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feat(stepfunctions-tasks): FastFile mode for SageMaker Training Job (#…
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…26675)

According to the AWS documentation, the TrainingInputMode for a SageMaker Training Job can be one of the following: `Pipe | File | FastFile`

https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_Channel.html#sagemaker-Type-Channel-InputMode

https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_AlgorithmSpecification.html#API_AlgorithmSpecification_Contents


I have just added `FastFile` below to align with the official documentation.
https://github.com/aws/aws-cdk/blob/v2.90.0/packages/aws-cdk-lib/aws-stepfunctions-tasks/lib/sagemaker/base-types.ts#L458

Closes #26653.

----

*By submitting this pull request, I confirm that my contribution is made under the terms of the Apache-2.0 license*
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tmyoda authored Aug 23, 2023
1 parent 7e1c038 commit 5fef403
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Showing 10 changed files with 61 additions and 49 deletions.
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@@ -1 +1 @@
{"version":"30.0.0"}
{"version":"33.0.0"}
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@@ -1,15 +1,15 @@
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Expand Up @@ -276,12 +276,6 @@
"StateMachine2E01A3A5": {
"Type": "AWS::StepFunctions::StateMachine",
"Properties": {
"RoleArn": {
"Fn::GetAtt": [
"StateMachineRoleB840431D",
"Arn"
]
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"",
Expand All @@ -297,7 +291,7 @@
"Arn"
]
},
"\",\"AlgorithmSpecification\":{\"TrainingInputMode\":\"File\",\"AlgorithmName\":\"arn:aws:sagemaker:us-east-1:865070037744:algorithm/scikit-decision-trees-15423055-57b73412d2e93e9239e4e16f83298b8f\"},\"InputDataConfig\":[{\"ChannelName\":\"InputData\",\"DataSource\":{\"S3DataSource\":{\"S3Uri\":\"https://s3.",
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{
"Ref": "AWS::Region"
},
Expand All @@ -324,6 +318,12 @@
"/result/\"},\"ResourceConfig\":{\"InstanceCount\":1,\"InstanceType\":\"ml.m4.xlarge\",\"VolumeSizeInGB\":10},\"StoppingCondition\":{\"MaxRuntimeInSeconds\":3600}}}}}"
]
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@@ -1,5 +1,5 @@
{
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"stacks": [
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@@ -1,5 +1,5 @@
{
"version": "30.0.0",
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"artifacts": {
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"type": "cdk:asset-manifest",
Expand All @@ -17,7 +17,7 @@
"validateOnSynth": false,
"assumeRoleArn": "arn:${AWS::Partition}:iam::${AWS::AccountId}:role/cdk-hnb659fds-deploy-role-${AWS::AccountId}-${AWS::Region}",
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"additionalDependencies": [
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Expand Up @@ -49,13 +49,13 @@
}
},
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}
},
Expand Down Expand Up @@ -87,13 +87,13 @@
}
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}
},
Expand All @@ -109,7 +109,7 @@
"id": "ImportSagemakerRole",
"path": "integ-stepfunctions-sagemaker/TrainTask/SagemakerRole/ImportSagemakerRole",
"constructInfo": {
"fqn": "@aws-cdk/core.Resource",
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}
},
Expand Down Expand Up @@ -156,7 +156,7 @@
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},
Expand Down Expand Up @@ -264,25 +264,25 @@
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}
},
Expand All @@ -298,7 +298,7 @@
"id": "ImportRole",
"path": "integ-stepfunctions-sagemaker/StateMachine/Role/ImportRole",
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}
},
Expand All @@ -323,7 +323,7 @@
}
},
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}
},
Expand Down Expand Up @@ -399,19 +399,19 @@
}
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}
},
Expand All @@ -421,12 +421,6 @@
"attributes": {
"aws:cdk:cloudformation:type": "AWS::StepFunctions::StateMachine",
"aws:cdk:cloudformation:props": {
"roleArn": {
"Fn::GetAtt": [
"StateMachineRoleB840431D",
"Arn"
]
},
"definitionString": {
"Fn::Join": [
"",
Expand All @@ -442,7 +436,7 @@
"Arn"
]
},
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{
"Ref": "AWS::Region"
},
Expand All @@ -469,47 +463,53 @@
"/result/\"},\"ResourceConfig\":{\"InstanceCount\":1,\"InstanceType\":\"ml.m4.xlarge\",\"VolumeSizeInGB\":10},\"StoppingCondition\":{\"MaxRuntimeInSeconds\":3600}}}}}"
]
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"id": "stateMachineArn",
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}
},
Expand All @@ -518,12 +518,12 @@
"path": "Tree",
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"fqn": "aws-cdk-lib.App",
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}
}
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Expand Up @@ -2,7 +2,7 @@ import { Key } from 'aws-cdk-lib/aws-kms';
import { Bucket, BucketEncryption } from 'aws-cdk-lib/aws-s3';
import { StateMachine } from 'aws-cdk-lib/aws-stepfunctions';
import { App, CfnOutput, RemovalPolicy, Stack } from 'aws-cdk-lib';
import { S3Location, SageMakerCreateTrainingJob } from 'aws-cdk-lib/aws-stepfunctions-tasks';
import { S3Location, SageMakerCreateTrainingJob, InputMode } from 'aws-cdk-lib/aws-stepfunctions-tasks';

