[Core][Optimization] change python dict to pytorch tensor

[youkaichao]

Prior to this PR, blocks_to_copy uses Dict[int, List[int]] type in Python, and convert to std::map<int64_t, std::vector<int64_t>>& in c++ . Although the type contains a reference & , it is actually a copy. Inside the cpp code, we convert the data into pytorch array.

In distributed setting, the cost is even larger: blocks_to_copy will be serialized, and broadcasted, deserialized, passed to c++, and finally convert to pytorch tensor.

This PR changes the python side data structure to List[Tuple[int, int]], and convert it once to pytorch tensor before broadcast. PyTorch tensor can be passed to c++ code without copy.

The convertion is done by flatten the data, i.e. old: Dict[int, List[int]], new = [(k, dst) for k, v in old.items() for dst in v].

e.g. old = {1: [2, 3, 4]} , new = [(1, 2), (1, 3), (1, 4)] .

Future todo:

• remove Dict[int, List[int]] in block manager (in [Core][Optimization] change copy-on-write from dict[int, list] to list #4648 )
• optimize blocks_to_swap_in and blocks_to_swap_out in the same way (in [Core][Optimization] change python dict to pytorch tensor for blocks to swap #4659 )

[LiuXiaoxuanPKU]

LGTM! Thanks for the PR!