Amazon SageMaker Service

2020/07/24 - Amazon SageMaker Service - 3 new 12 updated api methods

Changes  Update sagemaker client to latest version

ListWorkforces (new) Link ¶

Use this operation to list all private and vendor workforces in an AWS Region. Note that you can only have one private workforce per AWS Region.

See also: AWS API Documentation

Request Syntax

client.list_workforces(
    SortBy='Name'|'CreateDate',
    SortOrder='Ascending'|'Descending',
    NameContains='string',
    NextToken='string',
    MaxResults=123
)
type SortBy

string

param SortBy

Sort workforces using the workforce name or creation date.

type SortOrder

string

param SortOrder

Sort workforces in ascending or descending order.

type NameContains

string

param NameContains

A filter you can use to search for workforces using part of the workforce name.

type NextToken

string

param NextToken

A token to resume pagination.

type MaxResults

integer

param MaxResults

The maximum number of workforces returned in the response.

rtype

dict

returns

Response Syntax

{
    'Workforces': [
        {
            'WorkforceName': 'string',
            'WorkforceArn': 'string',
            'LastUpdatedDate': datetime(2015, 1, 1),
            'SourceIpConfig': {
                'Cidrs': [
                    'string',
                ]
            },
            'SubDomain': 'string',
            'CognitoConfig': {
                'UserPool': 'string',
                'ClientId': 'string'
            },
            'OidcConfig': {
                'ClientId': 'string',
                'Issuer': 'string',
                'AuthorizationEndpoint': 'string',
                'TokenEndpoint': 'string',
                'UserInfoEndpoint': 'string',
                'LogoutEndpoint': 'string',
                'JwksUri': 'string'
            },
            'CreateDate': datetime(2015, 1, 1)
        },
    ],
    'NextToken': 'string'
}

Response Structure

  • (dict) --

    • Workforces (list) --

      A list containing information about your workforce.

      • (dict) --

        A single private workforce, which is automatically created when you create your first private work team. You can create one private work force in each AWS Region. By default, any workforce-related API operation used in a specific region will apply to the workforce created in that region. To learn how to create a private workforce, see Create a Private Workforce.

        • WorkforceName (string) --

          The name of the private workforce.

        • WorkforceArn (string) --

          The Amazon Resource Name (ARN) of the private workforce.

        • LastUpdatedDate (datetime) --

          The most recent date that was used to successfully add one or more IP address ranges ( CIDRs ) to a private workforce's allow list.

        • SourceIpConfig (dict) --

          A list of one to ten IP address ranges ( CIDRs ) to be added to the workforce allow list.

          • Cidrs (list) --

            A list of one to ten Classless Inter-Domain Routing (CIDR) values.

            Maximum: Ten CIDR values

            Note

            The following Length Constraints apply to individual CIDR values in the CIDR value list.

            • (string) --

        • SubDomain (string) --

          The subdomain for your OIDC Identity Provider.

        • CognitoConfig (dict) --

          The configuration of an Amazon Cognito workforce. A single Cognito workforce is created using and corresponds to a single Amazon Cognito user pool.

          • UserPool (string) --

            A user pool is a user directory in Amazon Cognito. With a user pool, your users can sign in to your web or mobile app through Amazon Cognito. Your users can also sign in through social identity providers like Google, Facebook, Amazon, or Apple, and through SAML identity providers.

          • ClientId (string) --

            The client ID for your Amazon Cognito user pool.

        • OidcConfig (dict) --

          The configuration of an OIDC Identity Provider (IdP) private workforce.

          • ClientId (string) --

            The OIDC IdP client ID used to configure your private workforce.

          • Issuer (string) --

            The OIDC IdP issuer used to configure your private workforce.

          • AuthorizationEndpoint (string) --

            The OIDC IdP authorization endpoint used to configure your private workforce.

          • TokenEndpoint (string) --

            The OIDC IdP token endpoint used to configure your private workforce.

          • UserInfoEndpoint (string) --

            The OIDC IdP user information endpoint used to configure your private workforce.

          • LogoutEndpoint (string) --

            The OIDC IdP logout endpoint used to configure your private workforce.

          • JwksUri (string) --

            The OIDC IdP JSON Web Key Set (Jwks) URI used to configure your private workforce.

        • CreateDate (datetime) --

          The date that the workforce is created.

    • NextToken (string) --

      A token to resume pagination.

DeleteWorkforce (new) Link ¶

Use this operation to delete a workforce.

If you want to create a new workforce in an AWS Region where the a workforce already exists, use this operation to delete the existing workforce and then use to create a new workforce.

See also: AWS API Documentation

Request Syntax

client.delete_workforce(
    WorkforceName='string'
)
type WorkforceName

string

param WorkforceName

[REQUIRED]

The name of the workforce.

rtype

dict

returns

Response Syntax

{}

Response Structure

  • (dict) --

CreateWorkforce (new) Link ¶

Use this operation to create a workforce. This operation will return an error if a workforce already exists in the AWS Region that you specify. You can only create one workforce in each AWS Region.

If you want to create a new workforce in an AWS Region where the a workforce already exists, use the API operation to delete the existing workforce and then use this operation to create a new workforce.

To create a private workforce using Amazon Cognito, you must specify a Cognito user pool in CognitoConfig . You can also create an Amazon Cognito workforce using the Amazon SageMaker console. For more information, see Create a Private Workforce (Amazon Cognito).

To create a private workforce using your own OIDC Identity Provider (IdP), specify your IdP configuration in OidcConfig . You must create a OIDC IdP workforce using this API operation. For more information, see Create a Private Workforce (OIDC IdP).

See also: AWS API Documentation

Request Syntax

client.create_workforce(
    CognitoConfig={
        'UserPool': 'string',
        'ClientId': 'string'
    },
    OidcConfig={
        'ClientId': 'string',
        'ClientSecret': 'string',
        'Issuer': 'string',
        'AuthorizationEndpoint': 'string',
        'TokenEndpoint': 'string',
        'UserInfoEndpoint': 'string',
        'LogoutEndpoint': 'string',
        'JwksUri': 'string'
    },
    SourceIpConfig={
        'Cidrs': [
            'string',
        ]
    },
    WorkforceName='string',
    Tags=[
        {
            'Key': 'string',
            'Value': 'string'
        },
    ]
)
type CognitoConfig

dict

param CognitoConfig

Use this parameter to configure an Amazon Cognito private workforce. A single Cognito workforce is created using and corresponds to a single Amazon Cognito user pool.

Do not use OidcConfig if you specify values for CognitoConfig .

  • UserPool (string) -- [REQUIRED]

    A user pool is a user directory in Amazon Cognito. With a user pool, your users can sign in to your web or mobile app through Amazon Cognito. Your users can also sign in through social identity providers like Google, Facebook, Amazon, or Apple, and through SAML identity providers.

  • ClientId (string) -- [REQUIRED]

    The client ID for your Amazon Cognito user pool.

type OidcConfig

dict

param OidcConfig

Use this parameter to configure a private workforce using your own OIDC Identity Provider. Do not use CognitoConfig if you specify values for OidcConfig .

  • ClientId (string) -- [REQUIRED]

    The OIDC IdP client ID used to configure your private workforce.

  • ClientSecret (string) -- [REQUIRED]

    The OIDC IdP client secret used to configure your private workforce.

  • Issuer (string) -- [REQUIRED]

    The OIDC IdP issuer used to configure your private workforce.

  • AuthorizationEndpoint (string) -- [REQUIRED]

    The OIDC IdP authorization endpoint used to configure your private workforce.

  • TokenEndpoint (string) -- [REQUIRED]

    The OIDC IdP token endpoint used to configure your private workforce.

  • UserInfoEndpoint (string) -- [REQUIRED]

    The OIDC IdP user information endpoint used to configure your private workforce.

  • LogoutEndpoint (string) -- [REQUIRED]

    The OIDC IdP logout endpoint used to configure your private workforce.

  • JwksUri (string) -- [REQUIRED]

    The OIDC IdP JSON Web Key Set (Jwks) URI used to configure your private workforce.

type SourceIpConfig

dict

param SourceIpConfig

A list of IP address ranges ( CIDRs ). Used to create an allow list of IP addresses for a private workforce. For more information, see .

  • Cidrs (list) -- [REQUIRED]

    A list of one to ten Classless Inter-Domain Routing (CIDR) values.

    Maximum: Ten CIDR values

    Note

    The following Length Constraints apply to individual CIDR values in the CIDR value list.

    • (string) --

type WorkforceName

string

param WorkforceName

[REQUIRED]

The name of the private workforce.

type Tags

list

param Tags

An array of key-value pairs that contain metadata to help you categorize and organize our workforce. Each tag consists of a key and a value, both of which you define.

  • (dict) --

    Describes a tag.

    • Key (string) -- [REQUIRED]

      The tag key.

    • Value (string) -- [REQUIRED]

      The tag value.

rtype

dict

returns

Response Syntax

{
    'WorkforceArn': 'string'
}

Response Structure

  • (dict) --

    • WorkforceArn (string) --

      The Amazon Resource Name (ARN) of the workforce.

CreateCompilationJob (updated) Link ¶
Changes (request)
{'OutputConfig': {'CompilerOptions': 'string',
                  'TargetDevice': {'ml_g4dn', 'x86_win32', 'x86_win64'},
                  'TargetPlatform': {'Accelerator': 'INTEL_GRAPHICS | MALI | '
                                                    'NVIDIA',
                                     'Arch': 'X86_64 | X86 | ARM64 | ARM_EABI '
                                             '| ARM_EABIHF',
                                     'Os': 'ANDROID | LINUX'}}}

Starts a model compilation job. After the model has been compiled, Amazon SageMaker 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 hosting services, you can use the resulting model artifacts as part of the model. You can also use the artifacts with AWS 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 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.

See also: AWS API Documentation

Request Syntax

client.create_compilation_job(
    CompilationJobName='string',
    RoleArn='string',
    InputConfig={
        'S3Uri': 'string',
        'DataInputConfig': 'string',
        'Framework': 'TENSORFLOW'|'KERAS'|'MXNET'|'ONNX'|'PYTORCH'|'XGBOOST'|'TFLITE'
    },
    OutputConfig={
        'S3OutputLocation': 'string',
        'TargetDevice': 'lambda'|'ml_m4'|'ml_m5'|'ml_c4'|'ml_c5'|'ml_p2'|'ml_p3'|'ml_g4dn'|'ml_inf1'|'jetson_tx1'|'jetson_tx2'|'jetson_nano'|'jetson_xavier'|'rasp3b'|'imx8qm'|'deeplens'|'rk3399'|'rk3288'|'aisage'|'sbe_c'|'qcs605'|'qcs603'|'sitara_am57x'|'amba_cv22'|'x86_win32'|'x86_win64',
        'TargetPlatform': {
            'Os': 'ANDROID'|'LINUX',
            'Arch': 'X86_64'|'X86'|'ARM64'|'ARM_EABI'|'ARM_EABIHF',
            'Accelerator': 'INTEL_GRAPHICS'|'MALI'|'NVIDIA'
        },
        'CompilerOptions': 'string'
    },
    StoppingCondition={
        'MaxRuntimeInSeconds': 123,
        'MaxWaitTimeInSeconds': 123
    }
)
type CompilationJobName

string

param CompilationJobName

[REQUIRED]

A name for the model compilation job. The name must be unique within the AWS Region and within your AWS account.

type RoleArn

string

param RoleArn

[REQUIRED]

The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker to perform tasks on your behalf.

During model compilation, Amazon SageMaker 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, the caller of this API must have the iam:PassRole permission. For more information, see Amazon SageMaker Roles.

type InputConfig

dict

param InputConfig

[REQUIRED]

Provides information about the location of input model artifacts, the name and shape of the expected data inputs, and the framework in which the model was trained.

  • S3Uri (string) -- [REQUIRED]

    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 (string) -- [REQUIRED]

    Specifies the name and shape of the expected data inputs for your trained model with a JSON dictionary form. The data inputs are InputConfig$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\": [1,28,28,1], \"data2\":[1,28,28,1]}

    • KERAS : You must specify the name and shape (NCHW format) of expected data inputs using a dictionary format for your trained model. Note that while Keras model artifacts should be uploaded in NHWC (channel-last) format, DataInputConfig should be specified in NCHW (channel-first) format. The dictionary formats required for the console and CLI are different.

      • Examples for one input:

        • If using the console, {"input_1":[1,3,224,224]}

        • If using the CLI, {\"input_1\":[1,3,224,224]}

      • Examples for two inputs:

        • If using the console, {"input_1": [1,3,224,224], "input_2":[1,3,224,224]}

        • If using the CLI, {\"input_1\": [1,3,224,224], \"input_2\":[1,3,224,224]}

    • MXNET/ONNX : You must specify the name and shape (NCHW format) of the expected data inputs in order 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, {"data":[1,3,1024,1024]}

        • If using the CLI, {\"data\":[1,3,1024,1024]}

      • Examples for two inputs:

        • If using the console, {"var1": [1,1,28,28], "var2":[1,1,28,28]}

        • If using the CLI, {\"var1\": [1,1,28,28], \"var2\":[1,1,28,28]}

    • PyTorch : You can either specify the name and shape (NCHW format) of expected data inputs in order using a dictionary format for your trained model or you can specify the shape only using a list format. The dictionary formats required for the console and CLI are different. The list formats for the console and CLI are the same.

      • Examples for one input in dictionary format:

        • If using the console, {"input0":[1,3,224,224]}

        • If using the CLI, {\"input0\":[1,3,224,224]}

      • Example for one input in list format: [[1,3,224,224]]

      • Examples for two inputs in dictionary format:

        • If using the console, {"input0":[1,3,224,224], "input1":[1,3,224,224]}

        • If using the CLI, {\"input0\":[1,3,224,224], \"input1\":[1,3,224,224]}

      • Example for two inputs in list format: [[1,3,224,224], [1,3,224,224]]

    • XGBOOST : input data name and shape are not needed.

  • Framework (string) -- [REQUIRED]

    Identifies the framework in which the model was trained. For example: TENSORFLOW.

type OutputConfig

dict

param OutputConfig

[REQUIRED]

Provides information about the output location for the compiled model and the target device the model runs on.

