class_docstr: An MLflow Model that can support multiple model flavors. Provides APIs for implementing
  new Model flavors.
class_docstr_tok: ["An","MLflow","Model","that","can","support","multiple","model","flavors",".","Provides","APIs","for","implementing","new","Model","flavors","."]
docstr: Serialize the model to a dictionary.
docstr_tok: ["Serialize","the","model","to","a","dictionary","."]
code: def to_dict(self):
      """Serialize the model to a dictionary."""
      res = {
          k: v
          for k, v in self.__dict__.items()
          if not k.startswith("_")
      }
      databricks_runtime = get_databricks_runtime()
      if databricks_runtime:
          res["databricks_runtime"] = databricks_runtime
      if self.signature is not None:
          res["signature"] = self.signature.to_dict()
      if self.saved_input_example_info is not None:
          res[
              "saved_input_example_info"
          ] = self.saved_input_example_info
      if self.mlflow_version is None and _MLFLOW_VERSION_KEY in res:
          res.pop(_MLFLOW_VERSION_KEY)
      if self.metadata is not None:
          res["metadata"] = self.metadata
      if self.model_size_bytes is not None:
          res["model_size_bytes"] = self.model_size_bytes
      return res
  
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 18 for calling the Model obj's underlying member method code with example usage: obj.to_dict() and returns: res