ColossalAI/tests/test_utils/test_commons.py

45 lines
1.4 KiB
Python

from colossalai.utils import free_port
from colossalai.testing import rerun_if_address_is_in_use
from colossalai.zero.sharded_param import ShardedTensor
from colossalai.gemini.tensor_utils import colo_model_data_tensor_move, colo_model_data_tensor_move_inline
import colossalai
import torch
import torch.multiprocessing as mp
def run_tensor_move(rank):
colossalai.launch(config={}, rank=0, world_size=1, host='localhost', port=free_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():
mp.spawn(run_tensor_move, nprocs=1)
if __name__ == '__main__':
test_tensor_move()