code: def _parse_kubernetes_config(backend_config):
      """
      Creates build context tarfile containing Dockerfile and project code, returning path to tarfile
      """
      if not backend_config:
          raise ExecutionException("Backend_config file not found.")
      kube_config = backend_config.copy()
      if "kube-job-template-path" not in backend_config.keys():
          raise ExecutionException(
              "'kube-job-template-path' attribute must be specified in backend_config."
          )
      kube_job_template = backend_config["kube-job-template-path"]
      if os.path.exists(kube_job_template):
          with open(kube_job_template) as job_template:
              yaml_obj = yaml.safe_load(job_template.read())
          kube_job_template = yaml_obj
          kube_config["kube-job-template"] = kube_job_template
      else:
          raise ExecutionException(
              f"Could not find 'kube-job-template-path': {kube_job_template}"
          )
      if "kube-context" not in backend_config.keys():
          _logger.debug(
              "Could not find kube-context in backend_config."
              " Using current context or in-cluster config."
          )
      if "repository-uri" not in backend_config.keys():
          raise ExecutionException(
              "Could not find 'repository-uri' in backend_config."
          )
      return kube_config
  
imports: import json
  import logging
  import os
  import yaml
  import mlflow.projects.databricks
  import mlflow.utils.uri
  from mlflow import tracking
  from mlflow.entities import RunStatus
  from mlflow.exceptions import ExecutionException, MlflowException
  from mlflow.projects.backend import loader
  from mlflow.projects.submitted_run import SubmittedRun
  from mlflow.projects.utils import MLFLOW_LOCAL_BACKEND_RUN_ID_CONFIG, PROJECT_BUILD_IMAGE, PROJECT_DOCKER_ARGS, PROJECT_DOCKER_AUTH, PROJECT_ENV_MANAGER, PROJECT_STORAGE_DIR, PROJECT_SYNCHRONOUS, fetch_and_validate_project, get_entry_point_command, get_or_create_run, get_run_env_vars, load_project
  from mlflow.tracking.fluent import _get_experiment_id
  from mlflow.utils import env_manager
  from mlflow.utils.mlflow_tags import MLFLOW_DOCKER_IMAGE_ID, MLFLOW_PROJECT_BACKEND, MLFLOW_PROJECT_ENV, MLFLOW_RUN_NAME
label_desc: Use image node_id 7 for calling a global function with example usage: _parse_kubernetes_config(backend_config) and returns: kube_config