docstr: Inputs the tensor to the model for this Predictor and returns the result.
  
  Args:
      inputs: The tensor to input to the model.
  
  Returns:
      A tensor or dictionary of tensors containing the model output.
docstr_tok: ["Inputs","the","tensor","to","the","model","for","this","Predictor","and","returns","the","result",".","Args",":","inputs",":","The","tensor","to","input","to","the","model",".","Returns",":","A","tensor","or","dictionary","of","tensors","containing","the","model","output","."]
code: def call_model(
      self, inputs: Union[TensorType, Dict[str, TensorType]]
  ) -> Union[TensorType, Dict[str, TensorType]]:
      """Inputs the tensor to the model for this Predictor and returns the result.
  
      Args:
          inputs: The tensor to input to the model.
  
      Returns:
          A tensor or dictionary of tensors containing the model output.
      """
      raise NotImplementedError
  
file_path: ray/python/ray/train/_internal/dl_predictor.py
imports: import abc
  from typing import Dict, Optional, TypeVar, Union
  import numpy
  import pandas
  from ray.air.util.data_batch_conversion import BatchFormat, _convert_batch_type_to_pandas, _convert_pandas_to_batch_type
  from ray.train.predictor import Predictor
  from ray.util.annotations import DeveloperAPI
label_desc: Use image node_id 3 for calling the DLPredictor obj's underlying member method code with example usage: obj.call_model(inputs) without return types