Creating Workflows with Step Functions Solution.ipynb

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  {
   "cell_type": "markdown",
   "id": "4f300157",
   "metadata": {},
   "source": [
    "## Exercise: Fill out Preprocess Step\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "aa0b40d3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: stepfunctions in /home/ec2-user/anaconda3/envs/python3/lib/python3.6/site-packages (2.2.0)\n",
      "Requirement already satisfied: boto3>=1.14.38 in /home/ec2-user/anaconda3/envs/python3/lib/python3.6/site-packages (from stepfunctions) (1.20.25)\n",
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      "Requirement already satisfied: sagemaker>=2.1.0 in /home/ec2-user/anaconda3/envs/python3/lib/python3.6/site-packages (from stepfunctions) (2.72.1)\n",
      "Requirement already satisfied: s3transfer<0.6.0,>=0.5.0 in /home/ec2-user/anaconda3/envs/python3/lib/python3.6/site-packages (from boto3>=1.14.38->stepfunctions) (0.5.0)\n",
      "Requirement already satisfied: jmespath<1.0.0,>=0.7.1 in /home/ec2-user/anaconda3/envs/python3/lib/python3.6/site-packages (from boto3>=1.14.38->stepfunctions) (0.10.0)\n",
      "Requirement already satisfied: botocore<1.24.0,>=1.23.25 in /home/ec2-user/anaconda3/envs/python3/lib/python3.6/site-packages (from boto3>=1.14.38->stepfunctions) (1.23.25)\n",
      "Requirement already satisfied: protobuf3-to-dict>=0.1.5 in /home/ec2-user/anaconda3/envs/python3/lib/python3.6/site-packages (from sagemaker>=2.1.0->stepfunctions) (0.1.5)\n",
      "Requirement already satisfied: packaging>=20.0 in /home/ec2-user/anaconda3/envs/python3/lib/python3.6/site-packages (from sagemaker>=2.1.0->stepfunctions) (21.3)\n",
      "Requirement already satisfied: numpy>=1.9.0 in /home/ec2-user/anaconda3/envs/python3/lib/python3.6/site-packages (from sagemaker>=2.1.0->stepfunctions) (1.19.5)\n",
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      "Requirement already satisfied: pandas in /home/ec2-user/anaconda3/envs/python3/lib/python3.6/site-packages (from sagemaker>=2.1.0->stepfunctions) (1.1.5)\n",
      "Requirement already satisfied: google-pasta in /home/ec2-user/anaconda3/envs/python3/lib/python3.6/site-packages (from sagemaker>=2.1.0->stepfunctions) (0.2.0)\n",
      "Requirement already satisfied: smdebug-rulesconfig==1.0.1 in /home/ec2-user/anaconda3/envs/python3/lib/python3.6/site-packages (from sagemaker>=2.1.0->stepfunctions) (1.0.1)\n",
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      "Requirement already satisfied: python-dateutil<3.0.0,>=2.1 in /home/ec2-user/anaconda3/envs/python3/lib/python3.6/site-packages (from botocore<1.24.0,>=1.23.25->boto3>=1.14.38->stepfunctions) (2.8.1)\n",
      "Requirement already satisfied: zipp>=0.5 in /home/ec2-user/anaconda3/envs/python3/lib/python3.6/site-packages (from importlib-metadata>=1.4.0->sagemaker>=2.1.0->stepfunctions) (3.4.0)\n",
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      "Requirement already satisfied: pytz>=2017.2 in /home/ec2-user/anaconda3/envs/python3/lib/python3.6/site-packages (from pandas->sagemaker>=2.1.0->stepfunctions) (2021.1)\n",
      "Requirement already satisfied: dill>=0.3.4 in /home/ec2-user/anaconda3/envs/python3/lib/python3.6/site-packages (from pathos->sagemaker>=2.1.0->stepfunctions) (0.3.4)\n",
      "Requirement already satisfied: multiprocess>=0.70.12 in /home/ec2-user/anaconda3/envs/python3/lib/python3.6/site-packages (from pathos->sagemaker>=2.1.0->stepfunctions) (0.70.12.2)\n",
      "Requirement already satisfied: pox>=0.3.0 in /home/ec2-user/anaconda3/envs/python3/lib/python3.6/site-packages (from pathos->sagemaker>=2.1.0->stepfunctions) (0.3.0)\n",