/*
* Creates a state machine with a task state to create a training job in AWS SageMaker
Expand Down Expand Up @@ -35,7 +35,8 @@ const trainingData = new Bucket(stack, 'TrainingData', {
const sm = new StateMachine(stack, 'StateMachine', {
definition: new SageMakerCreateTrainingJob(stack, 'TrainTask', {
algorithmSpecification: {
algorithmName: 'arn:aws:sagemaker:us-east-1:865070037744:algorithm/scikit-decision-trees-15423055-57b73412d2e93e9239e4e16f83298b8f',
algorithmName: 'BlazingText',
trainingInputMode: InputMode.FAST_FILE,
},
inputDataConfig: [{
channelName: 'InputData',
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6 changes: 6 additions & 0 deletions packages/aws-cdk-lib/aws-stepfunctions-tasks/README.md
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Expand Up @@ -1060,6 +1060,12 @@ new tasks.SageMakerCreateTrainingJob(this, 'TrainSagemaker', {
});
```

You can specify [TrainingInputMode](https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_AlgorithmSpecification.html#API_AlgorithmSpecification_Contents) via the trainingInputMode property.

- To download the data from Amazon Simple Storage Service (Amazon S3) to the provisioned ML storage volume, and mount the directory to a Docker volume, choose `InputMode.FILE` if an algorithm supports it.
- To stream data directly from Amazon S3 to the container, choose `InputMode.PIPE` if an algorithm supports it.
- To stream data directly from Amazon S3 to the container with no code changes and to provide file system access to the data, choose `InputMode.FAST_FILE` if an algorithm supports it.

### Create Transform Job

You can call the [`CreateTransformJob`](https://docs.aws.amazon.com/sagemaker/latest/dg/API_CreateTransformJob.html) API from a `Task` state.
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Expand Up @@ -464,7 +464,12 @@ export enum InputMode {
/**
* File mode.
*/
FILE = 'File'
FILE = 'File',

/**
* FastFile mode.
*/
FAST_FILE = 'FastFile'
}

/**
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Expand Up @@ -134,7 +134,7 @@ test('create complex training job', () => {
role,
algorithmSpecification: {
algorithmName: 'BlazingText',
trainingInputMode: tasks.InputMode.FILE,
trainingInputMode: tasks.InputMode.FAST_FILE,
metricDefinitions: [
{
name: 'mymetric', regex: 'regex_pattern',
Expand Down Expand Up @@ -218,7 +218,7 @@ test('create complex training job', () => {
TrainingJobName: 'MyTrainJob',
RoleArn: { 'Fn::GetAtt': ['Role1ABCC5F0', 'Arn'] },
AlgorithmSpecification: {
TrainingInputMode: 'File',
TrainingInputMode: 'FastFile',
AlgorithmName: 'BlazingText',
MetricDefinitions: [
{ Name: 'mymetric', Regex: 'regex_pattern' },
Expand Down

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