CfnAIWorkloadConfigPropsMixin

class aws_cdk.cfn_property_mixins.aws_sagemaker.CfnAIWorkloadConfigPropsMixin(props, *, strategy=None)

Bases: Mixin

Resource Type definition for AWS::SageMaker::AIWorkloadConfig.

A reusable AI workload configuration that defines datasets, data sources and benchmark tool settings for consistent performance testing of generative AI inference deployments on Amazon SageMaker AI.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-aiworkloadconfig.html
CloudformationResource:: AWS::SageMaker::AIWorkloadConfig
Mixin:: true
ExampleMetadata:: fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk.cfn_property_mixins import aws_sagemaker as sagemaker
import aws_cdk as cdk

# merge_strategy: cdk.IMergeStrategy

cfn_ai_workload_config_props_mixin = sagemaker.CfnAIWorkloadConfigPropsMixin(sagemaker.CfnAIWorkloadConfigMixinProps(
    ai_workload_config_name="aiWorkloadConfigName",
    ai_workload_configs=sagemaker.CfnAIWorkloadConfigPropsMixin.AIWorkloadConfigsProperty(
        workload_spec=sagemaker.CfnAIWorkloadConfigPropsMixin.WorkloadSpecProperty(
            inline="inline"
        )
    ),
    dataset_config=sagemaker.CfnAIWorkloadConfigPropsMixin.AIDatasetConfigProperty(
        input_data_config=[sagemaker.CfnAIWorkloadConfigPropsMixin.AIWorkloadInputDataConfigProperty(
            channel_name="channelName",
            data_source=sagemaker.CfnAIWorkloadConfigPropsMixin.AIWorkloadDataSourceProperty(
                s3_data_source=sagemaker.CfnAIWorkloadConfigPropsMixin.AIWorkloadS3DataSourceProperty(
                    s3_uri="s3Uri"
                )
            )
        )]
    ),
    tags=[cdk.CfnTag(
        key="key",
        value="value"
    )]
),
    strategy=merge_strategy
)

Create a mixin to apply properties to AWS::SageMaker::AIWorkloadConfig.

Parameters:

props (Union[CfnAIWorkloadConfigMixinProps, Dict[str, Any]]) – L1 properties to apply.
strategy (Optional[IMergeStrategy]) – Strategy for merging nested properties. Default: - PropertyMergeStrategy.combine()

Methods

apply_to(construct)

Apply the mixin properties to the construct.

Parameters:: construct (IConstruct)
Return type:: None

supports(construct)

Check if this mixin supports the given construct.

Parameters:: construct (IConstruct)
Return type:: bool

Attributes

CFN_PROPERTY_KEYS = ['aiWorkloadConfigName', 'aiWorkloadConfigs', 'datasetConfig', 'tags']

Static Methods

classmethod is_mixin(x)

Checks if x is a Mixin.

Parameters:: x (Any) – Any object.
Return type:: bool
Returns:: true if x is an object created from a class which extends Mixin.

AIDatasetConfigProperty

class CfnAIWorkloadConfigPropsMixin.AIDatasetConfigProperty(*, input_data_config=None)

Bases: object

The dataset configuration for an AI workload.

Parameters:: input_data_config (Union[IResolvable, Sequence[Union[IResolvable, AIWorkloadInputDataConfigProperty, Dict[str, Any]]], None]) – An array of input data channel configurations for the workload.
See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-aiworkloadconfig-aidatasetconfig.html
ExampleMetadata:: fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk.cfn_property_mixins import aws_sagemaker as sagemaker

a_i_dataset_config_property = sagemaker.CfnAIWorkloadConfigPropsMixin.AIDatasetConfigProperty(
    input_data_config=[sagemaker.CfnAIWorkloadConfigPropsMixin.AIWorkloadInputDataConfigProperty(
        channel_name="channelName",
        data_source=sagemaker.CfnAIWorkloadConfigPropsMixin.AIWorkloadDataSourceProperty(
            s3_data_source=sagemaker.CfnAIWorkloadConfigPropsMixin.AIWorkloadS3DataSourceProperty(
                s3_uri="s3Uri"
            )
        )
    )]
)

Attributes

input_data_config

An array of input data channel configurations for the workload.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-aiworkloadconfig-aidatasetconfig.html#cfn-sagemaker-aiworkloadconfig-aidatasetconfig-inputdataconfig

AIWorkloadConfigsProperty

class CfnAIWorkloadConfigPropsMixin.AIWorkloadConfigsProperty(*, workload_spec=None)

Bases: object

The benchmark tool configuration for an AI workload.

