
"p2 244.0 401.0 25.0 4.0 0.31\n",
"p3 47.0 583.0 38.0 11.0 0.64\n",
"p4 287.0 402.0 15.0 7.0 -0.27\n",
"p5 203.0 495.0 21.0 5.0 -0.33"
]
},
"metadata": {
"tags": []
},
"execution_count": 3
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "w2KAAbYWjJuX",
"colab_type": "code",
"colab": {}
},
"source": [
"dfhoggs = ((dfhogg[['x', 'y']] - dfhogg[['x', 'y']].mean(0)) / \n",
" (2 * dfhogg[['x', 'y']].std(0)))\n",
"dfhoggs['sigma_x'] = dfhogg['sigma_x'] / ( 2 * dfhogg['x'].std())\n",
"dfhoggs['sigma_y'] = dfhogg['sigma_y'] / ( 2 * dfhogg['y'].std())"
],
"execution_count": 4,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "9DwgpbW-jJuO",
"colab_type": "text"
},
"source": [
"# PyMC3 version"
]
},
{
"cell_type": "code",
"metadata": {
"id": "EPL0w8DHjJuQ",
"colab_type": "code",
"colab": {}
},
"source": [
"import pymc3 as pm\n",
"import theano.tensor as tt"
],
"execution_count": 5,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "yfI6N7VRjJua",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 117
},
"outputId": "9ca67421-c666-46c6-eae3-ae09b3d68045"
},
"source": [
"with pm.Model() as better_hogg_:\n",
" tsv_x = pm.Data('tsv_x', dfhoggs['x'])\n",
" tsv_y = pm.Data('tsv_y', dfhoggs['y'])\n",
" tsv_sigma_y = pm.Data('tsv_sigma_y', dfhoggs['sigma_y'])\n",
" \n",
" b0 = pm.Normal('b0_intercept', mu=0, sigma=10, testval=pm.floatX(0.1))\n",
" b1 = pm.Normal('b1_slope', mu=0, sigma=10, testval=pm.floatX(1.))\n",
" y_est_in = b0 + b1 * tsv_x\n",
" y_est_out = pm.Normal('y_est_out', mu=0, sigma=10, testval=pm.floatX(1.))\n",
" sigma_y_out = pm.HalfNormal('sigma_y_out', sigma=1, testval=pm.floatX(1.))\n",
" \n",
" # Inlier/outlier likelihoods\n",
" inlier_logl = pm.Normal.dist(mu=y_est_in, \n",
" sigma=tsv_sigma_y).logp(tsv_y)\n",
"\n",
" outlier_logl = pm.Normal.dist(mu=y_est_out, \n",
" sigma=tsv_sigma_y + sigma_y_out).logp(tsv_y)\n",
" \n",
" # This fraction is really the *prior* probability of having an outlier\n",
" frac_outliers = pm.Uniform('frac_outliers', lower=0.0, upper=0.5)\n",
" \n",
" # Apply this prior to compute the joint prob\n",
" inlier_logp = tt.log(1 - frac_outliers) + inlier_logl\n",
" outlier_logp = tt.log(frac_outliers) + outlier_logl\n",
" \n",
" # Marginalize\n",
" logp_marg = pm.math.logaddexp(\n",
" inlier_logp,\n",
" outlier_logp\n",
" )\n",
" pm.Potential('obs', logp_marg)\n",
" \n",
" # Track the probability that each point is an outlier\n",
" pm.Deterministic(\"logp_outlier\", outlier_logp - logp_marg)\n",
"\n",
"better_hogg_.test_point, better_hogg_.logp(better_hogg_.test_point)"
],
"execution_count": 6,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"({'b0_intercept': array(0.1),\n",
" 'b1_slope': array(1.),\n",
" 'frac_outliers_interval__': array(0.),\n",
" 'sigma_y_out_log__': array(0.),\n",
" 'y_est_out': array(1.)},\n",
" array(-28.36282317))"
]
},
"metadata": {
"tags": []
},
"execution_count": 6
}
]
},
{
"cell_type": "code",
"metadata": {
"scrolled": true,
"id": "vcKI4QI2jJuf",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 117
},
"outputId": "3559237f-a14e-445c-b7e8-69abf810cc0e"
},
"source": [
"with pm.Model() as better_hogg:\n",
" tsv_x = pm.Data('tsv_x', dfhoggs['x'])\n",
" tsv_y = pm.Data('tsv_y', dfhoggs['y'])\n",
" tsv_sigma_y = pm.Data('tsv_sigma_y', dfhoggs['sigma_y'])\n",
" \n",
" b0 = pm.Normal('b0_intercept', mu=0, sigma=10, testval=pm.floatX(0.1))\n",
" b1 = pm.Normal('b1_slope', mu=0, sigma=10, testval=pm.floatX(1.))\n",
" y_est_in = b0 + b1 * tsv_x\n",
" y_est_out = pm.Normal('y_est_out', mu=0, sigma=10, testval=pm.floatX(1.))\n",
" sigma_y_out = pm.HalfNormal('sigma_y_out', sigma=1, testval=pm.floatX(1.))\n",
"\n",
" # Inlier/outlier likelihoods\n",
" inlier_logl = pm.Normal.dist(mu=y_est_in,\n",
" sigma=tsv_sigma_y)\n",
"\n",
" outlier_logl = pm.Normal.dist(mu=tt.repeat(y_est_out, 20),\n",
" sigma=tsv_sigma_y + sigma_y_out)\n",
"\n",
" # This fraction is really the *prior* probability of having an outlier\n",
" frac_outliers = pm.Uniform('frac_outliers', lower=0.0, upper=0.5)\n",
"\n",
" obs = pm.Mixture('obs',\n",
" w=[1.-frac_outliers, frac_outliers],\n",
" comp_dists=[inlier_logl, outlier_logl],\n",
" observed=tsv_y)\n",
"\n",
" # Track the probability that each point is an outlier\n",
" outlier_logp = tt.log(frac_outliers) + outlier_logl.logp(tsv_y)\n",
" pm.Deterministic(\"logp_outlier\", \n",
" outlier_logp - tt.squeeze(obs.logp_elemwiset))\n",
"\n",
"better_hogg.test_point, better_hogg.logp(better_hogg.test_point)"
],
"execution_count": 7,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"({'b0_intercept': array(0.1),\n",
" 'b1_slope': array(1.),\n",
" 'frac_outliers_interval__': array(0.),\n",
" 'sigma_y_out_log__': array(0.),\n",
" 'y_est_out': array(1.)},\n",
" array(-28.36282317))"
]
},
"metadata": {
"tags": []
},
"execution_count": 7
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "-KcZxxr-jJui",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 190
},
"outputId": "f0bc1778-9802-4528-cf06-ecc2654a2d07"
},
"source": [
"with better_hogg:\n",
" trc_better = pm.sample(tune=3000, draws=3000, target_accept=0.9)"
],
"execution_count": 8,
"outputs": [
{
"output_type": "stream",
"text": [
"Auto-assigning NUTS sampler...\n",
"Initializing NUTS using jitter+adapt_diag...\n",
"Sequential sampling (2 chains in 1 job)\n",
"NUTS: [frac_outliers, sigma_y_out, y_est_out, b1_slope, b0_intercept]\n"
],
"name": "stderr"
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" <div>\n",
