Amazon SageMaker Sagemaker Compilation Job API

openapi: 3.1.0
info:
  title: Amazon SageMaker Service Compilation Job API
  version: '2017-07-24'
  description: Generated from AWS's published Smithy model for Amazon SageMaker Service. 5 operation(s).
  contact:
    name: Amazon Web Services
    url: https://aws.amazon.com/contact-us/
  license:
    name: Apache 2.0
    identifier: Apache-2.0
    url: https://github.com/aws/api-models-aws/blob/main/LICENSE
servers:
- url: https://api.sagemaker.{region}.amazonaws.com
  variables:
    region:
      default: us-east-1
security:
- sigv4: []
paths:
  /#CreateCompilationJob:
    post:
      operationId: CreateCompilationJob
      summary: Create Compilation Job
      description: 'Starts a model compilation job. After the model has been compiled, Amazon SageMaker AI saves the resulting
        model artifacts to an Amazon Simple Storage Service (Amazon S3) bucket that you specify. If you choose to host your
        model using Amazon SageMaker AI hosting services, you can use the resulting model artifacts as part of the model.
        You can also use the artifacts with Amazon Web Services IoT Greengrass. In that case, deploy them as an ML resource.
        In the request body, you provide the following: A name for the compilation job Information about the input model artifacts
        The output location for the compiled model and the device (target) that the model runs on The Amazon Resource Name
        (ARN) of the IAM role that Amazon SageMaker AI assumes to perform the model compilation job. You can also provide
        a Tag to track the model compilation job''s resource use and costs. The response body contains the CompilationJobArn
        for the compiled job. To stop a model compilation job, use StopCompilationJob. To get information about a particular
        model compilation job, use DescribeCompilationJob. To get information about multiple model compilation jobs, use ListCompilationJobs.'
      responses:
        '200':
          description: Success
          content:
            application/x-amz-json-1.1:
              schema:
                $ref: '#/components/schemas/CreateCompilationJobResponse'
        '400':
          description: ResourceInUse; ResourceLimitExceeded
          content:
            application/x-amz-json-1.1:
              schema:
                $ref: '#/components/schemas/ResourceInUse'
      parameters:
      - name: X-Amz-Target
        in: header
        required: true
        schema:
          type: string
          enum:
          - SageMaker.CreateCompilationJob
      requestBody:
        required: true
        content:
          application/x-amz-json-1.1:
            schema:
              $ref: '#/components/schemas/CreateCompilationJobRequest'
      tags:
      - Compilation Job
  /#DeleteCompilationJob:
    post:
      operationId: DeleteCompilationJob
      summary: Delete Compilation Job
      description: Deletes the specified compilation job. This action deletes only the compilation job resource in Amazon
        SageMaker AI. It doesn't delete other resources that are related to that job, such as the model artifacts that the
        job creates, the compilation logs in CloudWatch, the compiled model, or the IAM role. You can delete a compilation
        job only if its current status is COMPLETED, FAILED, or STOPPED. If the job status is STARTING or INPROGRESS, stop
        the job, and then delete it after its status becomes STOPPED.
      responses:
        '200':
          description: Success
          content:
            application/x-amz-json-1.1:
              schema:
                type: string
        '400':
          description: ResourceNotFound
          content:
            application/x-amz-json-1.1:
              schema:
                $ref: '#/components/schemas/ResourceNotFound'
      parameters:
      - name: X-Amz-Target
        in: header
        required: true
        schema:
          type: string
          enum:
          - SageMaker.DeleteCompilationJob
      requestBody:
        required: true
        content:
          application/x-amz-json-1.1:
            schema:
              $ref: '#/components/schemas/DeleteCompilationJobRequest'
      tags:
      - Compilation Job
  /#DescribeCompilationJob:
    post:
      operationId: DescribeCompilationJob
      summary: Describe Compilation Job
      description: Returns information about a model compilation job. To create a model compilation job, use CreateCompilationJob.
