mirror of https://github.com/hpcaitech/ColossalAI
40 lines
1.2 KiB
Python
40 lines
1.2 KiB
Python
#!/usr/bin/env python
|
|
# -*- encoding: utf-8 -*-
|
|
|
|
from functools import partial
|
|
import pytest
|
|
|
|
import torch
|
|
import torch.multiprocessing as mp
|
|
|
|
import colossalai
|
|
from colossalai.zero.sharded_model.param_manager import Zero3ParameterManager
|
|
from colossalai.core import global_context as gpc
|
|
from colossalai.context.parallel_mode import ParallelMode
|
|
from colossalai.utils import free_port
|
|
from common import CONFIG
|
|
|
|
|
|
def run_shard_shape_check(rank, world_size, port):
|
|
colossalai.launch(config=CONFIG, rank=rank, world_size=world_size, host='localhost', port=port, backend='nccl')
|
|
|
|
model = torch.nn.Linear(2, 4 * world_size)
|
|
gpc.init_parallel_groups()
|
|
Zero3ParameterManager(module=model,
|
|
process_group=gpc.get_group(ParallelMode.DATA),
|
|
offload_config=CONFIG.get('offload_param_config'))
|
|
|
|
assert (model.weight.numel() == 4 * 2)
|
|
assert (model.bias.numel() == 4)
|
|
|
|
|
|
@pytest.mark.dist
|
|
@pytest.mark.parametrize("world_size", [1, 2, 4])
|
|
def test_run_shard_shape(world_size):
|
|
run_func = partial(run_shard_shape_check, world_size=world_size, port=free_port())
|
|
mp.spawn(run_func, nprocs=world_size)
|
|
|
|
|
|
if __name__ == '__main__':
|
|
test_run_shard_shape(2)
|