LBFGS
class torch.optim.LBFGS(params, lr=1, max_iter=20, max_eval=None, tolerance_grad=1e-07, tolerance_change=1e-09, history_size=100, line_search_fn=None)
Implements L-BFGS algorithm, heavily inspired by minFunc.
Warning:
 This optimizer doesn't support per-parameter options and
 parameter groups (there can be only one).

Warning:
 Right now all parameters have to be on a single device. This will
 be improved in the future.

Note:
 This is a very memory intensive optimizer (it requires additional
 "param_bytes * (history_size + 1)" bytes). If it doesn't fit in
 memory try reducing the history size, or use a different
 algorithm.

Parameters:
      * lr (float) -- learning rate (default: 1)
  * **max_iter** (*int*) -- maximal number of iterations per
    optimization step (default: 20)

  * **max_eval** (*int*) -- maximal number of function evaluations
    per optimization step (default: max_iter * 1.25).
