SageMakerCreateTransformJobProps¶
-
class
aws_cdk.aws_stepfunctions_tasks.
SageMakerCreateTransformJobProps
(*, comment=None, heartbeat=None, input_path=None, integration_pattern=None, output_path=None, result_path=None, timeout=None, model_name, transform_input, transform_job_name, transform_output, batch_strategy=None, environment=None, max_concurrent_transforms=None, max_payload=None, model_client_options=None, role=None, tags=None, transform_resources=None)¶ Bases:
aws_cdk.aws_stepfunctions.TaskStateBaseProps
(experimental) Properties for creating an Amazon SageMaker transform job task.
- Parameters
comment (
Optional
[str
]) – An optional description for this state. Default: - No commentheartbeat (
Optional
[Duration
]) – Timeout for the heartbeat. Default: - Noneinput_path (
Optional
[str
]) – JSONPath expression to select part of the state to be the input to this state. May also be the special value JsonPath.DISCARD, which will cause the effective input to be the empty object {}. Default: - The entire task input (JSON path ‘$’)integration_pattern (
Optional
[IntegrationPattern
]) – AWS Step Functions integrates with services directly in the Amazon States Language. You can control these AWS services using service integration patterns Default: IntegrationPattern.REQUEST_RESPONSEoutput_path (
Optional
[str
]) – JSONPath expression to select select a portion of the state output to pass to the next state. May also be the special value JsonPath.DISCARD, which will cause the effective output to be the empty object {}. Default: - The entire JSON node determined by the state input, the task result, and resultPath is passed to the next state (JSON path ‘$’)result_path (
Optional
[str
]) – JSONPath expression to indicate where to inject the state’s output. May also be the special value JsonPath.DISCARD, which will cause the state’s input to become its output. Default: - Replaces the entire input with the result (JSON path ‘$’)timeout (
Optional
[Duration
]) – Timeout for the state machine. Default: - Nonemodel_name (
str
) – (experimental) Name of the model that you want to use for the transform job.transform_input (
TransformInput
) – (experimental) Dataset to be transformed and the Amazon S3 location where it is stored.transform_job_name (
str
) – (experimental) Transform Job Name.transform_output (
TransformOutput
) – (experimental) S3 location where you want Amazon SageMaker to save the results from the transform job.batch_strategy (
Optional
[BatchStrategy
]) – (experimental) Number of records to include in a mini-batch for an HTTP inference request. Default: - No batch strategyenvironment (
Optional
[Mapping
[str
,str
]]) – (experimental) Environment variables to set in the Docker container. Default: - No environment variablesmax_concurrent_transforms (
Union
[int
,float
,None
]) – (experimental) Maximum number of parallel requests that can be sent to each instance in a transform job. Default: - Amazon SageMaker checks the optional execution-parameters to determine the settings for your chosen algorithm. If the execution-parameters endpoint is not enabled, the default value is 1.max_payload (
Optional
[Size
]) – (experimental) Maximum allowed size of the payload, in MB. Default: 6model_client_options (
Optional
[ModelClientOptions
]) – (experimental) Configures the timeout and maximum number of retries for processing a transform job invocation. Default: - 0 retries and 60 seconds of timeoutrole (
Optional
[IRole
]) – (experimental) Role for the Transform Job. Default: - A role is created withAmazonSageMakerFullAccess
managed policytags (
Optional
[Mapping
[str
,str
]]) – (experimental) Tags to be applied to the train job. Default: - No tagstransform_resources (
Optional
[TransformResources
]) – (experimental) ML compute instances for the transform job. Default: - 1 instance of type M4.XLarge
- Stability
experimental
Attributes
-
batch_strategy
¶ (experimental) Number of records to include in a mini-batch for an HTTP inference request.
- Default
No batch strategy
- Stability
experimental
- Return type
Optional
[BatchStrategy
]
-
comment
¶ An optional description for this state.
- Default
No comment
- Return type
Optional
[str
]
-
environment
¶ (experimental) Environment variables to set in the Docker container.
- Default
No environment variables
- Stability
experimental
- Return type
Optional
[Mapping
[str
,str
]]
-
input_path
¶ JSONPath expression to select part of the state to be the input to this state.
May also be the special value JsonPath.DISCARD, which will cause the effective input to be the empty object {}.
- Default
The entire task input (JSON path ‘$’)
- Return type
Optional
[str
]
-
integration_pattern
¶ AWS Step Functions integrates with services directly in the Amazon States Language.
You can control these AWS services using service integration patterns
- Default
IntegrationPattern.REQUEST_RESPONSE
- See
https://docs.aws.amazon.com/step-functions/latest/dg/connect-to-resource.html#connect-wait-token
- Return type
Optional
[IntegrationPattern
]
-
max_concurrent_transforms
¶ (experimental) Maximum number of parallel requests that can be sent to each instance in a transform job.
- Default
Amazon SageMaker checks the optional execution-parameters to determine the settings for your chosen algorithm.
If the execution-parameters endpoint is not enabled, the default value is 1.
- Stability
experimental
- Return type
Union
[int
,float
,None
]
-
max_payload
¶ (experimental) Maximum allowed size of the payload, in MB.
- Default
6
- Stability
experimental
- Return type
Optional
[Size
]
-
model_client_options
¶ (experimental) Configures the timeout and maximum number of retries for processing a transform job invocation.
- Default
0 retries and 60 seconds of timeout
- Stability
experimental
- Return type
Optional
[ModelClientOptions
]
-
model_name
¶ (experimental) Name of the model that you want to use for the transform job.
- Stability
experimental
- Return type
str
-
output_path
¶ JSONPath expression to select select a portion of the state output to pass to the next state.
May also be the special value JsonPath.DISCARD, which will cause the effective output to be the empty object {}.
- Default
The entire JSON node determined by the state input, the task result,
and resultPath is passed to the next state (JSON path ‘$’)
- Return type
Optional
[str
]
-
result_path
¶ JSONPath expression to indicate where to inject the state’s output.
May also be the special value JsonPath.DISCARD, which will cause the state’s input to become its output.
- Default
Replaces the entire input with the result (JSON path ‘$’)
- Return type
Optional
[str
]
-
role
¶ (experimental) Role for the Transform Job.
- Default
A role is created with
AmazonSageMakerFullAccess
managed policy
- Stability
experimental
- Return type
Optional
[IRole
]
(experimental) Tags to be applied to the train job.
- Default
No tags
- Stability
experimental
- Return type
Optional
[Mapping
[str
,str
]]
-
transform_input
¶ (experimental) Dataset to be transformed and the Amazon S3 location where it is stored.
- Stability
experimental
- Return type
-
transform_job_name
¶ (experimental) Transform Job Name.
- Stability
experimental
- Return type
str
-
transform_output
¶ (experimental) S3 location where you want Amazon SageMaker to save the results from the transform job.
- Stability
experimental
- Return type
-
transform_resources
¶ (experimental) ML compute instances for the transform job.
- Default
1 instance of type M4.XLarge
- Stability
experimental
- Return type
Optional
[TransformResources
]