A CV toolkit for my papers.

Last update: Jan 04, 2023

Overview

PyTorch-Encoding

Documentation

Please visit the Docs for detail instructions of installation and usage.
Please visit the link to image classification models.
Please visit the link to semantic segmentation models.

Citations

ResNeSt: Split-Attention Networks [arXiv]
Hang Zhang, Chongruo Wu, Zhongyue Zhang, Yi Zhu, Zhi Zhang, Haibin Lin, Yue Sun, Tong He, Jonas Muller, R. Manmatha, Mu Li and Alex Smola

@article{zhang2020resnest,
title={ResNeSt: Split-Attention Networks},
author={Zhang, Hang and Wu, Chongruo and Zhang, Zhongyue and Zhu, Yi and Zhang, Zhi and Lin, Haibin and Sun, Yue and He, Tong and Muller, Jonas and Manmatha, R. and Li, Mu and Smola, Alexander},
journal={arXiv preprint},
year={2020}
}

Context Encoding for Semantic Segmentation [arXiv]
Hang Zhang, Kristin Dana, Jianping Shi, Zhongyue Zhang, Xiaogang Wang, Ambrish Tyagi, Amit Agrawal

@InProceedings{Zhang_2018_CVPR,
author = {Zhang, Hang and Dana, Kristin and Shi, Jianping and Zhang, Zhongyue and Wang, Xiaogang and Tyagi, Ambrish and Agrawal, Amit},
title = {Context Encoding for Semantic Segmentation},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2018}
}

Deep TEN: Texture Encoding Network [arXiv]
Hang Zhang, Jia Xue, Kristin Dana

@InProceedings{Zhang_2017_CVPR,
author = {Zhang, Hang and Xue, Jia and Dana, Kristin},
title = {Deep TEN: Texture Encoding Network},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {July},
year = {2017}
}

Comments

No module named cpp_extension

Hi, I got the error named No module named cpp_extension (from torch.utils.cpp_extension import load) when I run the quick demo http://hangzh.com/PyTorch-Encoding/experiments/segmentation.html#install-package. The version of python and torch are 2.7 and 0.3.1 respectively. How can I handle it?
bug

opened by qiulesun 51
libENCODING.so library missing

Hello,

I've tried to install this Encoding-Layer on Linux 16.04 but I have the following error occuring during the installation :

x86_64-linux-gnu-g++: error: /usr/local/lib/python3.5/dist-packages/torch/lib/libENCODING.so: No file or repository of this type error: command 'x86_64-linux-gnu-g++' failed with exit status 1

I tried to find this library to see if the problem was coming from a wrong path but it looks like this library doesn't exist on my computer. I have installed Pytorch from the source following the instructions with no problems and I'm also using Cuda 8.0. Could you help me to find a solution to this problem please ?

Thanks
duplicate

opened by TFisichella 24
Results of Cityscapes using EncNet

I want to get results of Cityscapes dataset by training EncNet. Although you did not provide corresponding results, can I do it using directly the codes you have released, mainly involving prepare_cityscapes.py and cityscapes.py and other default hyper-parameters like lr=0.01, epoch=240?

opened by qiulesun 23
ninja: build stopped: subcommand failed.