  • S3OutputLocation (string) -- [REQUIRED]

    Identifies the S3 bucket where you want Amazon SageMaker to store the model artifacts. For example, s3://bucket-name/key-name-prefix .

  • TargetDevice (string) --

    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 .

  • TargetPlatform (dict) --

    Contains information about a target platform that you want your model to run on, such as OS, architecture, and accelerators. It is an alternative of TargetDevice .

    The following examples show how to configure the TargetPlatform and CompilerOptions JSON strings for popular target platforms:

    • Raspberry Pi 3 Model B+ "TargetPlatform": {"Os": "LINUX", "Arch": "ARM_EABIHF"}, "CompilerOptions": {'mattr': ['+neon']}

    • Jetson TX2 "TargetPlatform": {"Os": "LINUX", "Arch": "ARM64", "Accelerator": "NVIDIA"}, "CompilerOptions": {'gpu-code': 'sm_62', 'trt-ver': '6.0.1', 'cuda-ver': '10.0'}

    • EC2 m5.2xlarge instance OS "TargetPlatform": {"Os": "LINUX", "Arch": "X86_64", "Accelerator": "NVIDIA"}, "CompilerOptions": {'mcpu': 'skylake-avx512'}

    • RK3399 "TargetPlatform": {"Os": "LINUX", "Arch": "ARM64", "Accelerator": "MALI"}

    • ARMv7 phone (CPU) "TargetPlatform": {"Os": "ANDROID", "Arch": "ARM_EABI"}, "CompilerOptions": {'ANDROID_PLATFORM': 25, 'mattr': ['+neon']}

    • ARMv8 phone (CPU) "TargetPlatform": {"Os": "ANDROID", "Arch": "ARM64"}, "CompilerOptions": {'ANDROID_PLATFORM': 29}

    • Os (string) -- [REQUIRED]

      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 (string) -- [REQUIRED]

      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 (string) --

      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

  • CompilerOptions (string) --

    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 compliations. For any other cases, it is optional to specify CompilerOptions.

    • CPU : Compilation for CPU supports the following compiler options.

      • mcpu : CPU micro-architecture. For example, {'mcpu': 'skylake-avx512'}

      • mattr : CPU flags. For example, {'mattr': ['+neon', '+vfpv4']}

    • ARM : Details of ARM CPU compilations.

      • NEON : NEON is an implementation of the Advanced SIMD extension used in ARMv7 processors. For example, add {'mattr': ['+neon']} to the compiler options if compiling for ARM 32-bit platform with the NEON support.

    • NVIDIA : Compilation for NVIDIA GPU supports the following compiler options.

      • gpu_code : Specifies the targeted architecture.

      • trt-ver : Specifies the TensorRT versions in x.y.z. format.

      • cuda-ver : Specifies the CUDA version in x.y format.

    For example, {'gpu-code': 'sm_72', 'trt-ver': '6.0.1', 'cuda-ver': '10.1'}

    • ANDROID : Compilation for the Android OS supports the following compiler options:

      • ANDROID_PLATFORM : Specifies the Android API levels. Available levels range from 21 to 29. For example, {'ANDROID_PLATFORM': 28} .

      • mattr : Add {'mattr': ['+neon']} to compiler options if compiling for ARM 32-bit platform with NEON support.

type StoppingCondition

dict

param StoppingCondition

[REQUIRED]

Specifies a limit to how long a model compilation job can run. When the job reaches the time limit, Amazon SageMaker ends the compilation job. Use this API to cap model training costs.

  • MaxRuntimeInSeconds (integer) --

    The maximum length of time, in seconds, that the training or compilation job can run. If job does not complete during this time, Amazon SageMaker ends the job. If value is not specified, default value is 1 day. The maximum value is 28 days.

  • MaxWaitTimeInSeconds (integer) --

    The maximum length of time, in seconds, how long you are willing to wait for a managed spot training job to complete. It is the amount of time spent waiting for Spot capacity plus the amount of time the training job runs. It must be equal to or greater than MaxRuntimeInSeconds .

rtype

dict

returns

Response Syntax

{
    'CompilationJobArn': 'string'
}

Response Structure

  • (dict) --

    • CompilationJobArn (string) --

      If the action is successful, the service sends back an HTTP 200 response. Amazon SageMaker returns the following data in JSON format:

      • CompilationJobArn : The Amazon Resource Name (ARN) of the compiled job.

CreateWorkteam (updated) Link ¶
Changes (request)
{'MemberDefinitions': {'OidcMemberDefinition': {'Groups': ['string']}},
 'WorkforceName': 'string'}

Creates a new work team for labeling your data. A work team is defined by one or more Amazon Cognito user pools. You must first create the user pools before you can create a work team.

You cannot create more than 25 work teams in an account and region.

See also: AWS API Documentation

Request Syntax

client.create_workteam(
    WorkteamName='string',
    WorkforceName='string',
    MemberDefinitions=[
        {
            'CognitoMemberDefinition': {
                'UserPool': 'string',
                'UserGroup': 'string',
                'ClientId': 'string'
            },
            'OidcMemberDefinition': {
                'Groups': [
                    'string',
                ]
            }
        },
    ],
    Description='string',
    NotificationConfiguration={
        'NotificationTopicArn': 'string'
    },
    Tags=[
        {
            'Key': 'string',
            'Value': 'string'
        },
    ]
)
type WorkteamName

string

param WorkteamName

[REQUIRED]

The name of the work team. Use this name to identify the work team.

type WorkforceName

string

param WorkforceName

The name of the workforce.

type MemberDefinitions

list

param MemberDefinitions

[REQUIRED]

A list of MemberDefinition objects that contains objects that identify the Amazon Cognito user pool that makes up the work team. For more information, see Amazon Cognito User Pools.

All of the CognitoMemberDefinition objects that make up the member definition must have the same ClientId and UserPool values.

  • (dict) --

    Defines the Amazon Cognito user group that is part of a work team.

    • CognitoMemberDefinition (dict) --

      The Amazon Cognito user group that is part of the work team.

      • UserPool (string) -- [REQUIRED]

        An identifier for a user pool. The user pool must be in the same region as the service that you are calling.

      • UserGroup (string) -- [REQUIRED]

        An identifier for a user group.

      • ClientId (string) -- [REQUIRED]

        An identifier for an application client. You must create the app client ID using Amazon Cognito.

    • OidcMemberDefinition (dict) --

      A list user groups that exist in your OIDC Identity Provider (IdP). One to ten groups can be used to create a single private work team. When you add a user group to the list of Groups , you can add that user group to one or more private work teams. If you add a user group to a private work team, all workers in that user group are added to the work team.

      • Groups (list) -- [REQUIRED]

        A list of comma seperated strings that identifies user groups in your OIDC IdP. Each user group is made up of a group of private workers.

        • (string) --

type Description

string

param Description

[REQUIRED]

A description of the work team.

type NotificationConfiguration

dict

param NotificationConfiguration

Configures notification of workers regarding available or expiring work items.

  • NotificationTopicArn (string) --

    The ARN for the SNS topic to which notifications should be published.

type Tags

list

param Tags

An array of key-value pairs.

For more information, see Resource Tag and Using Cost Allocation Tags in the AWS Billing and Cost Management User Guide .

  • (dict) --

    Describes a tag.

    • Key (string) -- [REQUIRED]

      The tag key.

    • Value (string) -- [REQUIRED]

      The tag value.

rtype

dict

returns

Response Syntax

{
    'WorkteamArn': 'string'
}

Response Structure

  • (dict) --

    • WorkteamArn (string) --

      The Amazon Resource Name (ARN) of the work team. You can use this ARN to identify the work team.

DescribeCompilationJob (updated) Link ¶
Changes (response)
{'OutputConfig': {'CompilerOptions': 'string',
                  'TargetDevice': {'ml_g4dn', 'x86_win32', 'x86_win64'},
                  'TargetPlatform': {'Accelerator': 'INTEL_GRAPHICS | MALI | '
                                                    'NVIDIA',
                                     'Arch': 'X86_64 | X86 | ARM64 | ARM_EABI '
                                             '| ARM_EABIHF',
                                     'Os': 'ANDROID | LINUX'}}}

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.

See also: AWS API Documentation

Request Syntax

client.describe_compilation_job(
    CompilationJobName='string'
)
type CompilationJobName

string

param CompilationJobName

[REQUIRED]

The name of the model compilation job that you want information about.

rtype

dict

returns

Response Syntax

{
    'CompilationJobName': 'string',
    'CompilationJobArn': 'string',
    'CompilationJobStatus': 'INPROGRESS'|'COMPLETED'|'FAILED'|'STARTING'|'STOPPING'|'STOPPED',
    'CompilationStartTime': datetime(2015, 1, 1),
    'CompilationEndTime': datetime(2015, 1, 1),
    'StoppingCondition': {
        'MaxRuntimeInSeconds': 123,
        'MaxWaitTimeInSeconds': 123
    },
    'CreationTime': datetime(2015, 1, 1),
    'LastModifiedTime': datetime(2015, 1, 1),
    'FailureReason': 'string',
    'ModelArtifacts': {
        'S3ModelArtifacts': 'string'
    },
    'RoleArn': 'string',
    'InputConfig': {
        'S3Uri': 'string',
        'DataInputConfig': 'string',
        'Framework': 'TENSORFLOW'|'KERAS'|'MXNET'|'ONNX'|'PYTORCH'|'XGBOOST'|'TFLITE'
    },
    'OutputConfig': {
        'S3OutputLocation': 'string',
        'TargetDevice': 'lambda'|'ml_m4'|'ml_m5'|'ml_c4'|'ml_c5'|'ml_p2'|'ml_p3'|'ml_g4dn'|'ml_inf1'|'jetson_tx1'|'jetson_tx2'|'jetson_nano'|'jetson_xavier'|'rasp3b'|'imx8qm'|'deeplens'|'rk3399'|'rk3288'|'aisage'|'sbe_c'|'qcs605'|'qcs603'|'sitara_am57x'|'amba_cv22'|'x86_win32'|'x86_win64',
        'TargetPlatform': {
            'Os': 'ANDROID'|'LINUX',
            'Arch': 'X86_64'|'X86'|'ARM64'|'ARM_EABI'|'ARM_EABIHF',
            'Accelerator': 'INTEL_GRAPHICS'|'MALI'|'NVIDIA'
        },
        'CompilerOptions': 'string'
    }
}

Response Structure

  • (dict) --

    • CompilationJobName (string) --

      The name of the model compilation job.

    • CompilationJobArn (string) --

      The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker assumes to perform the model compilation job.

    • CompilationJobStatus (string) --

      The status of the model compilation job.

    • CompilationStartTime (datetime) --

      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 DescribeCompilationJobResponse$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 (datetime) --

      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 detected that the job failed.

    • StoppingCondition (dict) --

      Specifies a limit to how long a model compilation job can run. When the job reaches the time limit, Amazon SageMaker ends the compilation job. Use this API to cap model training costs.

      • MaxRuntimeInSeconds (integer) --

        The maximum length of time, in seconds, that the training or compilation job can run. If job does not complete during this time, Amazon SageMaker ends the job. If value is not specified, default value is 1 day. The maximum value is 28 days.

      • MaxWaitTimeInSeconds (integer) --

        The maximum length of time, in seconds, how long you are willing to wait for a managed spot training job to complete. It is the amount of time spent waiting for Spot capacity plus the amount of time the training job runs. It must be equal to or greater than MaxRuntimeInSeconds .

    • CreationTime (datetime) --

      The time that the model compilation job was created.

    • LastModifiedTime (datetime) --

      The time that the status of the model compilation job was last modified.

    • FailureReason (string) --

      If a model compilation job failed, the reason it failed.

    • ModelArtifacts (dict) --

      Information about the location in Amazon S3 that has been configured for storing the model artifacts used in the compilation job.

      • S3ModelArtifacts (string) --

        The path of the S3 object that contains the model artifacts. For example, s3://bucket-name/keynameprefix/model.tar.gz .

    • RoleArn (string) --

      The Amazon Resource Name (ARN) of the model compilation job.

    • InputConfig (dict) --

      Information about the location in Amazon S3 of the input model artifacts, the name and shape of the expected data inputs, and the framework in which the model was trained.

      • S3Uri (string) --

        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 (string) --

        Specifies the name and shape of the expected data inputs for your trained model with a JSON dictionary form. The data inputs are InputConfig$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\": [1,28,28,1], \"data2\":[1,28,28,1]}

        • KERAS : You must specify the name and shape (NCHW format) of expected data inputs using a dictionary format for your trained model. Note that while Keras model artifacts should be uploaded in NHWC (channel-last) format, DataInputConfig should be specified in NCHW (channel-first) format. The dictionary formats required for the console and CLI are different.

          • Examples for one input:

            • If using the console, {"input_1":[1,3,224,224]}

            • If using the CLI, {\"input_1\":[1,3,224,224]}

          • Examples for two inputs:

            • If using the console, {"input_1": [1,3,224,224], "input_2":[1,3,224,224]}

            • If using the CLI, {\"input_1\": [1,3,224,224], \"input_2\":[1,3,224,224]}

        • MXNET/ONNX : You must specify the name and shape (NCHW format) of the expected data inputs in order 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, {"data":[1,3,1024,1024]}

            • If using the CLI, {\"data\":[1,3,1024,1024]}

          • Examples for two inputs:

            • If using the console, {"var1": [1,1,28,28], "var2":[1,1,28,28]}

            • If using the CLI, {\"var1\": [1,1,28,28], \"var2\":[1,1,28,28]}

        • PyTorch : You can either specify the name and shape (NCHW format) of expected data inputs in order using a dictionary format for your trained model or you can specify the shape only using a list format. The dictionary formats required for the console and CLI are different. The list formats for the console and CLI are the same.

          • Examples for one input in dictionary format:

            • If using the console, {"input0":[1,3,224,224]}

            • If using the CLI, {\"input0\":[1,3,224,224]}

          • Example for one input in list format: [[1,3,224,224]]

          • Examples for two inputs in dictionary format:

            • If using the console, {"input0":[1,3,224,224], "input1":[1,3,224,224]}

            • If using the CLI, {\"input0\":[1,3,224,224], \"input1\":[1,3,224,224]}

          • Example for two inputs in list format: [[1,3,224,224], [1,3,224,224]]

        • XGBOOST : input data name and shape are not needed.

