import torch import colossalai from colossalai.legacy.zero.gemini.tensor_utils import colo_model_data_tensor_move, colo_model_data_tensor_move_inline from colossalai.legacy.zero.sharded_param import ShardedTensor from colossalai.testing import rerun_if_address_is_in_use, spawn def run_tensor_move(rank, world_size, port): colossalai.legacy.launch(config={}, rank=0, world_size=world_size, host='localhost', port=port, backend='nccl') src_t = torch.ones(2, 3).cuda() tgt_t = torch.zeros(2, 3) colo_model_data_tensor_move(src_t, tgt_t) assert (torch.sum(tgt_t) == 6.0), f"{torch.sum(tgt_t.payload)} vs. 6.0" src_t = torch.ones(2, 3) tgt_t = torch.zeros(2, 3).cuda().half() colo_model_data_tensor_move(src_t, tgt_t) # the src_t has been removed assert (src_t.numel() == 0) assert (torch.sum(tgt_t) == 6.0), f"{torch.sum(tgt_t.payload)} vs. 6.0" src_t = ShardedTensor(torch.ones(2, 3)) tgt_t = ShardedTensor(torch.zeros(2, 3).cuda().half()) colo_model_data_tensor_move(src_t, tgt_t) assert (torch.sum(tgt_t.payload) == 6.0), f"{torch.sum(tgt_t.payload)} vs. 6.0" assert (tgt_t.device.type == 'cuda') colo_model_data_tensor_move_inline(tgt_t, torch.device('cpu')) assert (tgt_t.device.type == 'cpu') @rerun_if_address_is_in_use() def test_tensor_move(): spawn(run_tensor_move, 1) if __name__ == '__main__': test_tensor_move()