class_docstr: Configuration object passed in when create a batch transform job.
  
  Specifies configuration related to batch transform job data capture for use with
  Amazon SageMaker Model Monitoring
class_docstr_tok: ["Configuration","object","passed","in","when","create","a","batch","transform","job",".","Specifies","configuration","related","to","batch","transform","job","data","capture","for","use","with","Amazon","SageMaker","Model","Monitoring"]
docstr: Generates a request dictionary using the parameters provided to the class.
docstr_tok: ["Generates","a","request","dictionary","using","the","parameters","provided","to","the","class","."]
code: def _to_request_dict(self):
      """Generates a request dictionary using the parameters provided to the class."""
      batch_data_capture_config = {
          "DestinationS3Uri": self.destination_s3_uri,
      }
  
      if self.kms_key_id is not None:
          batch_data_capture_config["KmsKeyId"] = self.kms_key_id
      if self.generate_inference_id is not None:
          batch_data_capture_config[
              "GenerateInferenceId"
          ] = self.generate_inference_id
  
      return batch_data_capture_config
  
imports: from __future__ import absolute_import, print_function
  from typing import Union, Optional, List
  import attr
  from sagemaker.workflow.entities import PipelineVariable
label_desc: Use image node_id 2 for calling the BatchDataCaptureConfig obj's underlying member method code with example usage: obj._to_request_dict() and returns: batch_data_capture_config