      • Framework (string) --

        Identifies the framework in which the model was trained. For example: TENSORFLOW.

    • OutputConfig (dict) --

      Information about the output location for the compiled model and the target device that the model runs on.

      • S3OutputLocation (string) --

        Identifies the S3 bucket where you want Amazon SageMaker to store the model artifacts. For example, s3://bucket-name/key-name-prefix .

      • TargetDevice (string) --

        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 .

      • TargetPlatform (dict) --

        Contains information about a target platform that you want your model to run on, such as OS, architecture, and accelerators. It is an alternative of TargetDevice .

        The following examples show how to configure the TargetPlatform and CompilerOptions JSON strings for popular target platforms:

        • Raspberry Pi 3 Model B+ "TargetPlatform": {"Os": "LINUX", "Arch": "ARM_EABIHF"}, "CompilerOptions": {'mattr': ['+neon']}

        • Jetson TX2 "TargetPlatform": {"Os": "LINUX", "Arch": "ARM64", "Accelerator": "NVIDIA"}, "CompilerOptions": {'gpu-code': 'sm_62', 'trt-ver': '6.0.1', 'cuda-ver': '10.0'}

        • EC2 m5.2xlarge instance OS "TargetPlatform": {"Os": "LINUX", "Arch": "X86_64", "Accelerator": "NVIDIA"}, "CompilerOptions": {'mcpu': 'skylake-avx512'}

        • RK3399 "TargetPlatform": {"Os": "LINUX", "Arch": "ARM64", "Accelerator": "MALI"}

        • ARMv7 phone (CPU) "TargetPlatform": {"Os": "ANDROID", "Arch": "ARM_EABI"}, "CompilerOptions": {'ANDROID_PLATFORM': 25, 'mattr': ['+neon']}

        • ARMv8 phone (CPU) "TargetPlatform": {"Os": "ANDROID", "Arch": "ARM64"}, "CompilerOptions": {'ANDROID_PLATFORM': 29}

        • Os (string) --

          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 (string) --

          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 (string) --

          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

      • CompilerOptions (string) --

        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 compliations. For any other cases, it is optional to specify CompilerOptions.

        • CPU : Compilation for CPU supports the following compiler options.

          • mcpu : CPU micro-architecture. For example, {'mcpu': 'skylake-avx512'}

          • mattr : CPU flags. For example, {'mattr': ['+neon', '+vfpv4']}

        • ARM : Details of ARM CPU compilations.

          • NEON : NEON is an implementation of the Advanced SIMD extension used in ARMv7 processors. For example, add {'mattr': ['+neon']} to the compiler options if compiling for ARM 32-bit platform with the NEON support.

        • NVIDIA : Compilation for NVIDIA GPU supports the following compiler options.

          • gpu_code : Specifies the targeted architecture.

          • trt-ver : Specifies the TensorRT versions in x.y.z. format.

          • cuda-ver : Specifies the CUDA version in x.y format.

        For example, {'gpu-code': 'sm_72', 'trt-ver': '6.0.1', 'cuda-ver': '10.1'}

        • ANDROID : Compilation for the Android OS supports the following compiler options:

          • ANDROID_PLATFORM : Specifies the Android API levels. Available levels range from 21 to 29. For example, {'ANDROID_PLATFORM': 28} .

          • mattr : Add {'mattr': ['+neon']} to compiler options if compiling for ARM 32-bit platform with NEON support.

DescribeLabelingJob (updated) Link ¶
Changes (response)
{'LabelingJobStatus': {'Initializing'}}

Gets information about a labeling job.

See also: AWS API Documentation

Request Syntax

client.describe_labeling_job(
    LabelingJobName='string'
)
type LabelingJobName

string

param LabelingJobName

[REQUIRED]

The name of the labeling job to return information for.

rtype

dict

returns

Response Syntax

{
    'LabelingJobStatus': 'Initializing'|'InProgress'|'Completed'|'Failed'|'Stopping'|'Stopped',
    'LabelCounters': {
        'TotalLabeled': 123,
        'HumanLabeled': 123,
        'MachineLabeled': 123,
        'FailedNonRetryableError': 123,
        'Unlabeled': 123
    },
    'FailureReason': 'string',
    'CreationTime': datetime(2015, 1, 1),
    'LastModifiedTime': datetime(2015, 1, 1),
    'JobReferenceCode': 'string',
    'LabelingJobName': 'string',
    'LabelingJobArn': 'string',
    'LabelAttributeName': 'string',
    'InputConfig': {
        'DataSource': {
            'S3DataSource': {
                'ManifestS3Uri': 'string'
            }
        },
        'DataAttributes': {
            'ContentClassifiers': [
                'FreeOfPersonallyIdentifiableInformation'|'FreeOfAdultContent',
            ]
        }
    },
    'OutputConfig': {
        'S3OutputPath': 'string',
        'KmsKeyId': 'string'
    },
    'RoleArn': 'string',
    'LabelCategoryConfigS3Uri': 'string',
    'StoppingConditions': {
        'MaxHumanLabeledObjectCount': 123,
        'MaxPercentageOfInputDatasetLabeled': 123
    },
    'LabelingJobAlgorithmsConfig': {
        'LabelingJobAlgorithmSpecificationArn': 'string',
        'InitialActiveLearningModelArn': 'string',
        'LabelingJobResourceConfig': {
            'VolumeKmsKeyId': 'string'
        }
    },
    'HumanTaskConfig': {
        'WorkteamArn': 'string',
        'UiConfig': {
            'UiTemplateS3Uri': 'string',
            'HumanTaskUiArn': 'string'
        },
        'PreHumanTaskLambdaArn': 'string',
        'TaskKeywords': [
            'string',
        ],
        'TaskTitle': 'string',
        'TaskDescription': 'string',
        'NumberOfHumanWorkersPerDataObject': 123,
        'TaskTimeLimitInSeconds': 123,
        'TaskAvailabilityLifetimeInSeconds': 123,
        'MaxConcurrentTaskCount': 123,
        'AnnotationConsolidationConfig': {
            'AnnotationConsolidationLambdaArn': 'string'
        },
        'PublicWorkforceTaskPrice': {
            'AmountInUsd': {
                'Dollars': 123,
                'Cents': 123,
                'TenthFractionsOfACent': 123
            }
        }
    },
    'Tags': [
        {
            'Key': 'string',
            'Value': 'string'
        },
    ],
    'LabelingJobOutput': {
        'OutputDatasetS3Uri': 'string',
        'FinalActiveLearningModelArn': 'string'
    }
}

Response Structure

  • (dict) --

    • LabelingJobStatus (string) --

      The processing status of the labeling job.

    • LabelCounters (dict) --

      Provides a breakdown of the number of data objects labeled by humans, the number of objects labeled by machine, the number of objects than couldn't be labeled, and the total number of objects labeled.

      • TotalLabeled (integer) --

        The total number of objects labeled.

      • HumanLabeled (integer) --

        The total number of objects labeled by a human worker.

      • MachineLabeled (integer) --

        The total number of objects labeled by automated data labeling.

      • FailedNonRetryableError (integer) --

        The total number of objects that could not be labeled due to an error.

      • Unlabeled (integer) --

        The total number of objects not yet labeled.

    • FailureReason (string) --

      If the job failed, the reason that it failed.

    • CreationTime (datetime) --

      The date and time that the labeling job was created.

    • LastModifiedTime (datetime) --

      The date and time that the labeling job was last updated.

    • JobReferenceCode (string) --

      A unique identifier for work done as part of a labeling job.

    • LabelingJobName (string) --

      The name assigned to the labeling job when it was created.

    • LabelingJobArn (string) --

      The Amazon Resource Name (ARN) of the labeling job.

    • LabelAttributeName (string) --

      The attribute used as the label in the output manifest file.

    • InputConfig (dict) --

      Input configuration information for the labeling job, such as the Amazon S3 location of the data objects and the location of the manifest file that describes the data objects.

      • DataSource (dict) --

        The location of the input data.

        • S3DataSource (dict) --

          The Amazon S3 location of the input data objects.

          • ManifestS3Uri (string) --

            The Amazon S3 location of the manifest file that describes the input data objects.

      • DataAttributes (dict) --

        Attributes of the data specified by the customer.

        • ContentClassifiers (list) --

          Declares that your content is free of personally identifiable information or adult content. Amazon SageMaker may restrict the Amazon Mechanical Turk workers that can view your task based on this information.

          • (string) --

    • OutputConfig (dict) --

      The location of the job's output data and the AWS Key Management Service key ID for the key used to encrypt the output data, if any.

      • S3OutputPath (string) --

        The Amazon S3 location to write output data.

      • KmsKeyId (string) --

        The AWS Key Management Service ID of the key used to encrypt the output data, if any.

        If you use a KMS key ID or an alias of your master key, the Amazon SageMaker execution role must include permissions to call kms:Encrypt . If you don't provide a KMS key ID, Amazon SageMaker uses the default KMS key for Amazon S3 for your role's account. Amazon SageMaker uses server-side encryption with KMS-managed keys for LabelingJobOutputConfig . If you use a bucket policy with an s3:PutObject permission that only allows objects with server-side encryption, set the condition key of s3:x-amz-server-side-encryption to "aws:kms" . For more information, see KMS-Managed Encryption Keys in the Amazon Simple Storage Service Developer Guide.

        The KMS key policy must grant permission to the IAM role that you specify in your CreateLabelingJob request. For more information, see Using Key Policies in AWS KMS in the AWS Key Management Service Developer Guide .

    • RoleArn (string) --

      The Amazon Resource Name (ARN) that Amazon SageMaker assumes to perform tasks on your behalf during data labeling.

    • LabelCategoryConfigS3Uri (string) --

      The S3 location of the JSON file that defines the categories used to label data objects. Please note the following label-category limits:

      • Semantic segmentation labeling jobs using automated labeling: 20 labels

      • Box bounding labeling jobs (all): 10 labels

      The file is a JSON structure in the following format:

      {

      "document-version": "2018-11-28"

      "labels": [

      {

      "label": "label 1"

      },

      {

      "label": "label 2"

      },

      ...

      {

      "label": "label n"

      }

      ]

      }

    • StoppingConditions (dict) --

      A set of conditions for stopping a labeling job. If any of the conditions are met, the job is automatically stopped.

      • MaxHumanLabeledObjectCount (integer) --

        The maximum number of objects that can be labeled by human workers.

      • MaxPercentageOfInputDatasetLabeled (integer) --

        The maximum number of input data objects that should be labeled.

    • LabelingJobAlgorithmsConfig (dict) --

      Configuration information for automated data labeling.

      • LabelingJobAlgorithmSpecificationArn (string) --

        Specifies the Amazon Resource Name (ARN) of the algorithm used for auto-labeling. You must select one of the following ARNs:

        • Image classification arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/image-classification

        • Text classification arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/text-classification

        • Object detection arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/object-detection

        • Semantic Segmentation arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/semantic-segmentation

      • InitialActiveLearningModelArn (string) --

        At the end of an auto-label job Amazon SageMaker Ground Truth sends the Amazon Resource Nam (ARN) of the final model used for auto-labeling. You can use this model as the starting point for subsequent similar jobs by providing the ARN of the model here.

      • LabelingJobResourceConfig (dict) --

        Provides configuration information for a labeling job.

        • VolumeKmsKeyId (string) --

          The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the training job. The VolumeKmsKeyId can be any of the following formats:

          • // KMS Key ID "1234abcd-12ab-34cd-56ef-1234567890ab"

          • // Amazon Resource Name (ARN) of a KMS Key "arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"

    • HumanTaskConfig (dict) --

      Configuration information required for human workers to complete a labeling task.

      • WorkteamArn (string) --

        The Amazon Resource Name (ARN) of the work team assigned to complete the tasks.

      • UiConfig (dict) --

        Information about the user interface that workers use to complete the labeling task.

        • UiTemplateS3Uri (string) --

          The Amazon S3 bucket location of the UI template, or worker task template. This is the template used to render the worker UI and tools for labeling job tasks. For more information about the contents of a UI template, see Creating Your Custom Labeling Task Template.

        • HumanTaskUiArn (string) --

          The ARN of the worker task template used to render the worker UI and tools for labeling job tasks.

          Use this parameter when you are creating a labeling job for 3D point cloud and video fram labeling jobs. Use your labeling job task type to select one of the following ARN's and use it with this parameter when you create a labeling job. Replace aws-region with the AWS region you are creating your labeling job in.

          3D Point Cloud HumanTaskUiArns

          Use this HumanTaskUiArn for 3D point cloud object detection and 3D point cloud object detection adjustment labeling jobs.

          • arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudObjectDetection

          Use this HumanTaskUiArn for 3D point cloud object tracking and 3D point cloud object tracking adjustment labeling jobs.

          • arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudObjectTracking

          Use this HumanTaskUiArn for 3D point cloud semantic segmentation and 3D point cloud semantic segmentation adjustment labeling jobs.

          • arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudSemanticSegmentation

          Video Frame HumanTaskUiArns

          Use this HumanTaskUiArn for video frame object detection and video frame object detection adjustment labeling jobs.

          • arn:aws:sagemaker:region:394669845002:human-task-ui/VideoObjectDetection

          Use this HumanTaskUiArn for video frame object tracking and video frame object tracking adjustment labeling jobs.

          • arn:aws:sagemaker:aws-region:394669845002:human-task-ui/VideoObjectTracking

      • PreHumanTaskLambdaArn (string) --

        The Amazon Resource Name (ARN) of a Lambda function that is run before a data object is sent to a human worker. Use this function to provide input to a custom labeling job.

        For built-in task types, use one of the following Amazon SageMaker Ground Truth Lambda function ARNs for PreHumanTaskLambdaArn . For custom labeling workflows, see Pre-annotation Lambda.

        Bounding box - Finds the most similar boxes from different workers based on the Jaccard index of the boxes.

