Fix Colab issues for 2.1, 2.2, 2.3, and 3.1

zenml-io · Oct 13, 2022 · 1b94a18 · 1b94a18
1 parent a5cbaa8
commit 1b94a18
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Showing 5 changed files with 42 additions and 72 deletions.
diff --git a/1-2_Artifact_Lineage.ipynb b/1-2_Artifact_Lineage.ipynb
@@ -29,6 +29,8 @@
    "source": [
     "%pip install \"zenml[server]\"\n",
     "!zenml integration install sklearn -y\n",
+    "!rm -rf .zen\n",
+    "!zenml init\n",
     "%pip install pyparsing==2.4.2  # required for Colab\n",
     "\n",
     "import IPython\n",
@@ -81,16 +83,6 @@
     "To illustrate, let us first rebuild our digits pipeline from the previous lesson:"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "!rm -rf .zen\n",
-    "!zenml init"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,

diff --git a/2-1_Experiment_Tracking.ipynb b/2-1_Experiment_Tracking.ipynb
@@ -29,6 +29,8 @@
    "source": [
     "%pip install \"zenml[server]\"\n",
     "!zenml integration install sklearn mlflow wandb -y\n",
+    "!rm -rf .zen\n",
+    "!zenml init\n",
     "%pip install pyparsing==2.4.2  # required for Colab\n",
     "\n",
     "import IPython\n",
@@ -37,34 +39,6 @@
     "IPython.Application.instance().kernel.do_shutdown(restart=True)"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Next, let's import our pipeline definition and some of the pipeline steps that we built in the previous lessons:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "!rm -rf .zen\n",
-    "!zenml init"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from pipelines.digits_pipeline import digits_pipeline\n",
-    "from steps.evaluator import evaluator\n",
-    "from steps.importer import importer"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -103,6 +77,24 @@
     "    !ngrok authtoken {NGROK_TOKEN}"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Next, let's import our pipeline definition and some of the pipeline steps that we built in the previous lessons:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from pipelines.digits_pipeline import digits_pipeline\n",
+    "from steps.evaluator import evaluator\n",
+    "from steps.importer import importer"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},

diff --git a/2-2_Local_Deployment.ipynb b/2-2_Local_Deployment.ipynb
@@ -27,6 +27,8 @@
    "source": [
     "%pip install \"zenml[server]\" matplotlib\n",
     "!zenml integration install sklearn mlflow -y\n",
+    "!rm -rf .zen\n",
+    "!zenml init\n",
     "%pip install pyparsing==2.4.2  # required for Colab\n",
     "\n",
     "import IPython\n",
@@ -51,16 +53,6 @@
     "    !mv zenbytes/pipelines ."
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "!rm -rf .zen\n",
-    "!zenml init"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -85,7 +77,10 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from zenml.integrations.mlflow.steps import mlflow_model_deployer_step\n",
+    "from zenml.integrations.mlflow.steps import (\n",
+    "    MLFlowDeployerParameters,\n",
+    "    mlflow_model_deployer_step\n",
+    ")\n",
     "from zenml.pipelines import pipeline\n",
     "from zenml.steps import step\n",
     "\n",
@@ -117,7 +112,9 @@
     "    trainer=svc_trainer_mlflow(),\n",
     "    evaluator=evaluator(),\n",
     "    deployment_trigger=deployment_trigger(),  # new\n",
-    "    model_deployer=mlflow_model_deployer_step(),  # new\n",
+    "    model_deployer=mlflow_model_deployer_step(\n",
+    "        MLFlowDeployerParameters(timeout=20)\n",
+    "    ),  # new\n",
     ")"
    ]
   },

diff --git a/2-3_Inference_Pipelines.ipynb b/2-3_Inference_Pipelines.ipynb
@@ -40,6 +40,8 @@
    "source": [
     "%pip install \"zenml[server]\"\n",
     "!zenml integration install sklearn mlflow -y\n",
+    "!rm -rf .zen\n",
+    "!zenml init\n",
     "!zenml stack set default\n",
     "!zenml experiment-tracker register mlflow_tracker --flavor=mlflow\n",
     "!zenml model-deployer register mlflow --flavor=mlflow\n",
@@ -75,17 +77,10 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "!rm -rf .zen\n",
-    "!zenml init"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from zenml.integrations.mlflow.steps import mlflow_model_deployer_step\n",
+    "from zenml.integrations.mlflow.steps import (\n",
+    "    MLFlowDeployerParameters, \n",
+    "    mlflow_model_deployer_step\n",
+    ")\n",
     "\n",
     "from pipelines.training_pipeline import train_evaluate_deploy_pipeline\n",
     "from steps.deployment_trigger import deployment_trigger\n",
@@ -98,7 +93,9 @@
     "    trainer=svc_trainer_mlflow(),\n",
     "    evaluator=evaluator(),\n",
     "    deployment_trigger=deployment_trigger(),\n",
-    "    model_deployer=mlflow_model_deployer_step(),\n",
+    "    model_deployer=mlflow_model_deployer_step(\n",
+    "        MLFlowDeployerParameters(timeout=20)\n",
+    "    ),  # new\n",
     ").run(unlisted=True)"
    ]
   },

diff --git a/3-1_Data_Skew.ipynb b/3-1_Data_Skew.ipynb
@@ -34,6 +34,8 @@
    "source": [
     "%pip install \"zenml[server]\"\n",
     "!zenml integration install sklearn mlflow evidently -y\n",
+    "!rm -rf .zen\n",
+    "!zenml init\n",
     "%pip install pyparsing==2.4.2  # required for Colab\n",
     "\n",
     "import IPython\n",
@@ -80,16 +82,6 @@
     "Let's define this pipeline in code and import the other steps (which we have already built during previous lessons):"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "!rm -rf .zen\n",
-    "!zenml init"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,