        To get information about multiple model compilation jobs, use ListCompilationJobs.
      responses:
        '200':
          description: Success
          content:
            application/x-amz-json-1.1:
              schema:
                $ref: '#/components/schemas/DescribeCompilationJobResponse'
        '400':
          description: ResourceNotFound
          content:
            application/x-amz-json-1.1:
              schema:
                $ref: '#/components/schemas/ResourceNotFound'
      parameters:
      - name: X-Amz-Target
        in: header
        required: true
        schema:
          type: string
          enum:
          - SageMaker.DescribeCompilationJob
      requestBody:
        required: true
        content:
          application/x-amz-json-1.1:
            schema:
              $ref: '#/components/schemas/DescribeCompilationJobRequest'
      tags:
      - Compilation Job
  /#ListCompilationJobs:
    post:
      operationId: ListCompilationJobs
      summary: List Compilation Jobs
      description: Lists model compilation jobs that satisfy various filters. To create a model compilation job, use CreateCompilationJob.
        To get information about a particular model compilation job you have created, use DescribeCompilationJob.
      responses:
        '200':
          description: Success
          content:
            application/x-amz-json-1.1:
              schema:
                $ref: '#/components/schemas/ListCompilationJobsResponse'
      parameters:
      - name: X-Amz-Target
        in: header
        required: true
        schema:
          type: string
          enum:
          - SageMaker.ListCompilationJobs
      requestBody:
        required: true
        content:
          application/x-amz-json-1.1:
            schema:
              $ref: '#/components/schemas/ListCompilationJobsRequest'
      tags:
      - Compilation Job
  /#StopCompilationJob:
    post:
      operationId: StopCompilationJob
      summary: Stop Compilation Job
      description: Stops a model compilation job. To stop a job, Amazon SageMaker AI sends the algorithm the SIGTERM signal.
        This gracefully shuts the job down. If the job hasn't stopped, it sends the SIGKILL signal. When it receives a StopCompilationJob
        request, Amazon SageMaker AI changes the CompilationJobStatus of the job to Stopping. After Amazon SageMaker stops
        the job, it sets the CompilationJobStatus to Stopped.
      responses:
        '200':
          description: Success
          content:
            application/x-amz-json-1.1:
              schema:
                type: string
        '400':
          description: ResourceNotFound
          content:
            application/x-amz-json-1.1:
              schema:
                $ref: '#/components/schemas/ResourceNotFound'
      parameters:
      - name: X-Amz-Target
        in: header
        required: true
        schema:
          type: string
          enum:
          - SageMaker.StopCompilationJob
      requestBody:
        required: true
        content:
          application/x-amz-json-1.1:
            schema:
              $ref: '#/components/schemas/StopCompilationJobRequest'
      tags:
      - Compilation Job
components:
  securitySchemes:
    sigv4:
      type: apiKey
      in: header
      name: Authorization
      description: AWS Signature Version 4. The Authorization header carries an AWS4-HMAC-SHA256 signature over the canonical
        request, with X-Amz-Date (and X-Amz-Security-Token for temporary credentials). Not a bearer token.
      x-aws-sigv4:
        signingName: sagemaker
  schemas:
    CompilationJobSummary:
      type: object
      properties:
        CompilationJobName:
          type: string
          description: The name of the model compilation job that you want a summary for.
        CompilationJobArn:
          type: string
          description: The Amazon Resource Name (ARN) of the model compilation job.
        CreationTime:
          type: string
          format: date-time
          description: The time when the model compilation job was created.
        CompilationStartTime:
          type: string
          format: date-time
          description: The time when the model compilation job started.
        CompilationEndTime:
          type: string
          format: date-time
          description: The time when the model compilation job completed.
        CompilationTargetDevice:
          type: string
          enum:
          - lambda
          - ml_m4
          - ml_m5
          - ml_m6g
          - ml_c4
          - ml_c5
          - ml_c6g
          - ml_p2
          - ml_p3
          - ml_g4dn
          - ml_inf1
          - ml_inf2
          - ml_trn1
          - ml_eia2
          - jetson_tx1
          - jetson_tx2
          - jetson_nano
          - jetson_xavier
          - rasp3b
          - rasp4b
          - imx8qm
          - deeplens
          - rk3399
          - rk3288
          - aisage
          - sbe_c
          - qcs605
          - qcs603
          - sitara_am57x
          - amba_cv2
          - amba_cv22
          - amba_cv25
          - x86_win32
          - x86_win64
          - coreml
          - jacinto_tda4vm
          - imx8mplus
          description: The type of device that the model will run on after the compilation job has completed.
        CompilationTargetPlatformOs:
          type: string
          enum:
          - ANDROID
          - LINUX
          description: The type of OS that the model will run on after the compilation job has completed.