        • arn:aws:lambda:us-east-1:432418664414:function:PRE-BoundingBox

        • arn:aws:lambda:us-east-2:266458841044:function:PRE-BoundingBox

        • arn:aws:lambda:us-west-2:081040173940:function:PRE-BoundingBox

        • arn:aws:lambda:ca-central-1:918755190332:function:PRE-BoundingBox

        • arn:aws:lambda:eu-west-1:568282634449:function:PRE-BoundingBox

        • arn:aws:lambda:eu-west-2:487402164563:function:PRE-BoundingBox

        • arn:aws:lambda:eu-central-1:203001061592:function:PRE-BoundingBox

        • arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-BoundingBox

        • arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-BoundingBox

        • arn:aws:lambda:ap-south-1:565803892007:function:PRE-BoundingBox

        • arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-BoundingBox

        • arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-BoundingBox

        Image classification - Uses a variant of the Expectation Maximization approach to estimate the true class of an image based on annotations from individual workers.

        • arn:aws:lambda:us-east-1:432418664414:function:PRE-ImageMultiClass

        • arn:aws:lambda:us-east-2:266458841044:function:PRE-ImageMultiClass

        • arn:aws:lambda:us-west-2:081040173940:function:PRE-ImageMultiClass

        • arn:aws:lambda:ca-central-1:918755190332:function:PRE-ImageMultiClass

        • arn:aws:lambda:eu-west-1:568282634449:function:PRE-ImageMultiClass

        • arn:aws:lambda:eu-west-2:487402164563:function:PRE-ImageMultiClass

        • arn:aws:lambda:eu-central-1:203001061592:function:PRE-ImageMultiClass

        • arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-ImageMultiClass

        • arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-ImageMultiClass

        • arn:aws:lambda:ap-south-1:565803892007:function:PRE-ImageMultiClass

        • arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-ImageMultiClass

        • arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-ImageMultiClass

        Multi-label image classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of an image based on annotations from individual workers.

        • arn:aws:lambda:us-east-1:432418664414:function:PRE-ImageMultiClassMultiLabel

        • arn:aws:lambda:us-east-2:266458841044:function:PRE-ImageMultiClassMultiLabel

        • arn:aws:lambda:us-west-2:081040173940:function:PRE-ImageMultiClassMultiLabel

        • arn:aws:lambda:ca-central-1:918755190332:function:PRE-ImageMultiClassMultiLabel

        • arn:aws:lambda:eu-west-1:568282634449:function:PRE-ImageMultiClassMultiLabel

        • arn:aws:lambda:eu-west-2:487402164563:function:PRE-ImageMultiClassMultiLabel

        • arn:aws:lambda:eu-central-1:203001061592:function:PRE-ImageMultiClassMultiLabel

        • arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-ImageMultiClassMultiLabel

        • arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-ImageMultiClassMultiLabel

        • arn:aws:lambda:ap-south-1:565803892007:function:PRE-ImageMultiClassMultiLabel

        • arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-ImageMultiClassMultiLabel

        • arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-ImageMultiClassMultiLabel

        Semantic segmentation - Treats each pixel in an image as a multi-class classification and treats pixel annotations from workers as "votes" for the correct label.

        • arn:aws:lambda:us-east-1:432418664414:function:PRE-SemanticSegmentation

        • arn:aws:lambda:us-east-2:266458841044:function:PRE-SemanticSegmentation

        • arn:aws:lambda:us-west-2:081040173940:function:PRE-SemanticSegmentation

        • arn:aws:lambda:ca-central-1:918755190332:function:PRE-SemanticSegmentation

        • arn:aws:lambda:eu-west-1:568282634449:function:PRE-SemanticSegmentation

        • arn:aws:lambda:eu-west-2:487402164563:function:PRE-SemanticSegmentation

        • arn:aws:lambda:eu-central-1:203001061592:function:PRE-SemanticSegmentation

        • arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-SemanticSegmentation

        • arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-SemanticSegmentation

        • arn:aws:lambda:ap-south-1:565803892007:function:PRE-SemanticSegmentation

        • arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-SemanticSegmentation

        • arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-SemanticSegmentation

        Text classification - Uses a variant of the Expectation Maximization approach to estimate the true class of text based on annotations from individual workers.

        • arn:aws:lambda:us-east-1:432418664414:function:PRE-TextMultiClass

        • arn:aws:lambda:us-east-2:266458841044:function:PRE-TextMultiClass

        • arn:aws:lambda:us-west-2:081040173940:function:PRE-TextMultiClass

        • arn:aws:lambda:ca-central-1:918755190332:function:PRE-TextMultiClass

        • arn:aws:lambda:eu-west-1:568282634449:function:PRE-TextMultiClass

        • arn:aws:lambda:eu-west-2:487402164563:function:PRE-TextMultiClass

        • arn:aws:lambda:eu-central-1:203001061592:function:PRE-TextMultiClass

        • arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-TextMultiClass

        • arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-TextMultiClass

        • arn:aws:lambda:ap-south-1:565803892007:function:PRE-TextMultiClass

        • arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-TextMultiClass

        • arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-TextMultiClass

        Multi-label text classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of text based on annotations from individual workers.

        • arn:aws:lambda:us-east-1:432418664414:function:PRE-TextMultiClassMultiLabel

        • arn:aws:lambda:us-east-2:266458841044:function:PRE-TextMultiClassMultiLabel

        • arn:aws:lambda:us-west-2:081040173940:function:PRE-TextMultiClassMultiLabel

        • arn:aws:lambda:ca-central-1:918755190332:function:PRE-TextMultiClassMultiLabel

        • arn:aws:lambda:eu-west-1:568282634449:function:PRE-TextMultiClassMultiLabel

        • arn:aws:lambda:eu-west-2:487402164563:function:PRE-TextMultiClassMultiLabel

        • arn:aws:lambda:eu-central-1:203001061592:function:PRE-TextMultiClassMultiLabel

        • arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-TextMultiClassMultiLabel

        • arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-TextMultiClassMultiLabel

        • arn:aws:lambda:ap-south-1:565803892007:function:PRE-TextMultiClassMultiLabel

        • arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-TextMultiClassMultiLabel

        • arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-TextMultiClassMultiLabel

        Named entity recognition - Groups similar selections and calculates aggregate boundaries, resolving to most-assigned label.

        • arn:aws:lambda:us-east-1:432418664414:function:PRE-NamedEntityRecognition

        • arn:aws:lambda:us-east-2:266458841044:function:PRE-NamedEntityRecognition

        • arn:aws:lambda:us-west-2:081040173940:function:PRE-NamedEntityRecognition

        • arn:aws:lambda:ca-central-1:918755190332:function:PRE-NamedEntityRecognition

        • arn:aws:lambda:eu-west-1:568282634449:function:PRE-NamedEntityRecognition

        • arn:aws:lambda:eu-west-2:487402164563:function:PRE-NamedEntityRecognition

        • arn:aws:lambda:eu-central-1:203001061592:function:PRE-NamedEntityRecognition

        • arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-NamedEntityRecognition

        • arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-NamedEntityRecognition

        • arn:aws:lambda:ap-south-1:565803892007:function:PRE-NamedEntityRecognition

        • arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-NamedEntityRecognition

        • arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-NamedEntityRecognition

        Video Classification - Use this task type when you need workers to classify videos using predefined labels that you specify. Workers are shown videos and are asked to choose one label for each video.

        • arn:aws:lambda:us-east-1:432418664414:function:PRE-VideoMultiClass

        • arn:aws:lambda:us-east-2:266458841044:function:PRE-VideoMultiClass

        • arn:aws:lambda:us-west-2:081040173940:function:PRE-VideoMultiClass

        • arn:aws:lambda:eu-west-1:568282634449:function:PRE-VideoMultiClass

        • arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VideoMultiClass

        • arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VideoMultiClass

        • arn:aws:lambda:ap-south-1:565803892007:function:PRE-VideoMultiClass

        • arn:aws:lambda:eu-central-1:203001061592:function:PRE-VideoMultiClass

        • arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VideoMultiClass

        • arn:aws:lambda:eu-west-2:487402164563:function:PRE-VideoMultiClass

        • arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VideoMultiClass

        • arn:aws:lambda:ca-central-1:918755190332:function:PRE-VideoMultiClass

        Video Frame Object Detection - Use this task type to have workers identify and locate objects in a sequence of video frames (images extracted from a video) using bounding boxes. For example, you can use this task to ask workers to identify and localize various objects in a series of video frames, such as cars, bikes, and pedestrians.

        • arn:aws:lambda:us-east-1:432418664414:function:PRE-VideoObjectDetection

        • arn:aws:lambda:us-east-2:266458841044:function:PRE-VideoObjectDetection

        • arn:aws:lambda:us-west-2:081040173940:function:PRE-VideoObjectDetection

        • arn:aws:lambda:eu-west-1:568282634449:function:PRE-VideoObjectDetection

        • arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VideoObjectDetection

        • arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VideoObjectDetection

        • arn:aws:lambda:ap-south-1:565803892007:function:PRE-VideoObjectDetection

        • arn:aws:lambda:eu-central-1:203001061592:function:PRE-VideoObjectDetection

        • arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VideoObjectDetection

        • arn:aws:lambda:eu-west-2:487402164563:function:PRE-VideoObjectDetection

        • arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VideoObjectDetection

        • arn:aws:lambda:ca-central-1:918755190332:function:PRE-VideoObjectDetection

        Video Frame Object Tracking - Use this task type to have workers track the movement of objects in a sequence of video frames (images extracted from a video) using bounding boxes. For example, you can use this task to ask workers to track the movement of objects, such as cars, bikes, and pedestrians.

        • arn:aws:lambda:us-east-1:432418664414:function:PRE-VideoObjectTracking

        • arn:aws:lambda:us-east-2:266458841044:function:PRE-VideoObjectTracking

        • arn:aws:lambda:us-west-2:081040173940:function:PRE-VideoObjectTracking

        • arn:aws:lambda:eu-west-1:568282634449:function:PRE-VideoObjectTracking

        • arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VideoObjectTracking

        • arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VideoObjectTracking

        • arn:aws:lambda:ap-south-1:565803892007:function:PRE-VideoObjectTracking

        • arn:aws:lambda:eu-central-1:203001061592:function:PRE-VideoObjectTracking

        • arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VideoObjectTracking

        • arn:aws:lambda:eu-west-2:487402164563:function:PRE-VideoObjectTracking

        • arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VideoObjectTracking

        • arn:aws:lambda:ca-central-1:918755190332:function:PRE-VideoObjectTracking

        3D Point Cloud Modalities

        Use the following pre-annotation lambdas for 3D point cloud labeling modality tasks. See 3D Point Cloud Task types to learn more.

        3D Point Cloud Object Detection - Use this task type when you want workers to classify objects in a 3D point cloud by drawing 3D cuboids around objects. For example, you can use this task type to ask workers to identify different types of objects in a point cloud, such as cars, bikes, and pedestrians.

        • arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudObjectDetection

        • arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudObjectDetection

        • arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudObjectDetection

        • arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudObjectDetection

        • arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudObjectDetection

        • arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudObjectDetection

        • arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudObjectDetection

        • arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudObjectDetection

        • arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudObjectDetection

        • arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudObjectDetection

        • arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudObjectDetection

        • arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudObjectDetection

        3D Point Cloud Object Tracking - Use this task type when you want workers to draw 3D cuboids around objects that appear in a sequence of 3D point cloud frames. For example, you can use this task type to ask workers to track the movement of vehicles across multiple point cloud frames.

        • arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudObjectTracking

        • arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudObjectTracking

        • arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudObjectTracking

        • arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudObjectTracking

        • arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudObjectTracking

        • arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudObjectTracking

        • arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudObjectTracking

        • arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudObjectTracking

        • arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudObjectTracking

        • arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudObjectTracking

        • arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudObjectTracking

        • arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudObjectTracking

        3D Point Cloud Semantic Segmentation - Use this task type when you want workers to create a point-level semantic segmentation masks by painting objects in a 3D point cloud using different colors where each color is assigned to one of the classes you specify.

        • arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudSemanticSegmentation

        • arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudSemanticSegmentation

        • arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudSemanticSegmentation

        • arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudSemanticSegmentation

        • arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudSemanticSegmentation

        • arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudSemanticSegmentation

        • arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudSemanticSegmentation

        • arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudSemanticSegmentation

        • arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudSemanticSegmentation

        • arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudSemanticSegmentation

        • arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudSemanticSegmentation

        • arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudSemanticSegmentation

        Use the following ARNs for Label Verification and Adjustment Jobs

        Use label verification and adjustment jobs to review and adjust labels. To learn more, see Verify and Adjust Labels.

        Bounding box verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgement for bounding box labels based on annotations from individual workers.

        • arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudObjectTracking

        • arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudObjectTracking

        • arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudObjectTracking

        • arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudObjectTracking

        • arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudObjectTracking

        • arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudObjectTracking

        • arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudObjectTracking

        • arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudObjectTracking

        • arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudObjectTracking

        • arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudObjectTracking

        • arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudObjectTracking

        • arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudObjectTracking

        Bounding box adjustment - Finds the most similar boxes from different workers based on the Jaccard index of the adjusted annotations.

        • arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentBoundingBox

        • arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentBoundingBox

        • arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentBoundingBox

        • arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentBoundingBox

        • arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentBoundingBox

        • arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentBoundingBox

        • arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentBoundingBox

        • arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentBoundingBox

        • arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentBoundingBox

        • arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentBoundingBox

        • arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentBoundingBox

        • arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentBoundingBox

        Semantic segmentation verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgment for semantic segmentation labels based on annotations from individual workers.

        • arn:aws:lambda:us-east-1:432418664414:function:PRE-VerificationSemanticSegmentation

        • arn:aws:lambda:us-east-2:266458841044:function:PRE-VerificationSemanticSegmentation

        • arn:aws:lambda:us-west-2:081040173940:function:PRE-VerificationSemanticSegmentation

        • arn:aws:lambda:ca-central-1:918755190332:function:PRE-VerificationSemanticSegmentation

        • arn:aws:lambda:eu-west-1:568282634449:function:PRE-VerificationSemanticSegmentation

        • arn:aws:lambda:eu-west-2:487402164563:function:PRE-VerificationSemanticSegmentation

        • arn:aws:lambda:eu-central-1:203001061592:function:PRE-VerificationSemanticSegmentation

        • arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VerificationSemanticSegmentation

        • arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VerificationSemanticSegmentation

        • arn:aws:lambda:ap-south-1:565803892007:function:PRE-VerificationSemanticSegmentation

        • arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VerificationSemanticSegmentation

        • arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VerificationSemanticSegmentation

        Semantic segmentation adjustment - Treats each pixel in an image as a multi-class classification and treats pixel adjusted annotations from workers as "votes" for the correct label.

        • arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentSemanticSegmentation

        • arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentSemanticSegmentation

        • arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentSemanticSegmentation

        • arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentSemanticSegmentation

        • arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentSemanticSegmentation

        • arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentSemanticSegmentation

        • arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentSemanticSegmentation

        • arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentSemanticSegmentation

        • arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentSemanticSegmentation

        • arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentSemanticSegmentation

        • arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentSemanticSegmentation

        • arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentSemanticSegmentation

        Video Frame Object Detection Adjustment - Use this task type when you want workers to adjust bounding boxes that workers have added to video frames to classify and localize objects in a sequence of video frames.

        • arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentVideoObjectDetection

        • arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentVideoObjectDetection

        • arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentVideoObjectDetection

        • arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentVideoObjectDetection

        • arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentVideoObjectDetection

        • arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentVideoObjectDetection

        • arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentVideoObjectDetection

        • arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentVideoObjectDetection

        • arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentVideoObjectDetection

        • arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentVideoObjectDetection

        • arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentVideoObjectDetection

        • arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentVideoObjectDetection

        Video Frame Object Tracking Adjustment - Use this task type when you want workers to adjust bounding boxes that workers have added to video frames to track object movement across a sequence of video frames.

        • arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentVideoObjectTracking

        • arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentVideoObjectTracking

        • arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentVideoObjectTracking

        • arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentVideoObjectTracking

        • arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentVideoObjectTracking

        • arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentVideoObjectTracking

        • arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentVideoObjectTracking

        • arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentVideoObjectTracking

        • arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentVideoObjectTracking

        • arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentVideoObjectTracking

        • arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentVideoObjectTracking

        • arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentVideoObjectTracking

        3D point cloud object detection adjustment - Adjust 3D cuboids in a point cloud frame.

        • arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudObjectDetection

        • arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudObjectDetection

        • arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudObjectDetection

        • arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudObjectDetection

        • arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudObjectDetection

        • arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudObjectDetection

        • arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudObjectDetection

        • arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudObjectDetection

        • arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudObjectDetection

        • arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudObjectDetection

        • arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudObjectDetection

        • arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudObjectDetection

        3D point cloud object tracking adjustment - Adjust 3D cuboids across a sequence of point cloud frames.

        • arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudObjectTracking

        • arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudObjectTracking

        • arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudObjectTracking

        • arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudObjectTracking

        • arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudObjectTracking

        • arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudObjectTracking

        • arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudObjectTracking

        • arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudObjectTracking

        • arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudObjectTracking

        • arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudObjectTracking

        • arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudObjectTracking

        • arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudObjectTracking

        3D point cloud semantic segmentation adjustment - Adjust semantic segmentation masks in a 3D point cloud.

        • arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudSemanticSegmentation

        • arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudSemanticSegmentation

        • arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudSemanticSegmentation

        • arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudSemanticSegmentation

        • arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudSemanticSegmentation

        • arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudSemanticSegmentation

        • arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudSemanticSegmentation

        • arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudSemanticSegmentation

        • arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudSemanticSegmentation

        • arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudSemanticSegmentation

        • arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudSemanticSegmentation

        • arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudSemanticSegmentation

      • TaskKeywords (list) --

        Keywords used to describe the task so that workers on Amazon Mechanical Turk can discover the task.

        • (string) --

      • TaskTitle (string) --

        A title for the task for your human workers.

      • TaskDescription (string) --

        A description of the task for your human workers.

      • NumberOfHumanWorkersPerDataObject (integer) --

        The number of human workers that will label an object.

      • TaskTimeLimitInSeconds (integer) --

        The amount of time that a worker has to complete a task.

      • TaskAvailabilityLifetimeInSeconds (integer) --

        The length of time that a task remains available for labeling by human workers. If you choose the Amazon Mechanical Turk workforce, the maximum is 12 hours (43200) . The default value is 864000 seconds (10 days). For private and vendor workforces, the maximum is as listed.

      • MaxConcurrentTaskCount (integer) --

        Defines the maximum number of data objects that can be labeled by human workers at the same time. Also referred to as batch size. Each object may have more than one worker at one time. The default value is 1000 objects.

      • AnnotationConsolidationConfig (dict) --

        Configures how labels are consolidated across human workers.

        • AnnotationConsolidationLambdaArn (string) --

          The Amazon Resource Name (ARN) of a Lambda function implements the logic for annotation consolidation and to process output data.

          This parameter is required for all labeling jobs. For built-in task types, use one of the following Amazon SageMaker Ground Truth Lambda function ARNs for AnnotationConsolidationLambdaArn . For custom labeling workflows, see Post-annotation Lambda.

          Bounding box - Finds the most similar boxes from different workers based on the Jaccard index of the boxes.

          • arn:aws:lambda:us-east-1:432418664414:function:ACS-BoundingBox arn:aws:lambda:us-east-2:266458841044:function:ACS-BoundingBox arn:aws:lambda:us-west-2:081040173940:function:ACS-BoundingBox arn:aws:lambda:eu-west-1:568282634449:function:ACS-BoundingBox arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-BoundingBox arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-BoundingBox arn:aws:lambda:ap-south-1:565803892007:function:ACS-BoundingBox arn:aws:lambda:eu-central-1:203001061592:function:ACS-BoundingBox arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-BoundingBox arn:aws:lambda:eu-west-2:487402164563:function:ACS-BoundingBox arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-BoundingBox arn:aws:lambda:ca-central-1:918755190332:function:ACS-BoundingBox

          Image classification - Uses a variant of the Expectation Maximization approach to estimate the true class of an image based on annotations from individual workers.

          • arn:aws:lambda:us-east-1:432418664414:function:ACS-ImageMultiClass arn:aws:lambda:us-east-2:266458841044:function:ACS-ImageMultiClass arn:aws:lambda:us-west-2:081040173940:function:ACS-ImageMultiClass arn:aws:lambda:eu-west-1:568282634449:function:ACS-ImageMultiClass arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-ImageMultiClass arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-ImageMultiClass arn:aws:lambda:ap-south-1:565803892007:function:ACS-ImageMultiClass arn:aws:lambda:eu-central-1:203001061592:function:ACS-ImageMultiClass arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-ImageMultiClass arn:aws:lambda:eu-west-2:487402164563:function:ACS-ImageMultiClass arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-ImageMultiClass arn:aws:lambda:ca-central-1:918755190332:function:ACS-ImageMultiClass

          Multi-label image classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of an image based on annotations from individual workers.

          • arn:aws:lambda:us-east-1:432418664414:function:ACS-ImageMultiClassMultiLabel arn:aws:lambda:us-east-2:266458841044:function:ACS-ImageMultiClassMultiLabel arn:aws:lambda:us-west-2:081040173940:function:ACS-ImageMultiClassMultiLabel arn:aws:lambda:eu-west-1:568282634449:function:ACS-ImageMultiClassMultiLabel arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-ImageMultiClassMultiLabel arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-ImageMultiClassMultiLabel arn:aws:lambda:ap-south-1:565803892007:function:ACS-ImageMultiClassMultiLabel arn:aws:lambda:eu-central-1:203001061592:function:ACS-ImageMultiClassMultiLabel arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-ImageMultiClassMultiLabel arn:aws:lambda:eu-west-2:487402164563:function:ACS-ImageMultiClassMultiLabel arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-ImageMultiClassMultiLabel arn:aws:lambda:ca-central-1:918755190332:function:ACS-ImageMultiClassMultiLabel

          Semantic segmentation - Treats each pixel in an image as a multi-class classification and treats pixel annotations from workers as "votes" for the correct label.

          • arn:aws:lambda:us-east-1:432418664414:function:ACS-SemanticSegmentation arn:aws:lambda:us-east-2:266458841044:function:ACS-SemanticSegmentation arn:aws:lambda:us-west-2:081040173940:function:ACS-SemanticSegmentation arn:aws:lambda:eu-west-1:568282634449:function:ACS-SemanticSegmentation arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-SemanticSegmentation arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-SemanticSegmentation arn:aws:lambda:ap-south-1:565803892007:function:ACS-SemanticSegmentation arn:aws:lambda:eu-central-1:203001061592:function:ACS-SemanticSegmentation arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-SemanticSegmentation arn:aws:lambda:eu-west-2:487402164563:function:ACS-SemanticSegmentation arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-SemanticSegmentation arn:aws:lambda:ca-central-1:918755190332:function:ACS-SemanticSegmentation

          Text classification - Uses a variant of the Expectation Maximization approach to estimate the true class of text based on annotations from individual workers.

          • arn:aws:lambda:us-east-1:432418664414:function:ACS-TextMultiClass arn:aws:lambda:us-east-2:266458841044:function:ACS-TextMultiClass arn:aws:lambda:us-west-2:081040173940:function:ACS-TextMultiClass arn:aws:lambda:eu-west-1:568282634449:function:ACS-TextMultiClass arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-TextMultiClass arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-TextMultiClass arn:aws:lambda:ap-south-1:565803892007:function:ACS-TextMultiClass arn:aws:lambda:eu-central-1:203001061592:function:ACS-TextMultiClass arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-TextMultiClass arn:aws:lambda:eu-west-2:487402164563:function:ACS-TextMultiClass arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-TextMultiClass arn:aws:lambda:ca-central-1:918755190332:function:ACS-TextMultiClass

          Multi-label text classification - Uses a variant of the Expectation Maximization approach to estimate the true classes of text based on annotations from individual workers.

          • arn:aws:lambda:us-east-1:432418664414:function:ACS-TextMultiClassMultiLabel arn:aws:lambda:us-east-2:266458841044:function:ACS-TextMultiClassMultiLabel arn:aws:lambda:us-west-2:081040173940:function:ACS-TextMultiClassMultiLabel arn:aws:lambda:eu-west-1:568282634449:function:ACS-TextMultiClassMultiLabel arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-TextMultiClassMultiLabel arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-TextMultiClassMultiLabel arn:aws:lambda:ap-south-1:565803892007:function:ACS-TextMultiClassMultiLabel arn:aws:lambda:eu-central-1:203001061592:function:ACS-TextMultiClassMultiLabel arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-TextMultiClassMultiLabel arn:aws:lambda:eu-west-2:487402164563:function:ACS-TextMultiClassMultiLabel arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-TextMultiClassMultiLabel arn:aws:lambda:ca-central-1:918755190332:function:ACS-TextMultiClassMultiLabel

          Named entity recognition - Groups similar selections and calculates aggregate boundaries, resolving to most-assigned label.

          • arn:aws:lambda:us-east-1:432418664414:function:ACS-NamedEntityRecognition arn:aws:lambda:us-east-2:266458841044:function:ACS-NamedEntityRecognition arn:aws:lambda:us-west-2:081040173940:function:ACS-NamedEntityRecognition arn:aws:lambda:eu-west-1:568282634449:function:ACS-NamedEntityRecognition arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-NamedEntityRecognition arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-NamedEntityRecognition arn:aws:lambda:ap-south-1:565803892007:function:ACS-NamedEntityRecognition arn:aws:lambda:eu-central-1:203001061592:function:ACS-NamedEntityRecognition arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-NamedEntityRecognition arn:aws:lambda:eu-west-2:487402164563:function:ACS-NamedEntityRecognition arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-NamedEntityRecognition arn:aws:lambda:ca-central-1:918755190332:function:ACS-NamedEntityRecognition

          Named entity recognition - Groups similar selections and calculates aggregate boundaries, resolving to most-assigned label.

          • arn:aws:lambda:us-east-1:432418664414:function:ACS-NamedEntityRecognition arn:aws:lambda:us-east-2:266458841044:function:ACS-NamedEntityRecognition arn:aws:lambda:us-west-2:081040173940:function:ACS-NamedEntityRecognition arn:aws:lambda:eu-west-1:568282634449:function:ACS-NamedEntityRecognition arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-NamedEntityRecognition arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-NamedEntityRecognition arn:aws:lambda:ap-south-1:565803892007:function:ACS-NamedEntityRecognition arn:aws:lambda:eu-central-1:203001061592:function:ACS-NamedEntityRecognition arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-NamedEntityRecognition arn:aws:lambda:eu-west-2:487402164563:function:ACS-NamedEntityRecognition arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-NamedEntityRecognition arn:aws:lambda:ca-central-1:918755190332:function:ACS-NamedEntityRecognition

          Video Classification - Use this task type when you need workers to classify videos using predefined labels that you specify. Workers are shown videos and are asked to choose one label for each video.

          • arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoMultiClass arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoMultiClass arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoMultiClass arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoMultiClass arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoMultiClass arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoMultiClass arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoMultiClass arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoMultiClass arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoMultiClass arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoMultiClass arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoMultiClass arn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoMultiClass

          Video Frame Object Detection - Use this task type to have workers identify and locate objects in a sequence of video frames (images extracted from a video) using bounding boxes. For example, you can use this task to ask workers to identify and localize various objects in a series of video frames, such as cars, bikes, and pedestrians.

          • arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoObjectDetection arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoObjectDetection arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoObjectDetection arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoObjectDetection arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoObjectDetection arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoObjectDetection arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoObjectDetection arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoObjectDetection arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoObjectDetection arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoObjectDetection arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoObjectDetection arn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoObjectDetection

          Video Frame Object Tracking - Use this task type to have workers track the movement of objects in a sequence of video frames (images extracted from a video) using bounding boxes. For example, you can use this task to ask workers to track the movement of objects, such as cars, bikes, and pedestrians.

          • arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoObjectTracking arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoObjectTracking arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoObjectTracking arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoObjectTracking arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoObjectTracking arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoObjectTracking arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoObjectTracking arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoObjectTracking arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoObjectTracking arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoObjectTracking arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoObjectTracking arn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoObjectTracking

          3D point cloud object detection - Use this task type when you want workers to classify objects in a 3D point cloud by drawing 3D cuboids around objects. For example, you can use this task type to ask workers to identify different types of objects in a point cloud, such as cars, bikes, and pedestrians.

          • arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudObjectDetection arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudObjectDetection arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudObjectDetection arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudObjectDetection arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudObjectDetection arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudObjectDetection arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudObjectDetection arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudObjectDetection arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudObjectDetection arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudObjectDetection arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudObjectDetection arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudObjectDetection

          3D point cloud object tracking - Use this task type when you want workers to draw 3D cuboids around objects that appear in a sequence of 3D point cloud frames. For example, you can use this task type to ask workers to track the movement of vehicles across multiple point cloud frames.

          • arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudObjectTracking arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudObjectTracking arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudObjectTracking arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudObjectTracking arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudObjectTracking arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudObjectTracking arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudObjectTracking arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudObjectTracking arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudObjectTracking arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudObjectTracking arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudObjectTracking arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudObjectTracking

          3D point cloud semantic segmentation - Use this task type when you want workers to create a point-level semantic segmentation masks by painting objects in a 3D point cloud using different colors where each color is assigned to one of the classes you specify.

          • arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudSemanticSegmentation arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudSemanticSegmentation arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudSemanticSegmentation arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudSemanticSegmentation arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudSemanticSegmentation arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudSemanticSegmentation arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudSemanticSegmentation arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudSemanticSegmentation arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudSemanticSegmentation arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudSemanticSegmentation arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudSemanticSegmentation arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudSemanticSegmentation

          Use the following ARNs for Label Verification and Adjustment Jobs

          Use label verification and adjustment jobs to review and adjust labels. To learn more, see Verify and Adjust Labels.

          Semantic segmentation adjustment - Treats each pixel in an image as a multi-class classification and treats pixel adjusted annotations from workers as "votes" for the correct label.

          • arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentSemanticSegmentation arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentSemanticSegmentation arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentSemanticSegmentation arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentSemanticSegmentation arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentSemanticSegmentation arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentSemanticSegmentation arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentSemanticSegmentation arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentSemanticSegmentation arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentSemanticSegmentation arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentSemanticSegmentation arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentSemanticSegmentation arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentSemanticSegmentation

          Semantic segmentation verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgment for semantic segmentation labels based on annotations from individual workers.

          • arn:aws:lambda:us-east-1:432418664414:function:ACS-VerificationSemanticSegmentation arn:aws:lambda:us-east-2:266458841044:function:ACS-VerificationSemanticSegmentation arn:aws:lambda:us-west-2:081040173940:function:ACS-VerificationSemanticSegmentation arn:aws:lambda:eu-west-1:568282634449:function:ACS-VerificationSemanticSegmentation arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VerificationSemanticSegmentation arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VerificationSemanticSegmentation arn:aws:lambda:ap-south-1:565803892007:function:ACS-VerificationSemanticSegmentation arn:aws:lambda:eu-central-1:203001061592:function:ACS-VerificationSemanticSegmentation arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VerificationSemanticSegmentation arn:aws:lambda:eu-west-2:487402164563:function:ACS-VerificationSemanticSegmentation arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VerificationSemanticSegmentation arn:aws:lambda:ca-central-1:918755190332:function:ACS-VerificationSemanticSegmentation

          Bounding box verification - Uses a variant of the Expectation Maximization approach to estimate the true class of verification judgement for bounding box labels based on annotations from individual workers.

          • arn:aws:lambda:us-east-1:432418664414:function:ACS-VerificationBoundingBox arn:aws:lambda:us-east-2:266458841044:function:ACS-VerificationBoundingBox arn:aws:lambda:us-west-2:081040173940:function:ACS-VerificationBoundingBox arn:aws:lambda:eu-west-1:568282634449:function:ACS-VerificationBoundingBox arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VerificationBoundingBox arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VerificationBoundingBox arn:aws:lambda:ap-south-1:565803892007:function:ACS-VerificationBoundingBox arn:aws:lambda:eu-central-1:203001061592:function:ACS-VerificationBoundingBox arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VerificationBoundingBox arn:aws:lambda:eu-west-2:487402164563:function:ACS-VerificationBoundingBox arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VerificationBoundingBox arn:aws:lambda:ca-central-1:918755190332:function:ACS-VerificationBoundingBox

          Bounding box adjustment - Finds the most similar boxes from different workers based on the Jaccard index of the adjusted annotations.

          • arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentBoundingBox arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentBoundingBox arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentBoundingBox arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentBoundingBox arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentBoundingBox arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentBoundingBox arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentBoundingBox arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentBoundingBox arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentBoundingBox arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentBoundingBox arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentBoundingBox arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentBoundingBox

          Video Frame Object Detection Adjustment - Use this task type when you want workers to adjust bounding boxes that workers have added to video frames to classify and localize objects in a sequence of video frames.

          • arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentVideoObjectDetection arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentVideoObjectDetection arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentVideoObjectDetection arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentVideoObjectDetection arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentVideoObjectDetection arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentVideoObjectDetection arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentVideoObjectDetection arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentVideoObjectDetection arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentVideoObjectDetection arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentVideoObjectDetection arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentVideoObjectDetection arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentVideoObjectDetection

          Video Frame Object Tracking Adjustment - Use this task type when you want workers to adjust bounding boxes that workers have added to video frames to track object movement across a sequence of video frames.

          • arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentVideoObjectTracking arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentVideoObjectTracking arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentVideoObjectTracking arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentVideoObjectTracking arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentVideoObjectTracking arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentVideoObjectTracking arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentVideoObjectTracking arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentVideoObjectTracking arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentVideoObjectTracking arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentVideoObjectTracking arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentVideoObjectTracking arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentVideoObjectTracking

          3D point cloud object detection adjustment - Use this task type when you want workers to adjust 3D cuboids around objects in a 3D point cloud.

          • arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudObjectDetection arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudObjectDetection arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudObjectDetection arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudObjectDetection arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudObjectDetection arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudObjectDetection arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudObjectDetection arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudObjectDetection arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudObjectDetection arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudObjectDetection arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudObjectDetection arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudObjectDetection

          3D point cloud object tracking adjustment - Use this task type when you want workers to adjust 3D cuboids around objects that appear in a sequence of 3D point cloud frames.

          • arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudObjectTracking arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudObjectTracking arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudObjectTracking arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudObjectTracking arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudObjectTracking arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudObjectTracking arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudObjectTracking arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudObjectTracking arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudObjectTracking arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudObjectTracking arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudObjectTracking arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudObjectTracking

          3D point cloud semantic segmentation adjustment - Use this task type when you want workers to adjust a point-level semantic segmentation masks using a paint tool.

          • arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudSemanticSegmentation arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudSemanticSegmentation

      • PublicWorkforceTaskPrice (dict) --

        The price that you pay for each task performed by an Amazon Mechanical Turk worker.

        • AmountInUsd (dict) --

          Defines the amount of money paid to an Amazon Mechanical Turk worker in United States dollars.

          • Dollars (integer) --

            The whole number of dollars in the amount.

          • Cents (integer) --

            The fractional portion, in cents, of the amount.

          • TenthFractionsOfACent (integer) --

            Fractions of a cent, in tenths.

    • Tags (list) --

      An array of key/value pairs. For more information, see Using Cost Allocation Tags in the AWS Billing and Cost Management User Guide .

      • (dict) --

        Describes a tag.

        • Key (string) --

          The tag key.

        • Value (string) --

          The tag value.

    • LabelingJobOutput (dict) --

      The location of the output produced by the labeling job.

      • OutputDatasetS3Uri (string) --

        The Amazon S3 bucket location of the manifest file for labeled data.

      • FinalActiveLearningModelArn (string) --

        The Amazon Resource Name (ARN) for the most recent Amazon SageMaker model trained as part of automated data labeling.

DescribeWorkforce (updated) Link ¶
Changes (response)
{'Workforce': {'CognitoConfig': {'ClientId': 'string', 'UserPool': 'string'},
               'CreateDate': 'timestamp',
               'OidcConfig': {'AuthorizationEndpoint': 'string',
                              'ClientId': 'string',
                              'Issuer': 'string',
                              'JwksUri': 'string',
                              'LogoutEndpoint': 'string',
                              'TokenEndpoint': 'string',
                              'UserInfoEndpoint': 'string'},
               'SubDomain': 'string'}}

Lists private workforce information, including workforce name, Amazon Resource Name (ARN), and, if applicable, allowed IP address ranges ( CIDRs ). Allowable IP address ranges are the IP addresses that workers can use to access tasks.

Warning

This operation applies only to private workforces.

See also: AWS API Documentation

Request Syntax

client.describe_workforce(
    WorkforceName='string'
)
type WorkforceName

string

param WorkforceName

[REQUIRED]

The name of the private workforce whose access you want to restrict. WorkforceName is automatically set to default when a workforce is created and cannot be modified.

rtype

dict

returns

Response Syntax

{
    'Workforce': {
        'WorkforceName': 'string',
        'WorkforceArn': 'string',
        'LastUpdatedDate': datetime(2015, 1, 1),
        'SourceIpConfig': {
            'Cidrs': [
                'string',
            ]
        },
        'SubDomain': 'string',
        'CognitoConfig': {
            'UserPool': 'string',
            'ClientId': 'string'
        },
        'OidcConfig': {
            'ClientId': 'string',
            'Issuer': 'string',
            'AuthorizationEndpoint': 'string',
            'TokenEndpoint': 'string',
            'UserInfoEndpoint': 'string',
            'LogoutEndpoint': 'string',
            'JwksUri': 'string'
        },
        'CreateDate': datetime(2015, 1, 1)
    }
}

Response Structure

  • (dict) --

    • Workforce (dict) --

      A single private workforce, which is automatically created when you create your first private work team. You can create one private work force in each AWS Region. By default, any workforce-related API operation used in a specific region will apply to the workforce created in that region. To learn how to create a private workforce, see Create a Private Workforce.

      • WorkforceName (string) --

        The name of the private workforce.

      • WorkforceArn (string) --

        The Amazon Resource Name (ARN) of the private workforce.

      • LastUpdatedDate (datetime) --

        The most recent date that was used to successfully add one or more IP address ranges ( CIDRs ) to a private workforce's allow list.

      • SourceIpConfig (dict) --

        A list of one to ten IP address ranges ( CIDRs ) to be added to the workforce allow list.

        • Cidrs (list) --

          A list of one to ten Classless Inter-Domain Routing (CIDR) values.

          Maximum: Ten CIDR values

          Note

          The following Length Constraints apply to individual CIDR values in the CIDR value list.

          • (string) --

      • SubDomain (string) --

        The subdomain for your OIDC Identity Provider.

      • CognitoConfig (dict) --

        The configuration of an Amazon Cognito workforce. A single Cognito workforce is created using and corresponds to a single Amazon Cognito user pool.

        • UserPool (string) --

          A user pool is a user directory in Amazon Cognito. With a user pool, your users can sign in to your web or mobile app through Amazon Cognito. Your users can also sign in through social identity providers like Google, Facebook, Amazon, or Apple, and through SAML identity providers.

        • ClientId (string) --

          The client ID for your Amazon Cognito user pool.

      • OidcConfig (dict) --

        The configuration of an OIDC Identity Provider (IdP) private workforce.

        • ClientId (string) --

          The OIDC IdP client ID used to configure your private workforce.

        • Issuer (string) --

          The OIDC IdP issuer used to configure your private workforce.

        • AuthorizationEndpoint (string) --

          The OIDC IdP authorization endpoint used to configure your private workforce.

        • TokenEndpoint (string) --

          The OIDC IdP token endpoint used to configure your private workforce.

        • UserInfoEndpoint (string) --

          The OIDC IdP user information endpoint used to configure your private workforce.

        • LogoutEndpoint (string) --

          The OIDC IdP logout endpoint used to configure your private workforce.

        • JwksUri (string) --

          The OIDC IdP JSON Web Key Set (Jwks) URI used to configure your private workforce.

      • CreateDate (datetime) --

        The date that the workforce is created.

DescribeWorkteam (updated) Link ¶
Changes (response)
{'Workteam': {'MemberDefinitions': {'OidcMemberDefinition': {'Groups': ['string']}},
              'WorkforceArn': 'string'}}

Gets information about a specific work team. You can see information such as the create date, the last updated date, membership information, and the work team's Amazon Resource Name (ARN).

See also: AWS API Documentation

Request Syntax

client.describe_workteam(
    WorkteamName='string'
)
type WorkteamName

string

param WorkteamName

[REQUIRED]

The name of the work team to return a description of.

rtype

dict

returns

Response Syntax

{
    'Workteam': {
        'WorkteamName': 'string',
        'MemberDefinitions': [
            {
                'CognitoMemberDefinition': {
                    'UserPool': 'string',
                    'UserGroup': 'string',
                    'ClientId': 'string'
                },
                'OidcMemberDefinition': {
                    'Groups': [
                        'string',
                    ]
                }
            },
        ],
        'WorkteamArn': 'string',
        'WorkforceArn': 'string',
        'ProductListingIds': [
            'string',
        ],
        'Description': 'string',
        'SubDomain': 'string',
        'CreateDate': datetime(2015, 1, 1),
        'LastUpdatedDate': datetime(2015, 1, 1),
        'NotificationConfiguration': {
            'NotificationTopicArn': 'string'
        }
    }
}

Response Structure

  • (dict) --

    • Workteam (dict) --

      A Workteam instance that contains information about the work team.

      • WorkteamName (string) --

        The name of the work team.

      • MemberDefinitions (list) --

        The Amazon Cognito user groups that make up the work team.

        • (dict) --

          Defines the Amazon Cognito user group that is part of a work team.

          • CognitoMemberDefinition (dict) --

            The Amazon Cognito user group that is part of the work team.

            • UserPool (string) --

              An identifier for a user pool. The user pool must be in the same region as the service that you are calling.

