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mp-bug.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"3.9.3\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Auto-assigning NUTS sampler...\n",
"Initializing NUTS using jitter+adapt_diag...\n",
"Multiprocess sampling (2 chains in 2 jobs)\n",
"NUTS: [mu]\n"
]
},
{
"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='0' class='' max='4000' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
" 0.00% [0/4000 00:00<00:00 Sampling 2 chains, 0 divergences]\n",
" </div>\n",
" "
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"ename": "RuntimeError",
"evalue": "Chain 0 failed.",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mRemoteTraceback\u001b[0m Traceback (most recent call last)",
"\u001b[0;31mRemoteTraceback\u001b[0m: \n\"\"\"\nTraceback (most recent call last):\n File \"/Users/dforeman/src/pymc-devs/pymc3/pymc3/parallel_sampling.py\", line 114, in _unpickle_step_method\n self._step_method = pickle.loads(self._step_method)\nAttributeError: Can't get attribute 'val' on <module '__main__' (built-in)>\n\nDuring handling of the above exception, another exception occurred:\n\nTraceback (most recent call last):\n File \"/Users/dforeman/src/pymc-devs/pymc3/pymc3/parallel_sampling.py\", line 135, in run\n self._unpickle_step_method()\n File \"/Users/dforeman/src/pymc-devs/pymc3/pymc3/parallel_sampling.py\", line 116, in _unpickle_step_method\n raise ValueError(unpickle_error)\nValueError: The model could not be unpickled. This is required for sampling with more than one core and multiprocessing context spawn or forkserver.\n\"\"\"",
"\nThe above exception was the direct cause of the following exception:\n",
"\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)",
"\u001b[0;31mValueError\u001b[0m: The model could not be unpickled. This is required for sampling with more than one core and multiprocessing context spawn or forkserver.",
"\nThe above exception was the direct cause of the following exception:\n",
"\u001b[0;31mRuntimeError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-1-a6c35ea91587>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 13\u001b[0m \u001b[0mpm\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mDensityDist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"obs\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mval\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobserved\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrandom\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrandn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m5\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 14\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 15\u001b[0;31m \u001b[0mpm\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msample\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mchains\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcores\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[0;32m~/src/pymc-devs/pymc3/pymc3/sampling.py\u001b[0m in \u001b[0;36msample\u001b[0;34m(draws, step, init, n_init, start, trace, chain_idx, chains, cores, tune, progressbar, model, random_seed, discard_tuned_samples, compute_convergence_checks, callback, return_inferencedata, idata_kwargs, mp_ctx, pickle_backend, **kwargs)\u001b[0m\n\u001b[1;32m 543\u001b[0m \u001b[0m_print_step_hierarchy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstep\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 544\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 545\u001b[0;31m \u001b[0mtrace\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_mp_sample\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0msample_args\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mparallel_args\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 546\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mpickle\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mPickleError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 547\u001b[0m \u001b[0m_log\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwarning\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Could not pickle model, sampling singlethreaded.\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m~/src/pymc-devs/pymc3/pymc3/sampling.py\u001b[0m in \u001b[0;36m_mp_sample\u001b[0;34m(draws, tune, step, chains, cores, chain, random_seed, start, progressbar, trace, model, callback, discard_tuned_samples, mp_ctx, pickle_backend, **kwargs)\u001b[0m\n\u001b[1;32m 1484\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1485\u001b[0m \u001b[0;32mwith\u001b[0m \u001b[0msampler\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1486\u001b[0;31m \u001b[0;32mfor\u001b[0m \u001b[0mdraw\u001b[0m \u001b[0;32min\u001b[0m \u001b[0msampler\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1487\u001b[0m \u001b[0mtrace\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtraces\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mdraw\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mchain\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mchain\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1488\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mtrace\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msupports_sampler_stats\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mdraw\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstats\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m~/src/pymc-devs/pymc3/pymc3/parallel_sampling.py\u001b[0m in \u001b[0;36m__iter__\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 490\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 491\u001b[0m \u001b[0;32mwhile\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_active\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 492\u001b[0;31m \u001b[0mdraw\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mProcessAdapter\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrecv_draw\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_active\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 493\u001b[0m \u001b[0mproc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mis_last\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdraw\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtuning\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstats\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mwarns\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdraw\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 494\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_total_draws\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m~/src/pymc-devs/pymc3/pymc3/parallel_sampling.py\u001b[0m in \u001b[0;36mrecv_draw\u001b[0;34m(processes, timeout)\u001b[0m\n\u001b[1;32m 363\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 364\u001b[0m \u001b[0merror\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mRuntimeError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Chain %s failed.\"\u001b[0m \u001b[0;34m%\u001b[0m \u001b[0mproc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mchain\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 365\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0merror\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0mold_error\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 366\u001b[0m \u001b[0;32melif\u001b[0m \u001b[0mmsg\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m\"writing_done\"\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 367\u001b[0m \u001b[0mproc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_readable\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mRuntimeError\u001b[0m: Chain 0 failed."
