code: def _process_conda_env(conda_env):
      """
      Processes `conda_env` passed to `mlflow.*.save_model` or `mlflow.*.log_model`, and returns
      a tuple of (conda_env, pip_requirements, pip_constraints).
      """
      if isinstance(conda_env, str):
          with open(conda_env) as f:
              conda_env = yaml.safe_load(f)
      elif not isinstance(conda_env, dict):
          raise TypeError(
              "Expected a string path to a conda env yaml file or a `dict` representing a conda env, "
              f"but got `{type(conda_env).__name__}`"
          )
  
      # User-specified `conda_env` may contain requirements/constraints file references
      pip_reqs = _get_pip_deps(conda_env)
      pip_reqs, constraints = _parse_pip_requirements(pip_reqs)
      if not _contains_mlflow_requirement(pip_reqs):
          pip_reqs.insert(0, _generate_mlflow_version_pinning())
  
      if constraints:
          pip_reqs.append(f"-c {_CONSTRAINTS_FILE_NAME}")
  
      conda_env = _overwrite_pip_deps(conda_env, pip_reqs)
      return conda_env, pip_reqs, constraints
  
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 18 for calling a global function with example usage: _process_conda_env(conda_env) and returns: conda_env,  pip_reqs,  constraints