/home/gaoxy/.conda/envs/pytorch/lib/python3.6/site-packages/torch/lib/include/pybind11/cast.h: In instantiation of ‘pybind11::object pybind11::detail::object_api::operator()(Args&& ...) const [with pybind11::return_value_policy policy = (pybind11::return_value_policy)1u; Args = {pybind11::handle&, pybind11::handle&}; Derived = pybind11::detail::accessorpybind11::detail::accessor_policies::str_attr]’: /home/gaoxy/.conda/envs/pytorch/lib/python3.6/site-packages/torch/lib/include/pybind11/pytypes.h:884:27: required from ‘pybind11::str pybind11::str::format(Args&& ...) const [with Args = {pybind11::handle&, pybind11::handle&}]’ /home/gaoxy/.conda/envs/pytorch/lib/python3.6/site-packages/torch/lib/include/pybind11/pybind11.h:749:72: required from here /home/gaoxy/.conda/envs/pytorch/lib/python3.6/site-packages/torch/lib/include/pybind11/cast.h:2096:74: error: no matching function for call to ‘collect_arguments(pybind11::handle&, pybind11::handle&)’ return detail::collect_arguments(std::forward(args)...).call(derived().ptr()); ^ /home/gaoxy/.conda/envs/pytorch/lib/python3.6/site-packages/torch/lib/include/pybind11/cast.h:2096:74: note: candidates are: /home/gaoxy/.conda/envs/pytorch/lib/python3.6/site-packages/torch/lib/include/pybind11/cast.h:2075:1: note: template<pybind11::return_value_policy policy, class ... Args, class> pybind11::detail::simple_collector pybind11::detail::collect_arguments(Args&& ...) simple_collector collect_arguments(Args &&...args) { ^ /home/gaoxy/.conda/envs/pytorch/lib/python3.6/site-packages/torch/lib/include/pybind11/cast.h:2075:1: note: template argument deduction/substitution failed: /home/gaoxy/.conda/envs/pytorch/lib/python3.6/site-packages/torch/lib/include/pybind11/cast.h:2082:1: note: template<pybind11::return_value_policy policy, class ... Args, class> pybind11::detail::unpacking_collector pybind11::detail::collect_arguments(Args&& ...) unpacking_collector collect_arguments(Args &&...args) { ^ /home/gaoxy/.conda/envs/pytorch/lib/python3.6/site-packages/torch/lib/include/pybind11/cast.h:2082:1: note: template argument deduction/substitution failed: ninja: build stopped: subcommand failed.
compatibility

opened by OilGao 21
subprocess.CalledProcessError: Command '['where', 'cl']' returned non-zero exit status 1.

Warning (from warnings module): File "C:\Users\ys\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\utils\cpp_extension.py", line 184 warnings.warn('Error checking compiler version for {}: {}'.format(compiler, error)) UserWarning: Error checking compiler version for c++: Command 'c++' returned non-zero exit status 1. Traceback (most recent call last): File "<pyshell#0>", line 1, in import encoding File "C:\Users\ys\AppData\Local\Programs\Python\Python36\lib\site-packages\encoding_init_.py", line 13, in from . import nn, functions, parallel, utils, models, datasets, transforms File "C:\Users\ys\AppData\Local\Programs\Python\Python36\lib\site-packages\encoding\nn_init_.py", line 12, in from .encoding import * File "C:\Users\ys\AppData\Local\Programs\Python\Python36\lib\site-packages\encoding\nn\encoding.py", line 18, in from ..functions import scaled_l2, aggregate, pairwise_cosine File "C:\Users\ys\AppData\Local\Programs\Python\Python36\lib\site-packages\encoding\functions_init_.py", line 2, in from .encoding import * File "C:\Users\ys\AppData\Local\Programs\Python\Python36\lib\site-packages\encoding\functions\encoding.py", line 14, in from .. import lib File "C:\Users\ys\AppData\Local\Programs\Python\Python36\lib\site-packages\encoding\lib_init_.py", line 15, in ], build_directory=cpu_path, verbose=False) File "C:\Users\ys\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\utils\cpp_extension.py", line 645, in load is_python_module) File "C:\Users\ys\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\utils\cpp_extension.py", line 814, in _jit_compile with_cuda=with_cuda) File "C:\Users\ys\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\utils\cpp_extension.py", line 859, in _write_ninja_file_and_build with_cuda=with_cuda) File "C:\Users\ys\AppData\Local\Programs\Python\Python36\lib\site-packages\torch\utils\cpp_extension.py", line 1064, in _write_ninja_file 'cl']).decode().split('\r\n') File "C:\Users\ys\AppData\Local\Programs\Python\Python36\lib\subprocess.py", line 336, in check_output **kwargs).stdout File "C:\Users\ys\AppData\Local\Programs\Python\Python36\lib\subprocess.py", line 418, in run output=stdout, stderr=stderr) subprocess.CalledProcessError: Command '['where', 'cl']' returned non-zero exit status 1.