]
}
],
"source": [
"import pymc3 as pm\n",
"import numpy as np\n",
"\n",
"print(pm.__version__)\n",
"\n",
"with pm.Model() as model:\n",
" \n",
" mu = pm.Flat(\"mu\")\n",
" \n",
" def val(x):\n",
" return -0.5 * pm.math.sum((x - mu) ** 2)\n",
" \n",
" pm.DensityDist(\"obs\", val, observed=np.random.randn(5))\n",
" \n",
" pm.sample(chains=2, cores=2)"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"name: pymc3\r\n",
"channels:\r\n",
" - defaults\r\n",
"dependencies:\r\n",
" - ca-certificates=2020.6.24=0\r\n",
" - certifi=2020.6.20=py38_0\r\n",
" - libcxx=10.0.0=1\r\n",
" - libedit=3.1.20191231=h1de35cc_1\r\n",
" - libffi=3.3=hb1e8313_2\r\n",
" - ncurses=6.2=h0a44026_1\r\n",
" - openssl=1.1.1g=h1de35cc_0\r\n",
" - pip=20.2.2=py38_0\r\n",
" - python=3.8.5=h26836e1_0\r\n",
" - readline=8.0=h1de35cc_0\r\n",
" - setuptools=49.3.1=py38_0\r\n",
" - sqlite=3.32.3=hffcf06c_0\r\n",
" - tk=8.6.10=hb0a8c7a_0\r\n",
" - wheel=0.34.2=py38_0\r\n",
" - xz=5.2.5=h1de35cc_0\r\n",
" - zlib=1.2.11=h1de35cc_3\r\n",
" - pip:\r\n",
" - appnope==0.1.0\r\n",
" - argon2-cffi==20.1.0\r\n",
" - arviz==0.9.0\r\n",
" - attrs==19.3.0\r\n",
" - backcall==0.2.0\r\n",
" - bleach==3.1.5\r\n",
" - cffi==1.14.1\r\n",
" - cftime==1.2.1\r\n",
" - cycler==0.10.0\r\n",
" - decorator==4.4.2\r\n",
" - defusedxml==0.6.0\r\n",
" - entrypoints==0.3\r\n",
" - fastprogress==0.2.6\r\n",
" - h5py==2.10.0\r\n",
" - ipykernel==5.3.4\r\n",
" - ipython==7.17.0\r\n",
" - ipython-genutils==0.2.0\r\n",
" - jedi==0.17.2\r\n",
" - jinja2==2.11.2\r\n",
" - jsonschema==3.2.0\r\n",
" - jupyter-client==6.1.6\r\n",
" - jupyter-core==4.6.3\r\n",
" - kiwisolver==1.2.0\r\n",
" - markupsafe==1.1.1\r\n",
" - matplotlib==3.3.0\r\n",
" - mistune==0.8.4\r\n",
" - nbconvert==5.6.1\r\n",
" - nbformat==5.0.7\r\n",
" - netcdf4==1.5.4\r\n",
" - notebook==6.1.3\r\n",
" - numpy==1.19.1\r\n",
" - packaging==20.4\r\n",
" - pandas==1.1.0\r\n",
" - pandocfilters==1.4.2\r\n",
" - parso==0.7.1\r\n",
" - patsy==0.5.1\r\n",
" - pexpect==4.8.0\r\n",
" - pickleshare==0.7.5\r\n",
" - pillow==7.2.0\r\n",
" - prometheus-client==0.8.0\r\n",
" - prompt-toolkit==3.0.6\r\n",
" - ptyprocess==0.6.0\r\n",
" - pycparser==2.20\r\n",
" - pygments==2.6.1\r\n",
" - pyparsing==2.4.7\r\n",
" - pyrsistent==0.16.0\r\n",
" - python-dateutil==2.8.1\r\n",
" - pytz==2020.1\r\n",
" - pyzmq==19.0.2\r\n",
" - scipy==1.5.2\r\n",
" - send2trash==1.5.0\r\n",
" - six==1.15.0\r\n",
" - terminado==0.8.3\r\n",
" - testpath==0.4.4\r\n",
" - theano==1.0.5\r\n",
" - tornado==6.0.4\r\n",
" - traitlets==4.3.3\r\n",
" - typing-extensions==3.7.4.2\r\n",
" - wcwidth==0.2.5\r\n",
" - webencodings==0.5.1\r\n",
" - xarray==0.16.0\r\n",
"prefix: /Users/dforeman/miniconda3/envs/pymc3\r\n",
"\r\n"
]
}
],
"source": [
"!conda env export"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.5"
}
},
"nbformat": 4,
"nbformat_minor": 4
}
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