parameters: (self, scale_idx)
return_statement: return res
docstring: Return the blobs to be used for the next minibatch.
docstring_summary: Return the blobs to be used for the next minibatch.
docstring_tokens: Return the blobs to be used for the next minibatch .
function: def _get_next_minibatch(self, scale_idx):
          """Return the blobs to be used for the next minibatch.
          """
  
          def merge_two_dicts(x, y):
              """Given two dicts, merge them into a new dict as a shallow copy."""
              z = x.copy()
              z.update(y)
              return z
  
          self.db_inds = self._get_next_minibatch_inds()
          minibatch_db = [
              merge_two_dicts(self._roidb[i], {"idx": i})
              for i in self.db_inds
          ]
          res, self.resize_ratio = get_minibatch(
              minibatch_db,
              scale_idx)
          for idx, scale_i in zip(self.db_inds, self.resize_ratio):
              if 'seen_scale' not in self._roidb[idx]:
                  self._roidb[idx]['seen_scale'] = []
              self._roidb[idx]['seen_scale'].append(scale_i)
              logger.debug('Scale {} seeing for {}, rank: {}'.format(
                  scale_i, idx, cfg.RANK))
          return res
function_tokens: def _get_next_minibatch ( self , scale_idx ) : def merge_two_dicts ( x , y ) : """Given two dicts, merge them into a new dict as a shallow copy.""" z = x . copy ( ) z . update ( y ) return z self . db_inds = self . _get_next_minibatch_inds ( ) minibatch_db = [ merge_two_dicts ( self . _roidb [ i ] , { "idx" : i } ) for i in self . db_inds ] res , self . resize_ratio = get_minibatch ( minibatch_db , scale_idx ) for idx , scale_i in zip ( self . db_inds , self . resize_ratio ) : if 'seen_scale' not in self . _roidb [ idx ] : self . _roidb [ idx ] [ 'seen_scale' ] = [ ] self . _roidb [ idx ] [ 'seen_scale' ] . append ( scale_i ) logger . debug ( 'Scale {} seeing for {}, rank: {}' . format ( scale_i , idx , cfg . RANK ) ) return res