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Unverified Commit c28a3d98 authored by VVsssssk's avatar VVsssssk Committed by GitHub
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[Feaute]support spconv2.0 (#1421) 

* support spconv2.0

* resolve comments

* try to fix ut

* fix ut

* fix docs

* add spconv2 check in collect.env

* resolve comments

* fix docs

* fix comments
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docs/en/getting_started.md
View file @ c28a3d98
......@@ -11,28 +11,28 @@
The required versions of MMCV, MMDetection and MMSegmentation for different versions of MMDetection3D are as below. Please install the correct version of MMCV, MMDetection and MMSegmentation to avoid installation issues.
| MMDetection3D version | MMDetection version | MMSegmentation version | MMCV version |
|:-------------------:|:-------------------:|:-------------------:|:-------------------:|
| master | mmdet>=2.19.0, <=3.0.0| mmseg>=0.20.0, <=1.0.0 | mmcv-full>=1.4.8, <=1.5.0|
| v1.0.0rc1 | mmdet>=2.19.0, <=3.0.0| mmseg>=0.20.0, <=1.0.0 | mmcv-full>=1.4.8, <=1.5.0|
| v1.0.0rc0 | mmdet>=2.19.0, <=3.0.0| mmseg>=0.20.0, <=1.0.0 | mmcv-full>=1.3.17, <=1.5.0|
| 0.18.1 | mmdet>=2.19.0, <=3.0.0| mmseg>=0.20.0, <=1.0.0 | mmcv-full>=1.3.17, <=1.5.0|
| 0.18.0 | mmdet>=2.19.0, <=3.0.0| mmseg>=0.20.0, <=1.0.0 | mmcv-full>=1.3.17, <=1.5.0|
| 0.17.3 | mmdet>=2.14.0, <=3.0.0| mmseg>=0.14.1, <=1.0.0 | mmcv-full>=1.3.8, <=1.4.0|
| 0.17.2 | mmdet>=2.14.0, <=3.0.0| mmseg>=0.14.1, <=1.0.0 | mmcv-full>=1.3.8, <=1.4.0|
| 0.17.1 | mmdet>=2.14.0, <=3.0.0| mmseg>=0.14.1, <=1.0.0 | mmcv-full>=1.3.8, <=1.4.0|
| 0.17.0 | mmdet>=2.14.0, <=3.0.0| mmseg>=0.14.1, <=1.0.0 | mmcv-full>=1.3.8, <=1.4.0|
| 0.16.0 | mmdet>=2.14.0, <=3.0.0| mmseg>=0.14.1, <=1.0.0 | mmcv-full>=1.3.8, <=1.4.0|
| 0.15.0 | mmdet>=2.14.0, <=3.0.0| mmseg>=0.14.1, <=1.0.0 | mmcv-full>=1.3.8, <=1.4.0|
| 0.14.0 | mmdet>=2.10.0, <=2.11.0| mmseg==0.14.0 | mmcv-full>=1.3.1, <=1.4.0|
| 0.13.0 | mmdet>=2.10.0, <=2.11.0| Not required | mmcv-full>=1.2.4, <=1.4.0|
| 0.12.0 | mmdet>=2.5.0, <=2.11.0 | Not required | mmcv-full>=1.2.4, <=1.4.0|
| 0.11.0 | mmdet>=2.5.0, <=2.11.0 | Not required | mmcv-full>=1.2.4, <=1.3.0|
| 0.10.0 | mmdet>=2.5.0, <=2.11.0 | Not required | mmcv-full>=1.2.4, <=1.3.0|
| 0.9.0 | mmdet>=2.5.0, <=2.11.0 | Not required | mmcv-full>=1.2.4, <=1.3.0|
| 0.8.0 | mmdet>=2.5.0, <=2.11.0 | Not required | mmcv-full>=1.1.5, <=1.3.0|
| 0.7.0 | mmdet>=2.5.0, <=2.11.0 | Not required | mmcv-full>=1.1.5, <=1.3.0|
| 0.6.0 | mmdet>=2.4.0, <=2.11.0 | Not required | mmcv-full>=1.1.3, <=1.2.0|
| 0.5.0 | 2.3.0 | Not required | mmcv-full==1.0.5|
| :-------------------: | :---------------------: | :--------------------: | :------------------------: |
| master | mmdet>=2.19.0, <=3.0.0 | mmseg>=0.20.0, <=1.0.0 | mmcv-full>=1.4.8, <=1.5.0 |
| v1.0.0rc1 | mmdet>=2.19.0, <=3.0.0 | mmseg>=0.20.0, <=1.0.0 | mmcv-full>=1.4.8, <=1.5.0 |
| v1.0.0rc0 | mmdet>=2.19.0, <=3.0.0 | mmseg>=0.20.0, <=1.0.0 | mmcv-full>=1.3.17, <=1.5.0 |
| 0.18.1 | mmdet>=2.19.0, <=3.0.0 | mmseg>=0.20.0, <=1.0.0 | mmcv-full>=1.3.17, <=1.5.0 |
| 0.18.0 | mmdet>=2.19.0, <=3.0.0 | mmseg>=0.20.0, <=1.0.0 | mmcv-full>=1.3.17, <=1.5.0 |
| 0.17.3 | mmdet>=2.14.0, <=3.0.0 | mmseg>=0.14.1, <=1.0.0 | mmcv-full>=1.3.8, <=1.4.0 |
| 0.17.2 | mmdet>=2.14.0, <=3.0.0 | mmseg>=0.14.1, <=1.0.0 | mmcv-full>=1.3.8, <=1.4.0 |
| 0.17.1 | mmdet>=2.14.0, <=3.0.0 | mmseg>=0.14.1, <=1.0.0 | mmcv-full>=1.3.8, <=1.4.0 |
| 0.17.0 | mmdet>=2.14.0, <=3.0.0 | mmseg>=0.14.1, <=1.0.0 | mmcv-full>=1.3.8, <=1.4.0 |
| 0.16.0 | mmdet>=2.14.0, <=3.0.0 | mmseg>=0.14.1, <=1.0.0 | mmcv-full>=1.3.8, <=1.4.0 |
