{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "Install Kubeflow Pipelines SDK" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "!pip3 install https://storage.googleapis.com/ml-pipeline/release/0.1.3/kfp.tar.gz --upgrade" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Import required library" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "import kfp\n", "from kfp import compiler\n", "from kubernetes import client as k8s_client" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Import pipeline definition" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "from cs_pipeline import github_code_index_update" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Create an experiment first" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "client = kfp.Client()\n", "exp = client.create_experiment(name='code-search-25')" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Compile it into a tar package.\n", "compiler.Compiler().compile(github_code_index_update, 'github_code_index_update.tar.gz')\n", "\n", "# Submit a run.\n", "# inputs - experiment id, run name, tarball file\n", "run = client.run_pipeline(exp.id, 'code-search-index-update', 'github_code_index_update.tar.gz')" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.4" } }, "nbformat": 4, "nbformat_minor": 2 }