add ai_platform test

samples/core/ai-platform/Chicago Crime Pipeline.ipynb → samples/core/ai_platform/ai_platform.ipynb

@@ -71,28 +71,41 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "parameters"
+    ]
+   },
    "outputs": [],
    "source": [
     "# Required Parameters\n",
-    "PROJECT_ID = '<ADD GCP PROJECT HERE>'\n",
-    "GCS_WORKING_DIR = 'gs://<ADD STORAGE LOCATION HERE>' # No ending slash\n",
-    "\n",
+    "project_id = '<ADD GCP PROJECT HERE>'\n",
+    "output = 'gs://<ADD STORAGE LOCATION HERE>' # No ending slash\n",
+    "experiment_name = 'Chicago Crime Prediction'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
     "# Optional Parameters\n",
     "REGION = 'us-central1'\n",
     "RUNTIME_VERSION = '1.13'\n",
     "PACKAGE_URIS=json.dumps(['gs://chicago-crime/chicago_crime_trainer-0.0.tar.gz'])\n",
-    "TRAINER_OUTPUT_GCS_PATH = GCS_WORKING_DIR + '/train/output/' + str(int(time.time())) + '/'\n",
-    "DATA_GCS_PATH = GCS_WORKING_DIR + '/reports.csv'\n",
+    "TRAINER_OUTPUT_GCS_PATH = output + '/train/output/' + str(int(time.time())) + '/'\n",
+    "DATA_GCS_PATH = output + '/reports.csv'\n",
     "PYTHON_MODULE = 'trainer.task'\n",
     "TRAINER_ARGS =  json.dumps([\n",
     "    '--data-file-url', DATA_GCS_PATH,\n",
-    "    '--job-dir', GCS_WORKING_DIR\n",
+    "    '--job-dir', output\n",
     "])\n",
-    "EXPERIMENT_NAME = 'Chicago Crime Prediction'\n",
     "PIPELINE_NAME = 'Chicago Crime Prediction'\n",
     "PIPELINE_FILENAME_PREFIX = 'chicago'\n",
-    "PIPELINE_DESCRIPTION = ''"
+    "PIPELINE_DESCRIPTION = ''\n",
+    "MODEL_NAME = 'chicago_pipeline_model' + str(int(time.time()))\n",
+    "MODEL_VERSION = 'chicago_pipeline_model_v1' + str(int(time.time()))"
    ]
   },
   {
@@ -191,6 +204,7 @@
     "    project_id,\n",
     "    model_uri,\n",
     "    model_id,\n",
+    "    model_version,\n",
     "    runtime_version):\n",
     "    \n",
     "    return mlengine_deploy_op(\n",
@@ -222,8 +236,8 @@
     "\n",
     "def pipeline(\n",
     "    data_gcs_path=DATA_GCS_PATH,\n",
-    "    gcs_working_dir=GCS_WORKING_DIR,\n",
-    "    project_id=PROJECT_ID,\n",
+    "    gcs_working_dir=output,\n",
+    "    project_id=project_id,\n",
     "    python_module=PYTHON_MODULE,\n",
     "    region=REGION,\n",
     "    runtime_version=RUNTIME_VERSION,\n",
@@ -245,7 +259,8 @@
     "    \n",
     "    deploy_task = deploy(project_id,\n",
     "                         train_task.outputs['job_dir'],\n",
-    "                         train_task.outputs['job_id'],\n",
+    "                         MODEL_NAME,\n",
+    "                         MODEL_VERSION,\n",
     "                         runtime_version)    \n",
     "    return True\n",
     "\n",
@@ -266,11 +281,29 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "kfp.Client().create_run_from_pipeline_func(pipeline, arguments={}, experiment_name=EXPERIMENT_NAME)"
+    "kfp.Client().create_run_from_pipeline_func(pipeline, arguments={}, experiment_name=experiment_name)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Clean models"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!gcloud ml-engine versions delete $MODEL_VERSION --model $MODEL_NAME\n",
+    "!gcloud ml-engine models delete $MODEL_NAME"
    ]
   }
  ],
  "metadata": {
+  "celltoolbar": "Tags",
   "kernelspec": {
    "display_name": "Python 3",
    "language": "python",
@@ -286,7 +319,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.8"
+   "version": "3.6.4"
   },
   "pycharm": {
    "stem_cell": {

test/sample-test/configs/ai_platform.config.yaml

@@ -0,0 +1,19 @@
+# Copyright 2019 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+test_name: ai_platform
+notebook_params:
+  output:
+  project_id: ml-pipeline-test
+  experiment_name: ai_platform-test

test/sample_test.yaml

@@ -86,6 +86,7 @@ spec:
               - loop_parameter
               - loop_static
               - resource_ops
+              - ai_platform
               - parameterized_tfx_oss
     # Build and push image
     - name: build-image-by-dockerfile