parameters: (self)
docstring: Updates parameters according to installed optimizer and the gradient computed
          in the previous forward-backward cycle.
  
          When KVStore is used to update parameters for multi-device or multi-machine training,
          a copy of the parameters are stored in KVStore. Note that for `row_sparse` parameters,
          this function does update the copy of parameters in KVStore, but doesn't broadcast the
          updated parameters to all devices / machines. Please call `prepare` to broadcast
          `row_sparse` parameters with the next batch of data.
docstring_summary: Updates parameters according to installed optimizer and the gradient computed
          in the previous forward-backward cycle.
docstring_tokens: Updates parameters according to installed optimizer and the gradient computed in the previous forward - backward cycle .
function: def update(self):
          """Updates parameters according to installed optimizer and the gradient computed
          in the previous forward-backward cycle.
  
          When KVStore is used to update parameters for multi-device or multi-machine training,
          a copy of the parameters are stored in KVStore. Note that for `row_sparse` parameters,
          this function does update the copy of parameters in KVStore, but doesn't broadcast the
          updated parameters to all devices / machines. Please call `prepare` to broadcast
          `row_sparse` parameters with the next batch of data.
  
          """
          assert self.binded and self.params_initialized and self.optimizer_initialized
          self._params_dirty = True
          self._curr_module.update()
function_tokens: def update ( self ) : assert self . binded and self . params_initialized and self . optimizer_initialized self . _params_dirty = True self . _curr_module . update ( )