| 0.15.0 | mmdet>=2.14.0, <=3.0.0 | mmseg>=0.14.1, <=1.0.0 | mmcv-full>=1.3.8, <=1.4.0 |
| 0.14.0 | mmdet>=2.10.0, <=2.11.0 | mmseg==0.14.0 | mmcv-full>=1.3.1, <=1.4.0 |
| 0.13.0 | mmdet>=2.10.0, <=2.11.0 | Not required | mmcv-full>=1.2.4, <=1.4.0 |
| 0.12.0 | mmdet>=2.5.0, <=2.11.0 | Not required | mmcv-full>=1.2.4, <=1.4.0 |
| 0.11.0 | mmdet>=2.5.0, <=2.11.0 | Not required | mmcv-full>=1.2.4, <=1.3.0 |
| 0.10.0 | mmdet>=2.5.0, <=2.11.0 | Not required | mmcv-full>=1.2.4, <=1.3.0 |
| 0.9.0 | mmdet>=2.5.0, <=2.11.0 | Not required | mmcv-full>=1.2.4, <=1.3.0 |
| 0.8.0 | mmdet>=2.5.0, <=2.11.0 | Not required | mmcv-full>=1.1.5, <=1.3.0 |
| 0.7.0 | mmdet>=2.5.0, <=2.11.0 | Not required | mmcv-full>=1.1.5, <=1.3.0 |
| 0.6.0 | mmdet>=2.4.0, <=2.11.0 | Not required | mmcv-full>=1.1.3, <=1.2.0 |
| 0.5.0 | 2.3.0 | Not required | mmcv-full==1.0.5 |
# Installation
......@@ -192,6 +192,19 @@ you can install it before installing MMCV.
4. Some dependencies are optional. Simply running `pip install -v -e .` will only install the minimum runtime requirements. To use optional dependencies like `albumentations` and `imagecorruptions` either install them manually with `pip install -r requirements/optional.txt` or specify desired extras when calling `pip` (e.g. `pip install -v -e .[optional]`). Valid keys for the extras field are: `all`, `tests`, `build`, and `optional`.
We have supported spconv2.0. If the user has installed spconv2.0, the code will use spconv2.0 first, which will take up less GPU memory than using the default mmcv spconv. Users can use the following commands to install spconv2.0:
```bash
pip install cumm-cuxxx
pip install spconv-cuxxx
```
Where xxx is the CUDA version in the environment.
For example, using CUDA 10.2, the command will be `pip install cumm-cu102 && pip install spconv-cu102`.
Supported CUDA versions include 10.2, 11.1, 11.3, and 11.4. Users can also install it by building from the source. For more details please refer to [spconv v2.x](https://github.com/traveller59/spconv).
We also support Minkowski Engine as a sparse convolution backend. If necessary please follow original [installation guide](https://github.com/NVIDIA/MinkowskiEngine#installation) or use `pip`:
```shell
......
mmdet3d/models/middle_encoders/sparse_encoder.py
View file @ c28a3d98
# Copyright (c) OpenMMLab. All rights reserved.
from mmcv.ops import SparseConvTensor, SparseSequential
from mmcv.runner import auto_fp16
from torch import nn as nn
from mmdet3d.ops import SparseBasicBlock, make_sparse_convmodule
from mmdet3d.ops.spconv import IS_SPCONV2_AVAILABLE
from ..builder import MIDDLE_ENCODERS
if IS_SPCONV2_AVAILABLE:
from spconv.pytorch import SparseConvTensor, SparseSequential
else:
from mmcv.ops import SparseConvTensor, SparseSequential
@MIDDLE_ENCODERS.register_module()
class SparseEncoder(nn.Module):
......
mmdet3d/models/middle_encoders/sparse_unet.py
View file @ c28a3d98
# Copyright (c) OpenMMLab. All rights reserved.
import torch
from mmcv.ops import SparseConvTensor, SparseSequential
from mmdet3d.ops.spconv import IS_SPCONV2_AVAILABLE
if IS_SPCONV2_AVAILABLE:
from spconv.pytorch import SparseConvTensor, SparseSequential
else:
from mmcv.ops import SparseConvTensor, SparseSequential
from mmcv.runner import BaseModule, auto_fp16
from mmdet3d.ops import SparseBasicBlock, make_sparse_convmodule
......
mmdet3d/ops/sparse_block.py
View file @ c28a3d98
# Copyright (c) OpenMMLab. All rights reserved.
from mmcv.cnn import build_conv_layer, build_norm_layer
from mmcv.ops import SparseModule, SparseSequential
from torch import nn
from mmdet.models.backbones.resnet import BasicBlock, Bottleneck
from .spconv import IS_SPCONV2_AVAILABLE