" <style>\n",
" /* Turns off some styling */\n",
" progress {\n",
" /* gets rid of default border in Firefox and Opera. */\n",
" border: none;\n",
" /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
" background-size: auto;\n",
" }\n",
" .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
" background: #F44336;\n",
" }\n",
" </style>\n",
" <progress value='6000' class='' max='6000' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
" 100.00% [6000/6000 00:10<00:00 Sampling chain 0, 2 divergences]\n",
" </div>\n",
" "
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "display_data",
"data": {
"text/html": [
"\n",
" <div>\n",
" <style>\n",
" /* Turns off some styling */\n",
" progress {\n",
" /* gets rid of default border in Firefox and Opera. */\n",
" border: none;\n",
" /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
" background-size: auto;\n",
" }\n",
" .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
" background: #F44336;\n",
" }\n",
" </style>\n",
" <progress value='6000' class='' max='6000' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
" 100.00% [6000/6000 00:10<00:00 Sampling chain 1, 103 divergences]\n",
" </div>\n",
" "
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {
"tags": []
}
},
{
"output_type": "stream",
"text": [
"Sampling 2 chains for 3_000 tune and 3_000 draw iterations (6_000 + 6_000 draws total) took 21 seconds.\n",
"There were 2 divergences after tuning. Increase `target_accept` or reparameterize.\n",
"There were 105 divergences after tuning. Increase `target_accept` or reparameterize.\n",
"The acceptance probability does not match the target. It is 0.8020511832217723, but should be close to 0.9. Try to increase the number of tuning steps.\n"
],
"name": "stderr"
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "ZV_ZHIjmjJum",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 798
},
"outputId": "e5747a34-1114-4899-b2c5-28cbb17014dd"
},
"source": [
"rvs = ['b0_intercept', 'b1_slope', 'y_est_out', 'sigma_y_out', 'frac_outliers']\n",
"_ = az.plot_trace(trc_better, var_names=rvs, combined=False)"
],
"execution_count": 9,
"outputs": [
{
"output_type": "stream",
"text": [
"/usr/local/lib/python3.6/dist-packages/arviz/data/io_pymc3.py:89: FutureWarning: Using `from_pymc3` without the model will be deprecated in a future release. Not using the model will return less accurate and less useful results. Make sure you use the model argument or call from_pymc3 within a model context.\n",
" FutureWarning,\n"
],
"name": "stderr"
},
{
"output_type": "display_data",
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 864x720 with 10 Axes>"
]
},
"metadata": {
"tags": [],
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "L7yWgziIjJut",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 269
},
"outputId": "df50c70b-719d-4316-f2f3-0900a05a4b5a"
},
"source": [
"plt.errorbar(dfhoggs['x'], dfhoggs['y'], yerr=dfhoggs['sigma_y'], fmt=\",k\", zorder=-1)\n",
"\n",
"p_outlier = np.exp(np.median(trc_better[\"logp_outlier\"], axis=0))\n",
"\n",
"plt.scatter(dfhoggs['x'], dfhoggs['y'], c=p_outlier)\n",
"plt.colorbar(label=\"outlier probability\");"
],
"execution_count": 10,
"outputs": [
{
"output_type": "display_data",
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
"tags": [],
"needs_background": "light"
}
}
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "287oBaQyjJuw",
"colab_type": "text"
},
"source": [
"# TFP version"
]
},
{
"cell_type": "code",
"metadata": {
"id": "fxqkSuX2jJux",
"colab_type": "code",
"colab": {}
},
"source": [
"import tensorflow.compat.v2 as tf\n",
"import tensorflow_probability as tfp\n",
"\n",
"tfd = tfp.distributions\n",
"tfb = tfp.bijectors\n",
"\n",
"dtype = tf.float64"
],
"execution_count": 11,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "x1Pa18_EjJu0",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 117
},
"outputId": "6b1213d8-1099-43d6-bb13-804362268ec1"
},
"source": [
"def gen_mixturemodel(X, sigma, hyperprior_mean=0, hyperprior_scale=10):\n",
" hyper_mean = tf.cast(hyperprior_mean, dtype)\n",
" hyper_scale = tf.cast(hyperprior_scale, dtype)\n",
" return tfd.JointDistributionSequential([\n",
" tfd.Sample(tfd.Normal(loc=hyper_mean, scale=hyper_scale),\n",
" sample_shape=1),\n",
" tfd.Sample(tfd.Normal(loc=hyper_mean, scale=hyper_scale),\n",
" sample_shape=1),\n",
" tfd.Sample(tfd.Normal(loc=hyper_mean, scale=10.),\n",
" sample_shape=1),\n",
" tfd.Sample(tfd.HalfNormal(scale=tf.cast(1., dtype)),\n",
" sample_shape=1), \n",
" tfd.Sample(tfd.Uniform(low=tf.cast(0, dtype), high=.5), sample_shape=1),\n",
" lambda weight, sigma_out, mu_out, b1, b0: tfd.Independent(\n",
" tfd.Mixture(\n",
" tfd.Categorical(probs=tf.stack(\n",
" [tf.repeat(1-weight, 20, axis=1),\n",
" tf.repeat(weight, 20, axis=1)], 2)),\n",
" [\n",
" tfd.Normal(loc=b0 + b1*X, scale=sigma),\n",
" tfd.Normal(loc=mu_out, scale=sigma+sigma_out)\n",
" ]\n",
" ), 1)\n",
" ], validate_args=True)\n",
"\n",
"mdl_mixture = gen_mixturemodel(\n",
" dfhoggs['x'].values[tf.newaxis, ...],\n",
" dfhoggs['sigma_y'].values[tf.newaxis, ...])\n",
"\n",
"# hack to get a partially batched JD model works\n",
"graph_id = -1 if tf.executing_eagerly() else id(tf.constant(True).graph)\n",
"mdl_mixture._single_sample_distributions[graph_id] = mdl_mixture._flat_sample_distributions(1, seed=42)[0]\n",
"\n",
"mdl_mixture.resolve_graph()"
],
