class_docstr: The metadata of a logged MLflow Model.
class_docstr_tok: ["The","metadata","of","a","logged","MLflow","Model","."]
docstr: A dictionary mapping the flavor name to how to serve
  the model as that flavor.
  
  :getter: Gets the mapping for the logged model's flavor that defines parameters used in
      serving of the model
  :type: Dict[str, str]
  
  .. code-block:: python
      :caption: Example flavor mapping for a scikit-learn logged model
  
      {
          "python_function": {
              "model_path": "model.pkl",
              "loader_module": "mlflow.sklearn",
              "python_version": "3.8.10",
              "env": "conda.yaml",
          },
          "sklearn": {
              "pickled_model": "model.pkl",
              "sklearn_version": "0.24.1",
              "serialization_format": "cloudpickle",
          },
      }
docstr_tok: ["A","dictionary","mapping","the","flavor","name","to","how","to","serve","the","model","as","that","flavor",".",":","getter",":","Gets","the","mapping","for","the","logged","model","'s","flavor","that","defines","parameters","used","in","serving","of","the","model",":","type",":","Dict","[","str",",","str","]","..","code-block",":",":","python",":","caption",":","Example","flavor","mapping","for","a","scikit-learn","logged","model","{","``","python_function","''",":","{","``","model_path","''",":","``","model.pkl","''",",","``","loader_module","''",":","``","mlflow.sklearn","''",",","``","python_version","''",":","``","3.8.10","''",",","``","env","''",":","``","conda.yaml","''",",","}",",","``","sklearn","''",":","{","``","pickled_model","''",":","``","model.pkl","''",",","``","sklearn_version","''",":","``","0.24.1","''",",","``","serialization_format","''",":","``","cloudpickle","''",",","}",",","}"]
code: def flavors(self):
      """
      A dictionary mapping the flavor name to how to serve
      the model as that flavor.
  
      :getter: Gets the mapping for the logged model's flavor that defines parameters used in
          serving of the model
      :type: Dict[str, str]
  
      .. code-block:: python
          :caption: Example flavor mapping for a scikit-learn logged model
  
          {
              "python_function": {
                  "model_path": "model.pkl",
                  "loader_module": "mlflow.sklearn",
                  "python_version": "3.8.10",
                  "env": "conda.yaml",
              },
              "sklearn": {
                  "pickled_model": "model.pkl",
                  "sklearn_version": "0.24.1",
                  "serialization_format": "cloudpickle",
              },
          }
  
      """
      return self._flavors
  
imports: import json
  import logging
  import os
  import uuid
  import warnings
  from datetime import datetime
  from typing import Any, Callable, Dict, Optional, Union
  import yaml
  import mlflow
  from mlflow.artifacts import download_artifacts
  from mlflow.exceptions import MlflowException
  from mlflow.tracking._model_registry import DEFAULT_AWAIT_MAX_SLEEP_SECONDS
  from mlflow.tracking._tracking_service.utils import _resolve_tracking_uri
  from mlflow.utils.annotations import experimental
  from mlflow.utils.databricks_utils import get_databricks_runtime
  from mlflow.utils.file_utils import TempDir
  from mlflow.utils.uri import get_uri_scheme
label_desc: Use image node_id 3 for calling the ModelInfo obj's underlying member method code with example usage: obj.flavors() and returns: self