parameters: (self,
                      input_fn=None,
                      batch_size=None)
return_statement: return (pred[key] for pred in preds)
docstring: Returns prediction probabilities for given features.
  
      Args:
        input_fn: Input function.
        batch_size: Override default batch size.
  
      Returns:
        An iterable of predicted probabilities with shape [batch_size, n_classes].
docstring_summary: Returns prediction probabilities for given features.
docstring_tokens: Returns prediction probabilities for given features .
function: def predict_proba(self,
                      input_fn=None,
                      batch_size=None):
      """Returns prediction probabilities for given features.
  
      Args:
        input_fn: Input function.
        batch_size: Override default batch size.
  
      Returns:
        An iterable of predicted probabilities with shape [batch_size, n_classes].
      """
      key = prediction_key.PredictionKey.PROBABILITIES
      preds = self.predict(
          input_fn=input_fn,
          batch_size=batch_size,
          outputs=[key])
      return (pred[key] for pred in preds)
function_tokens: def predict_proba ( self , input_fn = None , batch_size = None ) : key = prediction_key . PredictionKey . PROBABILITIES preds = self . predict ( input_fn = input_fn , batch_size = batch_size , outputs = [ key ] ) return ( pred [ key ] for pred in preds )