"execution_count": 12,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"(('b0', ()),\n",
" ('b1', ()),\n",
" ('mu_out', ()),\n",
" ('sigma_out', ()),\n",
" ('weight', ()),\n",
" ('x', ('weight', 'sigma_out', 'mu_out', 'b1', 'b0')))"
]
},
"metadata": {
"tags": []
},
"execution_count": 12
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "Z_Mw5HEDiB4P",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 318
},
"outputId": "3cfbf9ec-5187-4484-a742-566abe439ded"
},
"source": [
"mdl_mixture.log_prob_parts(mdl_mixture.sample(7))"
],
"execution_count": 13,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"[<tf.Tensor: shape=(7,), dtype=float64, numpy=\n",
" array([-4.40158728, -4.62087013, -4.60835387, -3.76896508, -3.53768907,\n",
" -3.79839279, -3.51119961])>,\n",
" <tf.Tensor: shape=(7,), dtype=float64, numpy=\n",
" array([-3.28694092, -3.95915419, -4.07460077, -3.22179831, -5.62272664,\n",
" -4.1475618 , -3.32503814])>,\n",
" <tf.Tensor: shape=(7,), dtype=float64, numpy=\n",
" array([-3.39046641, -3.47510034, -4.44127931, -3.31635069, -5.04100363,\n",
" -5.09520306, -3.38453393])>,\n",
" <tf.Tensor: shape=(7,), dtype=float64, numpy=\n",
" array([-0.22690733, -0.51375712, -0.34852645, -0.38080653, -0.24965774,\n",
" -0.22680682, -0.96158869])>,\n",
" <tf.Tensor: shape=(7,), dtype=float64, numpy=\n",
" array([0.69314718, 0.69314718, 0.69314718, 0.69314718, 0.69314718,\n",
" 0.69314718, 0.69314718])>,\n",
" <tf.Tensor: shape=(7,), dtype=float64, numpy=\n",
" array([ -1.35419048, -18.60569934, -19.09554255, 6.71831715,\n",
" -14.41093191, 2.02928976, 3.48929954])>]"
]
},
"metadata": {
"tags": []
},
"execution_count": 13
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "3seQVGRriIXt",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 67
},
"outputId": "7b6ac6f6-b5d0-4274-872c-7dfa5e65c81b"
},
"source": [
"mdl_mixture.log_prob(mdl_mixture.sample(7))"
],
"execution_count": 14,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"<tf.Tensor: shape=(7,), dtype=float64, numpy=\n",
"array([ -3.04581061, -25.56360524, -1.29576216, -12.73379249,\n",
" -23.43186341, -19.1988388 , -21.214426 ])>"
]
},
"metadata": {
"tags": []
},
"execution_count": 14
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "2CcoKye_ZVn9",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 33
},
"outputId": "d8629c65-83ea-495d-e050-29a0b5539268"
},
"source": [
"X = dfhoggs['x'].values[tf.newaxis, ...]\n",
"sigma = dfhoggs['sigma_y'].values[tf.newaxis, ...]\n",
"\n",
"mixture_dist_fn = lambda weight, sigma_out, mu_out, b1, b0: tfd.Independent(\n",
" tfd.Mixture(\n",
" tfd.Categorical(probs=tf.stack(\n",
" [tf.repeat(1-weight, 20, axis=1),\n",
" tf.repeat(weight, 20, axis=1)], 2)),\n",
" [\n",
" tfd.Normal(loc=b0 + b1*X, scale=sigma),\n",
" tfd.Normal(loc=mu_out, scale=sigma+sigma_out)\n",
" ]\n",
" ), 1)\n",
"\n",
"mixture_dist_fn(*mdl_mixture.sample(7)[:-1][::-1])"
],
"execution_count": 15,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"<tfp.distributions.Independent 'IndependentMixture' batch_shape=[7] event_shape=[20] dtype=float64>"
]
},
"metadata": {
"tags": []
},
"execution_count": 15
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "nJLT_mXejJu5",
"colab_type": "code",
"colab": {}
},
"source": [
"# nchain = 10\n",
"# b0, b1, mu_out, sigma_out, weight, _ = mdl_mixture.sample(nchain)\n",
"# init_state = [tf.ones_like(b0) * .1, tf.ones_like(b1),\n",
"# tf.ones_like(mu_out), tf.ones_like(sigma_out), tf.ones_like(b0) * .1]\n",
"\n",
"# step_size = [tf.cast(x, dtype=dtype) for x in [.3, .6, 3., 6., 11.]]\n",
"\n",
"# bijector to map contrained parameters to real\n",
"a, b = tf.constant(0., dtype), tf.constant(.5, dtype),\n",
"\n",
"# Interval transformation\n",
"tfp_interval = tfb.Inline(\n",
" inverse_fn=(\n",
" lambda x: tf.math.log(x - a) - tf.math.log(b - x)),\n",
" forward_fn=(\n",
" lambda y: (b - a) * tf.sigmoid(y) + a),\n",
" forward_log_det_jacobian_fn=(\n",
" lambda x: tf.math.log(b - a) - 2 * tf.nn.softplus(-x) - x),\n",
" forward_min_event_ndims=0,\n",
" name=\"interval\")\n",
"\n",
"unconstraining_bijectors = [\n",
" tfb.Identity(),\n",
" tfb.Identity(),\n",
" tfb.Identity(),\n",
" tfb.Exp(),\n",
" tfp_interval,\n",
"]\n",
"\n",
"target_log_prob_fn = lambda *x: mdl_mixture.log_prob(\n",
" x + (dfhoggs['y'].values[tf.newaxis, ...], ))"
],
"execution_count": 16,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "fUcLepRFtZX3",
"colab_type": "code",
"colab": {}
},
"source": [
"def gen_mixture_prior_model(hyperprior_mean=0, hyperprior_scale=10):\n",
" hyper_mean = tf.cast(hyperprior_mean, dtype)\n",
" hyper_scale = tf.cast(hyperprior_scale, dtype)\n",
" return tfd.JointDistributionSequential([\n",
" tfd.Sample(tfd.Normal(loc=hyper_mean, scale=hyper_scale),\n",
" sample_shape=1),\n",
" tfd.Sample(tfd.Normal(loc=hyper_mean, scale=hyper_scale),\n",
" sample_shape=1),\n",
" tfd.Sample(tfd.Normal(loc=hyper_mean, scale=10.),\n",
" sample_shape=1),\n",
" tfd.Sample(tfd.HalfNormal(scale=tf.cast(1., dtype)),\n",
" sample_shape=1), \n",
" tfd.Sample(tfd.Uniform(low=tf.cast(0, dtype), high=.5), sample_shape=1)])\n",
"prior_jds = gen_mixture_prior_model()\n",
"prior_samples = prior_jds.sample(2000)"
],
"execution_count": 17,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "u0saBRteb9D2",
"colab_type": "code",
"cellView": "form",
"colab": {}
},
"source": [
"#@title window_tune_nuts_sampling\n",
"# Copyright 2020 The TensorFlow Probability Authors.\n",
"#\n",