        CompilationTargetPlatformArch:
          type: string
          enum:
          - X86_64
          - X86
          - ARM64
          - ARM_EABI
          - ARM_EABIHF
          description: The type of architecture that the model will run on after the compilation job has completed.
        CompilationTargetPlatformAccelerator:
          type: string
          enum:
          - INTEL_GRAPHICS
          - MALI
          - NVIDIA
          - NNA
          description: The type of accelerator that the model will run on after the compilation job has completed.
        LastModifiedTime:
          type: string
          format: date-time
          description: The time when the model compilation job was last modified.
        CompilationJobStatus:
          type: string
          enum:
          - INPROGRESS
          - COMPLETED
          - FAILED
          - STARTING
          - STOPPING
          - STOPPED
          description: The status of the model compilation job.
      required:
      - CompilationJobName
      - CompilationJobArn
      - CreationTime
      - CompilationJobStatus
    CreateCompilationJobRequest:
      type: object
      properties:
        CompilationJobName:
          type: string
          description: A name for the model compilation job. The name must be unique within the Amazon Web Services Region
            and within your Amazon Web Services account.
        RoleArn:
          type: string
          description: 'The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker AI to perform tasks on
            your behalf. During model compilation, Amazon SageMaker AI needs your permission to: Read input data from an S3
            bucket Write model artifacts to an S3 bucket Write logs to Amazon CloudWatch Logs Publish metrics to Amazon CloudWatch
            You grant permissions for all of these tasks to an IAM role. To pass this role to Amazon SageMaker AI, the caller
            of this API must have the iam:PassRole permission. For more information, see Amazon SageMaker AI Roles.'
        ModelPackageVersionArn:
          type: string
          description: The Amazon Resource Name (ARN) of a versioned model package. Provide either a ModelPackageVersionArn
            or an InputConfig object in the request syntax. The presence of both objects in the CreateCompilationJob request
            will return an exception.
        InputConfig:
          $ref: '#/components/schemas/InputConfig'
        OutputConfig:
          $ref: '#/components/schemas/OutputConfig'
        VpcConfig:
          $ref: '#/components/schemas/NeoVpcConfig'
        StoppingCondition:
          $ref: '#/components/schemas/StoppingCondition'
        Tags:
          type: array
          items:
            $ref: '#/components/schemas/Tag'
          description: An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different
            ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
      required:
      - CompilationJobName
      - RoleArn
      - OutputConfig
      - StoppingCondition
    CreateCompilationJobResponse:
      type: object
      properties:
        CompilationJobArn:
          type: string
          description: 'If the action is successful, the service sends back an HTTP 200 response. Amazon SageMaker AI returns
            the following data in JSON format: CompilationJobArn: The Amazon Resource Name (ARN) of the compiled job.'
      required:
      - CompilationJobArn
    DeleteCompilationJobRequest:
      type: object
      properties:
        CompilationJobName:
          type: string
          description: The name of the compilation job to delete.
      required:
      - CompilationJobName
    DerivedInformation:
      type: object
      properties:
        DerivedDataInputConfig:
          type: string
          description: The data input configuration that SageMaker Neo automatically derived for the model. When SageMaker
            Neo derives this information, you don't need to specify the data input configuration when you create a compilation
            job.
    DescribeCompilationJobRequest:
      type: object
      properties:
        CompilationJobName:
          type: string
          description: The name of the model compilation job that you want information about.
      required:
      - CompilationJobName
    DescribeCompilationJobResponse:
      type: object
      properties:
        CompilationJobName:
          type: string
          description: The name of the model compilation job.
        CompilationJobArn:
          type: string
          description: The Amazon Resource Name (ARN) of the model compilation job.
        CompilationJobStatus:
          type: string
          enum:
          - INPROGRESS
          - COMPLETED
          - FAILED
          - STARTING
          - STOPPING
          - STOPPED
          description: The status of the model compilation job.
        CompilationStartTime:
          type: string
          format: date-time
          description: The time when the model compilation job started the CompilationJob instances. You are billed for the
            time between this timestamp and the timestamp in the CompilationEndTime field. In Amazon CloudWatch Logs, the
            start time might be later than this time. That's because it takes time to download the compilation job, which
            depends on the size of the compilation job container.
