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template.yaml
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template.yaml
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AWSTemplateFormatVersion: '2010-09-09'
Transform: AWS::Serverless-2016-10-31
Description: >-
SAM Template for SMX-Validator
Metadata:
AWS::ServerlessRepo::Application:
Name: SMX-Validator
Description: >-
Orchestrate k-fold cross validated SageMaker training jobs on Amazon
Web Services infrastructure.
Author: mrtj
SpdxLicenseId: Apache-2.0
LicenseUrl: LICENSE
ReadmeUrl: README.md
Labels: ['SageMaker', 'machine-learning', 'StepFunctions']
HomePageUrl: https://github.com/mrtj/smx-validator
SemanticVersion: 0.1.2
SourceCodeUrl: https://github.com/mrtj/smx-validator
Parameters:
InputBucketName:
Type: String
Description: >-
The name of the input S3 bucket where the dataset can be found. The
job_config.input_path runtime parameter should refer to a path in this
bucket.
OutputBucketName:
Type: String
Description: >-
The name of the output S3 bucket where the cross validation folds will
be written. The job_config.output_prefix runtime parameter should refer
to a path in this bucket.
Globals:
Function:
Tags:
application: smx_validator
Resources:
CrossValidatorStateMachine:
Type: AWS::Serverless::StateMachine
Description: >-
The state machine coordinating the training of cross-validation folds.
Properties:
DefinitionUri: statemachine/smx-validator.asl.yaml
DefinitionSubstitutions:
BootstrapperFunctionArn: !GetAtt BootstrapperFunction.Arn
DatasetSplitterFunctionArn: !GetAtt DatasetSplitterFunction.Arn
SplitPreparerFunctionArn: !GetAtt SplitPreparerFunction.Arn
SageMakerExecutionRoleArn: !GetAtt SageMakerExecutionRole.Arn
TrainingInfoGetterFunctionArn: !GetAtt TrainingInfoGetterFunction.Arn
Policies: # What can the State Machine do on your behalf?
- Statement:
# Invoke specific lambda functions defined in this template
- Sid: LambdaInvokePolicy
Effect: Allow
Action:
- lambda:InvokeFunction
Resource:
- Fn::Sub:
- arn:${AWS::Partition}:lambda:${AWS::Region}:${AWS::AccountId}:function:${functionName}*
- { functionName: !Ref BootstrapperFunction }
- Fn::Sub:
- arn:${AWS::Partition}:lambda:${AWS::Region}:${AWS::AccountId}:function:${functionName}*
- { functionName: !Ref DatasetSplitterFunction }
- Fn::Sub:
- arn:${AWS::Partition}:lambda:${AWS::Region}:${AWS::AccountId}:function:${functionName}*
- { functionName: !Ref SplitPreparerFunction }
- Fn::Sub:
- arn:${AWS::Partition}:lambda:${AWS::Region}:${AWS::AccountId}:function:${functionName}*
- { functionName: !Ref TrainingInfoGetterFunction }
# Start/stop SageMaker training jobs if their name starts crossvalidator-*
- Sid: SageMakerTrainingJobStartStopPolicy
Effect: Allow
Action:
- sagemaker:CreateTrainingJob
- sagemaker:DescribeTrainingJob
- sagemaker:StopTrainingJob
Resource:
- !Sub arn:${AWS::Partition}:sagemaker:${AWS::Region}:${AWS::AccountId}:training-job/crossvalidator-*
# Post and read events on EventBridge to signal end of SageMaker training
- Sid: PutSageMakerTrainingEventsPolicy
Effect: Allow
Action:
- events:PutTargets
- events:PutRule
- events:DescribeRule
Resource:
- !Sub arn:${AWS::Partition}:events:${AWS::Region}:${AWS::AccountId}:rule/StepFunctionsGetEventsForSageMakerTrainingJobsRule
# List SageMaker tags
- Sid: SageMakerListTagPolicy
Effect: Allow
Action:
- sagemaker:ListTags
Resource: '*'
# Pass execution role to SageMaker service
- Sid: PassRoleToSageMakerPolicy
Effect: Allow
Action:
- iam:PassRole
Resource: !GetAtt SageMakerExecutionRole.Arn
Condition:
StringEquals:
iam:PassedToService: sagemaker.amazonaws.com
Tags:
application: sagemaker_crossvalidator
BootstrapperFunction:
Type: AWS::Serverless::Function
Description: >-
This lambda function boostraps the sagemaker crossvalidation training
process.
Properties:
CodeUri: functions/bootstrapper
Handler: app.lambda_handler
Runtime: python3.8
Timeout: 60
Layers:
- !Ref SageMakerLayer
- !Ref JsonSchemaLayer
- !Ref ResourcesLayer
Policies:
- Statement:
- Sid: SageMakerExperimentsManagerPolicy
Effect: Allow
Action:
- sagemaker:ListExperiments
- sagemaker:DescribeExperiment
- sagemaker:CreateExperiment
- sagemaker:UpdateExperiment
- sagemaker:DeleteExperiment
- sagemaker:ListTrials
- sagemaker:DescribeTrial
- sagemaker:CreateTrial
- sagemaker:UpdateTrial
- sagemaker:DeleteTrial
- sagemaker:ListTrialComponents
- sagemaker:DescribeTrialComponent
- sagemaker:CreateTrialComponent
- sagemaker:UpdateTrialComponent
- sagemaker:DeleteTrialComponent
Resource: '*'
DatasetSplitterFunction:
Type: AWS::Serverless::Function
Description: >-
This lambda function splits the input dataset into cross-validation
folds.
