housekeeping in CI-tested notebooks

SeldonIO · May 22, 2020 · 0c14de6 · 0c14de6
1 parent 7fd05d1
commit 0c14de6
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Showing 11 changed files with 138 additions and 125 deletions.
diff --git a/examples/ambassador/custom/ambassador_custom.ipynb b/examples/ambassador/custom/ambassador_custom.ipynb
@@ -70,7 +70,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "!kubectl rollout status deploy/$(kubectl get deploy -l seldon-deployment-id=production-model-example -o jsonpath='{.items[0].metadata.name}')"
+    "%%bash\n",
+    "dep_name=$(kubectl get deploy -l seldon-deployment-id=example -o jsonpath='{.items[0].metadata.name}')\n",
+    "kubectl rollout status deploy/${dep_name}"
    ]
   },
   {
@@ -116,13 +118,6 @@
    "source": [
     "!kubectl delete -f model_custom_ambassador.json"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {
@@ -142,7 +137,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.8"
+   "version": "3.7.6"
   },
   "varInspector": {
    "cols": {
@@ -175,5 +170,5 @@
   }
  },
  "nbformat": 4,
- "nbformat_minor": 1
+ "nbformat_minor": 4
 }
diff --git a/examples/models/metadata/graph_metadata.ipynb b/examples/models/metadata/graph_metadata.ipynb
@@ -1131,6 +1131,23 @@
     "\n",
     "meta"
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Cleanup resources"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%%bash\n",
+    "kubectl delete -f graph-metadata/"
+   ]
   }
  ],
  "metadata": {

diff --git a/examples/models/sklearn_iris/.gitignore b/examples/models/sklearn_iris/.gitignore
@@ -1,2 +1,3 @@
 IrisClassifier.sav
-sklearn_iris_jsondata.py
+sklearn_iris_jsondata.py
+sklearn_iris.py
diff --git a/examples/models/sklearn_iris/IrisClassifier.py b/examples/models/sklearn_iris/IrisClassifier.py
@@ -1,4 +1,4 @@
-from sklearn.externals import joblib
+import joblib
 
 class IrisClassifier(object):
 

diff --git a/examples/models/sklearn_iris/sklearn_iris.ipynb b/examples/models/sklearn_iris/sklearn_iris.ipynb
@@ -29,31 +29,44 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "import numpy as np\n",
-    "import os\n",
-    "from sklearn.linear_model import LogisticRegression\n",
+    "%%writefile train_iris.py\n",
+    "import joblib\n",
     "from sklearn.pipeline import Pipeline\n",
-    "from sklearn.externals import joblib\n",
+    "from sklearn.linear_model import LogisticRegression\n",
     "from sklearn import datasets\n",
     "\n",
+    "\n",
+    "OUTPUT_FILE = \"IrisClassifier.sav\"\n",
+    "\n",
+    "\n",
     "def main():\n",
-    "    clf = LogisticRegression()\n",
-    "    p = Pipeline([('clf', clf)])\n",
-    "    print('Training model...')\n",
+    "    clf = LogisticRegression(solver=\"liblinear\", multi_class=\"ovr\")\n",
+    "    p = Pipeline([(\"clf\", clf)])\n",
+    "    print(\"Training model...\")\n",
     "    p.fit(X, y)\n",
-    "    print('Model trained!')\n",
+    "    print(\"Model trained!\")\n",
+    "\n",
+    "    print(f\"Saving model in {OUTPUT_FILE}\")\n",
+    "    joblib.dump(p, OUTPUT_FILE)\n",
+    "    print(\"Model saved!\")\n",
+    "\n",
     "\n",
-    "    filename_p = 'IrisClassifier.sav'\n",
-    "    print('Saving model in %s' % filename_p)\n",
-    "    joblib.dump(p, filename_p)\n",
-    "    print('Model saved!')\n",
-    "    \n",
     "if __name__ == \"__main__\":\n",
-    "    print('Loading iris data set...')\n",
+    "    print(\"Loading iris data set...\")\n",
     "    iris = datasets.load_iris()\n",
     "    X, y = iris.data, iris.target\n",
-    "    print('Dataset loaded!')\n",
-    "    main()\n"
+    "    print(\"Dataset loaded!\")\n",
+    "\n",
+    "    main()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!python train_iris.py"
    ]
   },
   {
@@ -65,20 +78,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Overwriting IrisClassifier.py\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "%%writefile IrisClassifier.py\n",
-    "from sklearn.externals import joblib\n",
+    "import joblib\n",
     "\n",
     "class IrisClassifier(object):\n",
     "\n",
@@ -109,7 +114,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "!s2i build -E environment_rest . seldonio/seldon-core-s2i-python3:0.18 seldonio/sklearn-iris:0.1"
+    "!s2i build -E environment_rest . seldonio/seldon-core-s2i-python3:1.1.0 seldonio/sklearn-iris:0.1"
    ]
   },
   {
@@ -187,17 +192,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Overwriting sklearn_iris_deployment.yaml\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "%%writefile sklearn_iris_deployment.yaml\n",
     "apiVersion: machinelearning.seldon.io/v1alpha2\n",
@@ -321,7 +318,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.4"
+   "version": "3.7.6"
   },
   "varInspector": {
    "cols": {
@@ -354,5 +351,5 @@
   }
  },
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }
diff --git a/examples/models/sklearn_iris/sklearn_iris_deployment.yaml b/examples/models/sklearn_iris/sklearn_iris_deployment.yaml
@@ -18,4 +18,4 @@ spec:
       name: sklearn-iris-classifier
       type: MODEL
     name: sklearn-iris-predictor
-    replicas: 1
+    replicas: 1
diff --git a/examples/models/sklearn_iris/train_iris.py b/examples/models/sklearn_iris/train_iris.py
@@ -1,25 +1,28 @@
-import numpy as np
-import os
-from sklearn.linear_model import LogisticRegression
+import joblib
 from sklearn.pipeline import Pipeline
-from sklearn.externals import joblib
+from sklearn.linear_model import LogisticRegression
 from sklearn import datasets
 