        CompilationEndTime:
          type: string
          format: date-time
          description: The time when the model compilation job on a compilation job instance ended. For a successful or stopped
            job, this is when the job's model artifacts have finished uploading. For a failed job, this is when Amazon SageMaker
            AI detected that the job failed.
        StoppingCondition:
          $ref: '#/components/schemas/StoppingCondition'
        InferenceImage:
          type: string
          description: The inference image to use when compiling a model. Specify an image only if the target device is a
            cloud instance.
        ModelPackageVersionArn:
          type: string
          description: The Amazon Resource Name (ARN) of the versioned model package that was provided to SageMaker Neo when
            you initiated a compilation job.
        CreationTime:
          type: string
          format: date-time
          description: The time that the model compilation job was created.
        LastModifiedTime:
          type: string
          format: date-time
          description: The time that the status of the model compilation job was last modified.
        FailureReason:
          type: string
          description: If a model compilation job failed, the reason it failed.
        ModelArtifacts:
          $ref: '#/components/schemas/ModelArtifacts'
        ModelDigests:
          $ref: '#/components/schemas/ModelDigests'
        RoleArn:
          type: string
          description: The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI assumes to perform the model
            compilation job.
        InputConfig:
          $ref: '#/components/schemas/InputConfig'
        OutputConfig:
          $ref: '#/components/schemas/OutputConfig'
        VpcConfig:
          $ref: '#/components/schemas/NeoVpcConfig'
        DerivedInformation:
          $ref: '#/components/schemas/DerivedInformation'
      required:
      - CompilationJobName
      - CompilationJobArn
      - CompilationJobStatus
      - StoppingCondition
      - CreationTime
      - LastModifiedTime
      - FailureReason
      - ModelArtifacts
      - RoleArn
      - InputConfig
      - OutputConfig
    InputConfig:
      type: object
      properties:
        S3Uri:
          type: string
          description: The S3 path where the model artifacts, which result from model training, are stored. This path must
            point to a single gzip compressed tar archive (.tar.gz suffix).
        DataInputConfig:
          type: string
          description: 'Specifies the name and shape of the expected data inputs for your trained model with a JSON dictionary
            form. The data inputs are Framework specific. TensorFlow: You must specify the name and shape (NHWC format) of
            the expected data inputs using a dictionary format for your trained model. The dictionary formats required for
            the console and CLI are different. Examples for one input: If using the console, {"input":[1,1024,1024,3]} If
            using the CLI, {\"input\":[1,1024,1024,3]} Examples for two inputs: If using the console, {"data1": [1,28,28,1],
            "data2":[1,28,28,1]} If using the CLI, {\"data1\": ['
        Framework:
          type: string
          enum:
          - TENSORFLOW
          - KERAS
          - MXNET
          - ONNX
          - PYTORCH
          - XGBOOST
          - TFLITE
          - DARKNET
          - SKLEARN
          description: 'Identifies the framework in which the model was trained. For example: TENSORFLOW.'
        FrameworkVersion:
          type: string
          description: Specifies the framework version to use. This API field is only supported for the MXNet, PyTorch, TensorFlow
            and TensorFlow Lite frameworks. For information about framework versions supported for cloud targets and edge
            devices, see Cloud Supported Instance Types and Frameworks and Edge Supported Frameworks.
      required:
      - S3Uri
      - Framework
    ListCompilationJobsRequest:
      type: object
      properties:
        NextToken:
          type: string
          description: If the result of the previous ListCompilationJobs request was truncated, the response includes a NextToken.
            To retrieve the next set of model compilation jobs, use the token in the next request.
        MaxResults:
          type: integer
          description: The maximum number of model compilation jobs to return in the response.
        CreationTimeAfter:
          type: string
          format: date-time
          description: A filter that returns the model compilation jobs that were created after a specified time.
        CreationTimeBefore:
          type: string
          format: date-time
          description: A filter that returns the model compilation jobs that were created before a specified time.
        LastModifiedTimeAfter:
          type: string
          format: date-time
          description: A filter that returns the model compilation jobs that were modified after a specified time.
        LastModifiedTimeBefore:
          type: string
          format: date-time
          description: A filter that returns the model compilation jobs that were modified before a specified time.
        NameContains:
          type: string
          description: A filter that returns the model compilation jobs whose name contains a specified string.