"# Licensed under the Apache License, Version 2.0 (the \"License\");\n",
"# you may not use this file except in compliance with the License.\n",
"# You may obtain a copy of the License at\n",
"#\n",
"# http://www.apache.org/licenses/LICENSE-2.0\n",
"#\n",
"# Unless required by applicable law or agreed to in writing, software\n",
"# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
"# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
"# See the License for the specific language governing permissions and\n",
"# limitations under the License.\n",
"# ============================================================================\n",
"\"\"\"MCMC sampling with HMC/NUTS using an expanding epoch tuning.\"\"\"\n",
"\n",
"import tensorflow.compat.v2 as tf\n",
"import tensorflow_probability as tfp\n",
"from tensorflow_probability.python.internal import assert_util\n",
"from tensorflow_probability.python.internal import prefer_static as ps\n",
"from tensorflow_probability.python.internal import tensorshape_util\n",
"from tensorflow_probability.python.mcmc.transformed_kernel import make_transform_fn\n",
"from tensorflow_probability.python.mcmc.transformed_kernel import make_transformed_log_prob\n",
"\n",
"tfb = tfp.bijectors\n",
"\n",
"__all__ = [\n",
" 'window_tune_nuts_sampling',\n",
"]\n",
"\n",
"\n",
"def _sample_posterior(target_log_prob_unbounded,\n",
" prior_samples_unbounded,\n",
" init_state=None,\n",
" num_samples=500,\n",
" nchains=4,\n",
" init_nchains=1,\n",
" target_accept_prob=.8,\n",
" max_tree_depth=9,\n",
" use_scaled_init=True,\n",
" tuning_window_schedule=(75, 25, 25, 25, 25, 25, 50),\n",
" use_wide_window_expanding_mode=True,\n",
" seed=None,\n",
" experimental_compile=True,\n",
" use_input_signature=True,\n",
" experimental_relax_shapes=False):\n",
" \"\"\"MCMC sampling with HMC/NUTS using an expanding epoch tuning.\"\"\"\n",
" if seed:\n",
" parallel_iterations = 1\n",
" else:\n",
" parallel_iterations = 10\n",
"\n",
" seed_stream = tfp.util.SeedStream(seed, 'window_tune_nuts_sampling')\n",
" rv_rank = ps.rank(prior_samples_unbounded)\n",
" assert rv_rank == 2\n",
" total_ndims = ps.shape(prior_samples_unbounded)[-1]\n",
" dtype = prior_samples_unbounded.dtype\n",
"\n",
" # Start with Identity Covariance matrix\n",
" loc_conditioner = tf.Variable(\n",
" tf.zeros([total_ndims], dtype=dtype), name='loc_conditioner')\n",
" scale_conditioner = tf.Variable(\n",
" tf.ones([total_ndims], dtype=dtype), name='scale_conditioner')\n",
"\n",
" scale = tf.linalg.LinearOperatorDiag(\n",
" diag=scale_conditioner,\n",
" is_non_singular=True,\n",
" is_self_adjoint=True,\n",
" is_positive_definite=True)\n",
" conditioning_bijector = tfb.Shift(shift=loc_conditioner)(\n",
" tfb.ScaleMatvecLinearOperator(scale))\n",
"\n",
" if init_state is None:\n",
" # Start at uniform random [-1, 1] around the prior mean in latent space\n",
" init_state_uniform = tf.random.uniform(\n",
" [init_nchains, total_ndims], dtype=dtype, seed=seed_stream()) * 2. - 1.\n",
" if use_scaled_init:\n",
" prior_z_mean = tf.math.reduce_mean(prior_samples_unbounded, axis=0)\n",
" prior_z_std = tf.math.reduce_std(prior_samples_unbounded, axis=0)\n",
" init_state = init_state_uniform * prior_z_std + prior_z_mean\n",
" else:\n",
" init_state = init_state_uniform\n",
"\n",
" init_step_size = tf.constant(0.25 / (total_ndims**0.25), dtype=dtype)\n",
"\n",
" hmc_inner = tfp.mcmc.TransformedTransitionKernel(\n",
" tfp.mcmc.NoUTurnSampler(\n",
" target_log_prob_fn=target_log_prob_unbounded,\n",
" step_size=init_step_size,\n",
" max_tree_depth=max_tree_depth,\n",
" seed=seed_stream,\n",
" parallel_iterations=parallel_iterations,\n",
" ), conditioning_bijector)\n",
"\n",
" hmc_step_size_tuning = tfp.mcmc.DualAveragingStepSizeAdaptation(\n",
" hmc_inner,\n",
" max(tuning_window_schedule),\n",
" target_accept_prob=target_accept_prob)\n",
"\n",
" if use_input_signature:\n",
" input_signature = [\n",
" tf.TensorSpec(shape=None, dtype=tf.int32),\n",
" tf.TensorSpec(shape=[None, total_ndims], dtype=dtype),\n",
" ]\n",
" else:\n",
" input_signature = None\n",
"\n",
" @tf.function(\n",
" input_signature=input_signature,\n",
" autograph=False,\n",
" experimental_compile=experimental_compile,\n",
" experimental_relax_shapes=experimental_relax_shapes)\n",
" def fast_adaptation_interval(num_steps, current_state):\n",
"\n",
" def body_fn(i, state, pkr):\n",
" next_state, next_pkr = hmc_step_size_tuning.one_step(state, pkr)\n",
" return i + 1, next_state, next_pkr\n",
"\n",
" current_pkr = hmc_step_size_tuning.bootstrap_results(current_state)\n",
" return tf.while_loop(\n",
" lambda i, *_: i < num_steps,\n",
" body_fn,\n",
" loop_vars=(0, current_state, current_pkr),\n",
" maximum_iterations=num_steps,\n",
" parallel_iterations=parallel_iterations)\n",
"\n",
" def body_fn_window2(\n",
" i, previous_state, previous_pkr, previous_mean, previous_cov):\n",
" next_state, next_pkr = hmc_step_size_tuning.one_step(\n",
" previous_state, previous_pkr)\n",
" n_next = i + 1\n",
" delta_pre = previous_state - previous_mean\n",
" next_mean = previous_mean + delta_pre / tf.cast(n_next, delta_pre.dtype)\n",
" delta_post = previous_state - next_mean\n",
" delta_cov = tf.expand_dims(delta_post, -1) * tf.expand_dims(delta_pre, -2)\n",
" next_cov = previous_cov + delta_cov\n",
"\n",
" next_mean.set_shape(previous_mean.shape)\n",
" next_cov.set_shape(previous_cov.shape)\n",
" return n_next, next_state, next_pkr, next_mean, next_cov\n",
