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