        StatusEquals:
          type: string
          enum:
          - INPROGRESS
          - COMPLETED
          - FAILED
          - STARTING
          - STOPPING
          - STOPPED
          description: A filter that retrieves model compilation jobs with a specific CompilationJobStatus status.
        SortBy:
          type: string
          enum:
          - Name
          - CreationTime
          - Status
          description: The field by which to sort results. The default is CreationTime.
        SortOrder:
          type: string
          enum:
          - Ascending
          - Descending
          description: The sort order for results. The default is Ascending.
    ListCompilationJobsResponse:
      type: object
      properties:
        CompilationJobSummaries:
          type: array
          items:
            $ref: '#/components/schemas/CompilationJobSummary'
          description: An array of CompilationJobSummary objects, each describing a model compilation job.
        NextToken:
          type: string
          description: If the response is truncated, Amazon SageMaker AI returns this NextToken. To retrieve the next set
            of model compilation jobs, use this token in the next request.
      required:
      - CompilationJobSummaries
    ModelArtifacts:
      type: object
      properties:
        S3ModelArtifacts:
          type: string
          description: The path of the S3 object that contains the model artifacts. For example, s3://bucket-name/keynameprefix/model.tar.gz.
      required:
      - S3ModelArtifacts
    ModelDigests:
      type: object
      properties:
        ArtifactDigest:
          type: string
          description: Provides a hash value that uniquely identifies the stored model artifacts.
    NeoVpcConfig:
      type: object
      properties:
        SecurityGroupIds:
          type: array
          items:
            type: string
          description: The VPC security group IDs. IDs have the form of sg-xxxxxxxx. Specify the security groups for the VPC
            that is specified in the Subnets field.
        Subnets:
          type: array
          items:
            type: string
          description: The ID of the subnets in the VPC that you want to connect the compilation job to for accessing the
            model in Amazon S3.
      required:
      - SecurityGroupIds
      - Subnets
    OutputConfig:
      type: object
      properties:
        S3OutputLocation:
          type: string
          description: Identifies the S3 bucket where you want Amazon SageMaker AI to store the model artifacts. For example,
            s3://bucket-name/key-name-prefix.
        TargetDevice:
          type: string
          enum:
          - lambda
          - ml_m4
          - ml_m5
          - ml_m6g
          - ml_c4
          - ml_c5
          - ml_c6g
          - ml_p2
          - ml_p3
          - ml_g4dn
          - ml_inf1
          - ml_inf2
          - ml_trn1
          - ml_eia2
          - jetson_tx1
          - jetson_tx2
          - jetson_nano
          - jetson_xavier
          - rasp3b
          - rasp4b
          - imx8qm
          - deeplens
          - rk3399
          - rk3288
          - aisage
          - sbe_c
          - qcs605
          - qcs603
          - sitara_am57x
          - amba_cv2
          - amba_cv22
          - amba_cv25
          - x86_win32
          - x86_win64
          - coreml
          - jacinto_tda4vm
          - imx8mplus
          description: Identifies the target device or the machine learning instance that you want to run your model on after
            the compilation has completed. Alternatively, you can specify OS, architecture, and accelerator using TargetPlatform
            fields. It can be used instead of TargetPlatform. Currently ml_trn1 is available only in US East (N. Virginia)
            Region, and ml_inf2 is available only in US East (Ohio) Region.
        TargetPlatform:
          $ref: '#/components/schemas/TargetPlatform'
        CompilerOptions:
          type: string
          description: 'Specifies additional parameters for compiler options in JSON format. The compiler options are TargetPlatform
            specific. It is required for NVIDIA accelerators and highly recommended for CPU compilations. For any other cases,
            it is optional to specify CompilerOptions. DTYPE: Specifies the data type for the input. When compiling for ml_*
            (except for ml_inf) instances using PyTorch framework, provide the data type (dtype) of the model''s input. "float32"
            is used if "DTYPE" is not specified. Options for data type are: float32: Use either "float" or "float32". int64:
            Use either "int64" or "long". For'
        KmsKeyId:
          type: string
          description: 'The Amazon Web Services Key Management Service key (Amazon Web Services KMS) that Amazon SageMaker
            AI uses to encrypt your output models with Amazon S3 server-side encryption after compilation job. If you don''t
            provide a KMS key ID, Amazon SageMaker AI uses the default KMS key for Amazon S3 for your role''s account. For
            more information, see KMS-Managed Encryption Keys in the Amazon Simple Storage Service Developer Guide. The KmsKeyId
            can be any of the following formats: Key ID: 1234abcd-12ab-34cd-56ef-1234567890ab Key ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-12345678'
      required:
      - S3OutputLocation
    ResourceInUse:
      type: object
      properties:
        Message:
          type: string
    ResourceNotFound:
      type: object
      properties:
        Message:
          type: string
    StopCompilationJobRequest:
      type: object
      properties:
        CompilationJobName:
          type: string
          description: The name of the model compilation job to stop.
