Untitled3.ipynb

Untitled3.ipynb

{
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        "ExecuteTime": {
          "end_time": "2022-02-04T12:56:56.852359Z",
          "start_time": "2022-02-04T12:56:55.586262Z"
        },
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      },
      "id": "c97bdb15",
      "cell_type": "code",
      "source": "%reload_ext autoreload\n%autoreload 2\n%matplotlib inline",
      "execution_count": 1,
      "outputs": []
    },
    {
      "metadata": {
        "ExecuteTime": {
          "end_time": "2022-02-04T12:57:01.991756Z",
          "start_time": "2022-02-04T12:56:56.855502Z"
        },
        "trusted": false
      },
      "id": "ddab5cb4",
      "cell_type": "code",
      "source": "import numpy as np\nimport pymc3 as pm\nimport aesara\nfrom aesara import tensor as aet",
      "execution_count": 2,
      "outputs": []
    },
    {
      "metadata": {
        "ExecuteTime": {
          "end_time": "2022-02-04T12:57:03.496016Z",
          "start_time": "2022-02-04T12:57:01.994854Z"
        },
        "trusted": false
      },
      "id": "45f05007",
      "cell_type": "code",
      "source": "with pm.Model() as monty_model:\n    car = pm.DiscreteUniform(\"car\", 0, 2)",
      "execution_count": 3,
      "outputs": []
    },
    {
      "metadata": {
        "ExecuteTime": {
          "end_time": "2022-02-04T12:57:05.320277Z",
          "start_time": "2022-02-04T12:57:03.499328Z"
        },
        "trusted": false
      },
      "id": "063fae0e",
      "cell_type": "code",
      "source": "p_open = aet.switch(\n    aet.eq(car, 0),\n    np.array([0, 0.5, 0.5]), # it is behind the first door\n    aet.switch(\n        aet.eq(car, 1),\n        np.array([0, 0, 1]), # it is behind the second door\n        np.array([0, 1, 0])  # it is behind the third door\n    )\n)",
      "execution_count": 4,
      "outputs": [
        {
          "ename": "NotImplementedError",
          "evalue": "Cannot convert car ~ DiscreteUniform to a tensor variable.",
          "output_type": "error",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mNotImplementedError\u001b[0m                       Traceback (most recent call last)",
            "\u001b[0;32m/var/folders/wk/1m4xnddx0qs1ffc6xypjgdnm0000gn/T/ipykernel_71729/2245227311.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m p_open = aet.switch(\n\u001b[0;32m----> 2\u001b[0;31m     \u001b[0maet\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0meq\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcar\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\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      3\u001b[0m     \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m0.5\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m0.5\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;31m# it is behind the first door\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m     aet.switch(\n\u001b[1;32m      5\u001b[0m         \u001b[0maet\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0meq\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcar\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m1\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[0;32m~/opt/anaconda3/envs/pymc3/lib/python3.9/site-packages/aesara/graph/op.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, *inputs, **kwargs)\u001b[0m\n\u001b[1;32m    281\u001b[0m         \"\"\"\n\u001b[1;32m    282\u001b[0m         \u001b[0mreturn_list\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"return_list\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 283\u001b[0;31m         \u001b[0mnode\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmake_node\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0minputs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\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    284\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    285\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mconfig\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcompute_test_value\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0;34m\"off\"\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m~/opt/anaconda3/envs/pymc3/lib/python3.9/site-packages/aesara/tensor/elemwise.py\u001b[0m in \u001b[0;36mmake_node\u001b[0;34m(self, *inputs)\u001b[0m\n\u001b[1;32m    460\u001b[0m         \u001b[0musing\u001b[0m \u001b[0mDimShuffle\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    461\u001b[0m         \"\"\"\n\u001b[0;32m--> 462\u001b[0;31m         \u001b[0minputs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mas_tensor_variable\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[0;32min\u001b[0m \u001b[0minputs\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    463\u001b[0m         out_dtypes, out_broadcastables, inputs = self.get_output_info(\n\u001b[1;32m    464\u001b[0m             \u001b[0mDimShuffle\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0minputs\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m~/opt/anaconda3/envs/pymc3/lib/python3.9/site-packages/aesara/tensor/elemwise.py\u001b[0m in \u001b[0;36m<listcomp>\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m    460\u001b[0m         \u001b[0musing\u001b[0m \u001b[0mDimShuffle\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    461\u001b[0m         \"\"\"\n\u001b[0;32m--> 462\u001b[0;31m         \u001b[0minputs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mas_tensor_variable\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[0;32min\u001b[0m \u001b[0minputs\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    463\u001b[0m         out_dtypes, out_broadcastables, inputs = self.get_output_info(\n\u001b[1;32m    464\u001b[0m             \u001b[0mDimShuffle\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0minputs\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m~/opt/anaconda3/envs/pymc3/lib/python3.9/site-packages/aesara/tensor/__init__.py\u001b[0m in \u001b[0;36mas_tensor_variable\u001b[0;34m(x, name, ndim, **kwargs)\u001b[0m\n\u001b[1;32m     40\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     41\u001b[0m     \"\"\"\n\u001b[0;32m---> 42\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0m_as_tensor_variable\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mndim\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\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     43\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     44\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m~/opt/anaconda3/envs/pymc3/lib/python3.9/functools.py\u001b[0m in \u001b[0;36mwrapper\u001b[0;34m(*args, **kw)\u001b[0m\n\u001b[1;32m    875\u001b[0m                             '1 positional argument')\n\u001b[1;32m    876\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 877\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mdispatch\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__class__\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkw\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    878\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    879\u001b[0m     \u001b[0mfuncname\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfunc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'__name__'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'singledispatch function'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m~/opt/anaconda3/envs/pymc3/lib/python3.9/site-packages/aesara/tensor/__init__.py\u001b[0m in \u001b[0;36m_as_tensor_variable\u001b[0;34m(x, name, ndim, **kwargs)\u001b[0m\n\u001b[1;32m     47\u001b[0m     \u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mOptional\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mstr\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mndim\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mOptional\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mint\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     48\u001b[0m ) -> NoReturn:\n\u001b[0;32m---> 49\u001b[0;31m     \u001b[0;32mraise\u001b[0m \u001b[0mNotImplementedError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mf\"Cannot convert {x} to a tensor variable.\"\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     50\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     51\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mNotImplementedError\u001b[0m: Cannot convert car ~ DiscreteUniform to a tensor variable."
          ]
        }
      ]
    },
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      "cell_type": "code",
      "source": "",
      "execution_count": null,
      "outputs": []
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