mirror of
https://github.com/open-mmlab/mmsegmentation.git
synced 2025-06-03 22:03:48 +08:00
ae78cb9d53
## Motivation Added ascending device support in mmseg. ## Modification The main modification points are as follows: We added an NPU device in the DDP scenario and DP scenario when using the NPU. ## BC-breaking (Optional) None ## Use cases (Optional) We tested [fcn_unet_s5-d16_4x4_512x1024_160k_cityscapes.py](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/unet/fcn_unet_s5-d16_4x4_512x1024_160k_cityscapes.py) .
84 lines
2.7 KiB
Python
84 lines
2.7 KiB
Python
# Copyright (c) OpenMMLab. All rights reserved.
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from unittest.mock import MagicMock, patch
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import mmcv
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import torch
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import torch.nn as nn
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from mmcv.parallel import (MMDataParallel, MMDistributedDataParallel,
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is_module_wrapper)
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from mmseg import digit_version
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from mmseg.utils import build_ddp, build_dp
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def mock(*args, **kwargs):
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pass
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class Model(nn.Module):
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def __init__(self):
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super().__init__()
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self.conv = nn.Conv2d(2, 2, 1)
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def forward(self, x):
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return self.conv(x)
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@patch('torch.distributed._broadcast_coalesced', mock)
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@patch('torch.distributed.broadcast', mock)
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@patch('torch.nn.parallel.DistributedDataParallel._ddp_init_helper', mock)
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def test_build_dp():
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model = Model()
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assert not is_module_wrapper(model)
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mmdp = build_dp(model, 'cpu')
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assert isinstance(mmdp, MMDataParallel)
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if torch.cuda.is_available():
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mmdp = build_dp(model, 'cuda')
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assert isinstance(mmdp, MMDataParallel)
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if digit_version(mmcv.__version__) >= digit_version('1.5.0'):
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from mmcv.device.mlu import MLUDataParallel
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from mmcv.utils import IS_MLU_AVAILABLE
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if IS_MLU_AVAILABLE:
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mludp = build_dp(model, 'mlu')
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assert isinstance(mludp, MLUDataParallel)
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if digit_version(mmcv.__version__) >= digit_version('1.7.0'):
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from mmcv.device.npu import NPUDataParallel
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from mmcv.utils import IS_NPU_AVAILABLE
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if IS_NPU_AVAILABLE:
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npu_dp = model.npu(model, 'npu')
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assert isinstance(npu_dp, NPUDataParallel)
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@patch('torch.distributed._broadcast_coalesced', mock)
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@patch('torch.distributed.broadcast', mock)
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@patch('torch.nn.parallel.DistributedDataParallel._ddp_init_helper', mock)
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def test_build_ddp():
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model = Model()
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assert not is_module_wrapper(model)
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if torch.cuda.is_available():
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mmddp = build_ddp(
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model, 'cuda', device_ids=[0], process_group=MagicMock())
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assert isinstance(mmddp, MMDistributedDataParallel)
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if digit_version(mmcv.__version__) >= digit_version('1.5.0'):
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from mmcv.device.mlu import MLUDistributedDataParallel
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from mmcv.utils import IS_MLU_AVAILABLE
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if IS_MLU_AVAILABLE:
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mluddp = build_ddp(
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model, 'mlu', device_ids=[0], process_group=MagicMock())
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assert isinstance(mluddp, MLUDistributedDataParallel)
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if digit_version(mmcv.__version__) >= digit_version('1.7.0'):
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from mmcv.device.npu import NPUDistributedDataParallel
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from mmcv.utils import IS_NPU_AVAILABLE
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if IS_NPU_AVAILABLE:
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npu_ddp = build_ddp(
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model, 'npu', device_ids=[0], process_group=MagicMock())
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assert isinstance(npu_ddp, NPUDistributedDataParallel)
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