      required:
      - CompilationJobName
    StoppingCondition:
      type: object
      properties:
        MaxRuntimeInSeconds:
          type: integer
          description: The maximum length of time, in seconds, that a training or compilation job can run before it is stopped.
            For compilation jobs, if the job does not complete during this time, a TimeOut error is generated. We recommend
            starting with 900 seconds and increasing as necessary based on your model. For all other jobs, if the job does
            not complete during this time, SageMaker ends the job. When RetryStrategy is specified in the job request, MaxRuntimeInSeconds
            specifies the maximum time for all of the attempts in total, not each individual attempt. The default value is
            1 day. The maximum value is 28 day
        MaxWaitTimeInSeconds:
          type: integer
          description: The maximum length of time, in seconds, that a managed Spot training job has to complete. It is the
            amount of time spent waiting for Spot capacity plus the amount of time the job can run. It must be equal to or
            greater than MaxRuntimeInSeconds. If the job does not complete during this time, SageMaker ends the job. When
            RetryStrategy is specified in the job request, MaxWaitTimeInSeconds specifies the maximum time for all of the
            attempts in total, not each individual attempt.
        MaxPendingTimeInSeconds:
          type: integer
          description: 'The maximum length of time, in seconds, that a training or compilation job can be pending before it
            is stopped. When working with training jobs that use capacity from training plans, not all Pending job states
            count against the MaxPendingTimeInSeconds limit. The following scenarios do not increment the MaxPendingTimeInSeconds
            counter: The plan is in a Scheduled state: Jobs queued (in Pending status) before a plan''s start date (waiting
            for scheduled start time) Between capacity reservations: Jobs temporarily back to Pending status between two capacity
            reservation periods MaxPendingTimeInSeconds'
    Tag:
      type: object
      properties:
        Key:
          type: string
          description: The tag key. Tag keys must be unique per resource.
        Value:
          type: string
          description: The tag value.
      required:
      - Key
      - Value
    TargetPlatform:
      type: object
      properties:
        Os:
          type: string
          enum:
          - ANDROID
          - LINUX
          description: 'Specifies a target platform OS. LINUX: Linux-based operating systems. ANDROID: Android operating systems.
            Android API level can be specified using the ANDROID_PLATFORM compiler option. For example, "CompilerOptions":
            {''ANDROID_PLATFORM'': 28}'
        Arch:
          type: string
          enum:
          - X86_64
          - X86
          - ARM64
          - ARM_EABI
          - ARM_EABIHF
          description: 'Specifies a target platform architecture. X86_64: 64-bit version of the x86 instruction set. X86:
            32-bit version of the x86 instruction set. ARM64: ARMv8 64-bit CPU. ARM_EABIHF: ARMv7 32-bit, Hard Float. ARM_EABI:
            ARMv7 32-bit, Soft Float. Used by Android 32-bit ARM platform.'
        Accelerator:
          type: string
          enum:
          - INTEL_GRAPHICS
          - MALI
          - NVIDIA
          - NNA
          description: 'Specifies a target platform accelerator (optional). NVIDIA: Nvidia graphics processing unit. It also
            requires gpu-code, trt-ver, cuda-ver compiler options MALI: ARM Mali graphics processor INTEL_GRAPHICS: Integrated
            Intel graphics'
      required:
      - Os
      - Arch
x-provenance:
  method: harvested
  publisher: Amazon Web Services
  source: https://raw.githubusercontent.com/aws/api-models-aws/582e55931c45b944739742a2c1620b6026dd2d13/models/sagemaker/service/2017-07-24/sagemaker-2017-07-24.json
  note: converted by smithy-to-openapi.py from AWS's Smithy model (roadmap#1001)