After i install the latest version of encoding, this error will still occur when i import encoding module. I use python3.6, pytorch1.0 stable, cuda9.0

opened by flyingshan 19
RuntimeError: Ninja is required to load C++ extension

Hi,author. I have followed the instructions on your page. I got your code by git clone, and run "python setup.py install" with no errors. However when I run "python3 demo.py", I got the error like this:

Traceback (most recent call last): File "/home/llg/.local/lib/python3.5/site-packages/torch/utils/cpp_extension.py", line 873, in verify_ninja_availability subprocess.check_call('ninja --version'.split(), stdout=devnull) File "/usr/lib/python3.5/subprocess.py", line 576, in check_call retcode = call(*popenargs, **kwargs) File "/usr/lib/python3.5/subprocess.py", line 557, in call with Popen(*popenargs, **kwargs) as p: File "/usr/lib/python3.5/subprocess.py", line 947, in init restore_signals, start_new_session) File "/usr/lib/python3.5/subprocess.py", line 1551, in _execute_child raise child_exception_type(errno_num, err_msg) FileNotFoundError: [Errno 2] No such file or directory: 'ninja'

During handling of the above exception, another exception occurred:

Traceback (most recent call last): File "1.py", line 2, in import encoding File "/home/llg/Documents/PyTorch-Encoding/encoding/init.py", line 13, in from . import nn, functions, parallel, utils, models, datasets, transforms File "/home/llg/Documents/PyTorch-Encoding/encoding/nn/init.py", line 12, in from .encoding import * File "/home/llg/Documents/PyTorch-Encoding/encoding/nn/encoding.py", line 18, in from ..functions import scaled_l2, aggregate, pairwise_cosine File "/home/llg/Documents/PyTorch-Encoding/encoding/functions/init.py", line 2, in from .encoding import * File "/home/llg/Documents/PyTorch-Encoding/encoding/functions/encoding.py", line 14, in from .. import lib File "/home/llg/Documents/PyTorch-Encoding/encoding/lib/init.py", line 15, in ], build_directory=cpu_path, verbose=False) File "/home/llg/.local/lib/python3.5/site-packages/torch/utils/cpp_extension.py", line 645, in load is_python_module) File "/home/llg/.local/lib/python3.5/site-packages/torch/utils/cpp_extension.py", line 814, in _jit_compile with_cuda=with_cuda) File "/home/llg/.local/lib/python3.5/site-packages/torch/utils/cpp_extension.py", line 837, in _write_ninja_file_and_build verify_ninja_availability() File "/home/llg/.local/lib/python3.5/site-packages/torch/utils/cpp_extension.py", line 875, in verify_ninja_availability raise RuntimeError("Ninja is required to load C++ extensions") RuntimeError: Ninja is required to load C++ extension

How to overcome it? What's the "Ninja"?

opened by lilingge 18
ninja: build stopped: subcommand failed.
After i installed ninja , When i run python main.py --dataset cifar10 --model encnetdrop --widen 8 --ncodes 32 --resume model/encnet_cifar.pth.tar --eval

it shows the error:

/home/anaconda3/lib/python3.6/site-packages/torch/utils/cpp_extension.py:118: UserWarning:

!! WARNING !!

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! Your compiler (c++) may be ABI-incompatible with PyTorch! Please use a compiler that is ABI-compatible with GCC 4.9 and above. See https://gcc.gnu.org/onlinedocs/libstdc++/manual/abi.html.

See https://gist.github.com/goldsborough/d466f43e8ffc948ff92de7486c5216d6 for instructions on how to install GCC 4.9 or higher. !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

!! WARNING !!

warnings.warn(ABI_INCOMPATIBILITY_WARNING.format(compiler)) Traceback (most recent call last): File "/home/anaconda3/lib/python3.6/site-packages/torch/utils/cpp_extension.py", line 759, in _build_extension_module ['ninja', '-v'], stderr=subprocess.STDOUT, cwd=build_directory) File "/home/anaconda3/lib/python3.6/subprocess.py", line 336, in check_output **kwargs).stdout File "/home/anaconda3/lib/python3.6/subprocess.py", line 418, in run output=stdout, stderr=stderr) subprocess.CalledProcessError: Command '['ninja', '-v']' returned non-zero exit status 1.

