repo stringlengths 7 90 | file_url stringlengths 81 315 | file_path stringlengths 4 228 | content stringlengths 0 32.8k | language stringclasses 1
value | license stringclasses 7
values | commit_sha stringlengths 40 40 | retrieved_at stringdate 2026-01-04 14:38:15 2026-01-05 02:33:18 | truncated bool 2
classes |
|---|---|---|---|---|---|---|---|---|
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/pointcept/models/point_group/utils.py | pointcept/models/point_group/utils.py | import torch
from torch.autograd import Function
import pointgroup_ops
class BallQueryBatchP(Function):
@staticmethod
def forward(ctx, coords, batch_idxs, batch_offsets, radius, meanActive):
"""
:param ctx:
:param coords: (n, 3) float
:param batch_idxs: (n) int
:param b... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/pointcept/models/point_group/__init__.py | pointcept/models/point_group/__init__.py | from .point_group_v1m1_base import PointGroup
| python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/pointcept/models/point_group/point_group_v1m1_base.py | pointcept/models/point_group/point_group_v1m1_base.py | """
PointGroup for instance segmentation
Author: Xiaoyang Wu (xiaoyang.wu.cs@gmail.com), Chengyao Wang
Please cite our work if the code is helpful to you.
"""
from functools import partial
import torch
import torch.nn as nn
import torch.nn.functional as F
try:
from pointgroup_ops import ballquery_batch_p, bfs_cl... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/pointcept/models/spvcnn/ts_spvcnn.py | pointcept/models/spvcnn/ts_spvcnn.py | """
SPVCNN
Author: Xiaoyang Wu (xiaoyang.wu.cs@gmail.com)
Please cite our work if the code is helpful to you.
"""
import torch
import torch.nn as nn
try:
import torchsparse
import torchsparse.nn as spnn
import torchsparse.nn.functional as F
from torchsparse.nn.utils import get_kernel_offsets
from... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/pointcept/models/spvcnn/__init__.py | pointcept/models/spvcnn/__init__.py | from .ts_spvcnn import *
| python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/pointcept/models/masked_scene_contrast/masked_scene_contrast_v1m2_csc.py | pointcept/models/masked_scene_contrast/masked_scene_contrast_v1m2_csc.py | """
Masked Scene Contrast v1m2
contrastive learning backend with CSC (https://arxiv.org/abs/2012.09165)
Author: Xiaoyang Wu (xiaoyang.wu.cs@gmail.com), Chengyao Wang (cywang22@cse.cuhk.edu.hk)
Please cite our work if the code is helpful to you.
"""
import random
from itertools import chain
import torch
import torch.n... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/pointcept/models/masked_scene_contrast/__init__.py | pointcept/models/masked_scene_contrast/__init__.py | from .masked_scene_contrast_v1m1_base import MaskedSceneContrast
from .masked_scene_contrast_v1m2_csc import MaskedSceneContrast
| python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/pointcept/models/masked_scene_contrast/masked_scene_contrast_v1m1_base.py | pointcept/models/masked_scene_contrast/masked_scene_contrast_v1m1_base.py | """
Masked Scene Contrast
https://arxiv.org/abs/2303.14191
Author: Xiaoyang Wu (xiaoyang.wu.cs@gmail.com)
Please cite our work if the code is helpful to you.
"""
import random
from itertools import chain
import torch
import torch.nn as nn
import torch.distributed as dist
from torch_geometric.nn.pool import voxel_grid... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/pointcept/models/point_transformer_v2/point_transformer_v2m3_pdnorm.py | pointcept/models/point_transformer_v2/point_transformer_v2m3_pdnorm.py | """
Point Transformer V2M3
Enable Prompt-Driven Normalization for Point Prompt Training
Author: Xiaoyang Wu (xiaoyang.wu.cs@gmail.com)
Please cite our work if the code is helpful to you.
"""
from functools import partial
from copy import deepcopy
import math
import torch
import torch.nn as nn
from torch.utils.checkp... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/pointcept/models/point_transformer_v2/point_transformer_v2m2_base.py | pointcept/models/point_transformer_v2/point_transformer_v2m2_base.py | """
Point Transformer V2 Mode 2 (recommend)
Disable Grouped Linear
Author: Xiaoyang Wu (xiaoyang.wu.cs@gmail.com)
Please cite our work if the code is helpful to you.
"""
from copy import deepcopy
import math
import torch
import torch.nn as nn
from torch.utils.checkpoint import checkpoint
from torch_geometric.nn.pool... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/pointcept/models/point_transformer_v2/point_transformer_v2m1_origin.py | pointcept/models/point_transformer_v2/point_transformer_v2m1_origin.py | """
Point Transformer V2 mode 1
Author: Xiaoyang Wu (xiaoyang.wu.cs@gmail.com)
Please cite our work if the code is helpful to you.
"""
from copy import deepcopy
import math
import torch
import torch.nn as nn
from torch.utils.checkpoint import checkpoint
from torch_geometric.nn.pool import voxel_grid
from torch_scatte... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/pointcept/models/point_transformer_v2/__init__.py | pointcept/models/point_transformer_v2/__init__.py | """
Point Transformer V2
Copyright (c) Xiaoyang Wu (xiaoyang.wu@connect.hku.hk). All Rights Reserved.
