code: def _get_mlflow_env_name(s):
      """Creates an environment name for an MLflow model by hashing the given string.
  
      Args:
          s: String to hash (e.g. the content of `conda.yaml`).
  
      Returns:
          String in the form of "mlflow-{hash}"
          (e.g. "mlflow-da39a3ee5e6b4b0d3255bfef95601890afd80709")
  
      """
      return (
          "mlflow-" + insecure_hash.sha1(s.encode("utf-8")).hexdigest()
      )
  
imports: import logging
  import os
  import re
  import subprocess
  import sys
  import tempfile
  import yaml
  from packaging.requirements import InvalidRequirement, Requirement
  from packaging.version import Version
  from mlflow.environment_variables import _MLFLOW_TESTING
  from mlflow.exceptions import MlflowException
  from mlflow.protos.databricks_pb2 import INVALID_PARAMETER_VALUE
  from mlflow.utils import PYTHON_VERSION, insecure_hash
  from mlflow.utils.process import _exec_cmd
  from mlflow.utils.requirements_utils import _infer_requirements, _parse_requirements
  from mlflow.version import VERSION
label_desc: Use image node_id 19 for calling a global function with example usage: _get_mlflow_env_name(s) and returns: unknown