During handling of the above exception, another exception occurred:

Traceback (most recent call last): File "main.py", line 24, in from encoding.utils import * File "/home/anaconda3/lib/python3.6/site-packages/encoding/init.py", line 13, in from . import nn, functions, dilated, parallel, utils, models, datasets File "/home/anaconda3/lib/python3.6/site-packages/encoding/nn/init.py", line 12, in from .encoding import * File "/home/anaconda3/lib/python3.6/site-packages/encoding/nn/encoding.py", line 18, in from ..functions import scaled_l2, aggregate, pairwise_cosine File "/home/anaconda3/lib/python3.6/site-packages/encoding/functions/init.py", line 2, in from .encoding import * File "/home/anaconda3/lib/python3.6/site-packages/encoding/functions/encoding.py", line 14, in from .. import lib File "/home/anaconda3/lib/python3.6/site-packages/encoding/lib/init.py", line 15, in ], build_directory=cpu_path, verbose=False) File "/home/anaconda3/lib/python3.6/site-packages/torch/utils/cpp_extension.py", line 514, in load with_cuda=with_cuda) File "/home/anaconda3/lib/python3.6/site-packages/torch/utils/cpp_extension.py", line 682, in _jit_compile _build_extension_module(name, build_directory) File "/home/anaconda3/lib/python3.6/site-packages/torch/utils/cpp_extension.py", line 765, in _build_extension_module name, error.output.decode())) RuntimeError: Error building extension 'enclib_cpu': [1/4] c++ -MMD -MF syncbn_cpu.o.d -DTORCH_EXTENSION_NAME=enclib_cpu -I/home/anaconda3/lib/python3.6/site-packages/torch/lib/include -I/home/anaconda3/lib/python3.6/site-packages/torch/lib/include/TH -I/home/anaconda3/lib/python3.6/site-packages/torch/lib/include/THC -I/home/anaconda3/include/python3.6m -D_GLIBCXX_USE_CXX11_ABI=0 -fPIC -std=c++11 -c /home/anaconda3/lib/python3.6/site-packages/encoding/lib/cpu/syncbn_cpu.cpp -o syncbn_cpu.o FAILED: syncbn_cpu.o c++ -MMD -MF syncbn_cpu.o.d -DTORCH_EXTENSION_NAME=enclib_cpu -I/home/anaconda3/lib/python3.6/site-packages/torch/lib/include -I/home/anaconda3/lib/python3.6/site-packages/torch/lib/include/TH -I/home/anaconda3/lib/python3.6/site-packages/torch/lib/include/THC -I/home/anaconda3/include/python3.6m -D_GLIBCXX_USE_CXX11_ABI=0 -fPIC -std=c++11 -c /home/anaconda3/lib/python3.6/site-packages/encoding/lib/cpu/syncbn_cpu.cpp -o syncbn_cpu.o /home/anaconda3/lib/python3.6/site-packages/encoding/lib/cpu/syncbn_cpu.cpp:1:26: fatal error: torch/tensor.h: No such file or directory compilation terminated. [2/4] c++ -MMD -MF roi_align_cpu.o.d -DTORCH_EXTENSION_NAME=enclib_cpu -I/home/anaconda3/lib/python3.6/site-packages/torch/lib/include -I/home/anaconda3/lib/python3.6/site-packages/torch/lib/include/TH -I/home/anaconda3/lib/python3.6/site-packages/torch/lib/include/THC -I/home/anaconda3/include/python3.6m -D_GLIBCXX_USE_CXX11_ABI=0 -fPIC -std=c++11 -c /home/anaconda3/lib/python3.6/site-packages/encoding/lib/cpu/roi_align_cpu.cpp -o roi_align_cpu.o FAILED: roi_align_cpu.o c++ -MMD -MF roi_align_cpu.o.d -DTORCH_EXTENSION_NAME=enclib_cpu -I/home/anaconda3/lib/python3.6/site-packages/torch/lib/include -I/home/anaconda3/lib/python3.6/site-packages/torch/lib/include/TH -I/home/anaconda3/lib/python3.6/site-packages/torch/lib/include/THC -I/home/anaconda3/include/python3.6m -D_GLIBCXX_USE_CXX11_ABI=0 -fPIC -std=c++11 -c /home/anaconda3/lib/python3.6/site-packages/encoding/lib/cpu/roi_align_cpu.cpp -o roi_align_cpu.o /home/anaconda3/lib/python3.6/site-packages/encoding/lib/cpu/roi_align_cpu.cpp:1:26: fatal error: torch/tensor.h: No such file or directory compilation terminated. [3/4] c++ -MMD -MF nms_cpu.o.d -DTORCH_EXTENSION_NAME=enclib_cpu -I/home/anaconda3/lib/python3.6/site-packages/torch/lib/include -I/home/anaconda3/lib/python3.6/site-packages/torch/lib/include/TH -I/home/anaconda3/lib/python3.6/site-packages/torch/lib/include/THC -I/home/anaconda3/include/python3.6m -D_GLIBCXX_USE_CXX11_ABI=0 -fPIC -std=c++11 -c /home/anaconda3/lib/python3.6/site-packages/encoding/lib/cpu/nms_cpu.cpp -o nms_cpu.o FAILED: nms_cpu.o c++ -MMD -MF nms_cpu.o.d -DTORCH_EXTENSION_NAME=enclib_cpu -I/home/anaconda3/lib/python3.6/site-packages/torch/lib/include -I/home/anaconda3/lib/python3.6/site-packages/torch/lib/include/TH -I/home/anaconda3/lib/python3.6/site-packages/torch/lib/include/THC -I/home/anaconda3/include/python3.6m -D_GLIBCXX_USE_CXX11_ABI=0 -fPIC -std=c++11 -c /home/anaconda3/lib/python3.6/site-packages/encoding/lib/cpu/nms_cpu.cpp -o nms_cpu.o /home/anaconda3/lib/python3.6/site-packages/encoding/lib/cpu/nms_cpu.cpp:1:26: fatal error: torch/tensor.h: No such file or directory compilation terminated. ninja: build stopped: subcommand failed.
bug high priority
opened by sanersbug 18