if IS_SPCONV2_AVAILABLE:
from spconv.pytorch import SparseModule, SparseSequential
else:
from mmcv.ops import SparseModule, SparseSequential
def replace_feature(out, new_features):
if 'replace_feature' in out.__dir__():
# spconv 2.x behaviour
return out.replace_feature(new_features)
else:
out.features = new_features
return out
class SparseBottleneck(Bottleneck, SparseModule):
......@@ -46,21 +60,21 @@ class SparseBottleneck(Bottleneck, SparseModule):
identity = x.features
out = self.conv1(x)
out.features = self.bn1(out.features)
out.features = self.relu(out.features)
out = replace_feature(out, self.bn1(out.features))
out = replace_feature(out, self.relu(out.features))
out = self.conv2(out)
out.features = self.bn2(out.features)
out.features = self.relu(out.features)
out = replace_feature(out, self.bn2(out.features))
out = replace_feature(out, self.relu(out.features))
out = self.conv3(out)
out.features = self.bn3(out.features)
out = replace_feature(out, self.bn3(out.features))
if self.downsample is not None:
identity = self.downsample(x)
out.features += identity
out.features = self.relu(out.features)
out = replace_feature(out, out.features + identity)
out = replace_feature(out, self.relu(out.features))
return out
......@@ -104,19 +118,18 @@ class SparseBasicBlock(BasicBlock, SparseModule):
identity = x.features
assert x.features.dim() == 2, f'x.features.dim()={x.features.dim()}'
out = self.conv1(x)
out.features = self.norm1(out.features)
out.features = self.relu(out.features)
out = replace_feature(out, self.norm1(out.features))
out = replace_feature(out, self.relu(out.features))
out = self.conv2(out)
out.features = self.norm2(out.features)
out = replace_feature(out, self.norm2(out.features))
if self.downsample is not None:
identity = self.downsample(x)
out.features += identity
out.features = self.relu(out.features)
out = replace_feature(out, out.features + identity)
out = replace_feature(out, self.relu(out.features))
return out
......
mmdet3d/ops/spconv/__init__.py 0 → 100644
View file @ c28a3d98
# Copyright (c) OpenMMLab. All rights reserved.
from .overwrite_spconv.write_spconv2 import register_spconv2
try:
import spconv
except ImportError:
IS_SPCONV2_AVAILABLE = False
else:
if hasattr(spconv, '__version__') and spconv.__version__ >= '2.0.0':
IS_SPCONV2_AVAILABLE = register_spconv2()
else:
IS_SPCONV2_AVAILABLE = False
__all__ = ['IS_SPCONV2_AVAILABLE']
mmdet3d/ops/spconv/overwrite_spconv/write_spconv2.py 0 → 100644
View file @ c28a3d98
# Copyright (c) OpenMMLab. All rights reserved.
import itertools
from mmcv.cnn.bricks.registry import CONV_LAYERS
from torch.nn.parameter import Parameter
def register_spconv2():
"""This func registers spconv2.0 spconv ops to overwrite the default mmcv
spconv ops."""
try:
from spconv.pytorch import (SparseConv2d, SparseConv3d, SparseConv4d,
SparseConvTranspose2d,
SparseConvTranspose3d, SparseInverseConv2d,
SparseInverseConv3d, SparseModule,
SubMConv2d, SubMConv3d, SubMConv4d)
except ImportError:
return False
else:
CONV_LAYERS._register_module(SparseConv2d, 'SparseConv2d', force=True)
CONV_LAYERS._register_module(SparseConv3d, 'SparseConv3d', force=True)
CONV_LAYERS._register_module(SparseConv4d, 'SparseConv4d', force=True)
CONV_LAYERS._register_module(
SparseConvTranspose2d, 'SparseConvTranspose2d', force=True)
CONV_LAYERS._register_module(
SparseConvTranspose3d, 'SparseConvTranspose3d', force=True)
CONV_LAYERS._register_module(
SparseInverseConv2d, 'SparseInverseConv2d', force=True)
CONV_LAYERS._register_module(
SparseInverseConv3d, 'SparseInverseConv3d', force=True)
CONV_LAYERS._register_module(SubMConv2d, 'SubMConv2d', force=True)