Please cite our work if you use any part of the code.
"""
from .point_transformer_v2m1_origin import *
from .point_transformer_v2m2_base import *
from .point_transformer_v2m3_pdnorm import *
| python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/pointcept/models/swin3d/swin3d_v1m1_base.py | pointcept/models/swin3d/swin3d_v1m1_base.py | import torch
import torch.nn as nn
import MinkowskiEngine as ME
from MinkowskiEngine import SparseTensor
from timm.models.layers import trunc_normal_
from .mink_layers import MinkConvBNRelu, MinkResBlock
from .swin3d_layers import GridDownsample, GridKNNDownsample, BasicLayer, Upsample
from pointcept.models.builder im... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/pointcept/models/swin3d/swin3d_layers.py | pointcept/models/swin3d/swin3d_layers.py | """
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
"""
import numpy as np
import torch
import torch.nn as nn
from timm.models.layers import DropPath, trunc_normal_
import MinkowskiEngine as ME
from MinkowskiEngine import SparseTensor
from Swin3D.sparse_dl.attn.attn_coff import (
SelfAttnA... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/pointcept/models/swin3d/mink_layers.py | pointcept/models/swin3d/mink_layers.py | """
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
"""
import torch
import torch.nn as nn
import torch.nn.functional as F
import MinkowskiEngine as ME
import numpy as np
def assign_feats(sp, x):
return ME.SparseTensor(
features=x.float(),
coordinate_map_key=sp.coordinate... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/pointcept/models/swin3d/__init__.py | pointcept/models/swin3d/__init__.py | from .swin3d_v1m1_base import Swin3DUNet
| python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/pointcept/models/point_transformer_v3/__init__.py | pointcept/models/point_transformer_v3/__init__.py | from .point_transformer_v3m1_base import *
| python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/pointcept/models/point_transformer_v3/point_transformer_v3m1_base.py | pointcept/models/point_transformer_v3/point_transformer_v3m1_base.py | """
Point Transformer - V3 Mode1
Author: Xiaoyang Wu (xiaoyang.wu.cs@gmail.com)
Please cite our work if the code is helpful to you.
"""
from functools import partial
from addict import Dict
import math
import torch
import torch.nn as nn
import torch.fft as fft
import spconv.pytorch as spconv
import torch_scatter
from... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | true |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/pointcept/models/stratified_transformer/stratified_transformer_v1m2_refine.py | pointcept/models/stratified_transformer/stratified_transformer_v1m2_refine.py | """
Stratified Transformer
Modified from https://github.com/dvlab-research/Stratified-Transformer
Author: Xiaoyang Wu (xiaoyang.wu.cs@gmail.com)
Please cite our work if the code is helpful to you.
"""
from copy import deepcopy
import torch
import torch.nn as nn
try:
import torch_points_kernels as tp
except Impo... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/pointcept/models/stratified_transformer/stratified_transformer_v1m1_origin.py | pointcept/models/stratified_transformer/stratified_transformer_v1m1_origin.py | import torch
import torch.nn as nn
try:
import torch_points_kernels as tp
except ImportError:
tp = None
try:
from torch_points3d.modules.KPConv.kernels import KPConvLayer
from torch_points3d.core.common_modules import FastBatchNorm1d
except ImportError:
KPConvLayer = None
FastBatchNorm1d = Non... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/pointcept/models/stratified_transformer/__init__.py | pointcept/models/stratified_transformer/__init__.py | from .stratified_transformer_v1m1_origin import StratifiedTransformer
from .stratified_transformer_v1m2_refine import StratifiedTransformer
| python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/pointcept/models/point_transformer/point_transformer_partseg.py | pointcept/models/point_transformer/point_transformer_partseg.py | """
Point Transformer V1 for Part Segmentation
Might be a bit different from the original paper
Author: Xiaoyang Wu (xiaoyang.wu.cs@gmail.com)
Please cite our work if the code is helpful to you.
"""
import torch
import torch.nn as nn
import einops
import pointops
from pointcept.models.builder import MODELS
from .ut... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/pointcept/models/point_transformer/utils.py | pointcept/models/point_transformer/utils.py | import torch
import torch.nn as nn
torch.nn.LayerNorm
class LayerNorm1d(nn.BatchNorm1d):
def forward(self, input: torch.Tensor) -> torch.Tensor:
return (
super()
.forward(input.transpose(1, 2).contiguous())
.transpose(1, 2)
.contiguous()
)
| python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/pointcept/models/point_transformer/__init__.py | pointcept/models/point_transformer/__init__.py | from .point_transformer_seg import *
from .point_transformer_partseg import *
from .point_transformer_cls import *
| python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/pointcept/models/point_transformer/point_transformer_cls.py | pointcept/models/point_transformer/point_transformer_cls.py | """
Point Transformer V1 for Object Classification
Might be a bit different from the original paper
Author: Xiaoyang Wu (xiaoyang.wu.cs@gmail.com)
Please cite our work if the code is helpful to you.