      "Requirement already satisfied: ppft>=1.6.6.4 in /home/ec2-user/anaconda3/envs/python3/lib/python3.6/site-packages (from pathos->sagemaker>=2.1.0->stepfunctions) (1.6.6.4)\n"
     ]
    }
   ],
   "source": [
    "%%bash\n",
    "pip install stepfunctions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "88f0dccc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "arn:aws:iam::248116845806:role/service-role/AmazonSageMaker-ExecutionRole-20220101T170667\n",
      "sagemaker-us-east-1-248116845806\n",
      "<sagemaker.session.Session object at 0x7f87c428eba8>\n"
     ]
    }
   ],
   "source": [
    "from sagemaker import get_execution_role\n",
    "import sagemaker\n",
    "\n",
    "role = get_execution_role()\n",
    "print(role)\n",
    "print(sagemaker.Session().default_bucket())\n",
    "print(sagemaker.Session())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "22e5ea0f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "arn:aws:iam::248116845806:role/service-role/AmazonSageMaker-ExecutionRole-20220101T170667\n",
      "sagemaker-us-east-1-248116845806\n",
      "<sagemaker.session.Session object at 0x7f87c5ce9748>\n",
      "s3://sagemaker-us-east-1-248116845806//hello_blaze_train_scikit s3://sagemaker-us-east-1-248116845806//hello_blaze_test_scikit\n",
      "[<sagemaker.processing.ProcessingInput object at 0x7f87c74144a8>, <sagemaker.processing.ProcessingInput object at 0x7f87c47a5470>]\n"
     ]
    }
   ],
   "source": [
    "from sagemaker import get_execution_role\n",
    "from sagemaker.sklearn.processing import SKLearnProcessor\n",
    "from sagemaker.processing import ProcessingInput, ProcessingOutput\n",
    "from stepfunctions.steps.sagemaker import ProcessingStep\n",
    "import sagemaker\n",
    "\n",
    "role = get_execution_role()\n",
    "print(role)\n",
    "print(sagemaker.Session().default_bucket())\n",
    "print(sagemaker.Session())\n",
    "\n",
    "PREPROCESSING_JOB_NAME = 'test-job-preprocess-17'\n",
    "input_data = 's3://sagemaker-us-east-1-248116845806/reviews_Musical_Instruments_5.json.zip'\n",
    "input_preprocessing_code = 's3://sagemaker-us-east-1-248116845806/HelloBlazePreprocess.py'\n",
    "sess = sagemaker.Session()\n",
    "\n",
    "sklearn_processor = SKLearnProcessor(framework_version='0.20.0',\n",
    "                                     role=role,\n",
    "                                     instance_type='ml.m5.large',\n",
    "                                     instance_count=1)\n",
    "\n",
    "\n",
    "processed_data_train = \"{}{}/{}\".format(\"s3://\", sess.default_bucket(), '/hello_blaze_train_scikit')\n",
    "processed_data_test = \"{}{}/{}\".format(\"s3://\", sess.default_bucket(), '/hello_blaze_test_scikit')\n",
    "\n",
    "inputs=[ProcessingInput(source=input_data, destination='/opt/ml/processing/input', input_name = 'input-1'),  ProcessingInput(source=input_preprocessing_code , destination='/opt/ml/processing/input/code', input_name = 'code')]\n",
    "\n",
    "\n",
    "outputs=[ProcessingOutput(source='/opt/ml/processing/output/train', destination=processed_data_train, output_name = 'train_data'), ProcessingOutput(source='/opt/ml/processing/output/test', destination=processed_data_test, output_name = 'test_data')]\n",
    "\n",
    "\n",
    "processing_step = ProcessingStep(\n",
    "    \"SageMaker pre-processing step 4\",\n",
    "    processor=sklearn_processor,\n",
    "    job_name=PREPROCESSING_JOB_NAME,\n",
    "    inputs=inputs,\n",
    "    outputs=outputs,\n",
    "    container_entrypoint=[\"python3\", \"/opt/ml/processing/input/code/HelloBlazePreprocess.py\"],\n",
