examples: add metric pull from mlflow for demo

examples/v1-client-tensorflow-mnist-classifier/demo.ipynb

@@ -31,7 +31,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 12,
    "metadata": {
     "tags": []
    },
@@ -53,7 +53,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -176,7 +176,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 14,
    "metadata": {
     "tags": []
    },
@@ -194,9 +194,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 15,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'username': 'pluginuser', 'status': 'Login successful'}"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "try:\n",
     "    client.users.create('pluginuser','[email protected]','pleasemakesuretoPLUGINthecomputer','pleasemakesuretoPLUGINthecomputer')\n",
@@ -214,7 +225,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -252,7 +263,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 17,
    "metadata": {
     "scrolled": true,
     "tags": []
@@ -492,7 +503,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -516,7 +527,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 130,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -544,7 +555,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 131,
+   "execution_count": 32,
    "metadata": {
     "scrolled": true
    },
@@ -575,7 +586,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 132,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [
     {
@@ -613,7 +624,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 133,
+   "execution_count": 33,
    "metadata": {},
    "outputs": [
     {
@@ -642,23 +653,25 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 139,
+   "execution_count": 31,
    "metadata": {},
    "outputs": [
     {
-     "ename": "AttributeError",
-     "evalue": "'JobsClient' object has no attribute 'get_mlflow_run_id'",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
-      "Cell \u001b[0;32mIn[139], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mclient\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mjobs\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_mlflow_run_id\u001b[49m(infer_job[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mid\u001b[39m\u001b[38;5;124m'\u001b[39m])\n",
-      "\u001b[0;31mAttributeError\u001b[0m: 'JobsClient' object has no attribute 'get_mlflow_run_id'"
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "bfac3e7023404ff6a6312ae8da2e0826\n",
+      "{'compile_metrics': 0.5866386294364929, 'loss': 0.9697718620300293}\n"
      ]
     }
    ],
    "source": [
-    "client.jobs.get_mlflow_run_id(infer_job['id'])"
+    "from mlflow.tracking import MlflowClient\n",
+    "mlflow_client = MlflowClient()\n",
+    "mlflow_runid = client.jobs.get_mlflow_run_id(infer_job['id'])['mlflowRunId'].replace('-','') # why\n",
+    "print(mlflow_runid)\n",
+    "mlflow_run = mlflow_client.get_run(mlflow_runid)\n",
+    "pprint.pprint(mlflow_run.data.metrics)"
    ]
   },
   {