我怎么才能直接使用Encoding Layer呢?我这里使用pip命令不能成功安装

您好,我的环境是python3.7 pytorch1.7 torchvision 0.8.1 使用命令pip install git+https://github.com/zhanghang1989/PyTorch-Encoding/后大量报错,我无法解决, 因此求助,我尝试将Encoding Layer相关的代码进行呢copy,但是encoding/lib/中的代码无法进行引用,我应该怎么做呢?

另外我使用pytorch矩阵运算实现了Encoding模块,但是我发现在计算eik的过程中会出现数据爆炸的情况(Nan),不知道您是否有解决办法呢?我的代码详见后续

望指点迷津,非常感谢

class CodeBookBlock(nn.Module):
    def __init__(self, in_channels, c2, out_channels):
        super(CodeBookBlock, self).__init__()
        self.c2 = c2
        self.conv1 = nn.Sequential(
            nn.Conv2d(in_channels, c2, kernel_size=1),
            nn.BatchNorm2d(c2),
            nn.LeakyReLU()
        )
        self.codebook = nn.Parameter(torch. Tensor(c2, Config.K), requires_grad=True)
        self.scale = nn.Parameter(torch.Tensor(Config.K), requires_grad=True)
        self.dp = nn.Dropout(0.5)  # 不能用batchnorm2d,否则会造成fc之后数值全部变成nan
        self.relu = nn.ReLU6()
        self.leakyRelu = nn.LeakyReLU()
        self.fc = nn.Linear(self.c2, out_channels)
        self.sigmoid = nn.Sigmoid()
        self.init_params()  # 初始化参数
        torch.autograd.set_detect_anomaly(True)

    def init_params(self):
        std1 = 1. / ((Config.K * self.c2) ** (1 / 2))
        self.codebook.data.uniform_(-std1, std1)
        self.scale.data.uniform_(-1, 0)