+
+OUTPUT_FILE = "IrisClassifier.sav"
+
+
 def main():
-    clf = LogisticRegression()
-    p = Pipeline([('clf', clf)])
-    print('Training model...')
+    clf = LogisticRegression(solver="liblinear", multi_class="ovr")
+    p = Pipeline([("clf", clf)])
+    print("Training model...")
     p.fit(X, y)
-    print('Model trained!')
+    print("Model trained!")
+
+    print(f"Saving model in {OUTPUT_FILE}")
+    joblib.dump(p, OUTPUT_FILE)
+    print("Model saved!")
+
 
-    filename_p = 'IrisClassifier.sav'
-    print('Saving model in %s' % filename_p)
-    joblib.dump(p, filename_p)
-    print('Model saved!')
-
 if __name__ == "__main__":
-    print('Loading iris data set...')
+    print("Loading iris data set...")
     iris = datasets.load_iris()
     X, y = iris.data, iris.target
-    print('Dataset loaded!')
+    print("Dataset loaded!")
+
     main()
diff --git a/examples/models/sklearn_iris_jsondata/IrisClassifier.py b/examples/models/sklearn_iris_jsondata/IrisClassifier.py
@@ -1,4 +1,4 @@
-from sklearn.externals import joblib
+import joblib
 import sys
 
 

diff --git a/examples/models/sklearn_iris_jsondata/sklearn_iris_jsondata.ipynb b/examples/models/sklearn_iris_jsondata/sklearn_iris_jsondata.ipynb
@@ -29,31 +29,44 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "import numpy as np\n",
-    "import os\n",
-    "from sklearn.linear_model import LogisticRegression\n",
+    "%%writefile train_iris.py\n",
+    "import joblib\n",
     "from sklearn.pipeline import Pipeline\n",
-    "from sklearn.externals import joblib\n",
+    "from sklearn.linear_model import LogisticRegression\n",
     "from sklearn import datasets\n",
     "\n",
+    "\n",
+    "OUTPUT_FILE = \"IrisClassifier.sav\"\n",
+    "\n",
+    "\n",
     "def main():\n",
-    "    clf = LogisticRegression()\n",
-    "    p = Pipeline([('clf', clf)])\n",
-    "    print('Training model...')\n",
+    "    clf = LogisticRegression(solver=\"liblinear\", multi_class=\"ovr\")\n",
+    "    p = Pipeline([(\"clf\", clf)])\n",
+    "    print(\"Training model...\")\n",
     "    p.fit(X, y)\n",
-    "    print('Model trained!')\n",
+    "    print(\"Model trained!\")\n",
+    "\n",
+    "    print(f\"Saving model in {OUTPUT_FILE}\")\n",
+    "    joblib.dump(p, OUTPUT_FILE)\n",
+    "    print(\"Model saved!\")\n",
+    "\n",
     "\n",
-    "    filename_p = 'IrisClassifier.sav'\n",
-    "    print('Saving model in %s' % filename_p)\n",
-    "    joblib.dump(p, filename_p)\n",
-    "    print('Model saved!')\n",
-    "    \n",
     "if __name__ == \"__main__\":\n",
-    "    print('Loading iris data set...')\n",
+    "    print(\"Loading iris data set...\")\n",
     "    iris = datasets.load_iris()\n",
     "    X, y = iris.data, iris.target\n",
-    "    print('Dataset loaded!')\n",
-    "    main()\n"
+    "    print(\"Dataset loaded!\")\n",
+    "\n",
+    "    main()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!python train_iris.py"
    ]
   },
   {
@@ -65,20 +78,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Overwriting IrisClassifier.py\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "%%writefile IrisClassifier.py\n",
-    "from sklearn.externals import joblib\n",
+    "import joblib\n",
     "import sys\n",
     "\n",
     "\n",
@@ -118,7 +123,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "!s2i build -E environment_rest . seldonio/seldon-core-s2i-python3:0.18 seldonio/sklearn-iris-jsondata:0.1"
+    "!s2i build -E environment_rest . seldonio/seldon-core-s2i-python3:1.1.0 seldonio/sklearn-iris-jsondata:0.1"
    ]
   },
   {
@@ -203,17 +208,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Overwriting sklearn_iris_jsondata_deployment.yaml\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "%%writefile sklearn_iris_jsondata_deployment.yaml\n",
     "apiVersion: machinelearning.seldon.io/v1alpha2\n",
@@ -340,7 +337,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.4"
+   "version": "3.7.6"
   },
   "varInspector": {
    "cols": {
@@ -373,5 +370,5 @@
   }
  },
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }