class_docstr: Placeholder docstring
docstr: Placeholder docstring
docstr_tok: ["Placeholder","docstring"]
code: def _get_transform_args(
      cls,
      transformer,
      data,
      data_type,
      content_type,
      compression_type,
      split_type,
      input_filter,
      output_filter,
      join_source,
      experiment_config,
      model_client_config,
      batch_data_capture_config,
  ):
      """Placeholder docstring"""
  
      config = _TransformJob._load_config(
          data,
          data_type,
          content_type,
          compression_type,
          split_type,
          transformer,
      )
      data_processing = _TransformJob._prepare_data_processing(
          input_filter, output_filter, join_source
      )
  
      transform_args = config.copy()
      transform_args.update(
          {
              "job_name": transformer._current_job_name,
              "model_name": transformer.model_name,
              "strategy": transformer.strategy,
              "max_concurrent_transforms": transformer.max_concurrent_transforms,
              "max_payload": transformer.max_payload,
              "env": transformer.env,
              "experiment_config": experiment_config,
              "model_client_config": model_client_config,
              "tags": transformer.tags,
              "data_processing": data_processing,
              "batch_data_capture_config": batch_data_capture_config,
          }
      )
  
      return transform_args
  
imports: from __future__ import absolute_import
  from typing import Union, Optional, Dict
  import logging
  import copy
  import time
  from botocore import exceptions
  from sagemaker import s3
  from sagemaker.config import TRANSFORM_JOB_ENVIRONMENT_PATH, TRANSFORM_OUTPUT_KMS_KEY_ID_PATH, TRANSFORM_JOB_KMS_KEY_ID_PATH, TRANSFORM_RESOURCES_VOLUME_KMS_KEY_ID_PATH, PIPELINE_ROLE_ARN_PATH
  from sagemaker.job import _Job
  from sagemaker.session import Session, get_execution_role
  from sagemaker.inputs import BatchDataCaptureConfig
  from sagemaker.workflow.entities import PipelineVariable
  from sagemaker.workflow.functions import Join
  from sagemaker.workflow.pipeline_context import runnable_by_pipeline, PipelineSession
  from sagemaker.workflow import is_pipeline_variable
  from sagemaker.workflow.execution_variables import ExecutionVariables
  from sagemaker.utils import base_name_from_image, name_from_base, check_and_get_run_experiment_config, resolve_value_from_config, resolve_class_attribute_from_config, format_tags, Tags
label_desc: Use image node_id 2 for calling the _TransformJob obj's underlying member method code with example usage: obj._get_transform_args(cls, transformer, data, data_type, content_type, compression_type, split_type, input_filter, output_filter, join_source, experiment_config, model_client_config, batch_data_capture_config) and returns: transform_args