    def forward(self, z):
        """
        :param z: (Batch, c, h, w)
        :return: (Batch, c2)
        """
        batch, c, h, w = z.shape
        N = h * w
        z1 = self.conv1(z)
        z1 = z1.flatten(start_dim=2, end_dim=-1)  # Batch, c2, N
        # print("我是z1")
        # print(z1.shape)
        # print(z1)
        # --------------开始计算放缩因子gama--------------
        # ---处理特征向量z1
        z1 = z1.unsqueeze(2)  # Batch, c2, 1, N
        z1 = z1.repeat(1, 1, Config.K, 1)  # Batch, c2, K, h*w
        # 将z1的K, N(即h*w)交换
        z1 = z1.transpose(2, 3)  # Batch, c2, N, K
        # print("z1")
        # print(z1)
        # ---处理codebook
        d = self.codebook.unsqueeze(1)  # c2, 1, K
        d = d.repeat(1, N, 1)  # c2, N, K
        d = d.unsqueeze(0)  # 1, c2, N, K
        d = d.repeat(batch, 1, 1, 1)  # batch, c2, N, K
        # print("d")
        # print(d.shape)
        # ---计算rik
        rik = z1 - d  # batch, c2, N, K
        # ---计算numerator
        rik = torch.pow(torch.abs(rik), 2)  # 对rik取绝对值并且平方   batch, c2, N, K
        # print(rik.shape)
        # 把scale从1, K变成   batch, c2, N, K
        scale = self.scale.repeat(N, 1)  # N, K
        scale = scale.unsqueeze(0).unsqueeze(0)  # 1, 1, N, K
        scale = scale.repeat(batch, self.c2, 1, 1)  # batch, c2, N, K
        # print(scale.shape)
        # 获得numerator
        # print("我是-scale * rik")
        # print(torch.max(-scale * rik))
        # 这里如果使用exp函数,会造成numerator的数值很大,进而造成后面的变量出现nan, 不用的话Rei可能为0造成后面除法出问题,因此这里改成+某个常数或者leakyRelu
        numerator = self.leakyRelu(-scale * rik)  # batch, c2, N, K
        # print("我是numerator")
        # print(torch.max(numerator))
        Rei = numerator.sum(3)  # eik公式中的分母   batch, c2, N
        # print(Rei.shape)
        # ---开始计算eik,必须在Rei计算完之后
        numerator = numerator * rik  # batch, c2, N, K
        # 将Rei从batch, c2, N变到batch, c2, K, N
        Rei = Rei.unsqueeze(2)  # batch, c2, 1, N
        # print(Rei.shape)
        Rei = Rei.repeat(1, 1, Config.K, 1)  # batch, c2, K, N
        # print(Rei.shape)
        # 将Rei的K, N交换
        Rei = Rei.transpose(2, 3)  # batch, c2, N, K
        # print("我是Rei")
        # print(Rei.shape)
        # # print(Rei)
        # print("Rei的最小值")
        # print(torch.min(Rei))
        # 获得eik
        # print("我是Rei")
        # print(torch.min(Rei))
        eik = numerator / Rei  # batch, c2, N, K
        # print("eik")
        # print(torch.max(eik))
        # 获得ek
        ek = eik.sum(2)  # batch, c2, K
        # print("ek")
        # print(ek.shape)
        # print(ek)
        # print(ek.shape)
        # 获得e
        e = ek.sum(2)  # batch, c2
        e = self.dp(e)
        e = self.relu(e)
        e = self.fc(e)
        # print("我是e")
        # print(torch.max(e))
        gama = self.sigmoid(e)
        # print("我是gama")
        # print(torch.max(gama))
        return gama  # batch, c2

opened by RSMung 16

AttributeError: 'NoneType' object has no attribute 'run_slave'

Hi ZHang:

segmentation

when i train segmentation model,

CUDA_VISIBLE_DEVICES=0  python train.py --dataset pcontext --model encnet --aux --se-loss

i face an error:

Using poly LR Scheduler!
Starting Epoch: 0
Total Epoches: 80
  0%|                                                                                                                                         | 0/1249 [00:00<?, ?it/s]
=>Epoches 0, learning rate = 0.0003,                 previous best = 0.0000
Traceback (most recent call last):
  File "train.py", line 175, in <module>
    trainer.training(epoch)
  File "train.py", line 105, in training
    outputs = self.model(image)
  File "/root/anaconda3/lib/python3.6/site-packages/torch/nn/modules/module.py", line 468, in __call__
    result = self.forward(*input, **kwargs)
  File "/root/anaconda3/lib/python3.6/site-packages/torch/nn/parallel/data_parallel.py", line 121, in forward
    return self.module(*inputs[0], **kwargs[0])
  File "/root/anaconda3/lib/python3.6/site-packages/torch/nn/modules/module.py", line 468, in __call__
    result = self.forward(*input, **kwargs)
  File "/root/anaconda3/lib/python3.6/site-packages/encoding/models/encnet.py", line 32, in forward
    features = self.base_forward(x)
  File "/root/anaconda3/lib/python3.6/site-packages/encoding/models/base.py", line 51, in base_forward
    x = self.pretrained.bn1(x)
  File "/root/anaconda3/lib/python3.6/site-packages/torch/nn/modules/module.py", line 468, in __call__
    result = self.forward(*input, **kwargs)
  File "/root/anaconda3/lib/python3.6/site-packages/encoding/nn/syncbn.py", line 57, in forward
    mean, inv_std = self._slave_pipe.run_slave(_ChildMessage(xsum, xsqsum, N))
AttributeError: 'NoneType' object has no attribute 'run_slave'

my environment:

Quick Demo has been done (success)
version

>>> torch.__version__
'0.5.0a0+32bc28d'

only one nvidia card : 1080(8G)

recognition

when i run recognition demo, i

python main.py --dataset cifar10 --model encnetdrop --widen 8 --ncodes 32 --resume model/encnet_cifar.pth.tar --eval

also face an error:

    (9): View()
    (10): Linear(in_features=512, out_features=10, bias=True)
  )
)
Traceback (most recent call last):
  File "main.py", line 181, in <module>
    main()
  File "main.py", line 56, in main
    Dataloader = dataset.Dataloader
AttributeError: module 'dataset.cifar10' has no attribute 'Dataloader'

my environment:

torchvision:

>>> import torchvision
>>> torchvision.__version__
'0.2.1'

Can you help me with this problem? Thank you ~

opened by hellodfan 16

Subprocess.CalledProcessError:Command '['ninja','-v']' returned non-zero exit status 1.

the environment configure: pytorch: 1.0.0 python:3.6.7 ubuntu:16.04 Anaconda3

when i run python and import encoding,it could appeare below errors. $python Python 3.6.7 |Anaconda, Inc.| (default, Oct 23 2018, 19:16:44) [GCC 7.3.0] on linux Type "help", "copyright", "credits" or "license" for more information.

import torch print(torch.version) 1.0.0 import encoding Traceback (most recent call last): File "/data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/utils/cpp_extension.py", line 946, in _build_extension_module check=True) File "/data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/subprocess.py", line 418, in run output=stdout, stderr=stderr) **subprocess.CalledProcessError: Command '['ninja', '-v']' returned non-zero exit status 1.

During handling of the above exception, another exception occurred:**

Traceback (most recent call last): File "", line 1, in File "/data_2/pytorch_project/PyTorch-Encoding/encoding/init.py", line 13, in from . import nn, functions, parallel, utils, models, datasets, transforms File "/data_2/pytorch_project/PyTorch-Encoding/encoding/nn/init.py", line 12, in from .encoding import * File "/data_2/pytorch_project/PyTorch-Encoding/encoding/nn/encoding.py", line 18, in from ..functions import scaled_l2, aggregate, pairwise_cosine File "/data_2/pytorch_project/PyTorch-Encoding/encoding/functions/init.py", line 2, in from .encoding import * File "/data_2/pytorch_project/PyTorch-Encoding/encoding/functions/encoding.py", line 14, in from .. import lib File "/data_2/pytorch_project/PyTorch-Encoding/encoding/lib/init.py", line 27, in build_directory=gpu_path, verbose=False) File "/data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/utils/cpp_extension.py", line 645, in load is_python_module) File "/data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/utils/cpp_extension.py", line 814, in jit_compile with_cuda=with_cuda) File "/data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/utils/cpp_extension.py", line 863, in write_ninja_file_and_build build_extension_module(name, build_directory, verbose) File "/data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/utils/cpp_extension.py", line 959, in build_extension_module raise RuntimeError(message) RuntimeError: Error building extension 'enclib_gpu': [1/7] /usr/local/cuda-8.0/bin/nvcc -DTORCH_EXTENSION_NAME=enclib_gpu -DTORCH_API_INCLUDE_EXTENSION_H -isystem /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include -isystem /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include/torch/csrc/api/include -isystem /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include/TH -isystem /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include/THC -isystem /usr/local/cuda-8.0/include -isystem /data_2/Anaconda3/envs/pytorch1.0.0/include/python3.6m -D_GLIBCXX_USE_CXX11_ABI=0 -D__CUDA_NO_HALF_OPERATORS -D__CUDA_NO_HALF_CONVERSIONS -D__CUDA_NO_HALF2_OPERATORS__ --compiler-options '-fPIC' --expt-extended-lambda -std=c++11 -c /data_2/pytorch_project/PyTorch-Encoding/encoding/lib/gpu/syncbn_kernel.cu -o syncbn_kernel.cuda.o FAILED: syncbn_kernel.cuda.o /usr/local/cuda-8.0/bin/nvcc -DTORCH_EXTENSION_NAME=enclib_gpu -DTORCH_API_INCLUDE_EXTENSION_H -isystem /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include -isystem /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include/torch/csrc/api/include -isystem /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include/TH -isystem /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include/THC -isystem /usr/local/cuda-8.0/include -isystem /data_2/Anaconda3/envs/pytorch1.0.0/include/python3.6m -D_GLIBCXX_USE_CXX11_ABI=0 -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --compiler-options '-fPIC' --expt-extended-lambda -std=c++11 -c /data_2/pytorch_project/PyTorch-Encoding/encoding/lib/gpu/syncbn_kernel.cu -o syncbn_kernel.cuda.o nvcc warning : The 'compute_20', 'sm_20', and 'sm_21' architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning). /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include/torch/csrc/jit/argument_spec.h(59): error: static assertion failed with "ArgumentInfo is to be a POD struct"