    ")\n",
    "\n",
    "\n",
    "\n",
    "print(\" \".join([processed_data_train, processed_data_test]))\n",
    "print(inputs)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "523a16b4",
   "metadata": {},
   "source": [
    "## Exercise: Fill out Training Step"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "888f1374",
   "metadata": {},
   "outputs": [],
   "source": [
    "from stepfunctions.steps.sagemaker import TrainingStep\n",
    "import boto3\n",
    "\n",
    "WORKFLOW_OUTPUT = \"s3://sagemaker-us-east-1-248116845806/ex3-output/\"\n",
    "TRAINING_JOB_NAME = \"test-job-train-17\"\n",
    "\n",
    "region_name = boto3.Session().region_name\n",
    "container = sagemaker.image_uris.retrieve(\n",
    "    region=region_name, framework=\"blazingtext\", version=\"latest\"\n",
    ")\n",
    "\n",
    "helloBlazeEstimator = sagemaker.estimator.Estimator(\n",
    "    container,\n",
    "    role=role,\n",
    "    instance_count=1,\n",
    "    instance_type='ml.m5.large',\n",
    "    volume_size=30,\n",
    "    max_run=360000,\n",
    "    input_mode=\"File\",\n",
    "    output_path=WORKFLOW_OUTPUT,\n",
    "    sagemaker_session=sess,\n",
    ")\n",
    "\n",
    "helloBlazeEstimator.set_hyperparameters(mode='supervised')\n",
    "\n",
    "training_step = TrainingStep(\n",
    "    \"SageMaker Training Step\",\n",
    "    estimator=helloBlazeEstimator,\n",
    "    data={\"train\": sagemaker.TrainingInput(processed_data_train, content_type=\"text/plain\"), \"validation\": sagemaker.TrainingInput(processed_data_test, content_type=\"text/plain\")},\n",
    "    job_name=TRAINING_JOB_NAME,\n",
    "    wait_for_completion=True,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "253e8f61",
   "metadata": {},
   "source": [
    "## Exercise: Create & Execute Workflow"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "83b424e5",
   "metadata": {},
   "outputs": [],
   "source": [
    "from stepfunctions.steps import Chain\n",
    "from stepfunctions.workflow import Workflow\n",
    "\n",
    "workflow_role = 'arn:aws:iam::248116845806:role/step-function-execution-role'\n",
    "\n",
    "workflow_graph = Chain([processing_step, training_step])\n",
    "workflow = Workflow(\n",
    "    name=\"SageMakerProcessingWorkflow-17\",\n",
    "    definition=workflow_graph,\n",
    "    role=workflow_role,\n",
    ")\n",
    "\n",
    "workflow.create()\n",
    "\n",
    "# Execute workflow\n",
    "execution = workflow.execute(\n",
    "    inputs={\n",
    "        \"PreprocessingJobName\": PREPROCESSING_JOB_NAME,  # Each pre processing job (SageMaker processing job) requires a unique name,\n",
    "        \"TrainingJobName\": TRAINING_JOB_NAME  # Each Sagemaker Training job requires a unique name,       \n",
    "    }\n",
    ")\n",
    "\n",
    "execution_output = execution.get_output(wait=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "3c6ac853",
   "metadata": {},
   "outputs": [
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       "\n",
       "    <svg></svg>\n",
       "    <a href=\"https://console.aws.amazon.com/states/home?region=us-east-1#/executions/details/arn:aws:states:us-east-1:248116845806:execution:SageMakerProcessingWorkflow-17:6352e249-5567-4e98-ae1f-61dc491abf47\" target=\"_blank\"> Inspect in AWS Step Functions </a>\n",
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       "        sfn: \"https://do0of8uwbahzz.cloudfront.net/sfn\",\n",
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       "\n",
       "require(['sfn'], function(sfn) {\n",
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       "\n",
