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Starting
on
L40S
# Copyright (c) OpenMMLab. All rights reserved. | |
import os | |
import platform | |
import numpy as np | |
import pytest | |
import torch | |
import torch.distributed as dist | |
from mmcv.cnn.bricks import ConvModule | |
from mmcv.cnn.utils import revert_sync_batchnorm | |
if platform.system() == 'Windows': | |
import regex as re | |
else: | |
import re | |
def test_revert_syncbn(): | |
conv = ConvModule(3, 8, 2, norm_cfg=dict(type='SyncBN')) | |
x = torch.randn(1, 3, 10, 10) | |
# Expect a ValueError prompting that SyncBN is not supported on CPU | |
with pytest.raises(ValueError): | |
y = conv(x) | |
conv = revert_sync_batchnorm(conv) | |
y = conv(x) | |
assert y.shape == (1, 8, 9, 9) | |
def test_revert_mmsyncbn(): | |
if 'SLURM_NTASKS' not in os.environ or int(os.environ['SLURM_NTASKS']) < 2: | |
print('Must run on slurm with more than 1 process!\n' | |
'srun -p test --gres=gpu:2 -n2') | |
return | |
rank = int(os.environ['SLURM_PROCID']) | |
world_size = int(os.environ['SLURM_NTASKS']) | |
local_rank = int(os.environ['SLURM_LOCALID']) | |
node_list = str(os.environ['SLURM_NODELIST']) | |
node_parts = re.findall('[0-9]+', node_list) | |
os.environ['MASTER_ADDR'] = (f'{node_parts[1]}.{node_parts[2]}' + | |
f'.{node_parts[3]}.{node_parts[4]}') | |
os.environ['MASTER_PORT'] = '12341' | |
os.environ['WORLD_SIZE'] = str(world_size) | |
os.environ['RANK'] = str(rank) | |
dist.init_process_group('nccl') | |
torch.cuda.set_device(local_rank) | |
x = torch.randn(1, 3, 10, 10).cuda() | |
dist.broadcast(x, src=0) | |
conv = ConvModule(3, 8, 2, norm_cfg=dict(type='MMSyncBN')).cuda() | |
conv.eval() | |
y_mmsyncbn = conv(x).detach().cpu().numpy() | |
conv = revert_sync_batchnorm(conv) | |
y_bn = conv(x).detach().cpu().numpy() | |
assert np.all(np.isclose(y_bn, y_mmsyncbn, 1e-3)) | |
conv, x = conv.to('cpu'), x.to('cpu') | |
y_bn_cpu = conv(x).detach().numpy() | |
assert np.all(np.isclose(y_bn, y_bn_cpu, 1e-3)) | |