🔥 ready for 0.7.2

juanjucm · Apr 14, 2022 · eb8b877 · eb8b877
1 parent 06db28b
commit eb8b877
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Showing 6 changed files with 63 additions and 46 deletions.
diff --git a/.gitignore b/.gitignore
@@ -129,3 +129,7 @@ dmypy.json
 .pyre/
 
 *.zen/
+.idea/
+
+# for wandb
+mlruns
diff --git a/00 - Basics.ipynb b/00 - Basics.ipynb
@@ -59,7 +59,7 @@
    "source": [
     "!rm -rf .zen\n",
     "!zenml init\n",
-    "!zenml stack set local_stack"
+    "!zenml stack set default"
    ]
   },
   {
@@ -163,8 +163,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "pipelines = repo.get_pipelines()\n",
-    "p = pipelines[-1]\n",
+    "p = repo.get_pipeline('my_pipeline')\n",
     "p"
    ]
   },
@@ -248,7 +247,7 @@
    "source": [
     "@step\n",
     "def c() -> int:\n",
-    "    return 10"
+    "    return 11"
    ]
   },
   {
@@ -274,7 +273,7 @@
     "    PipelineRunLineageVisualizer,\n",
     ")\n",
     "\n",
-    "latest_run = repo.get_pipelines()[-1].runs[-1]\n",
+    "latest_run = repo.get_pipeline('my_pipeline').runs[-1]\n",
     "PipelineRunLineageVisualizer().visualize(latest_run)"
    ]
   }

diff --git a/01 - Building a ML(Ops) pipeline.ipynb b/01 - Building a ML(Ops) pipeline.ipynb
@@ -51,8 +51,7 @@
    "outputs": [],
    "source": [
     "!rm -rf .zen\n",
-    "!zenml init\n",
-    "!zenml stack set default"
+    "!zenml init"
    ]
   },
   {
@@ -78,6 +77,37 @@
     "!zenml integration install sklearn dash evidently mlflow -f"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Add a Model Deployer to your Stack"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Register the MLflow model deployer\n",
+    "!zenml model-deployer register mlflow --type=mlflow\n",
+    "\n",
+    "# Create a new stack with MLflow deployer in it\n",
+    "!zenml stack register local_with_mlflow -m default -a default -o default -d mlflow"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Set it as the active stack\n",
+    "!zenml stack set local_with_mlflow\n",
+    "!zenml stack describe"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -165,7 +195,6 @@
     "    y_train: np.ndarray,\n",
     ") -> ClassifierMixin:\n",
     "    \"\"\"Train another simple sklearn classifier for the digits dataset.\"\"\"\n",
-    "    print(\"test\")\n",
     "    model = SVC(gamma=0.001)\n",
     "    model.fit(X_train, y_train)\n",
     "    return model"
@@ -258,8 +287,7 @@
     "from zenml.repository import Repository\n",
     "\n",
     "repo = Repository()\n",
-    "pipelines = repo.get_pipelines()\n",
-    "p = pipelines[-1]\n",
+    "p = repo.get_pipeline('digits_pipeline')\n",
     "run = p.runs[-1]\n",
     "steps = run.steps\n",
     "s = steps[-1]\n",
@@ -675,8 +703,8 @@
     "\n",
     "with MLFlowEnvironment() as env:\n",
     "    env.tracking_uri\n",
-    "    !mlflow ui --backend-store-uri {env.tracking_uri} --port 4998\n",
-    "  "
+    "    !mlflow ui --backend-store-uri {env.tracking_uri} --port 4997\n",
+    "    print(env.tracking_uri)"
    ]
   },
   {
@@ -753,7 +781,7 @@
     "from zenml.integrations.mlflow.mlflow_environment import MLFlowEnvironment\n",
     "\n",
     "with MLFlowEnvironment() as env:\n",
-    "    !mlflow ui --backend-store-uri {env.tracking_uri} --port 4998"
+    "    !mlflow ui --backend-store-uri {env.tracking_uri} --port 4997"
    ]
   },
   {
@@ -803,30 +831,6 @@
     "    model_deployer(deployment_decision, model)"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Add a Model Deployer to your Stack"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Register the MLflow model deployer\n",
-    "!zenml model-deployer register mlflow --type=mlflow\n",
-    "\n",
-    "# Create a new stack with MLflow deployer in it\n",
-    "!zenml stack register local_with_mlflow -m default -a default -o default -d mlflow\n",
-    "\n",
-    "# Set it as the active stack\n",
-    "!zenml stack set local_with_mlflow\n",
-    "!zenml stack describe"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -908,6 +912,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "from zenml.repository import Repository\n",
+    "\n",
     "repo = Repository()\n",
     "p = repo.get_pipeline('continuous_deployment_pipeline_notebook')\n",
     "last_run = p.runs[-1]\n",
@@ -924,10 +930,10 @@
     "model_deployer = repo.active_stack.model_deployer\n",
     "services = model_deployer.find_model_server(\n",
     "    pipeline_name=\"continuous_deployment_pipeline_notebook\",\n",
-    "    pipeline_step_name=\"model_deployer\",\n",
+    "    pipeline_step_name=\"mlflow_model_deployer_step\",\n",
     "    running=True,\n",
     ")\n",
-    "service = services[0]\n"
+    "service = services[0]"
    ]
   },
   {
@@ -1156,7 +1162,7 @@
     "    prediction_service_loader=prediction_service_loader(\n",
     "        PredictionServiceLoaderStepConfig(\n",
     "            pipeline_name=\"continuous_deployment_pipeline_notebook\",\n",
-    "            step_name=\"model_deployer\",\n",
+    "            step_name=\"mlflow_model_deployer_step\",\n",
     "            model_name=\"model\",\n",
     "        )\n",
     "    ),\n",

