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()