"""
import torch
import torch.nn as nn
from .point_transformer_seg import TransitionDown, Bottleneck
from pointcept.m... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/pointcept/models/point_transformer/point_transformer_seg.py | pointcept/models/point_transformer/point_transformer_seg.py | """
Point Transformer V1 for Semantic Segmentation
Might be a bit different from the original paper
Author: Xiaoyang Wu (xiaoyang.wu.cs@gmail.com)
Please cite our work if the code is helpful to you.
"""
import torch
import torch.nn as nn
import einops
import pointops
from pointcept.models.builder import MODELS
from... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/pointcept/models/context_aware_classifier/__init__.py | pointcept/models/context_aware_classifier/__init__.py | from .context_aware_classifier_v1m1_base import CACSegmentor
| python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/pointcept/models/context_aware_classifier/context_aware_classifier_v1m1_base.py | pointcept/models/context_aware_classifier/context_aware_classifier_v1m1_base.py | """
Context-aware Classifier for Semantic Segmentation
Author: Zhuotao Tian, Xiaoyang Wu (xiaoyang.wu.cs@gmail.com)
Please cite our work if the code is helpful to you.
"""
import torch
import torch.nn as nn
import torch.nn.functional as F
from pointcept.models.losses import build_criteria
from pointcept.models.builde... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/pointcept/utils/path.py | pointcept/utils/path.py | # Copyright (c) OpenMMLab. All rights reserved.
import os
import os.path as osp
from pathlib import Path
from .misc import is_str
def is_filepath(x):
return is_str(x) or isinstance(x, Path)
def fopen(filepath, *args, **kwargs):
if is_str(filepath):
return open(filepath, *args, **kwargs)
elif is... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/pointcept/utils/registry.py | pointcept/utils/registry.py | # Copyright (c) OpenMMLab. All rights reserved.
import inspect
import warnings
from functools import partial
from .misc import is_seq_of
def build_from_cfg(cfg, registry, default_args=None):
"""Build a module from configs dict.
Args:
cfg (dict): Config dict. It should at least contain the key "type"... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/pointcept/utils/timer.py | pointcept/utils/timer.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
# -*- coding: utf-8 -*-
from time import perf_counter
from typing import Optional
class Timer:
"""
A timer which computes the time elapsed since the start/reset of the timer.
"""
def __init__(self) -> None:
self.reset()
... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/pointcept/utils/optimizer.py | pointcept/utils/optimizer.py | """
Optimizer
Author: Xiaoyang Wu (xiaoyang.wu.cs@gmail.com)
Please cite our work if the code is helpful to you.
"""
import torch
from pointcept.utils.logger import get_root_logger
from pointcept.utils.registry import Registry
OPTIMIZERS = Registry("optimizers")
OPTIMIZERS.register_module(module=torch.optim.SGD, n... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/pointcept/utils/logger.py | pointcept/utils/logger.py | """
Logger Utils
Modified from mmcv
Author: Xiaoyang Wu (xiaoyang.wu.cs@gmail.com)
Please cite our work if the code is helpful to you.
"""
import logging
import torch
import torch.distributed as dist
from termcolor import colored
logger_initialized = {}
root_status = 0
class _ColorfulFormatter(logging.Formatter)... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/pointcept/utils/events.py | pointcept/utils/events.py | """
Events Utils
Modified from Detectron2
Author: Xiaoyang Wu (xiaoyang.wu.cs@gmail.com)
Please cite our work if the code is helpful to you.
"""
import datetime
import json
import logging
import os
import time
import torch
import numpy as np
from typing import List, Optional, Tuple
from collections import defaultdi... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/pointcept/utils/misc.py | pointcept/utils/misc.py | """
Misc
Author: Xiaoyang Wu (xiaoyang.wu.cs@gmail.com)
Please cite our work if the code is helpful to you.
"""
import os
import warnings
from collections import abc
import numpy as np
import torch
from importlib import import_module
class AverageMeter(object):
"""Computes and stores the average and current val... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/pointcept/utils/comm.py | pointcept/utils/comm.py | # Copyright (c) Facebook, Inc. and its affiliates.
"""
This file contains primitives for multi-gpu communication.
This is useful when doing distributed training.
Modified from detectron2(https://github.com/facebookresearch/detectron2)
Copyright (c) Xiaoyang Wu (xiaoyang.wu@connect.hku.hk). All Rights Reserved.
Please ... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/pointcept/utils/config.py | pointcept/utils/config.py | # Copyright (c) OpenMMLab. All rights reserved.
import ast
import copy
import os
import os.path as osp
import platform
import shutil
import sys
import tempfile
import uuid
import warnings
from argparse import Action, ArgumentParser
from collections import abc
from importlib import import_module
from addict import Dict... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/pointcept/utils/__init__.py | pointcept/utils/__init__.py | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false | |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/pointcept/utils/cache.py | pointcept/utils/cache.py | """
Data Cache Utils
Author: Xiaoyang Wu (xiaoyang.wu.cs@gmail.com)
Please cite our work if the code is helpful to you.
"""
import os
import SharedArray
try:
from multiprocessing.shared_memory import ShareableList
except ImportError:
import warnings
warnings.warn("Please update python version >= 3.8 to ... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/pointcept/utils/scheduler.py | pointcept/utils/scheduler.py | """
Scheduler
Author: Xiaoyang Wu (xiaoyang.wu.cs@gmail.com)
Please cite our work if the code is helpful to you.
"""
import torch.optim.lr_scheduler as lr_scheduler
from .registry import Registry
SCHEDULERS = Registry("schedulers")
@SCHEDULERS.register_module()
class MultiStepLR(lr_scheduler.MultiStepLR):
def ... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/pointcept/utils/visualization.py | pointcept/utils/visualization.py | """
Visualization Utils
Author: Xiaoyang Wu (xiaoyang.wu.cs@gmail.com)
Please cite our work if the code is helpful to you.
"""
import os
import open3d as o3d
import numpy as np
import torch
def to_numpy(x):
if isinstance(x, torch.Tensor):
x = x.clone().detach().cpu().numpy()
assert isinstance(x, np.... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/pointcept/utils/env.py | pointcept/utils/env.py | """
Environment Utils
Author: Xiaoyang Wu (xiaoyang.wu.cs@gmail.com)
Please cite our work if the code is helpful to you.
"""
import os
import random
import numpy as np
import torch
import torch.backends.cudnn as cudnn
from datetime import datetime
def get_random_seed():
seed = (
os.getpid()
+ i... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/pointcept/engines/train.py | pointcept/engines/train.py | """
Trainer
Author: Xiaoyang Wu (xiaoyang.wu.cs@gmail.com)
Please cite our work if the code is helpful to you.
"""
import os
import sys
import weakref
import torch
import torch.nn as nn
import torch.utils.data
from functools import partial
if sys.version_info >= (3, 10):
from collections.abc import Iterator
else... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/pointcept/engines/defaults.py | pointcept/engines/defaults.py | """
Default training/testing logic
modified from detectron2(https://github.com/facebookresearch/detectron2)
Author: Xiaoyang Wu (xiaoyang.wu.cs@gmail.com)
Please cite our work if the code is helpful to you.
"""
import os
import sys
import argparse
import multiprocessing as mp
from torch.nn.parallel import Distribute... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/pointcept/engines/__init__.py | pointcept/engines/__init__.py | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false | |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/pointcept/engines/launch.py | pointcept/engines/launch.py | """
Launcher
modified from detectron2(https://github.com/facebookresearch/detectron2)
Author: Xiaoyang Wu (xiaoyang.wu.cs@gmail.com)
Please cite our work if the code is helpful to you.
"""
import os
import logging
from datetime import timedelta
import torch
import torch.distributed as dist
import torch.multiprocessi... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/pointcept/engines/test.py | pointcept/engines/test.py | """
Tester
Author: Xiaoyang Wu (xiaoyang.wu.cs@gmail.com)
Please cite our work if the code is helpful to you.
"""
import os
import time
import numpy as np
from collections import OrderedDict
import torch
import torch.distributed as dist
import torch.nn.functional as F
import torch.utils.data
from .defaults import cr... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/pointcept/engines/hooks/default.py | pointcept/engines/hooks/default.py | """
Default Hook
Author: Xiaoyang Wu (xiaoyang.wu.cs@gmail.com)
Please cite our work if the code is helpful to you.
"""
class HookBase:
"""
Base class for hooks that can be registered with :class:`TrainerBase`.
"""
trainer = None # A weak reference to the trainer object.
def before_train(self)... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/pointcept/engines/hooks/evaluator.py | pointcept/engines/hooks/evaluator.py | """
Evaluate Hook
Author: Xiaoyang Wu (xiaoyang.wu.cs@gmail.com)
Please cite our work if the code is helpful to you.
"""
import numpy as np
import torch
import torch.distributed as dist
import pointops
from uuid import uuid4
import pointcept.utils.comm as comm
from pointcept.utils.misc import intersection_and_union_... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/pointcept/engines/hooks/misc.py | pointcept/engines/hooks/misc.py | """
Misc Hook
Author: Xiaoyang Wu (xiaoyang.wu.cs@gmail.com)
Please cite our work if the code is helpful to you.
"""
import sys
import glob
import os
import shutil
import time
import torch
import torch.utils.data
from collections import OrderedDict
if sys.version_info >= (3, 10):
from collections.abc import Sequ... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/pointcept/engines/hooks/__init__.py | pointcept/engines/hooks/__init__.py | from .default import HookBase
from .misc import *
from .evaluator import *
from .builder import build_hooks
| python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/pointcept/engines/hooks/builder.py | pointcept/engines/hooks/builder.py | """
Hook Builder
Author: Xiaoyang Wu (xiaoyang.wu.cs@gmail.com)
Please cite our work if the code is helpful to you.
