code: def _mlflow_conda_env(
      path=None,
      additional_conda_deps=None,
      additional_pip_deps=None,
      additional_conda_channels=None,
      install_mlflow=True,
  ):
      """Creates a Conda environment with the specified package channels and dependencies. If there
      are any pip dependencies, including from the install_mlflow parameter, then pip will be added to
      the conda dependencies. This is done to ensure that the pip inside the conda environment is
      used to install the pip dependencies.
  
      Args:
          path: Local filesystem path where the conda env file is to be written. If unspecified,
              the conda env will not be written to the filesystem; it will still be returned
              in dictionary format.
          additional_conda_deps: List of additional conda dependencies passed as strings.
          additional_pip_deps: List of additional pip dependencies passed as strings.
          additional_conda_channels: List of additional conda channels to search when resolving
              packages.
  
      Returns:
          None if path is specified. Otherwise, the a dictionary representation of the
          Conda environment.
  
      """
      additional_pip_deps = additional_pip_deps or []
      mlflow_deps = (
          [f"mlflow=={VERSION}"]
          if install_mlflow
          and not _contains_mlflow_requirement(additional_pip_deps)
          else []
      )
      pip_deps = mlflow_deps + additional_pip_deps
      conda_deps = (
          additional_conda_deps if additional_conda_deps else []
      )
      if pip_deps:
          pip_version = _get_pip_version()
          if pip_version is not None:
              # When a new version of pip is released on PyPI, it takes a while until that version is
              # uploaded to conda-forge. This time lag causes `conda create` to fail with
              # a `ResolvePackageNotFound` error. As a workaround for this issue, use `<=` instead
              # of `==` so conda installs `pip_version - 1` when `pip_version` is unavailable.
              conda_deps.append(f"pip<={pip_version}")
          else:
              _logger.warning(
                  "Failed to resolve installed pip version. ``pip`` will be added to conda.yaml"
                  " environment spec without a version specifier."
              )
              conda_deps.append("pip")
  
      env = yaml.safe_load(_conda_header)
      env["dependencies"] = [f"python={PYTHON_VERSION}"]
      env["dependencies"] += conda_deps
      env["dependencies"].append({"pip": pip_deps})
      if additional_conda_channels is not None:
          env["channels"] += additional_conda_channels
  
      if path is not None:
          with open(path, "w") as out:
              yaml.safe_dump(env, stream=out, default_flow_style=False)
          return None
      else:
          return env
  
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 1 for calling a global function with example usage: _mlflow_conda_env(path, additional_conda_deps, additional_pip_deps, additional_conda_channels, install_mlflow) and returns: None, env