code: def before_run_validations(tracking_uri, backend_config):
      """Validations to perform before running a project on Databricks."""
      if backend_config is None:
          raise ExecutionException(
              "Backend spec must be provided when launching MLflow project runs on Databricks."
          )
      elif "existing_cluster_id" in backend_config:
          raise MlflowException(
              message=(
                  "MLflow Project runs on Databricks must provide a *new cluster* specification."
                  " Project execution against existing clusters is not currently supported. For more"
                  " information, see https://mlflow.org/docs/latest/projects.html"
                  "#run-an-mlflow-project-on-databricks"
              ),
              error_code=INVALID_PARAMETER_VALUE,
          )
      if not is_databricks_uri(tracking_uri) and not is_http_uri(
          tracking_uri
      ):
          raise ExecutionException(
              "When running on Databricks, the MLflow tracking URI must be of the form "
              "'databricks' or 'databricks://profile', or a remote HTTP URI accessible to both the "
              "current client and code running on Databricks. Got local tracking URI %s. "
              "Please specify a valid tracking URI via mlflow.set_tracking_uri or by setting the "
              "MLFLOW_TRACKING_URI environment variable." % tracking_uri
          )
  
imports: import hashlib
  import json
  import logging
  import os
  import posixpath
  import re
  import tempfile
  import textwrap
  import time
  from shlex import quote
  from mlflow import tracking
  from mlflow.entities import RunStatus
  from mlflow.environment_variables import MLFLOW_EXPERIMENT_ID, MLFLOW_TRACKING_URI
  from mlflow.exceptions import ExecutionException, MlflowException
  from mlflow.projects.submitted_run import SubmittedRun
  from mlflow.projects.utils import MLFLOW_LOCAL_BACKEND_RUN_ID_CONFIG
  from mlflow.protos.databricks_pb2 import INVALID_PARAMETER_VALUE
  from mlflow.utils import databricks_utils, file_utils, rest_utils
  from mlflow.utils.mlflow_tags import MLFLOW_DATABRICKS_RUN_URL, MLFLOW_DATABRICKS_SHELL_JOB_ID, MLFLOW_DATABRICKS_SHELL_JOB_RUN_ID, MLFLOW_DATABRICKS_WEBAPP_URL
  from mlflow.utils.uri import is_databricks_uri, is_http_uri
  from mlflow.version import VERSION, is_release_version
label_desc: Use image node_id 3 for calling a global function with example usage: before_run_validations(tracking_uri, backend_config) without return types