ColossalAI/tests/test_zero/test_gemini/test_search.py

67 lines
2.4 KiB
Python

import pytest
import torch
import colossalai
from colossalai.testing import rerun_if_address_is_in_use, spawn
from colossalai.utils import get_current_device
from colossalai.zero.gemini.chunk import init_chunk_manager, search_chunk_configuration
from tests.components_to_test.registry import non_distributed_component_funcs
def exam_search_chunk_size():
world_size = torch.distributed.get_world_size()
get_components_func = non_distributed_component_funcs.get_callable('gpt2')
model_builder, train_dataloader, test_dataloader, optimizer_class, criterion = get_components_func()
# make sure torch_model and model has the same parameter values
model = model_builder()
config_dict, *_ = search_chunk_configuration(model,
search_range_m=1,
search_interval=16,
min_chunk_size_m=0,
filter_exlarge_params=True)
for key in config_dict:
chunk_size = config_dict[key]['chunk_size']
if world_size == 1 or True:
assert chunk_size == 31616
else:
assert chunk_size == 1024
def exam_chunk_manager():
world_size = torch.distributed.get_world_size()
get_components_func = non_distributed_component_funcs.get_callable('gpt2')
model_builder, train_dataloader, test_dataloader, optimizer_class, criterion = get_components_func()
sharded_ddp_model = model_builder()
chunk_manager = init_chunk_manager(sharded_ddp_model,
get_current_device(),
hidden_dim=16,
search_range_m=1,
min_chunk_size_m=0,
filter_exlarge_params=True,
strict_ddp_flag=True)
config_dict = chunk_manager.dp_degree_chunk_size_dict
assert len(config_dict) == 1
assert config_dict[world_size] == 31616
def run_dist(rank, world_size, port):
colossalai.launch(config={}, rank=rank, world_size=world_size, host='localhost', port=port, backend='nccl')
exam_search_chunk_size()
exam_chunk_manager()
@pytest.mark.dist
@pytest.mark.parametrize('world_size', [1, 4])
@rerun_if_address_is_in_use()
def test_search(world_size):
spawn(run_dist, world_size)
if __name__ == '__main__':
test_search(4)