Parameters:: workload_spec (Union[IResolvable, WorkloadSpecProperty, Dict[str, Any], None]) – The workload specification for benchmark tool configuration.
See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-aiworkloadconfig-aiworkloadconfigs.html
ExampleMetadata:: fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk.cfn_property_mixins import aws_sagemaker as sagemaker

a_i_workload_configs_property = sagemaker.CfnAIWorkloadConfigPropsMixin.AIWorkloadConfigsProperty(
    workload_spec=sagemaker.CfnAIWorkloadConfigPropsMixin.WorkloadSpecProperty(
        inline="inline"
    )
)

Attributes

workload_spec

The workload specification for benchmark tool configuration.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-aiworkloadconfig-aiworkloadconfigs.html#cfn-sagemaker-aiworkloadconfig-aiworkloadconfigs-workloadspec

AIWorkloadDataSourceProperty

class CfnAIWorkloadConfigPropsMixin.AIWorkloadDataSourceProperty(*, s3_data_source=None)

Bases: object

The data source for an AI workload input data channel.

Parameters:: s3_data_source (Union[IResolvable, AIWorkloadS3DataSourceProperty, Dict[str, Any], None]) – The Amazon S3 data source for an AI workload.
See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-aiworkloadconfig-aiworkloaddatasource.html
ExampleMetadata:: fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk.cfn_property_mixins import aws_sagemaker as sagemaker

a_i_workload_data_source_property = sagemaker.CfnAIWorkloadConfigPropsMixin.AIWorkloadDataSourceProperty(
    s3_data_source=sagemaker.CfnAIWorkloadConfigPropsMixin.AIWorkloadS3DataSourceProperty(
        s3_uri="s3Uri"
    )
)

Attributes

s3_data_source

The Amazon S3 data source for an AI workload.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-aiworkloadconfig-aiworkloaddatasource.html#cfn-sagemaker-aiworkloadconfig-aiworkloaddatasource-s3datasource

AIWorkloadInputDataConfigProperty

class CfnAIWorkloadConfigPropsMixin.AIWorkloadInputDataConfigProperty(*, channel_name=None, data_source=None)

Bases: object

A channel of input data for an AI workload configuration.

Parameters:

channel_name (Optional[str]) – The logical name for the data channel.
data_source (Union[IResolvable, AIWorkloadDataSourceProperty, Dict[str, Any], None]) – The data source for an AI workload input data channel.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-aiworkloadconfig-aiworkloadinputdataconfig.html

ExampleMetadata:

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk.cfn_property_mixins import aws_sagemaker as sagemaker

a_i_workload_input_data_config_property = sagemaker.CfnAIWorkloadConfigPropsMixin.AIWorkloadInputDataConfigProperty(
    channel_name="channelName",
    data_source=sagemaker.CfnAIWorkloadConfigPropsMixin.AIWorkloadDataSourceProperty(
        s3_data_source=sagemaker.CfnAIWorkloadConfigPropsMixin.AIWorkloadS3DataSourceProperty(
            s3_uri="s3Uri"
        )
    )
)

Attributes

channel_name

The logical name for the data channel.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-aiworkloadconfig-aiworkloadinputdataconfig.html#cfn-sagemaker-aiworkloadconfig-aiworkloadinputdataconfig-channelname

data_source

The data source for an AI workload input data channel.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-aiworkloadconfig-aiworkloadinputdataconfig.html#cfn-sagemaker-aiworkloadconfig-aiworkloadinputdataconfig-datasource

AIWorkloadS3DataSourceProperty

class CfnAIWorkloadConfigPropsMixin.AIWorkloadS3DataSourceProperty(*, s3_uri=None)

Bases: object

The Amazon S3 data source for an AI workload.

Parameters:: s3_uri (Optional[str]) – The Amazon S3 URI of the data.
See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-aiworkloadconfig-aiworkloads3datasource.html
ExampleMetadata:: fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk.cfn_property_mixins import aws_sagemaker as sagemaker

a_i_workload_s3_data_source_property = sagemaker.CfnAIWorkloadConfigPropsMixin.AIWorkloadS3DataSourceProperty(
    s3_uri="s3Uri"
)

Attributes

s3_uri

The Amazon S3 URI of the data.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-aiworkloadconfig-aiworkloads3datasource.html#cfn-sagemaker-aiworkloadconfig-aiworkloads3datasource-s3uri

WorkloadSpecProperty

class CfnAIWorkloadConfigPropsMixin.WorkloadSpecProperty(*, inline=None)

Bases: object

The workload specification for benchmark tool configuration.

Parameters:: inline (Optional[str]) – An inline YAML or JSON string that defines benchmark parameters. The service validates the document against its own benchmark schema: it must declare a benchmark object whose type member matches the pattern ^(aiperf)$.
See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-aiworkloadconfig-workloadspec.html
ExampleMetadata:: fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
from aws_cdk.cfn_property_mixins import aws_sagemaker as sagemaker

workload_spec_property = sagemaker.CfnAIWorkloadConfigPropsMixin.WorkloadSpecProperty(
    inline="inline"
)

Attributes

inline

An inline YAML or JSON string that defines benchmark parameters.

The service validates the document against its own benchmark schema: it must declare a benchmark object whose type member matches the pattern ^(aiperf)$.

See:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-aiworkloadconfig-workloadspec.html#cfn-sagemaker-aiworkloadconfig-workloadspec-inline