diff --git a/02 - Transitioning To Production.ipynb b/02 - Transitioning To Production.ipynb
@@ -84,13 +84,20 @@
     "![All](_assets/integrations_all.png \"All\")"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "![All](_assets/seldon.png \"Seldon Model Deployer.png\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
-    "!zenml integration install kubeflow seldon aws -f"
+    "!zenml integration install kubeflow seldon s3 -f"
    ]
   },
   {
@@ -142,7 +149,7 @@
    "source": [
     "Now we want to transition to a kubeflow stack that will look a little bit like this. Note that for kubeflow pipelines we also need a registry where the docker images for each step are registered. \n",
     "\n",
-    "![KubeflowStack](_assets/aws_stack_redesigned.png \"KubeflowStack\")\n",
+    "![KubeflowStack](_assets/aws_stack_seldon.png \"KubeflowStack\")\n",
     "\n",
     "But we have good news! You barely have to do anything to transition."
    ]
@@ -283,14 +290,16 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "scrolled": true
+   },
    "outputs": [],
    "source": [
     "# Register container registry\n",
     "!zenml container-registry register ecr_registry --type=default --uri={ECR_REGISTRY_NAME}\n",
     "\n",
     "# Register orchestrator (Kubeflow on AWS)\n",
-    "!zenml orchestrator register eks_orchestrator --type=kubeflow \n",
+    "!zenml orchestrator register eks_orchestrator --type=kubeflow\n",
     "\n",
     "# Register metadata store and artifact store\n",
     "!zenml metadata-store register kubeflow_metadata_store --type=kubeflow\n",
@@ -349,9 +358,8 @@
    },
    "outputs": [],
    "source": [
-    "\n",
     "# Let's train within kubeflow pipelines - this will deploy the pipeline\n",
-    "!python run.py --deploy --predict # --interval-second=300"
+    "!python run.py --deploy # --interval-second=300"
    ]
   },
   {

diff --git a/_assets/aws_stack_seldon.png b/_assets/aws_stack_seldon.png
diff --git a/_assets/seldon.png b/_assets/seldon.png
-Original file line number
+Diff line change
@@ Expand Up / @@ -129,3 +129,7 @@ dmypy.json @@
     .pyre/
     *.zen/
+    .idea/
+    # for wandb
+    mlruns