"\n",
" if use_input_signature:\n",
" input_signature = [\n",
" tf.TensorSpec(shape=None, dtype=tf.int32),\n",
" tf.TensorSpec(shape=None, dtype=tf.int32),\n",
" tf.TensorSpec(shape=[None, total_ndims], dtype=dtype),\n",
" tf.TensorSpec(shape=[None, total_ndims], dtype=dtype),\n",
" tf.TensorSpec(shape=[None, total_ndims, total_ndims], dtype=dtype),\n",
" ]\n",
" else:\n",
" input_signature = None\n",
"\n",
" @tf.function(\n",
" input_signature=input_signature,\n",
" autograph=False,\n",
" experimental_compile=experimental_compile,\n",
" experimental_relax_shapes=experimental_relax_shapes)\n",
" def slow_adaptation_interval(num_steps, last_n, previous_state, previous_mean,\n",
" previous_cov):\n",
" previous_pkr = hmc_step_size_tuning.bootstrap_results(previous_state)\n",
" total_n, next_state, next_pkr, next_mean, next_cov = tf.while_loop(\n",
" lambda i, *_: i < num_steps + last_n,\n",
" body_fn_window2,\n",
" loop_vars=(last_n, previous_state, previous_pkr, previous_mean,\n",
" previous_cov),\n",
" maximum_iterations=num_steps,\n",
" parallel_iterations=parallel_iterations)\n",
" float_n = tf.cast(total_n, next_cov.dtype)\n",
" cov = next_cov / (float_n - 1.)\n",
"\n",
" # Regularization\n",
" scaled_cov = (float_n / (float_n + 5.)) * cov\n",
" shrinkage = 1e-3 * (5. / (float_n + 5.))\n",
" next_cov = scaled_cov + shrinkage\n",
"\n",
" return total_n, next_state, next_pkr, next_mean, next_cov\n",
"\n",
" def trace_fn(_, pkr):\n",
" return (\n",
" pkr.inner_results.target_log_prob,\n",
" pkr.inner_results.leapfrogs_taken,\n",
" pkr.inner_results.has_divergence,\n",
" pkr.inner_results.energy,\n",
" pkr.inner_results.log_accept_ratio,\n",
" pkr.inner_results.reach_max_depth,\n",
" pkr.inner_results.step_size,\n",
" )\n",
"\n",
" @tf.function(autograph=False, experimental_compile=experimental_compile)\n",
" def run_chain(num_results, current_state, previous_kernel_results):\n",
" return tfp.mcmc.sample_chain(\n",
" num_results=num_results,\n",
" num_burnin_steps=0,\n",
" current_state=current_state,\n",
" previous_kernel_results=previous_kernel_results,\n",
" kernel=hmc_inner,\n",
" trace_fn=trace_fn,\n",
" parallel_iterations=parallel_iterations)\n",
"\n",
" # Main sampling with tuning routine.\n",
" num_steps_tuning_window_schedule0 = tuning_window_schedule[0]\n",
"\n",
" # Window 1 to tune step size\n",
" print('Tuning Window 1...')\n",
" i, next_state, _ = fast_adaptation_interval(num_steps_tuning_window_schedule0,\n",
" init_state)\n",
"\n",
" next_mean = tf.zeros_like(init_state)\n",
" next_cov = tf.zeros(\n",
" ps.concat([ps.shape(init_state), ps.shape(init_state)[-1:]], axis=-1),\n",
" dtype=dtype)\n",
"\n",
" mean_updater = tf.zeros([total_ndims], dtype=dtype)\n",
" diag_updater = tf.ones([total_ndims], dtype=dtype)\n",
"\n",
" # Window 2 to tune mass matrix.\n",
" total_n = 0\n",
" for i, num_steps in enumerate(tuning_window_schedule[1:-1]):\n",
" print(f'Tuning Window 2 - {i}...')\n",
" if not use_wide_window_expanding_mode:\n",
" num_steps = num_steps * 2**i\n",
" with tf.control_dependencies([\n",
" loc_conditioner.assign(mean_updater, read_value=False),\n",
" scale_conditioner.assign(diag_updater, read_value=False)\n",
" ]):\n",
" (total_n, next_state_, _, next_mean_,\n",
" next_cov_) = slow_adaptation_interval(num_steps, total_n, next_state,\n",
" next_mean, next_cov)\n",
" diag_part = tf.linalg.diag_part(next_cov_)\n",
" if ps.rank(next_state) > 1:\n",
" mean_updater = tf.reduce_mean(next_mean_, axis=0)\n",
" diag_updater = tf.math.sqrt(tf.reduce_mean(diag_part, axis=0))\n",
" else:\n",
" mean_updater = next_mean_\n",
" diag_updater = tf.math.sqrt(diag_part)\n",
"\n",
" if use_wide_window_expanding_mode:\n",
" next_mean = tf.concat([next_mean_, next_mean_], axis=0)\n",
" next_cov = tf.concat([next_cov_, next_cov_], axis=0)\n",
" next_state = tf.concat([next_state_, next_state_], axis=0)\n",
" else:\n",
" next_mean, next_cov, next_state = next_mean_, next_cov_, next_state_\n",
"\n",
" num_steps_tuning_window_schedule3 = tuning_window_schedule[-1]\n",
" num_batches = ps.size0(next_state)\n",
" if nchains > num_batches:\n",
" final_init_state = tf.repeat(\n",
" next_state, (nchains + 1) // num_batches, axis=0)[:nchains]\n",
" else:\n",
" final_init_state = next_state[:nchains]\n",
"\n",
" with tf.control_dependencies([\n",
" loc_conditioner.assign(mean_updater, read_value=False),\n",
" scale_conditioner.assign(diag_updater, read_value=False)\n",
" ]):\n",
" # Window 3 step size tuning\n",
" print('Tuning Window 3...')\n",
" i, final_tuned_state, final_pkr = fast_adaptation_interval(\n",
" num_steps_tuning_window_schedule3, final_init_state)\n",
"\n",
" # Final samples\n",
" print('Sampling...')\n",
" nuts_samples, diagnostic = run_chain(num_samples, final_tuned_state,\n",
" final_pkr.inner_results)\n",
"\n",
" return nuts_samples, diagnostic, conditioning_bijector\n",
"\n",
"\n",
"def window_tune_nuts_sampling(target_log_prob,\n",
" prior_samples,\n",
" constraining_bijectors=None,\n",
" init_state=None,\n",
" num_samples=500,\n",
" nchains=4,\n",
" init_nchains=1,\n",
" target_accept_prob=.8,\n",
" max_tree_depth=9,\n",
" use_scaled_init=True,\n",
" tuning_window_schedule=(\n",
" 75, 25, 25, 25, 25, 25, 50),\n",
" use_wide_window_expanding_mode=True,\n",
" seed=None,\n",
" experimental_compile=True,\n",
" use_input_signature=True,\n",
" experimental_relax_shapes=False):\n",