            • UserGroup (string) --

              An identifier for a user group.

            • ClientId (string) --

              An identifier for an application client. You must create the app client ID using Amazon Cognito.

          • OidcMemberDefinition (dict) --

            A list user groups that exist in your OIDC Identity Provider (IdP). One to ten groups can be used to create a single private work team. When you add a user group to the list of Groups , you can add that user group to one or more private work teams. If you add a user group to a private work team, all workers in that user group are added to the work team.

            • Groups (list) --

              A list of comma seperated strings that identifies user groups in your OIDC IdP. Each user group is made up of a group of private workers.

              • (string) --

      • WorkteamArn (string) --

        The Amazon Resource Name (ARN) that identifies the work team.

      • WorkforceArn (string) --

        The Amazon Resource Name (ARN) of the workforce.

      • ProductListingIds (list) --

        The Amazon Marketplace identifier for a vendor's work team.

        • (string) --

      • Description (string) --

        A description of the work team.

      • SubDomain (string) --

        The URI of the labeling job's user interface. Workers open this URI to start labeling your data objects.

      • CreateDate (datetime) --

        The date and time that the work team was created (timestamp).

      • LastUpdatedDate (datetime) --

        The date and time that the work team was last updated (timestamp).

      • NotificationConfiguration (dict) --

        Configures SNS notifications of available or expiring work items for work teams.

        • NotificationTopicArn (string) --

          The ARN for the SNS topic to which notifications should be published.

ListCompilationJobs (updated) Link ¶
Changes (response)
{'CompilationJobSummaries': {'CompilationTargetDevice': {'ml_g4dn',
                                                         'x86_win32',
                                                         'x86_win64'},
                             'CompilationTargetPlatformAccelerator': 'INTEL_GRAPHICS '
                                                                     '| MALI | '
                                                                     'NVIDIA',
                             'CompilationTargetPlatformArch': 'X86_64 | X86 | '
                                                              'ARM64 | '
                                                              'ARM_EABI | '
                                                              'ARM_EABIHF',
                             'CompilationTargetPlatformOs': 'ANDROID | LINUX'}}

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.

See also: AWS API Documentation

Request Syntax

client.list_compilation_jobs(
    NextToken='string',
    MaxResults=123,
    CreationTimeAfter=datetime(2015, 1, 1),
    CreationTimeBefore=datetime(2015, 1, 1),
    LastModifiedTimeAfter=datetime(2015, 1, 1),
    LastModifiedTimeBefore=datetime(2015, 1, 1),
    NameContains='string',
    StatusEquals='INPROGRESS'|'COMPLETED'|'FAILED'|'STARTING'|'STOPPING'|'STOPPED',
    SortBy='Name'|'CreationTime'|'Status',
    SortOrder='Ascending'|'Descending'
)
type NextToken

string

param NextToken

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.

type MaxResults

integer

param MaxResults

The maximum number of model compilation jobs to return in the response.

type CreationTimeAfter

datetime

param CreationTimeAfter

A filter that returns the model compilation jobs that were created after a specified time.

type CreationTimeBefore

datetime

param CreationTimeBefore

A filter that returns the model compilation jobs that were created before a specified time.

type LastModifiedTimeAfter

datetime

param LastModifiedTimeAfter

A filter that returns the model compilation jobs that were modified after a specified time.

type LastModifiedTimeBefore

datetime

param LastModifiedTimeBefore

A filter that returns the model compilation jobs that were modified before a specified time.

type NameContains

string

param NameContains

A filter that returns the model compilation jobs whose name contains a specified string.

type StatusEquals

string

param StatusEquals

A filter that retrieves model compilation jobs with a specific DescribeCompilationJobResponse$CompilationJobStatus status.

type SortBy

string

param SortBy

The field by which to sort results. The default is CreationTime .

type SortOrder

string

param SortOrder

The sort order for results. The default is Ascending .

rtype

dict

returns

Response Syntax

{
    'CompilationJobSummaries': [
        {
            'CompilationJobName': 'string',
            'CompilationJobArn': 'string',
            'CreationTime': datetime(2015, 1, 1),
            'CompilationStartTime': datetime(2015, 1, 1),
            'CompilationEndTime': datetime(2015, 1, 1),
            'CompilationTargetDevice': 'lambda'|'ml_m4'|'ml_m5'|'ml_c4'|'ml_c5'|'ml_p2'|'ml_p3'|'ml_g4dn'|'ml_inf1'|'jetson_tx1'|'jetson_tx2'|'jetson_nano'|'jetson_xavier'|'rasp3b'|'imx8qm'|'deeplens'|'rk3399'|'rk3288'|'aisage'|'sbe_c'|'qcs605'|'qcs603'|'sitara_am57x'|'amba_cv22'|'x86_win32'|'x86_win64',
            'CompilationTargetPlatformOs': 'ANDROID'|'LINUX',
            'CompilationTargetPlatformArch': 'X86_64'|'X86'|'ARM64'|'ARM_EABI'|'ARM_EABIHF',
            'CompilationTargetPlatformAccelerator': 'INTEL_GRAPHICS'|'MALI'|'NVIDIA',
            'LastModifiedTime': datetime(2015, 1, 1),
            'CompilationJobStatus': 'INPROGRESS'|'COMPLETED'|'FAILED'|'STARTING'|'STOPPING'|'STOPPED'
        },
    ],
    'NextToken': 'string'
}

Response Structure

  • (dict) --

    • CompilationJobSummaries (list) --

      An array of CompilationJobSummary objects, each describing a model compilation job.

      • (dict) --

        A summary of a model compilation job.

        • CompilationJobName (string) --

          The name of the model compilation job that you want a summary for.

        • CompilationJobArn (string) --

          The Amazon Resource Name (ARN) of the model compilation job.

        • CreationTime (datetime) --

          The time when the model compilation job was created.

        • CompilationStartTime (datetime) --

          The time when the model compilation job started.

        • CompilationEndTime (datetime) --

          The time when the model compilation job completed.

        • CompilationTargetDevice (string) --

          The type of device that the model will run on after the compilation job has completed.

        • CompilationTargetPlatformOs (string) --

          The type of OS that the model will run on after the compilation job has completed.

        • CompilationTargetPlatformArch (string) --

          The type of architecture that the model will run on after the compilation job has completed.

        • CompilationTargetPlatformAccelerator (string) --

          The type of accelerator that the model will run on after the compilation job has completed.

        • LastModifiedTime (datetime) --

          The time when the model compilation job was last modified.

        • CompilationJobStatus (string) --

          The status of the model compilation job.

    • NextToken (string) --

      If the response is truncated, Amazon SageMaker returns this NextToken . To retrieve the next set of model compilation jobs, use this token in the next request.

ListLabelingJobs (updated) Link ¶
Changes (request, response)
Request
{'StatusEquals': {'Initializing'}}
Response
{'LabelingJobSummaryList': {'LabelingJobStatus': {'Initializing'}}}

Gets a list of labeling jobs.

See also: AWS API Documentation

Request Syntax

client.list_labeling_jobs(
    CreationTimeAfter=datetime(2015, 1, 1),
    CreationTimeBefore=datetime(2015, 1, 1),
    LastModifiedTimeAfter=datetime(2015, 1, 1),
    LastModifiedTimeBefore=datetime(2015, 1, 1),
    MaxResults=123,
    NextToken='string',
    NameContains='string',
    SortBy='Name'|'CreationTime'|'Status',
    SortOrder='Ascending'|'Descending',
    StatusEquals='Initializing'|'InProgress'|'Completed'|'Failed'|'Stopping'|'Stopped'
)
type CreationTimeAfter

datetime

param CreationTimeAfter

A filter that returns only labeling jobs created after the specified time (timestamp).

type CreationTimeBefore

datetime

param CreationTimeBefore

A filter that returns only labeling jobs created before the specified time (timestamp).

type LastModifiedTimeAfter

datetime

param LastModifiedTimeAfter

A filter that returns only labeling jobs modified after the specified time (timestamp).

type LastModifiedTimeBefore

datetime

param LastModifiedTimeBefore

A filter that returns only labeling jobs modified before the specified time (timestamp).

type MaxResults

integer

param MaxResults

The maximum number of labeling jobs to return in each page of the response.

type NextToken

string

param NextToken

If the result of the previous ListLabelingJobs request was truncated, the response includes a NextToken . To retrieve the next set of labeling jobs, use the token in the next request.

type NameContains

string

param NameContains

A string in the labeling job name. This filter returns only labeling jobs whose name contains the specified string.

type SortBy

string

param SortBy

The field to sort results by. The default is CreationTime .

type SortOrder

string

param SortOrder

The sort order for results. The default is Ascending .

type StatusEquals

string

param StatusEquals

A filter that retrieves only labeling jobs with a specific status.

rtype

dict

returns

Response Syntax

{
    'LabelingJobSummaryList': [
        {
            'LabelingJobName': 'string',
            'LabelingJobArn': 'string',
            'CreationTime': datetime(2015, 1, 1),
            'LastModifiedTime': datetime(2015, 1, 1),
            'LabelingJobStatus': 'Initializing'|'InProgress'|'Completed'|'Failed'|'Stopping'|'Stopped',
            'LabelCounters': {
                'TotalLabeled': 123,
                'HumanLabeled': 123,
                'MachineLabeled': 123,
                'FailedNonRetryableError': 123,
                'Unlabeled': 123
            },
            'WorkteamArn': 'string',
            'PreHumanTaskLambdaArn': 'string',
            'AnnotationConsolidationLambdaArn': 'string',
            'FailureReason': 'string',
            'LabelingJobOutput': {
                'OutputDatasetS3Uri': 'string',
                'FinalActiveLearningModelArn': 'string'
            },
            'InputConfig': {
                'DataSource': {
                    'S3DataSource': {
                        'ManifestS3Uri': 'string'
                    }
                },
                'DataAttributes': {
                    'ContentClassifiers': [
                        'FreeOfPersonallyIdentifiableInformation'|'FreeOfAdultContent',
                    ]
                }
            }
        },
    ],
    'NextToken': 'string'
}

Response Structure

  • (dict) --

    • LabelingJobSummaryList (list) --

      An array of LabelingJobSummary objects, each describing a labeling job.

      • (dict) --

        Provides summary information about a labeling job.

        • LabelingJobName (string) --

          The name of the labeling job.

        • LabelingJobArn (string) --

          The Amazon Resource Name (ARN) assigned to the labeling job when it was created.

        • CreationTime (datetime) --

          The date and time that the job was created (timestamp).

        • LastModifiedTime (datetime) --

          The date and time that the job was last modified (timestamp).

        • LabelingJobStatus (string) --

          The current status of the labeling job.

        • LabelCounters (dict) --

          Counts showing the progress of the labeling job.

          • TotalLabeled (integer) --

            The total number of objects labeled.

          • HumanLabeled (integer) --

            The total number of objects labeled by a human worker.

          • MachineLabeled (integer) --

            The total number of objects labeled by automated data labeling.

          • FailedNonRetryableError (integer) --

            The total number of objects that could not be labeled due to an error.

          • Unlabeled (integer) --

            The total number of objects not yet labeled.

        • WorkteamArn (string) --

          The Amazon Resource Name (ARN) of the work team assigned to the job.

        • PreHumanTaskLambdaArn (string) --

          The Amazon Resource Name (ARN) of a Lambda function. The function is run before each data object is sent to a worker.

        • AnnotationConsolidationLambdaArn (string) --

          The Amazon Resource Name (ARN) of the Lambda function used to consolidate the annotations from individual workers into a label for a data object. For more information, see Annotation Consolidation.

        • FailureReason (string) --

          If the LabelingJobStatus field is Failed , this field contains a description of the error.

        • LabelingJobOutput (dict) --

          The location of the output produced by the labeling job.

          • OutputDatasetS3Uri (string) --

            The Amazon S3 bucket location of the manifest file for labeled data.

          • FinalActiveLearningModelArn (string) --

            The Amazon Resource Name (ARN) for the most recent Amazon SageMaker model trained as part of automated data labeling.

        • InputConfig (dict) --

          Input configuration for the labeling job.

          • DataSource (dict) --

            The location of the input data.

            • S3DataSource (dict) --

              The Amazon S3 location of the input data objects.

              • ManifestS3Uri (string) --

                The Amazon S3 location of the manifest file that describes the input data objects.

          • DataAttributes (dict) --

            Attributes of the data specified by the customer.

            • ContentClassifiers (list) --

              Declares that your content is free of personally identifiable information or adult content. Amazon SageMaker may restrict the Amazon Mechanical Turk workers that can view your task based on this information.

              • (string) --

    • NextToken (string) --

      If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of labeling jobs, use it in the subsequent request.

ListWorkteams (updated) Link ¶
Changes (response)
{'Workteams': {'MemberDefinitions': {'OidcMemberDefinition': {'Groups': ['string']}},
               'WorkforceArn': 'string'}}

Gets a list of work teams that you have defined in a region. The list may be empty if no work team satisfies the filter specified in the NameContains parameter.

See also: AWS API Documentation

Request Syntax

client.list_workteams(
    SortBy='Name'|'CreateDate',
    SortOrder='Ascending'|'Descending',
    NameContains='string',
    NextToken='string',
    MaxResults=123
)
type SortBy

string

param SortBy

The field to sort results by. The default is CreationTime .

type SortOrder

string

param SortOrder

The sort order for results. The default is Ascending .

type NameContains

string

param NameContains

A string in the work team's name. This filter returns only work teams whose name contains the specified string.

type NextToken

string

param NextToken

If the result of the previous ListWorkteams request was truncated, the response includes a NextToken . To retrieve the next set of labeling jobs, use the token in the next request.

type MaxResults

integer

param MaxResults

The maximum number of work teams to return in each page of the response.

rtype

dict

returns

Response Syntax

{
    'Workteams': [
        {
            'WorkteamName': 'string',
            'MemberDefinitions': [
                {
                    'CognitoMemberDefinition': {
                        'UserPool': 'string',
                        'UserGroup': 'string',
                        'ClientId': 'string'
                    },
                    'OidcMemberDefinition': {
                        'Groups': [
                            'string',
                        ]
                    }
                },
            ],
            'WorkteamArn': 'string',
            'WorkforceArn': 'string',
            'ProductListingIds': [
                'string',
            ],
            'Description': 'string',
            'SubDomain': 'string',
            'CreateDate': datetime(2015, 1, 1),
            'LastUpdatedDate': datetime(2015, 1, 1),
            'NotificationConfiguration': {
                'NotificationTopicArn': 'string'
            }
        },
    ],
    'NextToken': 'string'
}

Response Structure

  • (dict) --

    • Workteams (list) --

      An array of Workteam objects, each describing a work team.

