class_docstr: Helper class to create a model with added dependency wheels from an existing registered model.
  The `wheeled` model contains all the model dependencies as wheels stored as model artifacts.
  .. note::
      This utility only operates on a model that has been registered to the Model Registry.
class_docstr_tok: ["Helper","class","to","create","a","model","with","added","dependency","wheels","from","an","existing","registered","model",".","The","`","wheeled","`","model","contains","all","the","model","dependencies","as","wheels","stored","as","model","artifacts",".","..","note",":",":","This","utility","only","operates","on","a","model","that","has","been","registered","to","the","Model","Registry","."]
docstr: Downloads all the wheels of the dependencies specified in the requirements.txt file.
  The pip wheel download_command defaults to downloading only binary packages using
  the `--only-binary=:all:` option. This behavior can be overridden using an
  environment variable `MLFLOW_WHEELED_MODEL_PIP_DOWNLOAD_OPTIONS`, which will allows
  setting different options such as `--prefer-binary`, `--no-binary`, etc.
  :param pip_requirements_path: Path to requirements.txt in the model directory
  :param dst_path: Path to the directory where the wheels are to be downloaded
docstr_tok: ["Downloads","all","the","wheels","of","the","dependencies","specified","in","the","requirements.txt","file",".","The","pip","wheel","download_command","defaults","to","downloading","only","binary","packages","using","the","`","--","only-binary=",":","all",":","`","option",".","This","behavior","can","be","overridden","using","an","environment","variable","`","MLFLOW_WHEELED_MODEL_PIP_DOWNLOAD_OPTIONS","`",",","which","will","allows","setting","different","options","such","as","`","--","prefer-binary","`",",","`","--","no-binary","`",",","etc",".",":","param","pip_requirements_path",":","Path","to","requirements.txt","in","the","model","directory",":","param","dst_path",":","Path","to","the","directory","where","the","wheels","are","to","be","downloaded"]
code: def _download_wheels(cls, pip_requirements_path, dst_path):
      """
      Downloads all the wheels of the dependencies specified in the requirements.txt file.
      The pip wheel download_command defaults to downloading only binary packages using
      the `--only-binary=:all:` option. This behavior can be overridden using an
      environment variable `MLFLOW_WHEELED_MODEL_PIP_DOWNLOAD_OPTIONS`, which will allows
      setting different options such as `--prefer-binary`, `--no-binary`, etc.
      :param pip_requirements_path: Path to requirements.txt in the model directory
      :param dst_path: Path to the directory where the wheels are to be downloaded
      """
      if not os.path.exists(dst_path):
          os.makedirs(dst_path)
  
      pip_wheel_options = (
          MLFLOW_WHEELED_MODEL_PIP_DOWNLOAD_OPTIONS.get()
      )
  
      try:
          subprocess.run(
              [
                  sys.executable,
                  "-m",
                  "pip",
                  "wheel",
                  pip_wheel_options,
                  "--wheel-dir",
                  dst_path,
                  "-r",
                  pip_requirements_path,
                  "--no-cache-dir",
              ],
              check=True,
              capture_output=True,
          )
      except subprocess.CalledProcessError as e:
          raise MlflowException(
              f"An error occurred while downloading the dependency wheels: {e.stderr}"
          )
  
imports: import os
  import platform
  import shutil
  import subprocess
  import sys
  import yaml
  import mlflow
  from mlflow import MlflowClient
  from mlflow.environment_variables import MLFLOW_WHEELED_MODEL_PIP_DOWNLOAD_OPTIONS
  from mlflow.exceptions import MlflowException
  from mlflow.protos.databricks_pb2 import BAD_REQUEST
  from mlflow.pyfunc.model import MLMODEL_FILE_NAME, Model
  from mlflow.store.artifact.utils.models import _parse_model_uri, get_model_name_and_version
  from mlflow.tracking.artifact_utils import _download_artifact_from_uri
  from mlflow.utils.annotations import experimental
  from mlflow.utils.environment import _REQUIREMENTS_FILE_NAME, _get_pip_deps, _mlflow_additional_pip_env, _overwrite_pip_deps
  from mlflow.utils.model_utils import _validate_and_prepare_target_save_path
  from mlflow.utils.uri import get_databricks_profile_uri_from_artifact_uri
label_desc: Use image node_id 6 for calling the WheeledModel obj's underlying member method code with example usage: obj._download_wheels(cls, pip_requirements_path, dst_path) without return types