ColossalAI/tests/test_moe/test_moe_colo_init.py

57 lines
1.8 KiB
Python

import pytest
import torch
import torch.distributed as dist
import colossalai
from colossalai.context import MOE_CONTEXT
from colossalai.tensor import ColoParameter
from colossalai.testing import parameterize, rerun_if_address_is_in_use, spawn
from colossalai.utils import get_current_device
from colossalai.zero import ColoInitContext
from tests.test_moe.test_moe_zero_init import MoeModel
from tests.test_tensor.common_utils import debug_print
from tests.test_zero.test_legacy.common import CONFIG
@parameterize("init_device_type", ['cpu', 'cuda'])
def exam_moe_colo_init(init_device_type):
world_size = dist.get_world_size()
if init_device_type == 'cuda':
init_device = get_current_device()
elif init_device_type == 'cpu':
init_device = torch.device("cpu")
else:
raise NotImplementedError("Unknown device found.")
with ColoInitContext(device=init_device):
model = MoeModel(checkpoint=True)
for name, param in model.named_parameters():
assert isinstance(param, ColoParameter), "parameter `{}` has an init problem".format(name)
if hasattr(param, "moe_info"):
param.set_process_group(param.moe_info.pg)
if hasattr(param, "moe_info"):
assert param.process_group.dp_world_size() == param.moe_info.dp_size
else:
assert param.process_group.dp_world_size() == world_size
def _run_dist(rank, world_size, port):
colossalai.launch(config=CONFIG, rank=rank, world_size=world_size, host='localhost', port=port, backend='nccl')
MOE_CONTEXT.setup(seed=42)
exam_moe_colo_init()
@pytest.mark.dist
@pytest.mark.parametrize("world_size", [4])
@rerun_if_address_is_in_use()
def test_moe_colo_init(world_size):
spawn(_run_dist, world_size)
if __name__ == '__main__':
test_moe_colo_init(world_size=4)