" \"\"\"Sample from a density function with NUTS and an expanding window tuning.\n",
"\n",
" This function implements a turnkey MCMC sampling routine using NUTS and an\n",
" expanding window tuning strategy similar to Stan [1]. It learns a pre-\n",
" conditioner that scales and rotates the target distribution using a series of\n",
" expanding window - either in number of sample (same as in Stan,\n",
" use_wide_window_expanding_mode=False) or in number of batches/chains (\n",
" use_wide_window_expanding_mode=True).\n",
"\n",
" Internally, it calls `_sample_posterior` that assuming a real-valued target\n",
" density function and takes a Tensor with shape=(batch * dimension) as input.\n",
" The tuning routine is a memory-less (i.e., no warm-up samples are saved) MCMC\n",
" sampling with number of samples specified by a list-like\n",
" `tuning_window_schedule`.\n",
"\n",
" Args:\n",
" target_log_prob: Python callable which takes an argument like\n",
" `current_state` (or `*current_state` if it's a list) and returns its\n",
" (possibly unnormalized) log-density under the target distribution.\n",
" prior_samples: Nested structure of `Tensor`s, each of shape `[batches,\n",
" latent_part_event_shape]` and should be sample from the prior. They are\n",
" used to generate an inital chain position if `init_state` is not supplied.\n",
" constraining_bijectors: `tfp.distributions.Bijector` or list of\n",
" `tfp.distributions.Bijector`s. These bijectors use `forward` to map the\n",
" state on the real space to the constrained state expected by\n",
" `target_log_prob`.\n",
" init_state: (Optional) `Tensor` or Python `list` of `Tensor`s representing\n",
" the inital state(s) of the Markov chain(s).\n",
" num_samples: Integer number of the Markov chain draws after tuning.\n",
" nchains: Integer number of the Markov chains after tuning.\n",
" init_nchains: Integer number of the Markov chains in the initial tuning.\n",
" target_accept_prob: Floating point scalar `Tensor`. Target accept\n",
" probability.\n",
" max_tree_depth: Maximum depth of the tree implicitly built by NUTS.\n",
" use_scaled_init: Boolean. If `True`, generate inital state within [-1, 1]\n",
" scaled by prior sample standard deviation in the unconstrained real space.\n",
" This kwarg is ignored if `init_state` is not None\n",
" tuning_window_schedule: List-like sequence of integers that specify the\n",
" tuning schedule. Each integer number specifies the number of MCMC samples\n",
" within a single warm-up window. The first and the last window tunes the\n",
" step size (a scaler) only, while the intermedia windows tune both step\n",
" size and the pre-conditioner. More over, the intermedia windows takes\n",
" number of samples double in size: for example, the default schedule (75,\n",
" 25, 25, 25, 25, 25, 50) actually means it will take (75, 25 * 2**0, 25 *\n",
" 2**1, 25 * 2**2, 25 * 2**2, 25 * 2**3, 50) samples.\n",
" use_wide_window_expanding_mode: Boolean. Default to `True` that we double\n",
" the number of chains from the previous stage for the intermedia windows.\n",
" seed: Python integer to seed the random number generator.\n",
" experimental_compile: kwarg pass to tf.function decorator. If True, the\n",
" function is always compiled by XLA.\n",
" use_input_signature: If True, generate an input_signature kwarg that pass to\n",
" tf.function decorator.\n",
" experimental_relax_shapes: kwarg pass to tf.function decorator. When True,\n",
" tf.function may generate fewer, graphs that are less specialized on input\n",
" shapes.\n",
"\n",
" Returns:\n",
" posterior_samples: A `Tensor` or Python list of `Tensor`s representing the\n",
" posterior MCMC samples after tuning. The leading shape is (num_samples *\n",
" nchains)\n",
" diagnostic: A list of `Tensor` representing the diagnositc from NUTS:\n",
" `target_log_prob`, `leapfrogs_taken`, `has_divergence`, `energy`,\n",
" `log_accept_ratio`, `reach_max_depth`, `step_size.\n",
" conditioning_bijector: A tfp bijector that scales and rotates the target\n",
" density function in latent unbounded space.\n",
"\n",
" ### Examples\n",
"\n",
" Sampling from a multivariate Student-T distribution.\n",
"\n",
" ```python\n",
" DTYPE = np.float32\n",
"\n",
" nd = 50\n",
" concentration = 1.\n",
"\n",
" prior_dist = tfd.Sample(tfd.Normal(tf.constant(0., DTYPE), 100.), nd)\n",
"\n",
" mu = tf.cast(np.linspace(-100, 100, nd), dtype=DTYPE)\n",
" sigma = tf.cast(np.exp(np.linspace(-1, 1.5, nd)), dtype=DTYPE)\n",
" corr_tril = tfd.CholeskyLKJ(\n",
" dimension=nd, concentration=concentration).sample()\n",
" scale_tril = tf.linalg.matmul(tf.linalg.diag(sigma), corr_tril)\n",
" target_dist = tfd.MultivariateStudentTLinearOperator(\n",
" df=5., loc=mu, scale=tf.linalg.LinearOperatorLowerTriangular(scale_tril))\n",
"\n",
" target_log_prob = lambda *x: (\n",
" prior_dist.log_prob(*x) + target_dist.log_prob(*x))\n",
"\n",
" (\n",
" [mcmc_samples], diagnostic, conditioning_bijector\n",
" ) = window_tune_nuts_sampling(target_log_prob, [prior_dist.sample(2000)])\n",
"\n",
" loc_conditioner, scale_conditioner = conditioning_bijector.trainable_variables\n",
"\n",
" _, ax = plt.subplots(1, 2, figsize=(10, 5))\n",
" ax[0].plot(mu, loc_conditioner.numpy(), 'o', label='conditioner mean')\n",
" ax[0].plot(mu, tf.reduce_mean(\n",
" mcmc_samples, axis=[0, 1]), 'o', label='estimated mean')\n",
" ax[0].legend()\n",
"\n",
" sigma_sim = np.std(target_dist.sample(10000), axis=0)\n",