"""
from pointcept.utils.registry import Registry
HOOKS = Registry("hooks")
def build_hooks(cfg):
hooks = []
for hook_cfg in cfg:
hooks.append(HOOKS.build(hook_cfg))
return hooks... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/assets/init.py | assets/init.py | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false | |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/configs/scannet200/Baseline.py | configs/scannet200/Baseline.py | from pointcept.datasets.preprocessing.scannet.meta_data.scannet200_constants import (
CLASS_LABELS_200,
)
_base_ = ["../_base_/default_runtime.py"]
# ---- common ---/data/qwt/dataset/scannet_npy
batch_size = 8 # bs=2 for 1 GPU, bs=4 for 2 GPUs, bs=8 for 4GPUs
num_worker = 16 # the num_worker is double batch_size.... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/configs/scannet200/PTv3_CNF.py | configs/scannet200/PTv3_CNF.py | from pointcept.datasets.preprocessing.scannet.meta_data.scannet200_constants import (
CLASS_LABELS_200,
)
_base_ = ["../_base_/default_runtime.py"]
# ---- common ---/data/qwt/dataset/scannet_npy
batch_size = 12 # bs=2 for 1 GPU, bs=6 for 2 GPUs, bs=12 for 4GPUs
num_worker = 24 # the num_worker is double batch_siz... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/configs/scannet200/PTv3.py | configs/scannet200/PTv3.py | from pointcept.datasets.preprocessing.scannet.meta_data.scannet200_constants import (
CLASS_LABELS_200,
)
_base_ = ["../_base_/default_runtime.py"]
# ---- common ---/data/qwt/dataset/scannet_npy
batch_size = 12 # bs=2 for 1 GPU, bs=6 for 2 GPUs, bs=12 for 4GPUs
num_worker = 24 # the num_worker is double batch_siz... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/configs/scannet200/CDSegNet.py | configs/scannet200/CDSegNet.py | from pointcept.datasets.preprocessing.scannet.meta_data.scannet200_constants import (
CLASS_LABELS_200,
)
_base_ = ["../_base_/default_runtime.py"]
# ---- common ---/data/qwt/dataset/scannet_npy
batch_size = 8 # bs=2 for 1 GPU, bs=4 for 2 GPUs, bs=8 for 4GPUs
num_worker = 16 # the num_worker is double batch_size.... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/configs/_base_/default_runtime.py | configs/_base_/default_runtime.py | weight = None # path to model weight
resume = False # whether to resume training process
evaluate = True # evaluate after each epoch training process
test_only = False # test process
seed = None # train process will init a random seed and record
save_path = "exp/default"
num_worker = 16 # total worker in all gpu... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/configs/scannet/Baseline.py | configs/scannet/Baseline.py | _base_ = ["../_base_/default_runtime.py"]
# ---- common ---
batch_size = 8 # bs=2 for 1 GPU, bs=4 for 2 GPUs, bs=8 for 4GPUs
num_worker = 16 # the num_worker is double batch_size.
mix_prob = 0.8
empty_cache = False
enable_amp = True
seed = 54421566 # 54421566, 42
gredient_clip = []
ignore_index = -1
# ---- common --... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/configs/scannet/PTv3_CNF.py | configs/scannet/PTv3_CNF.py | _base_ = ["../_base_/default_runtime.py"]
# ---- common ---
batch_size = 12 # bs=2 for 1 GPU, bs=6 for 2 GPUs, bs=12 for 4GPUs
num_worker = 24 # the num_worker is double batch_size.
mix_prob = 0.8
empty_cache = False
enable_amp = True
seed = 54421566 # 54421566, 42
gredient_clip = []
ignore_index = -1
# ---- common ... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/configs/scannet/CDSegNet_time.py | configs/scannet/CDSegNet_time.py | _base_ = ["../_base_/default_runtime.py"]
# ---- common ---
batch_size = 4
num_worker = 8
mix_prob = 0.8
empty_cache = False
enable_amp = True
seed = 54421566 # 54421566, 42
gredient_clip = []
ignore_index = -1
# ---- common ---
# ---- Seg Model ----
condition = True
dm = True
dm_input = "xt"
dm_target = "noise"
dm... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/configs/scannet/PTv3_CNF_time.py | configs/scannet/PTv3_CNF_time.py | _base_ = ["../_base_/default_runtime.py"]
# ---- common ---
batch_size = 6
num_worker = 12
mix_prob = 0.8
empty_cache = False
enable_amp = True
seed = 54421566 # 54421566, 42
gredient_clip = []
ignore_index = -1
# ---- common ---
# ---- Seg Model ----
condition = True
dm = True
dm_input = "xt"
dm_target = "noise"
d... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/configs/scannet/PTv3.py | configs/scannet/PTv3.py | _base_ = ["../_base_/default_runtime.py"]
# ---- common ---
batch_size = 12 # bs=2 for 1 GPU, bs=6 for 2 GPUs, bs=12 for 4GPUs
num_worker = 24 # the num_worker is double batch_size.
mix_prob = 0.8
empty_cache = False
enable_amp = True
seed = 54421566 # 54421566, 42
gredient_clip = []
ignore_index = -1
# ---- common ... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/configs/scannet/CDSegNet.py | configs/scannet/CDSegNet.py | _base_ = ["../_base_/default_runtime.py"]
# ---- common ---
batch_size = 8 # bs=2 for 1 GPU, bs=4 for 2 GPUs, bs=8 for 4GPUs
num_worker = 16 # the num_worker is double batch_size.
mix_prob = 0.8
empty_cache = False
enable_amp = True
seed = 54421566 # 54421566, 42
gredient_clip = []
ignore_index = -1
# ---- common --... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/configs/nuscenes/Baseline.py | configs/nuscenes/Baseline.py | _base_ = ["../_base_/default_runtime.py"]
# ---- common ---
batch_size = 8 # bs=2 for 1 GPU, bs=4 for 2 GPUs, bs=8 for 4GPUs
num_worker = 16 # the num_worker is double batch_size.
mix_prob = 0.8
empty_cache = False
enable_amp = True
seed = 54421566 # 54421566, 42
gredient_clip = []
ignore_index = -1
# ---- common --... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/configs/nuscenes/PTv3_CNF_testing_82.8.py | configs/nuscenes/PTv3_CNF_testing_82.8.py | _base_ = ["../_base_/default_runtime.py"]
# ---- common ---
batch_size = 8 # bs=2 for 1 GPU, bs=4 for 2 GPUs, bs=8 for 4GPUs
num_worker = 16 # the num_worker is double batch_size.
mix_prob = 0.8
empty_cache = False
enable_amp = True
seed = 54421566 # 54421566, 42
gredient_clip = []
ignore_index = -1
# ---- common --... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/configs/nuscenes/PTv3_time.py | configs/nuscenes/PTv3_time.py | _base_ = ["../_base_/default_runtime.py"]
# ---- common ---
batch_size = 6
num_worker = 12
mix_prob = 0.8
empty_cache = False
enable_amp = True
seed = 54421566 # 54421566, 42
gredient_clip = []
ignore_index = -1
# ---- common ---
# ---- Seg Model ----
condition = False
dm = False
dm_input = "xt"
dm_target = "noise"... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/configs/nuscenes/PTv3_CNF.py | configs/nuscenes/PTv3_CNF.py | _base_ = ["../_base_/default_runtime.py"]
# ---- common ---
batch_size = 8 # bs=2 for 1 GPU, bs=4 for 2 GPUs, bs=8 for 4GPUs
num_worker = 16 # the num_worker is double batch_size.
mix_prob = 0.8
empty_cache = False
enable_amp = True
seed = 54421566 # 54421566, 42
gredient_clip = []
ignore_index = -1
# ---- common --... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/configs/nuscenes/CDSegNet_time.py | configs/nuscenes/CDSegNet_time.py | _base_ = ["../_base_/default_runtime.py"]
# ---- common ---
batch_size = 8
num_worker = 16
mix_prob = 0.8
empty_cache = False
enable_amp = True
seed = 54421566 # 54421566, 42
gredient_clip = []
ignore_index = -1
# ---- common ---
# ---- Seg Model ----
condition = True
dm = True
dm_input = "xt"
dm_target = "noise"
d... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/configs/nuscenes/PTv3_CNF_time.py | configs/nuscenes/PTv3_CNF_time.py | _base_ = ["../_base_/default_runtime.py"]
# ---- common ---
batch_size = 16
num_worker = 32
mix_prob = 0.8
empty_cache = False
enable_amp = True
seed = 54421566 # 54421566, 42
gredient_clip = []
ignore_index = -1
# ---- common ---
# ---- Seg Model ----
condition = True
dm = True
dm_input = "xt"
dm_target = "noise"
... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/configs/nuscenes/PTv3.py | configs/nuscenes/PTv3.py | _base_ = ["../_base_/default_runtime.py"]
# ---- common ---
batch_size = 12 # bs=2 for 1 GPU, bs=6 for 2 GPUs, bs=12 for 4GPUs
num_worker = 24 # the num_worker is double batch_size.
mix_prob = 0.8
empty_cache = False
enable_amp = True
seed = 54421566 # 54421566, 42
gredient_clip = []
ignore_index = -1
# ---- common ... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/configs/nuscenes/CDSegNet.py | configs/nuscenes/CDSegNet.py | _base_ = ["../_base_/default_runtime.py"]
# ---- common ---
batch_size = 8 # bs=2 for 1 GPU, bs=4 for 2 GPUs, bs=8 for 4GPUs
num_worker = 16 # the num_worker is double batch_size.
