original_docstring: Make prediction on a given data.
  
          Parameters:
              data: CDFMDataset instance.
  
          Returns:
              pred_labels: an array of predicted labels. shape (#samples, )
          
docstring: Make prediction on a given data.
docstring_tokens: Make prediction on a given data .
code: def predict(self, data: CDFMDataset) -> np.ndarray:
          """Make prediction on a given data.
  
          Parameters:
              data: CDFMDataset instance.
  
          Returns:
              pred_labels: an array of predicted labels. shape (#samples, )
          """
          pred_labels: np.ndarray = np.empty(len(data), dtype=DTYPE)
          for i, row in enumerate(data):
              eind = self.map[row[self._eid_loc]]
              cinds = [self.map[cid] for cid in row[self._cids_loc]]
              x = row[self._feat_loc]
              d = row[self._prox_loc]
              ps = self._pred_probas(d)
              pred_labels[i] = self._model_equation(eind, cinds, x, ps)
          return pred_labels
code_tokens: def predict ( self , data : CDFMDataset ) -> np . ndarray : pred_labels : np . ndarray = np . empty ( len ( data ) , dtype = DTYPE ) for i , row in enumerate ( data ) : eind = self . map [ row [ self . _eid_loc ] ] cinds = [ self . map [ cid ] for cid in row [ self . _cids_loc ] ] x = row [ self . _feat_loc ] d = row [ self . _prox_loc ] ps = self . _pred_probas ( d ) pred_labels [ i ] = self . _model_equation ( eind , cinds , x , ps ) return pred_labels
short_docstring: Make prediction on a given data.
short_docstring_tokens: Make prediction on a given data .
comment: """Make prediction on a given data.
  
          Parameters:
              data: CDFMDataset instance.
  
          Returns:
              pred_labels: an array of predicted labels. shape (#samples, )
          """