" ax[1].plot(sigma_sim, scale_conditioner.numpy(), 'o', label='conditioner std')\n",
" ax[1].plot(sigma_sim, tf.math.reduce_std(\n",
" mcmc_samples, axis=[0, 1]), 'o', label='estimated std');\n",
" ax[1].legend()\n",
"\n",
" ax[0].plot([min(mu), max(mu)], [min(mu), max(mu)])\n",
" ax[1].plot([min(sigma_sim), max(sigma_sim)], [min(sigma_sim), max(sigma_sim)])\n",
" ```\n",
"\n",
" #### References\n",
"\n",
" [1]: Stan Reference Manual.\n",
" https://mc-stan.org/docs/2_23/reference-manual/hmc-algorithm-parameters.html#automatic-parameter-tuning\n",
" \"\"\"\n",
"\n",
" log_prob_val = target_log_prob(*prior_samples)\n",
" log_prob_rank = ps.rank(log_prob_val)\n",
" assert log_prob_rank == 1\n",
"\n",
" if constraining_bijectors is not None:\n",
" target_log_prob_unbounded = make_transformed_log_prob(\n",
" target_log_prob,\n",
" constraining_bijectors,\n",
" direction='forward',\n",
" enable_bijector_caching=False)\n",
" # bound to unbound\n",
" inverse_transform = make_transform_fn(constraining_bijectors, 'inverse')\n",
" # unbound to bound\n",
" forward_transform = make_transform_fn(constraining_bijectors, 'forward')\n",
" else:\n",
" target_log_prob_unbounded = target_log_prob\n",
" inverse_transform = lambda x: x\n",
" forward_transform = lambda y: y\n",
"\n",
" prior_samples_unbounded = inverse_transform(prior_samples)\n",
" init_state_unbounded = None\n",
"\n",
" if tf.nest.is_nested(prior_samples_unbounded):\n",
" free_rv_event_shape = [x.shape[log_prob_rank:] for x in prior_samples]\n",
" flat_event_splits = [s.num_elements() for s in free_rv_event_shape]\n",
"\n",
" # TODO(junpenglao): replace the two function below with `tfb.Split`.\n",
" def split_and_reshape(x):\n",
" assertions = []\n",
" message = 'Input must have at least one dimension.'\n",
" if tensorshape_util.rank(x.shape) is not None:\n",
" if tensorshape_util.rank(x.shape) == 0:\n",
" raise ValueError(message)\n",
" else:\n",
" assertions.append(\n",
" assert_util.assert_rank_at_least(x, 1, message=message))\n",
" with tf.control_dependencies(assertions):\n",
" x = tf.nest.pack_sequence_as(free_rv_event_shape,\n",
" tf.split(x, flat_event_splits, axis=-1))\n",
"\n",
" def _reshape_map_part(part, event_shape):\n",
" static_rank = tf.get_static_value(ps.rank_from_shape(event_shape))\n",
" if static_rank == 1:\n",
" return part\n",
" new_shape = ps.concat([ps.shape(part)[:-1], event_shape], axis=-1)\n",
" return tf.reshape(part, ps.cast(new_shape, tf.int32))\n",
"\n",
" x = tf.nest.map_structure(_reshape_map_part, x, free_rv_event_shape)\n",
" return x\n",
"\n",
" def concat_list_event(x):\n",
"\n",
" def handle_part(x, shape):\n",
" if len(shape) == 0: # pylint: disable=g-explicit-length-test\n",
" return x[..., tf.newaxis]\n",
" return tf.reshape(x, list(x.shape)[:-len(shape)] + [-1])\n",
"\n",
" flat_parts = [handle_part(v, s) for v, s in zip(x, free_rv_event_shape)]\n",
" return tf.concat(flat_parts, axis=-1)\n",
"\n",
" def target_log_prob_unbounded_concated(x):\n",
" x = split_and_reshape(x)\n",
" return target_log_prob_unbounded(*x)\n",
"\n",
" prior_samples_unbounded_concated = concat_list_event(\n",
" prior_samples_unbounded)\n",
" if init_state is not None:\n",
" init_state_unbounded = concat_list_event(inverse_transform(init_state))\n",
" else:\n",
" target_log_prob_unbounded_concated = target_log_prob_unbounded\n",
" prior_samples_unbounded_concated = prior_samples_unbounded\n",
" split_and_reshape = lambda x: x\n",
" if init_state is not None:\n",
" init_state_unbounded = inverse_transform(init_state)\n",
"\n",
" nuts_samples, diagnostic, conditioning_bijector = _sample_posterior(\n",
" target_log_prob_unbounded_concated,\n",
" prior_samples_unbounded_concated,\n",
" init_state=init_state_unbounded,\n",
" num_samples=num_samples,\n",
" nchains=nchains,\n",
" init_nchains=init_nchains,\n",
" target_accept_prob=target_accept_prob,\n",
" max_tree_depth=max_tree_depth,\n",
" use_scaled_init=use_scaled_init,\n",
" tuning_window_schedule=tuning_window_schedule,\n",
" use_wide_window_expanding_mode=use_wide_window_expanding_mode,\n",
" seed=seed,\n",
" experimental_compile=experimental_compile,\n",
" use_input_signature=use_input_signature,\n",
" experimental_relax_shapes=experimental_relax_shapes)\n",
" return forward_transform(\n",
" split_and_reshape(nuts_samples)), diagnostic, conditioning_bijector\n"
],
"execution_count": 18,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "E5R5Th2Ub9D7",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 221
},
"outputId": "8aa3b8f7-f7c0-401e-9f85-065c0f80d24a"
},
"source": [
"%%time\n",
"\n",
"samples, sampler_stats, conditioning_bijector = window_tune_nuts_sampling(\n",
" target_log_prob_fn, prior_samples, unconstraining_bijectors, init_nchains=2,\n",
" use_scaled_init=True,\n",
" num_samples=1000, max_tree_depth=10, use_input_signature=False)"
],
"execution_count": 19,
"outputs": [
{
"output_type": "stream",
"text": [
"Tuning Window 1...\n",
"Tuning Window 2 - 0...\n",
"Tuning Window 2 - 1...\n",
"Tuning Window 2 - 2...\n",
"Tuning Window 2 - 3...\n",
"Tuning Window 2 - 4...\n",
"WARNING:tensorflow:5 out of the last 5 calls to <function _sample_posterior.<locals>.slow_adaptation_interval at 0x7f58480767b8> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for more details.\n",
"Tuning Window 3...\n",
"Sampling...\n",
"CPU times: user 55.4 s, sys: 3.92 s, total: 59.3 s\n",