mix_prob = 0.8
empty_cache = False
enable_amp = True
seed = 54421566 # 54421566, 42
gredient_clip = []
ignore_index = -1
# ---- common --... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/libs/pointgroup_ops/setup.py | libs/pointgroup_ops/setup.py | import os
from sys import argv
from setuptools import setup
from torch.utils.cpp_extension import BuildExtension, CUDAExtension
from distutils.sysconfig import get_config_vars
(opt,) = get_config_vars("OPT")
os.environ["OPT"] = " ".join(
flag for flag in opt.split() if flag != "-Wstrict-prototypes"
)
def _argpar... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/libs/pointgroup_ops/functions/__init__.py | libs/pointgroup_ops/functions/__init__.py | from .functions import bfs_cluster, ballquery_batch_p, Clustering
| python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/libs/pointgroup_ops/functions/functions.py | libs/pointgroup_ops/functions/functions.py | import torch
from torch.autograd import Function
import pointgroup_ops_cuda
class BallQueryBatchP(Function):
@staticmethod
def forward(ctx, coords, batch_idxs, batch_offsets, radius, meanActive):
"""
:param ctx:
:param coords: (n, 3) float
:param batch_idxs: (n) int
:pa... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/libs/pointops2/setup.py | libs/pointops2/setup.py | import os
from setuptools import setup
from torch.utils.cpp_extension import BuildExtension, CUDAExtension
from distutils.sysconfig import get_config_vars
(opt,) = get_config_vars("OPT")
os.environ["OPT"] = " ".join(
flag for flag in opt.split() if flag != "-Wstrict-prototypes"
)
src = "src"
sources = [
os.pa... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/libs/pointops2/__init__.py | libs/pointops2/__init__.py | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false | |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/libs/pointops2/src/__init__.py | libs/pointops2/src/__init__.py | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false | |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/libs/pointops2/functions/test_attention_op_step1_v2.py | libs/pointops2/functions/test_attention_op_step1_v2.py | import torch
import pointops
from torch_scatter import (
scatter_max,
scatter_mean,
scatter_add,
scatter_min,
scatter_sum,
)
torch.manual_seed(1)
M = 800000
N = 35000
C = 96
h = 6
query = torch.rand(N, h, C // h).cuda()
key = torch.rand(N, h, C // h).cuda()
index_0 = torch.rand(M)
index_0[index_0... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/libs/pointops2/functions/test_relative_pos_encoding_op_step1_v3.py | libs/pointops2/functions/test_relative_pos_encoding_op_step1_v3.py | import torch
import pointops
from torch_scatter import (
scatter_max,
scatter_mean,
scatter_add,
scatter_min,
scatter_sum,
)
torch.manual_seed(1)
M = 80000
N = 3500
# M = 80
# N = 5
hdim = 16
h = 6
L = 31
query = torch.rand(N, h, hdim).cuda()
table_q = torch.rand(L, h, hdim, 3).cuda()
key = torch.... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/libs/pointops2/functions/pointops2.py | libs/pointops2/functions/pointops2.py | from typing import Tuple
import torch
from torch.autograd import Function
import torch.nn as nn
import pointops2_cuda as pointops_cuda
class FurthestSampling(Function):
@staticmethod
def forward(ctx, xyz, offset, new_offset):
"""
input: xyz: (n, 3), offset: (b), new_offset: (b)
outpu... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/libs/pointops2/functions/pointops_ablation.py | libs/pointops2/functions/pointops_ablation.py | from typing import Tuple
import torch
from torch.autograd import Function
import torch.nn as nn
import pointops2_cuda as pointops_cuda
class FurthestSampling(Function):
@staticmethod
def forward(ctx, xyz, offset, new_offset):
"""
input: xyz: (n, 3), offset: (b), new_offset: (b)
outpu... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/libs/pointops2/functions/test_attention_op_step2.py | libs/pointops2/functions/test_attention_op_step2.py | import torch
import pointops
from torch_scatter import (
scatter_max,
scatter_mean,
scatter_add,
scatter_min,
scatter_sum,
)
torch.manual_seed(1)
M = 800000
N = 35000
C = 96
h = 6
softmax_attn_flat = torch.rand(M, h).cuda()
value = torch.rand(N, h, C // h).cuda()
index_0 = torch.rand(M)
index_0[i... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/libs/pointops2/functions/test_relative_pos_encoding_op_step2_v2.py | libs/pointops2/functions/test_relative_pos_encoding_op_step2_v2.py | import torch
import pointops
from torch_scatter import (
scatter_max,
scatter_mean,
scatter_add,
scatter_min,
scatter_sum,
)
torch.manual_seed(1)
M = 80000
N = 3500
hdim = 16
h = 6
L = 31
attn = torch.rand(M, h).cuda()
v = torch.rand(N, h, hdim).cuda()
table = torch.rand(L, h, hdim, 3).cuda()
ind... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/libs/pointops2/functions/test_attention_op_step1.py | libs/pointops2/functions/test_attention_op_step1.py | import torch
import pointops
from torch_scatter import (
scatter_max,
scatter_mean,
scatter_add,
scatter_min,
scatter_sum,
)
torch.manual_seed(1)
M = 800000
N = 35000
C = 96
h = 6
query = torch.rand(N, h, C // h).cuda()
key = torch.rand(N, h, C // h).cuda()
index_0 = torch.rand(M)
index_0[index_0... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/libs/pointops2/functions/test_relative_pos_encoding_op_step1_v2.py | libs/pointops2/functions/test_relative_pos_encoding_op_step1_v2.py | import torch
import pointops
from torch_scatter import (
scatter_max,
scatter_mean,
scatter_add,
scatter_min,
scatter_sum,
)
torch.manual_seed(1)
M = 80000
N = 3500
hdim = 16
h = 6
L = 31
query = torch.rand(N, h, hdim).cuda()
table_q = torch.rand(L, h, hdim, 3).cuda()
key = torch.rand(N, h, hdim).... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/libs/pointops2/functions/__init__.py | libs/pointops2/functions/__init__.py | from pointops2 import *
| python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/libs/pointops2/functions/test_relative_pos_encoding_op_step1.py | libs/pointops2/functions/test_relative_pos_encoding_op_step1.py | import torch
import pointops
from torch_scatter import (
scatter_max,
scatter_mean,
scatter_add,
scatter_min,
scatter_sum,
)
torch.manual_seed(1)
M = 80000
N = 3500
hdim = 16
h = 6
L = 31
query = torch.rand(N, h, hdim).cuda()
table = torch.rand(L, h, hdim, 3).cuda()
index = torch.rand(M)
index[in... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/libs/pointops2/functions/test_relative_pos_encoding_op_step2.py | libs/pointops2/functions/test_relative_pos_encoding_op_step2.py | import torch
import pointops
from torch_scatter import (
scatter_max,
scatter_mean,
scatter_add,
scatter_min,
scatter_sum,
)
torch.manual_seed(1)
M = 80000
N = 3500
hdim = 16
h = 6
L = 31
attn = torch.rand(M, h).cuda()
v = torch.rand(N, h, hdim).cuda()
table = torch.rand(L, h, hdim, 3).cuda()
ind... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/libs/pointops2/functions/pointops.py | libs/pointops2/functions/pointops.py | """
The part of attention operations is written by Xin Lai.
