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pub struct TransformJobDefinition {
    pub batch_strategy: Option<String>,
    pub environment: Option<HashMap<String, String>>,
    pub max_concurrent_transforms: Option<i64>,
    pub max_payload_in_mb: Option<i64>,
    pub transform_input: TransformInput,
    pub transform_output: TransformOutput,
    pub transform_resources: TransformResources,
}
Expand description

Defines the input needed to run a transform job using the inference specification specified in the algorithm.

Fields

batch_strategy: Option<String>

A string that determines the number of records included in a single mini-batch.

SingleRecord means only one record is used per mini-batch. MultiRecord means a mini-batch is set to contain as many records that can fit within the MaxPayloadInMB limit.

environment: Option<HashMap<String, String>>

The environment variables to set in the Docker container. We support up to 16 key and values entries in the map.

max_concurrent_transforms: Option<i64>

The maximum number of parallel requests that can be sent to each instance in a transform job. The default value is 1.

max_payload_in_mb: Option<i64>

The maximum payload size allowed, in MB. A payload is the data portion of a record (without metadata).

transform_input: TransformInput

A description of the input source and the way the transform job consumes it.

transform_output: TransformOutput

Identifies the Amazon S3 location where you want Amazon SageMaker to save the results from the transform job.

transform_resources: TransformResources

Identifies the ML compute instances for the transform job.

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