code: def _is_mlflow_requirement(requirement_string):
      """
      Returns True if `requirement_string` represents a requirement for mlflow (e.g. 'mlflow==1.2.3').
      """
      # "/opt/mlflow" is the path where we mount the mlflow source code in the Docker container
      # when running tests.
      if _MLFLOW_TESTING.get() and requirement_string == "/opt/mlflow":
          return True
  
      try:
          # `Requirement` throws an `InvalidRequirement` exception if `requirement_string` doesn't
          # conform to PEP 508 (https://www.python.org/dev/peps/pep-0508).
          return Requirement(requirement_string).name.lower() in [
              "mlflow",
              "mlflow-skinny",
          ]
      except InvalidRequirement:
          # A local file path or URL falls into this branch.
  
          # `Requirement` throws an `InvalidRequirement` exception if `requirement_string` contains
          # per-requirement options (ex: package hashes)
          # GitHub issue: https://github.com/pypa/packaging/issues/488
          # Per-requirement-option spec: https://pip.pypa.io/en/stable/reference/requirements-file-format/#per-requirement-options
          requirement_specifier = _get_pip_requirement_specifier(
              requirement_string
          )
          try:
              # Try again with the per-requirement options removed
              return (
                  Requirement(requirement_specifier).name.lower()
                  == "mlflow"
              )
          except InvalidRequirement:
              # Support defining branch dependencies for local builds or direct GitHub builds
              # from source.
              # Example: mlflow @ git+https://github.com/mlflow/mlflow@branch_2.0
              repository_matches = ["/mlflow", "mlflow@git"]
  
              return any(
                  match in requirement_string.replace(" ", "").lower()
                  for match in repository_matches
              )
  
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 12 for calling a global function with example usage: _is_mlflow_requirement(requirement_string) and returns: True, unknown, unknown, any