Remove state.

docs/examples/example_onnx.ipynb

@@ -67,7 +67,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -113,20 +113,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<metalearners.xlearner.XLearner at 0x10e5b9520>"
-      ]
-     },
-     "execution_count": 2,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "from metalearners import XLearner\n",
     "from lightgbm import LGBMRegressor, LGBMClassifier\n",
@@ -172,22 +161,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "{'propensity_model': [LGBMClassifier(n_estimators=5, verbose=-1)],\n",
-       " 'control_effect_model': [LGBMRegressor(n_estimators=5, verbose=-1)],\n",
-       " 'treatment_effect_model': [LGBMRegressor(n_estimators=5, verbose=-1)]}"
-      ]
-     },
-     "execution_count": 3,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "necessary_models = xlearner._necessary_onnx_models()\n",
     "necessary_models"
@@ -211,19 +187,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "The maximum opset needed by this model is only 9.\n",
-      "The maximum opset needed by this model is only 8.\n",
-      "The maximum opset needed by this model is only 8.\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "import onnx\n",
     "from onnxmltools import convert_lightgbm\n",
@@ -255,18 +221,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/Users/kevinklein/Code/metalearners/metalearners/xlearner.py:463: UserWarning: _build_onnx is an experimental feature. Use it at your own risk!\n",
-      "  warning_experimental_feature(\"_build_onnx\")\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "onnx_model = xlearner._build_onnx(onnx_models)"
    ]
@@ -282,47 +239,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "ONNX model input:  [name: \"X\"\n",
-      "type {\n",
-      "  tensor_type {\n",
-      "    elem_type: 1\n",
-      "    shape {\n",
-      "      dim {\n",
-      "      }\n",
-      "      dim {\n",
-      "        dim_value: 11\n",
-      "      }\n",
-      "    }\n",
-      "  }\n",
-      "}\n",
-      "]\n",
-      "ONNX model output:  [name: \"tau\"\n",
-      "type {\n",
-      "  tensor_type {\n",
-      "    elem_type: 1\n",
-      "    shape {\n",
-      "      dim {\n",
-      "      }\n",
-      "      dim {\n",
-      "        dim_value: 1\n",
-      "      }\n",
-      "      dim {\n",
-      "        dim_value: 1\n",
-      "      }\n",
-      "    }\n",
-      "  }\n",
-      "}\n",
-      "]\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "print(\"ONNX model input: \", onnx_model.graph.input)\n",
     "print(\"ONNX model output: \", onnx_model.graph.output)"
@@ -350,7 +269,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -371,7 +290,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -389,7 +308,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [