docstr: Args:
      dataframe: Model input data.
      params: Additional parameters to pass to the model for inference.
  
          .. Note:: Experimental: This parameter may change or be removed in a future
              release without warning.
  
  Returns:
      Model predictions.
docstr_tok: ["Args",":","dataframe",":","Model","input","data",".","params",":","Additional","parameters","to","pass","to","the","model","for","inference",".","..","Note",":",":","Experimental",":","This","parameter","may","change","or","be","removed","in","a","future","release","without","warning",".","Returns",":","Model","predictions","."]
code: def predict(
      self, dataframe, params: Optional[Dict[str, Any]] = None
  ):  # pylint: disable=unused-argument
      """
      Args:
          dataframe: Model input data.
          params: Additional parameters to pass to the model for inference.
  
              .. Note:: Experimental: This parameter may change or be removed in a future
                  release without warning.
  
      Returns:
          Model predictions.
      """
      return self.pr_model.predict(dataframe)
  
imports: import json
  import logging
  import os
  from typing import Any, Dict, Optional
  import yaml
  import mlflow
  from mlflow import pyfunc
  from mlflow.models import Model, ModelInputExample, ModelSignature
  from mlflow.models.model import MLMODEL_FILE_NAME
  from mlflow.models.signature import _infer_signature_from_input_example
  from mlflow.models.utils import _save_example
  from mlflow.tracking._model_registry import DEFAULT_AWAIT_MAX_SLEEP_SECONDS
  from mlflow.tracking.artifact_utils import _download_artifact_from_uri
  from mlflow.utils.docstring_utils import LOG_MODEL_PARAM_DOCS, format_docstring
  from mlflow.utils.environment import _CONDA_ENV_FILE_NAME, _CONSTRAINTS_FILE_NAME, _PYTHON_ENV_FILE_NAME, _REQUIREMENTS_FILE_NAME, _mlflow_conda_env, _process_conda_env, _process_pip_requirements, _PythonEnv, _validate_env_arguments
  from mlflow.utils.file_utils import get_total_file_size, write_to
  from mlflow.utils.model_utils import _add_code_from_conf_to_system_path, _get_flavor_configuration, _validate_and_copy_code_paths, _validate_and_prepare_target_save_path
  from mlflow.utils.requirements_utils import _get_pinned_requirement
label_desc: Use image node_id 2 for calling the _ProphetModelWrapper obj's underlying member method code with example usage: obj.predict(dataframe, params) and returns: self