github/ColossalAI
1
0
Fork 0
mirror of https://github.com/hpcaitech/ColossalAI.git synced 2026-01-29 21:49:54 +00:00
Code Issues Packages Projects Releases Wiki Activity

[zero] able to place params on cpu after zero init context (#365)

Browse Source 
* place params on cpu after zero init context

* polish code
This commit is contained in:
Jiarui Fang
2022-03-10 14:08:58 +08:00
committed by Frank Lee
parent b66f3b994c
commit 44e4891f57
6 changed files with 58 additions and 20 deletions
Download Patch File Download Diff File Expand all files Collapse all files

23
tests/test_zero_data_parallel/test_init_context.py
View File

@@ -4,6 +4,7 @@
from functools import partial
import colossalai
from colossalai.utils.cuda import get_current_device
import pytest
import torch
import torch.multiprocessing as mp
@@ -17,13 +18,13 @@ from common import CONFIG
from colossalai.utils.memory_tracer.allocator import GLOBAL_MODEL_DATA_TRACER
def run_dist(rank, world_size, port):
def run_dist(rank, world_size, port, init_device):
colossalai.launch(config=CONFIG, rank=rank, world_size=world_size, host='localhost', port=port, backend='nccl')
for get_components_func in non_distributed_component_funcs:
model_builder, _, _, _, _ = get_components_func()
with ZeroInitContext(convert_fp16=True,
convert_cuda=True,
target_device=init_device,
shard_strategy=TensorShardStrategy(),
shard_param=True):
model = model_builder(checkpoint=True)
@@ -32,18 +33,26 @@ def run_dist(rank, world_size, port):
assert hasattr(param, 'col_attr')
assert param.col_attr.data.dtype == torch.half
assert param.col_attr.data.is_sharded
assert param.col_attr.data.payload.device.type == 'cuda'
assert param.col_attr.data.payload.device.type == init_device.type, \
f'{param.col_attr.data.payload.device.type} vs. {init_device.type}'
print(f'cpu usgae {GLOBAL_MODEL_DATA_TRACER.cpu_usage}')
print(f'cuda usgae {GLOBAL_MODEL_DATA_TRACER.cuda_usage}')
assert (GLOBAL_MODEL_DATA_TRACER.cuda_usage > 0)
if init_device.type == 'cuda':
assert (GLOBAL_MODEL_DATA_TRACER.cuda_usage > 0)
elif init_device.type == 'cpu':
assert (GLOBAL_MODEL_DATA_TRACER.cpu_usage > 0)
@pytest.mark.dist
@pytest.mark.parametrize("world_size", [1, 4])
def test_zero_init_context(world_size):
run_func = partial(run_dist, world_size=world_size, port=free_port())
@pytest.mark.parametrize("init_device", [torch.device('cpu'), torch.device(f'cuda:{get_current_device()}')])
def test_zero_init_context(world_size, init_device):
run_func = partial(run_dist, world_size=world_size, port=free_port(), init_device=init_device)
mp.spawn(run_func, nprocs=world_size)
if __name__ == '__main__':
test_zero_init_context(2)
test_zero_init_context(2, torch.device('cpu'))
test_zero_init_context(2, torch.device(f'cuda:{get_current_device()}'))