docstr: Return predictions for the model.
  
  Parameters
  ----------
  data: dict[str, value] or list[dict[str, value]]
      Dictionary of data to use for predictions, where the keys are the names of the input features.
      For batch predictons, use a list of such dictionaries.
  
  Returns
  -------
  dict[str, value]
      Predictions as a dictionary where each key is the output feature name.
  
  list[dict[str, value]]
      For batch prediction, returns a list of the above dictionaries.
  
  Examples
  --------
  .. sourcecode:: python
  
                  data = {'bedroom': 1.0, 'bath': 1.0, 'size': 1240}
                  predictions = model.predict(data)
      
                  data = [ {'bedroom': 1.0, 'bath': 1.0, 'size': 1240},
                                   {'bedroom': 4.0, 'bath': 2.5, 'size': 2400} ]
                  batch_predictions = model.predict(data)
docstr_tok: ["Return","predictions","for","the","model",".","Parameters","--","--","--","--","--","data",":","dict","[","str",",","value","]","or","list","[","dict","[","str",",","value","]","]","Dictionary","of","data","to","use","for","predictions",",","where","the","keys","are","the","names","of","the","input","features",".","For","batch","predictons",",","use","a","list","of","such","dictionaries",".","Returns","--","--","--","-","dict","[","str",",","value","]","Predictions","as","a","dictionary","where","each","key","is","the","output","feature","name",".","list","[","dict","[","str",",","value","]","]","For","batch","prediction",",","returns","a","list","of","the","above","dictionaries",".","Examples","--","--","--","--","..","sourcecode",":",":","python","data","=","{","'bedroom","'",":","1.0",",","'bath","'",":","1.0",",","'size","'",":","1240","}","predictions","=","model.predict","(","data",")","data","=","[","{","'bedroom","'",":","1.0",",","'bath","'",":","1.0",",","'size","'",":","1240","}",",","{","'bedroom","'",":","4.0",",","'bath","'",":","2.5",",","'size","'",":","2400","}","]","batch_predictions","=","model.predict","(","data",")"]
code: def predict(self, data):
      """
      Return predictions for the model.
  
      Parameters
      ----------
      data: dict[str, value] or list[dict[str, value]]
          Dictionary of data to use for predictions, where the keys are the names of the input features.
          For batch predictons, use a list of such dictionaries.
  
      Returns
      -------
      dict[str, value]
          Predictions as a dictionary where each key is the output feature name.
  
      list[dict[str, value]]
          For batch prediction, returns a list of the above dictionaries.
  
      Examples
      --------
      .. sourcecode:: python
  
                      data = {'bedroom': 1.0, 'bath': 1.0, 'size': 1240}
                      predictions = model.predict(data)
  
                      data = [ {'bedroom': 1.0, 'bath': 1.0, 'size': 1240},
                                       {'bedroom': 4.0, 'bath': 2.5, 'size': 2400} ]
                      batch_predictions = model.predict(data)
  
      """
      _MLModel._check_predict_data(data)
  
      return _MLModel._get_predictions(
          self._proxy,
          _MLModel._update_float16_multiarray_input_to_float32,
          data,
      )
  
imports: from os.path import expanduser
  from .model import MLModel
  from .utils import _macos_version
  from coremltools import ComputeUnit
label_desc: Use image node_id 2 for calling the CompiledMLModel obj's underlying member method code with example usage: obj.predict(data) and returns: _MLModel