       "    var options = {\n",
       "        width: parseFloat(getComputedStyle(element, null).width.replace(\"px\", \"\")),\n",
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       "        layout: 'LR',\n",
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       "    var definition = {\"StartAt\": \"SageMaker pre-processing step 4\", \"States\": {\"SageMaker pre-processing step 4\": {\"Resource\": \"arn:aws:states:::sagemaker:createProcessingJob.sync\", \"Parameters\": {\"ProcessingJobName\": \"test-job-preprocess-17\", \"ProcessingInputs\": [{\"InputName\": \"input-1\", \"AppManaged\": false, \"S3Input\": {\"S3Uri\": \"s3://sagemaker-us-east-1-248116845806/reviews_Musical_Instruments_5.json.zip\", \"LocalPath\": \"/opt/ml/processing/input\", \"S3DataType\": \"S3Prefix\", \"S3InputMode\": \"File\", \"S3DataDistributionType\": \"FullyReplicated\", \"S3CompressionType\": \"None\"}}, {\"InputName\": \"code\", \"AppManaged\": false, \"S3Input\": {\"S3Uri\": \"s3://sagemaker-us-east-1-248116845806/HelloBlazePreprocess.py\", \"LocalPath\": \"/opt/ml/processing/input/code\", \"S3DataType\": \"S3Prefix\", \"S3InputMode\": \"File\", \"S3DataDistributionType\": \"FullyReplicated\", \"S3CompressionType\": \"None\"}}], \"ProcessingOutputConfig\": {\"Outputs\": [{\"OutputName\": \"train_data\", \"AppManaged\": false, \"S3Output\": {\"S3Uri\": \"s3://sagemaker-us-east-1-248116845806//hello_blaze_train_scikit\", \"LocalPath\": \"/opt/ml/processing/output/train\", \"S3UploadMode\": \"EndOfJob\"}}, {\"OutputName\": \"test_data\", \"AppManaged\": false, \"S3Output\": {\"S3Uri\": \"s3://sagemaker-us-east-1-248116845806//hello_blaze_test_scikit\", \"LocalPath\": \"/opt/ml/processing/output/test\", \"S3UploadMode\": \"EndOfJob\"}}]}, \"AppSpecification\": {\"ImageUri\": \"683313688378.dkr.ecr.us-east-1.amazonaws.com/sagemaker-scikit-learn:0.20.0-cpu-py3\", \"ContainerEntrypoint\": [\"python3\", \"/opt/ml/processing/input/code/HelloBlazePreprocess.py\"]}, \"RoleArn\": \"arn:aws:iam::248116845806:role/service-role/AmazonSageMaker-ExecutionRole-20220101T170667\", \"ProcessingResources\": {\"ClusterConfig\": {\"InstanceCount\": 1, \"InstanceType\": \"ml.m5.large\", \"VolumeSizeInGB\": 30}}}, \"Type\": \"Task\", \"Next\": \"SageMaker Training Step\"}, \"SageMaker Training Step\": {\"Resource\": \"arn:aws:states:::sagemaker:createTrainingJob.sync\", \"Parameters\": {\"AlgorithmSpecification\": {\"TrainingImage\": \"811284229777.dkr.ecr.us-east-1.amazonaws.com/blazingtext:1\", \"TrainingInputMode\": \"File\"}, \"OutputDataConfig\": {\"S3OutputPath\": \"s3://sagemaker-us-east-1-248116845806/ex3-output/\"}, \"StoppingCondition\": {\"MaxRuntimeInSeconds\": 360000}, \"ResourceConfig\": {\"InstanceCount\": 1, \"InstanceType\": \"ml.m5.large\", \"VolumeSizeInGB\": 30}, \"RoleArn\": \"arn:aws:iam::248116845806:role/service-role/AmazonSageMaker-ExecutionRole-20220101T170667\", \"InputDataConfig\": [{\"DataSource\": {\"S3DataSource\": {\"S3DataType\": \"S3Prefix\", \"S3Uri\": \"s3://sagemaker-us-east-1-248116845806//hello_blaze_train_scikit\", \"S3DataDistributionType\": \"FullyReplicated\"}}, \"ContentType\": \"text/plain\", \"ChannelName\": \"train\"}, {\"DataSource\": {\"S3DataSource\": {\"S3DataType\": \"S3Prefix\", \"S3Uri\": \"s3://sagemaker-us-east-1-248116845806//hello_blaze_test_scikit\", \"S3DataDistributionType\": \"FullyReplicated\"}}, \"ContentType\": \"text/plain\", \"ChannelName\": \"validation\"}], \"HyperParameters\": {\"mode\": \"supervised\"}, \"TrainingJobName\": \"test-job-train-17\"}, \"Type\": \"Task\", \"End\": true}}};\n",
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