STOPINFERENCEEXPERIMENT()`¶

About StopInferenceExperiment¶

Stops an inference experiment.

Method Signature¶

METHODS /AWS1/IF_SGM~STOPINFERENCEEXPERIMENT
  IMPORTING
    !IV_NAME TYPE /AWS1/SGMINFERENCEEXPERIMENT00 OPTIONAL
    !IT_MODELVARIANTACTIONS TYPE /AWS1/CL_SGMMDELVARIANTACTMA00=>TT_MODELVARIANTACTIONMAP OPTIONAL
    !IT_DESIREDMODELVARIANTS TYPE /AWS1/CL_SGMMODELVARIANTCONFIG=>TT_MODELVARIANTCONFIGLIST OPTIONAL
    !IV_DESIREDSTATE TYPE /AWS1/SGMINFERENCEEXPERIMENT06 OPTIONAL
    !IV_REASON TYPE /AWS1/SGMINFERENCEEXPERIMENT05 OPTIONAL
  RETURNING
    VALUE(OO_OUTPUT) TYPE REF TO /aws1/cl_sgmstopinferenceexp01
  RAISING
    /AWS1/CX_SGMCONFLICTEXCEPTION
    /AWS1/CX_SGMRESOURCENOTFOUND
    /AWS1/CX_SGMCLIENTEXC
    /AWS1/CX_SGMSERVEREXC
    /AWS1/CX_RT_TECHNICAL_GENERIC
    /AWS1/CX_RT_SERVICE_GENERIC.

IMPORTING¶

Required arguments:¶

`iv_name` `TYPE /AWS1/SGMINFERENCEEXPERIMENT00` `/AWS1/SGMINFERENCEEXPERIMENT00`¶

The name of the inference experiment to stop.

`it_modelvariantactions` `TYPE /AWS1/CL_SGMMDELVARIANTACTMA00=>TT_MODELVARIANTACTIONMAP` `TT_MODELVARIANTACTIONMAP`¶

Array of key-value pairs, with names of variants mapped to actions. The possible actions are the following:

Promote - Promote the shadow variant to a production variant

Remove - Delete the variant

Retain - Keep the variant as it is

Optional arguments:¶

`it_desiredmodelvariants` `TYPE /AWS1/CL_SGMMODELVARIANTCONFIG=>TT_MODELVARIANTCONFIGLIST` `TT_MODELVARIANTCONFIGLIST`¶

An array of ModelVariantConfig objects. There is one for each variant that you want to deploy after the inference experiment stops. Each ModelVariantConfig describes the infrastructure configuration for deploying the corresponding variant.

`iv_desiredstate` `TYPE /AWS1/SGMINFERENCEEXPERIMENT06` `/AWS1/SGMINFERENCEEXPERIMENT06`¶

The desired state of the experiment after stopping. The possible states are the following:

Completed: The experiment completed successfully

Cancelled: The experiment was canceled

`iv_reason` `TYPE /AWS1/SGMINFERENCEEXPERIMENT05` `/AWS1/SGMINFERENCEEXPERIMENT05`¶

The reason for stopping the experiment.

RETURNING¶

`oo_output` `TYPE REF TO /aws1/cl_sgmstopinferenceexp01` `/AWS1/CL_SGMSTOPINFERENCEEXP01`¶

Domain /AWS1/RT_ACCOUNT_ID

Primitive Type NUMC

Examples¶

Syntax Example¶

This is an example of the syntax for calling the method. It includes every possible argument and initializes every possible value. The data provided is not necessarily semantically accurate (for example the value "string" may be provided for something that is intended to be an instance ID, or in some cases two arguments may be mutually exclusive). The syntax shows the ABAP syntax for creating the various data structures.

DATA(lo_result) = lo_client->stopinferenceexperiment(
  it_desiredmodelvariants = VALUE /aws1/cl_sgmmodelvariantconfig=>tt_modelvariantconfiglist(
    (
      new /aws1/cl_sgmmodelvariantconfig(
        io_infrastructureconfig = new /aws1/cl_sgmmdelinfrastructu00(
          io_realtimeinferenceconfig = new /aws1/cl_sgmrealtimeinferenc01(
            iv_instancecount = 123
            iv_instancetype = |string|
          )
          iv_infrastructuretype = |string|
        )
        iv_modelname = |string|
        iv_variantname = |string|
      )
    )
  )
  it_modelvariantactions = VALUE /aws1/cl_sgmmdelvariantactma00=>tt_modelvariantactionmap(
    (
      VALUE /aws1/cl_sgmmdelvariantactma00=>ts_modelvariantactmap_maprow(
        key = |string|
        value = new /aws1/cl_sgmmdelvariantactma00( |string| )
      )
    )
  )
  iv_desiredstate = |string|
  iv_name = |string|
  iv_reason = |string|
).

This is an example of reading all possible response values

lo_result = lo_result.
IF lo_result IS NOT INITIAL.
  lv_inferenceexperimentarn = lo_result->get_inferenceexperimentarn( ).
ENDIF.

/AWS1/IF_SGM=>STOPINFERENCEEXPERIMENT()¶