      • (dict) --

        Provides details about a labeling work team.

        • WorkteamName (string) --

          The name of the work team.

        • MemberDefinitions (list) --

          The Amazon Cognito user groups that make up the work team.

          • (dict) --

            Defines the Amazon Cognito user group that is part of a work team.

            • CognitoMemberDefinition (dict) --

              The Amazon Cognito user group that is part of the work team.

              • UserPool (string) --

                An identifier for a user pool. The user pool must be in the same region as the service that you are calling.

              • UserGroup (string) --

                An identifier for a user group.

              • ClientId (string) --

                An identifier for an application client. You must create the app client ID using Amazon Cognito.

            • OidcMemberDefinition (dict) --

              A list user groups that exist in your OIDC Identity Provider (IdP). One to ten groups can be used to create a single private work team. When you add a user group to the list of Groups , you can add that user group to one or more private work teams. If you add a user group to a private work team, all workers in that user group are added to the work team.

              • Groups (list) --

                A list of comma seperated strings that identifies user groups in your OIDC IdP. Each user group is made up of a group of private workers.

                • (string) --

        • WorkteamArn (string) --

          The Amazon Resource Name (ARN) that identifies the work team.

        • WorkforceArn (string) --

          The Amazon Resource Name (ARN) of the workforce.

        • ProductListingIds (list) --

          The Amazon Marketplace identifier for a vendor's work team.

          • (string) --

        • Description (string) --

          A description of the work team.

        • SubDomain (string) --

          The URI of the labeling job's user interface. Workers open this URI to start labeling your data objects.

        • CreateDate (datetime) --

          The date and time that the work team was created (timestamp).

        • LastUpdatedDate (datetime) --

          The date and time that the work team was last updated (timestamp).

        • NotificationConfiguration (dict) --

          Configures SNS notifications of available or expiring work items for work teams.

          • NotificationTopicArn (string) --

            The ARN for the SNS topic to which notifications should be published.

    • NextToken (string) --

      If the response is truncated, Amazon SageMaker returns this token. To retrieve the next set of work teams, use it in the subsequent request.

UpdateWorkforce (updated) Link ¶
Changes (request, response)
Request
{'OidcConfig': {'AuthorizationEndpoint': 'string',
                'ClientId': 'string',
                'ClientSecret': 'string',
                'Issuer': 'string',
                'JwksUri': 'string',
                'LogoutEndpoint': 'string',
                'TokenEndpoint': 'string',
                'UserInfoEndpoint': 'string'}}
Response
{'Workforce': {'CognitoConfig': {'ClientId': 'string', 'UserPool': 'string'},
               'CreateDate': 'timestamp',
               'OidcConfig': {'AuthorizationEndpoint': 'string',
                              'ClientId': 'string',
                              'Issuer': 'string',
                              'JwksUri': 'string',
                              'LogoutEndpoint': 'string',
                              'TokenEndpoint': 'string',
                              'UserInfoEndpoint': 'string'},
               'SubDomain': 'string'}}

Restricts access to tasks assigned to workers in the specified workforce to those within specific ranges of IP addresses. You specify allowed IP addresses by creating a list of up to ten CIDRs.

By default, a workforce isn't restricted to specific IP addresses. If you specify a range of IP addresses, workers who attempt to access tasks using any IP address outside the specified range are denied access and get a Not Found error message on the worker portal. After restricting access with this operation, you can see the allowed IP values for a private workforce with the operation.

Warning

This operation applies only to private workforces.

See also: AWS API Documentation

Request Syntax

client.update_workforce(
    WorkforceName='string',
    SourceIpConfig={
        'Cidrs': [
            'string',
        ]
    },
    OidcConfig={
        'ClientId': 'string',
        'ClientSecret': 'string',
        'Issuer': 'string',
        'AuthorizationEndpoint': 'string',
        'TokenEndpoint': 'string',
        'UserInfoEndpoint': 'string',
        'LogoutEndpoint': 'string',
        'JwksUri': 'string'
    }
)
type WorkforceName

string

param WorkforceName

[REQUIRED]

The name of the private workforce whose access you want to restrict. WorkforceName is automatically set to default when a workforce is created and cannot be modified.

type SourceIpConfig

dict

param SourceIpConfig

A list of one to ten worker IP address ranges ( CIDRs ) that can be used to access tasks assigned to this workforce.

Maximum: Ten CIDR values

  • Cidrs (list) -- [REQUIRED]

    A list of one to ten Classless Inter-Domain Routing (CIDR) values.

    Maximum: Ten CIDR values

    Note

    The following Length Constraints apply to individual CIDR values in the CIDR value list.

    • (string) --

type OidcConfig

dict

param OidcConfig

Use this parameter to update your OIDC Identity Provider (IdP) configuration for a workforce made using your own IdP.

  • ClientId (string) -- [REQUIRED]

    The OIDC IdP client ID used to configure your private workforce.

  • ClientSecret (string) -- [REQUIRED]

    The OIDC IdP client secret used to configure your private workforce.

  • Issuer (string) -- [REQUIRED]

    The OIDC IdP issuer used to configure your private workforce.

  • AuthorizationEndpoint (string) -- [REQUIRED]

    The OIDC IdP authorization endpoint used to configure your private workforce.

  • TokenEndpoint (string) -- [REQUIRED]

    The OIDC IdP token endpoint used to configure your private workforce.

  • UserInfoEndpoint (string) -- [REQUIRED]

    The OIDC IdP user information endpoint used to configure your private workforce.

  • LogoutEndpoint (string) -- [REQUIRED]

    The OIDC IdP logout endpoint used to configure your private workforce.

  • JwksUri (string) -- [REQUIRED]

    The OIDC IdP JSON Web Key Set (Jwks) URI used to configure your private workforce.

rtype

dict

returns

Response Syntax

{
    'Workforce': {
        'WorkforceName': 'string',
        'WorkforceArn': 'string',
        'LastUpdatedDate': datetime(2015, 1, 1),
        'SourceIpConfig': {
            'Cidrs': [
                'string',
            ]
        },
        'SubDomain': 'string',
        'CognitoConfig': {
            'UserPool': 'string',
            'ClientId': 'string'
        },
        'OidcConfig': {
            'ClientId': 'string',
            'Issuer': 'string',
            'AuthorizationEndpoint': 'string',
            'TokenEndpoint': 'string',
            'UserInfoEndpoint': 'string',
            'LogoutEndpoint': 'string',
            'JwksUri': 'string'
        },
        'CreateDate': datetime(2015, 1, 1)
    }
}

Response Structure

  • (dict) --

    • Workforce (dict) --

      A single private workforce, which is automatically created when you create your first private work team. You can create one private work force in each AWS Region. By default, any workforce-related API operation used in a specific region will apply to the workforce created in that region. To learn how to create a private workforce, see Create a Private Workforce.

      • WorkforceName (string) --

        The name of the private workforce.

      • WorkforceArn (string) --

        The Amazon Resource Name (ARN) of the private workforce.

      • LastUpdatedDate (datetime) --

        The most recent date that was used to successfully add one or more IP address ranges ( CIDRs ) to a private workforce's allow list.

      • SourceIpConfig (dict) --

        A list of one to ten IP address ranges ( CIDRs ) to be added to the workforce allow list.

        • Cidrs (list) --

          A list of one to ten Classless Inter-Domain Routing (CIDR) values.

          Maximum: Ten CIDR values

          Note

          The following Length Constraints apply to individual CIDR values in the CIDR value list.

          • (string) --

      • SubDomain (string) --

        The subdomain for your OIDC Identity Provider.

      • CognitoConfig (dict) --

        The configuration of an Amazon Cognito workforce. A single Cognito workforce is created using and corresponds to a single Amazon Cognito user pool.

        • UserPool (string) --

          A user pool is a user directory in Amazon Cognito. With a user pool, your users can sign in to your web or mobile app through Amazon Cognito. Your users can also sign in through social identity providers like Google, Facebook, Amazon, or Apple, and through SAML identity providers.

        • ClientId (string) --

          The client ID for your Amazon Cognito user pool.

      • OidcConfig (dict) --

        The configuration of an OIDC Identity Provider (IdP) private workforce.

        • ClientId (string) --

          The OIDC IdP client ID used to configure your private workforce.

        • Issuer (string) --

          The OIDC IdP issuer used to configure your private workforce.

        • AuthorizationEndpoint (string) --

          The OIDC IdP authorization endpoint used to configure your private workforce.

        • TokenEndpoint (string) --

          The OIDC IdP token endpoint used to configure your private workforce.

        • UserInfoEndpoint (string) --

          The OIDC IdP user information endpoint used to configure your private workforce.

        • LogoutEndpoint (string) --

          The OIDC IdP logout endpoint used to configure your private workforce.

        • JwksUri (string) --

          The OIDC IdP JSON Web Key Set (Jwks) URI used to configure your private workforce.

      • CreateDate (datetime) --

        The date that the workforce is created.

UpdateWorkteam (updated) Link ¶
Changes (request, response)
Request
{'MemberDefinitions': {'OidcMemberDefinition': {'Groups': ['string']}}}
Response
{'Workteam': {'MemberDefinitions': {'OidcMemberDefinition': {'Groups': ['string']}},
              'WorkforceArn': 'string'}}

Updates an existing work team with new member definitions or description.

See also: AWS API Documentation

Request Syntax

client.update_workteam(
    WorkteamName='string',
    MemberDefinitions=[
        {
            'CognitoMemberDefinition': {
                'UserPool': 'string',
                'UserGroup': 'string',
                'ClientId': 'string'
            },
            'OidcMemberDefinition': {
                'Groups': [
                    'string',
                ]
            }
        },
    ],
    Description='string',
    NotificationConfiguration={
        'NotificationTopicArn': 'string'
    }
)
type WorkteamName

string

param WorkteamName

[REQUIRED]

The name of the work team to update.

type MemberDefinitions

list

param MemberDefinitions

A list of MemberDefinition objects that contain the updated work team members.

  • (dict) --

    Defines the Amazon Cognito user group that is part of a work team.

    • CognitoMemberDefinition (dict) --

      The Amazon Cognito user group that is part of the work team.

      • UserPool (string) -- [REQUIRED]

        An identifier for a user pool. The user pool must be in the same region as the service that you are calling.

      • UserGroup (string) -- [REQUIRED]

        An identifier for a user group.

      • ClientId (string) -- [REQUIRED]

        An identifier for an application client. You must create the app client ID using Amazon Cognito.

    • OidcMemberDefinition (dict) --

      A list user groups that exist in your OIDC Identity Provider (IdP). One to ten groups can be used to create a single private work team. When you add a user group to the list of Groups , you can add that user group to one or more private work teams. If you add a user group to a private work team, all workers in that user group are added to the work team.

      • Groups (list) -- [REQUIRED]

        A list of comma seperated strings that identifies user groups in your OIDC IdP. Each user group is made up of a group of private workers.

        • (string) --

type Description

string

param Description

An updated description for the work team.

type NotificationConfiguration

dict

param NotificationConfiguration

Configures SNS topic notifications for available or expiring work items

  • NotificationTopicArn (string) --

    The ARN for the SNS topic to which notifications should be published.

rtype

dict

returns

Response Syntax

{
    'Workteam': {
        'WorkteamName': 'string',
        'MemberDefinitions': [
            {
                'CognitoMemberDefinition': {
                    'UserPool': 'string',
                    'UserGroup': 'string',
                    'ClientId': 'string'
                },
                'OidcMemberDefinition': {
                    'Groups': [
                        'string',
                    ]
                }
            },
        ],
        'WorkteamArn': 'string',
        'WorkforceArn': 'string',
        'ProductListingIds': [
            'string',
        ],
        'Description': 'string',
        'SubDomain': 'string',
        'CreateDate': datetime(2015, 1, 1),
        'LastUpdatedDate': datetime(2015, 1, 1),
        'NotificationConfiguration': {
            'NotificationTopicArn': 'string'
        }
    }
}

Response Structure

  • (dict) --

    • Workteam (dict) --

      A Workteam object that describes the updated work team.

      • WorkteamName (string) --

        The name of the work team.

      • MemberDefinitions (list) --

        The Amazon Cognito user groups that make up the work team.

        • (dict) --

          Defines the Amazon Cognito user group that is part of a work team.

          • CognitoMemberDefinition (dict) --

            The Amazon Cognito user group that is part of the work team.

            • UserPool (string) --

              An identifier for a user pool. The user pool must be in the same region as the service that you are calling.

            • UserGroup (string) --

              An identifier for a user group.

            • ClientId (string) --

              An identifier for an application client. You must create the app client ID using Amazon Cognito.

          • OidcMemberDefinition (dict) --

            A list user groups that exist in your OIDC Identity Provider (IdP). One to ten groups can be used to create a single private work team. When you add a user group to the list of Groups , you can add that user group to one or more private work teams. If you add a user group to a private work team, all workers in that user group are added to the work team.

            • Groups (list) --

              A list of comma seperated strings that identifies user groups in your OIDC IdP. Each user group is made up of a group of private workers.

              • (string) --

      • WorkteamArn (string) --

        The Amazon Resource Name (ARN) that identifies the work team.

      • WorkforceArn (string) --

        The Amazon Resource Name (ARN) of the workforce.

      • ProductListingIds (list) --

        The Amazon Marketplace identifier for a vendor's work team.

        • (string) --

      • Description (string) --

        A description of the work team.

      • SubDomain (string) --

        The URI of the labeling job's user interface. Workers open this URI to start labeling your data objects.

      • CreateDate (datetime) --

        The date and time that the work team was created (timestamp).

      • LastUpdatedDate (datetime) --

        The date and time that the work team was last updated (timestamp).

      • NotificationConfiguration (dict) --

        Configures SNS notifications of available or expiring work items for work teams.

        • NotificationTopicArn (string) --

          The ARN for the SNS topic to which notifications should be published.