CONV_LAYERS._register_module(SubMConv3d, 'SubMConv3d', force=True)
CONV_LAYERS._register_module(SubMConv4d, 'SubMConv4d', force=True)
SparseModule._load_from_state_dict = _load_from_state_dict
SparseModule._save_to_state_dict = _save_to_state_dict
return True
def _save_to_state_dict(self, destination, prefix, keep_vars):
"""Rewrite this func to compat the convolutional kernel weights between
spconv 1.x in MMCV and 2.x in spconv2.x.
Kernel weights in MMCV spconv has shape in (D,H,W,in_channel,out_channel) ,
while those in spcon2.x is in (out_channel,D,H,W,in_channel).
"""
for name, param in self._parameters.items():
if param is not None:
param = param if keep_vars else param.detach()
if name == 'weight':
dims = list(range(1, len(param.shape))) + [0]
param = param.permute(*dims)
destination[prefix + name] = param
for name, buf in self._buffers.items():
if buf is not None and name not in self._non_persistent_buffers_set:
destination[prefix + name] = buf if keep_vars else buf.detach()
def _load_from_state_dict(self, state_dict, prefix, local_metadata, strict,
missing_keys, unexpected_keys, error_msgs):
"""Rewrite this func to compat the convolutional kernel weights between
spconv 1.x in MMCV and 2.x in spconv2.x.
Kernel weights in MMCV spconv has shape in (D,H,W,in_channel,out_channel) ,
while those in spcon2.x is in (out_channel,D,H,W,in_channel).
"""
for hook in self._load_state_dict_pre_hooks.values():
hook(state_dict, prefix, local_metadata, strict, missing_keys,
unexpected_keys, error_msgs)
local_name_params = itertools.chain(self._parameters.items(),
self._buffers.items())
local_state = {k: v.data for k, v in local_name_params if v is not None}
for name, param in local_state.items():
key = prefix + name
if key in state_dict:
input_param = state_dict[key]
# Backward compatibility: loading 1-dim tensor from
# 0.3.* to version 0.4+
if len(param.shape) == 0 and len(input_param.shape) == 1:
input_param = input_param[0]
dims = [len(input_param.shape) - 1] + list(
range(len(input_param.shape) - 1))
input_param = input_param.permute(*dims)
if input_param.shape != param.shape:
# local shape should match the one in checkpoint
error_msgs.append(
f'size mismatch for {key}: copying a param with '
f'shape {key, input_param.shape} from checkpoint,'
f'the shape in current model is {param.shape}.')
continue
if isinstance(input_param, Parameter):
# backwards compatibility for serialized parameters
input_param = input_param.data
try:
param.copy_(input_param)
except Exception:
error_msgs.append(
f'While copying the parameter named "{key}", whose '
f'dimensions in the model are {param.size()} and whose '
f'dimensions in the checkpoint are {input_param.size()}.')
elif strict:
missing_keys.append(key)
if strict:
for key, input_param in state_dict.items():
if key.startswith(prefix):
input_name = key[len(prefix):]
input_name = input_name.split(
'.', 1)[0] # get the name of param/buffer/child
if input_name not in self._modules \
and input_name not in local_state:
unexpected_keys.append(key)
mmdet3d/utils/collect_env.py
View file @ c28a3d98
......@@ -5,6 +5,7 @@ from mmcv.utils import get_git_hash
import mmdet
import mmdet3d
import mmseg
from mmdet3d.ops.spconv import IS_SPCONV2_AVAILABLE
def collect_env():
......@@ -13,7 +14,7 @@ def collect_env():
env_info['MMDetection'] = mmdet.__version__
env_info['MMSegmentation'] = mmseg.__version__
env_info['MMDetection3D'] = mmdet3d.__version__ + '+' + get_git_hash()[:7]
env_info['spconv2.0'] = IS_SPCONV2_AVAILABLE
return env_info
......
requirements/optional.txt
View file @ c28a3d98
open3d
spconv
waymo-open-dataset-tf-2-1-0==1.2.0
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