"Wall time: 1min 11s\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "eVK_-HqMjJvB",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 745
},
"outputId": "50dc602a-537f-4102-ca11-baef23ddc281"
},
"source": [
"# using the pymc3 naming convention\n",
"sample_stats_name = ['lp', 'tree_size', 'diverging', 'energy', 'mean_tree_accept']\n",
"sample_stats = {k:v.numpy().T for k, v in zip(sample_stats_name, sampler_stats)}\n",
"\n",
"var_name = ['b0', 'b1', 'mu_out', 'sigma_out', 'weight']\n",
"posterior = {k:np.swapaxes(v.numpy(), 1, 0) \n",
" for k, v in zip(var_name, samples)}\n",
"\n",
"az_trace = az.from_dict(posterior=posterior, sample_stats=sample_stats)\n",
"az.plot_trace(az_trace);"
],
"execution_count": 20,
"outputs": [
{
"output_type": "display_data",
"data": {
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\n",
"text/plain": [
"<Figure size 864x720 with 10 Axes>"
]
},
"metadata": {
"tags": [],
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "kCMjsifsYdC-",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 265
},
"outputId": "f6f3ba7e-4357-477c-beca-c80bde0c2a98"
},
"source": [
"plt.hist(az_trace.sample_stats['tree_size'], 100);"
],
"execution_count": 21,
"outputs": [
{
"output_type": "display_data",
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": [],
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "QbbuT786jJvE",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 196
},
"outputId": "f4a400fe-ca71-4781-cf17-63044ceffce5"
},
"source": [
"az.summary(az_trace)"
],
"execution_count": 22,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>mean</th>\n",
" <th>sd</th>\n",
" <th>hdi_3%</th>\n",
" <th>hdi_97%</th>\n",
" <th>mcse_mean</th>\n",
" <th>mcse_sd</th>\n",
" <th>ess_mean</th>\n",
" <th>ess_sd</th>\n",
" <th>ess_bulk</th>\n",
" <th>ess_tail</th>\n",
" <th>r_hat</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>b0[0]</th>\n",
" <td>0.017</td>\n",
" <td>0.032</td>\n",
" <td>-0.043</td>\n",
" <td>0.076</td>\n",
" <td>0.001</td>\n",
" <td>0.001</td>\n",
" <td>3721.0</td>\n",
" <td>1717.0</td>\n",
" <td>4113.0</td>\n",
" <td>2397.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>b1[0]</th>\n",
" <td>1.240</td>\n",
" <td>0.066</td>\n",
" <td>1.121</td>\n",
" <td>1.365</td>\n",
" <td>0.001</td>\n",
" <td>0.001</td>\n",
" <td>4108.0</td>\n",
" <td>4032.0</td>\n",
" <td>4341.0</td>\n",
" <td>2637.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>mu_out[0]</th>\n",
" <td>0.102</td>\n",
" <td>0.304</td>\n",
" <td>-0.449</td>\n",
" <td>0.706</td>\n",
" <td>0.008</td>\n",
" <td>0.007</td>\n",
" <td>1539.0</td>\n",
" <td>1071.0</td>\n",
" <td>2011.0</td>\n",
" <td>1616.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>sigma_out[0]</th>\n",
" <td>0.433</td>\n",
" <td>0.292</td>\n",
" <td>0.038</td>\n",
" <td>0.946</td>\n",
" <td>0.006</td>\n",
" <td>0.004</td>\n",
" <td>2320.0</td>\n",
" <td>2320.0</td>\n",
" <td>2326.0</td>\n",
" <td>1947.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>weight[0]</th>\n",
" <td>0.276</td>\n",
" <td>0.106</td>\n",
" <td>0.091</td>\n",
" <td>0.468</td>\n",
" <td>0.002</td>\n",
" <td>0.001</td>\n",
" <td>3631.0</td>\n",
" <td>2964.0</td>\n",
" <td>3550.0</td>\n",
" <td>1998.0</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" mean sd hdi_3% hdi_97% ... ess_sd ess_bulk ess_tail r_hat\n",
"b0[0] 0.017 0.032 -0.043 0.076 ... 1717.0 4113.0 2397.0 1.0\n",
"b1[0] 1.240 0.066 1.121 1.365 ... 4032.0 4341.0 2637.0 1.0\n",
"mu_out[0] 0.102 0.304 -0.449 0.706 ... 1071.0 2011.0 1616.0 1.0\n",
"sigma_out[0] 0.433 0.292 0.038 0.946 ... 2320.0 2326.0 1947.0 1.0\n",
"weight[0] 0.276 0.106 0.091 0.468 ... 2964.0 3550.0 1998.0 1.0\n",
"\n",
"[5 rows x 11 columns]"
]
},
"metadata": {
"tags": []
},
"execution_count": 22
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "Fo_hvSl1jJvK",
"colab_type": "code",
"colab": {}
},
"source": [
"b0, b1, mu_out, sigma_out, weight = [\n",
" tf.reshape(x, (1000*4, 1)) for x in samples]\n",
"X = dfhoggs['x'].values[tf.newaxis, ...]\n",
"sigma = dfhoggs['sigma_y'].values[tf.newaxis, ...]\n",
"y_obs = dfhoggs['y'].values[tf.newaxis, ...]\n",
"\n",
"outlier_logp = tf.math.log(weight) + tfd.Normal(loc=mu_out, scale=sigma+sigma_out).log_prob(y_obs)\n",
"\n",
"marg_logp = tfd.Mixture(\n",
" tfd.Categorical(probs=tf.stack(\n",
" [tf.repeat(1-weight, 20, axis=1),\n",
" tf.repeat(weight, 20, axis=1)], 2)),\n",
" [\n",
" tfd.Normal(loc=b0 + b1*X, scale=sigma),\n",
" tfd.Normal(loc=mu_out, scale=sigma+sigma_out)\n",
" ]\n",
").log_prob(y_obs)\n",
"\n",
"logp_outlier = outlier_logp - marg_logp"
],
"execution_count": 25,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "-_Vq26VVjJvO",
"colab_type": "code",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 269
},
"outputId": "a5d0dccc-c9e2-47a8-f15c-efac9ec77f88"
},
"source": [
"plt.errorbar(dfhoggs['x'], dfhoggs['y'], yerr=dfhoggs['sigma_y'], fmt=\",k\", zorder=-1)\n",
"\n",
"p_outlier = np.exp(np.median(logp_outlier, axis=0))\n",
"\n",
"plt.scatter(dfhoggs['x'], dfhoggs['y'], c=p_outlier)\n",
"plt.colorbar(label=\"outlier probability\");"
],
"execution_count": 26,
"outputs": [
{
"output_type": "display_data",
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
"tags": [],
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "-11wvPB2jJvW",
"colab_type": "code",
"colab": {}
},
"source": [
""
],
"execution_count": null,
"outputs": []
}
]
}
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