Email: xinlai@cse.cuhk.edu.hk
"""
from typing import Tuple
import torch
from torch.autograd import Function
import torch.nn as nn
import pointops2_cuda as pointops_cuda
import time
class FurthestSampling(Function):
@staticmethod
def forward(ctx, x... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | true |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/libs/pointops/setup.py | libs/pointops/setup.py | import os
from setuptools import setup
from torch.utils.cpp_extension import BuildExtension, CUDAExtension
from distutils.sysconfig import get_config_vars
(opt,) = get_config_vars("OPT")
os.environ["OPT"] = " ".join(
flag for flag in opt.split() if flag != "-Wstrict-prototypes"
)
src = "src"
sources = [
os.pa... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/libs/pointops/__init__.py | libs/pointops/__init__.py | from .functions import *
| python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/libs/pointops/src/__init__.py | libs/pointops/src/__init__.py | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false | |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/libs/pointops/functions/subtraction.py | libs/pointops/functions/subtraction.py | import torch
from torch.autograd import Function
from pointops._C import subtraction_forward_cuda, subtraction_backward_cuda
class Subtraction(Function):
@staticmethod
def forward(ctx, input1, input2, idx):
"""
input: input1: (n, c), input2: (n, c), idx: (n, nsample)
output: (n, nsam... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/libs/pointops/functions/query.py | libs/pointops/functions/query.py | import torch
from torch.autograd import Function
from pointops._C import knn_query_cuda, random_ball_query_cuda, ball_query_cuda
class KNNQuery(Function):
@staticmethod
def forward(ctx, nsample, xyz, offset, new_xyz=None, new_offset=None):
"""
input: coords: (n, 3), new_xyz: (m, 3), offset: (... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/libs/pointops/functions/sampling.py | libs/pointops/functions/sampling.py | import torch
from torch.autograd import Function
from pointops._C import farthest_point_sampling_cuda
class FarthestPointSampling(Function):
@staticmethod
def forward(ctx, xyz, offset, new_offset):
"""
input: coords: (n, 3), offset: (b), new_offset: (b)
output: idx: (m)
"""
... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/libs/pointops/functions/grouping.py | libs/pointops/functions/grouping.py | import torch
from torch.autograd import Function
from pointops._C import grouping_forward_cuda, grouping_backward_cuda
class Grouping(Function):
@staticmethod
def forward(ctx, input, idx):
"""
input: input: (n, c), idx : (m, nsample)
output: (m, nsample, c)
"""
assert ... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/libs/pointops/functions/interpolation.py | libs/pointops/functions/interpolation.py | import torch
from torch.autograd import Function
from pointops._C import interpolation_forward_cuda, interpolation_backward_cuda
from .query import knn_query
def interpolation(xyz, new_xyz, feat, offset, new_offset, k=3):
"""
input: coords: (m, 3), new_xyz: (n, 3), color: (m, c), offset: (b), new_offset: (b)... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/libs/pointops/functions/utils.py | libs/pointops/functions/utils.py | import torch
from pointops import knn_query, ball_query, grouping
def knn_query_and_group(
feat,
xyz,
offset=None,
new_xyz=None,
new_offset=None,
idx=None,
nsample=None,
with_xyz=False,
):
if idx is None:
assert nsample is not None
idx, _ = knn_query(nsample, xyz, o... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
QWTforGithub/CDSegNet | https://github.com/QWTforGithub/CDSegNet/blob/87b603dbd011c0f57fb498d70680e32d4f8cf2f0/libs/pointops/functions/__init__.py | libs/pointops/functions/__init__.py | from .query import knn_query, ball_query, random_ball_query
from .sampling import farthest_point_sampling
from .grouping import grouping, grouping2
from .interpolation import interpolation, interpolation2
from .subtraction import subtraction
from .aggregation import aggregation
from .attention import attention_relation... | python | MIT | 87b603dbd011c0f57fb498d70680e32d4f8cf2f0 | 2026-01-05T07:13:40.759144Z | false |
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