code: def _validate_version_constraints(requirements):
      """
      Validates the version constraints of given Python package requirements using pip's resolver with
      the `--dry-run` option enabled that performs validation only (will not install packages).
  
      This function writes the requirements to a temporary file and then attempts to resolve
      them using pip's `--dry-run` install option. If any version conflicts are detected, it
      raises an MlflowException with details of the conflict.
  
      Args:
          requirements (list of str): A list of package requirements (e.g., `["pandas>=1.15",
          "pandas<2"]`).
  
      Raises:
          MlflowException: If any version conflicts are detected among the provided requirements.
  
      Returns:
          None: This function does not return anything. It either completes successfully or raises
          an MlflowException.
  
      Example:
          _validate_version_constraints(["tensorflow<2.0", "tensorflow>2.3"])
          # This will raise an exception due to boundary validity.
      """
      with tempfile.NamedTemporaryFile(
          mode="w+", delete=False
      ) as tmp_file:
          tmp_file.write("\n".join(requirements))
          tmp_file_name = tmp_file.name
  
      try:
          subprocess.run(
              [
                  sys.executable,
                  "-m",
                  "pip",
                  "install",
                  "--dry-run",
                  "-r",
                  tmp_file_name,
              ],
              check=True,
              capture_output=True,
          )
      except subprocess.CalledProcessError as e:
          raise MlflowException.invalid_parameter_value(
              "The specified requirements versions are incompatible. Detected "
              f"conflicts: \n{e.stderr.decode()}"
          )
      finally:
          os.remove(tmp_file_name)
  
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 17 for calling a global function with example usage: _validate_version_constraints(requirements) without return types