Properties:
CodeUri: functions/dataset_splitter/
Handler: app.lambda_handler
Runtime: python3.8
Timeout: 300
MemorySize: 512
Layers:
- !Ref NumpyLayer
- !Ref S3fsLayer
Policies:
- S3ReadPolicy:
BucketName: !Ref InputBucketName
- S3WritePolicy:
BucketName: !Ref OutputBucketName
SplitPreparerFunction:
Type: AWS::Serverless::Function
Description: >-
This lambda function compiles the hyperparameter template and other
parameters of the current split
Properties:
CodeUri: functions/split_preparer
Handler: app.lambda_handler
Runtime: python3.8
TrainingInfoGetterFunction:
Type: AWS::Serverless::Function
Description: >-
This lambda function gets training results and other information
after the training has finished
Properties:
CodeUri: functions/training_info_getter/
Handler: app.lambda_handler
Runtime: python3.8
Timeout: 10
Layers:
- !Ref CommonUtilsLayer
Policies:
- Statement:
- Sid: SageMakerDescribeTrainingJobPolicy
Effect: Allow
Action:
- sagemaker:DescribeTrainingJob
Resource:
- !Sub arn:${AWS::Partition}:sagemaker:${AWS::Region}:${AWS::AccountId}:training-job/crossvalidator-*
NumpyLayer:
Type: AWS::Serverless::LayerVersion
Description: Lambda layer containing the numpy library
Properties:
ContentUri: layers/numpy
CompatibleRuntimes:
- python3.8
Metadata:
BuildMethod: python3.8
S3fsLayer:
Type: AWS::Serverless::LayerVersion
Description: Lambda layer containing the s3fs library and a wrapper class
Properties:
ContentUri: layers/s3fs
CompatibleRuntimes:
- python3.8
Metadata:
BuildMethod: python3.8
SageMakerLayer:
Type: AWS::Serverless::LayerVersion
Description: Lambda layer containing the sagemaker and smexperiments libraries
Properties:
ContentUri: layers/sagemaker
CompatibleRuntimes:
- python3.8
Metadata:
BuildMethod: python3.8
JsonSchemaLayer:
Type: AWS::Serverless::LayerVersion
Description: Lambda layer containing the jsonschema library
Properties:
ContentUri: layers/jsonschema
CompatibleRuntimes:
- python3.8
Metadata:
BuildMethod: python3.8
ResourcesLayer:
Type: AWS::Serverless::LayerVersion
Description: Lambda layer containing resources
Properties:
ContentUri: resources
CompatibleRuntimes:
- python3.8
Metadata:
BuildMethod: makefile
CommonUtilsLayer:
Type: AWS::Serverless::LayerVersion
Description: Lambda layer containing common utils
Properties:
ContentUri: layers/utils
CompatibleRuntimes:
- python3.8
Metadata:
BuildMethod: python3.8
SageMakerExecutionRole:
Type: AWS::IAM::Role
Description: Execution role for the SageMaker training job
Properties:
AssumeRolePolicyDocument:
Statement:
- Effect: Allow
Principal:
Service:
- sagemaker.amazonaws.com
Action:
- sts:AssumeRole
ManagedPolicyArns:
- arn:aws:iam::aws:policy/AmazonSageMakerFullAccess
Path: /service-role/
Policies:
- PolicyName: SageMakerS3InputBucketAccess
PolicyDocument:
Version: '2012-10-17'
Statement:
- Effect: Allow
Action:
- s3:GetObject
- s3:ListBucket
- s3:GetBucketLocation
- s3:GetObjectVersion
- s3:GetLifecycleConfiguration
Resource:
- !Sub arn:aws:s3:::${InputBucketName}
- !Sub arn:aws:s3:::${InputBucketName}/*
- PolicyName: SageMakerS3OutputBucketAccess
PolicyDocument:
Version: '2012-10-17'
Statement:
- Effect: Allow
Action:
- s3:PutObject
- s3:PutObjectAcl
- s3:PutLifecycleConfiguration
Resource:
- !Sub arn:aws:s3:::${OutputBucketName}
- !Sub arn:aws:s3:::${OutputBucketName}/*
Tags:
- Key: application
Value: sagemaker_crossvalidator
Outputs:
CrossValidatorStateMachineArn:
Description: SageMaker Crossvalidator State Machine ARN
Value: !Ref CrossValidatorStateMachine
CrossValidatorStateMachineRoleArn:
Description: IAM Role created for Cross Validator State Machine
Value: !GetAtt CrossValidatorStateMachineRole.Arn