1 error detected in the compilation of "/tmp/tmpxft_00003cd1_00000000-7_syncbn_kernel.cpp1.ii". [2/7] /usr/local/cuda-8.0/bin/nvcc -DTORCH_EXTENSION_NAME=enclib_gpu -DTORCH_API_INCLUDE_EXTENSION_H -isystem /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include -isystem /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include/torch/csrc/api/include -isystem /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include/TH -isystem /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include/THC -isystem /usr/local/cuda-8.0/include -isystem /data_2/Anaconda3/envs/pytorch1.0.0/include/python3.6m -D_GLIBCXX_USE_CXX11_ABI=0 -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --compiler-options '-fPIC' --expt-extended-lambda -std=c++11 -c /data_2/pytorch_project/PyTorch-Encoding/encoding/lib/gpu/encodingv2_kernel.cu -o encodingv2_kernel.cuda.o FAILED: encodingv2_kernel.cuda.o /usr/local/cuda-8.0/bin/nvcc -DTORCH_EXTENSION_NAME=enclib_gpu -DTORCH_API_INCLUDE_EXTENSION_H -isystem /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include -isystem /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include/torch/csrc/api/include -isystem /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include/TH -isystem /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include/THC -isystem /usr/local/cuda-8.0/include -isystem /data_2/Anaconda3/envs/pytorch1.0.0/include/python3.6m -D_GLIBCXX_USE_CXX11_ABI=0 -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --compiler-options '-fPIC' --expt-extended-lambda -std=c++11 -c /data_2/pytorch_project/PyTorch-Encoding/encoding/lib/gpu/encodingv2_kernel.cu -o encodingv2_kernel.cuda.o nvcc warning : The 'compute_20', 'sm_20', and 'sm_21' architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning). /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include/torch/csrc/jit/argument_spec.h(59): error: static assertion failed with "ArgumentInfo is to be a POD struct"

1 error detected in the compilation of "/tmp/tmpxft_00003cd0_00000000-7_encodingv2_kernel.cpp1.ii". [3/7] /usr/local/cuda-8.0/bin/nvcc -DTORCH_EXTENSION_NAME=enclib_gpu -DTORCH_API_INCLUDE_EXTENSION_H -isystem /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include -isystem /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include/torch/csrc/api/include -isystem /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include/TH -isystem /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include/THC -isystem /usr/local/cuda-8.0/include -isystem /data_2/Anaconda3/envs/pytorch1.0.0/include/python3.6m -D_GLIBCXX_USE_CXX11_ABI=0 -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --compiler-options '-fPIC' --expt-extended-lambda -std=c++11 -c /data_2/pytorch_project/PyTorch-Encoding/encoding/lib/gpu/nms_kernel.cu -o nms_kernel.cuda.o FAILED: nms_kernel.cuda.o /usr/local/cuda-8.0/bin/nvcc -DTORCH_EXTENSION_NAME=enclib_gpu -DTORCH_API_INCLUDE_EXTENSION_H -isystem /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include -isystem /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include/torch/csrc/api/include -isystem /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include/TH -isystem /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include/THC -isystem /usr/local/cuda-8.0/include -isystem /data_2/Anaconda3/envs/pytorch1.0.0/include/python3.6m -D_GLIBCXX_USE_CXX11_ABI=0 -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --compiler-options '-fPIC' --expt-extended-lambda -std=c++11 -c /data_2/pytorch_project/PyTorch-Encoding/encoding/lib/gpu/nms_kernel.cu -o nms_kernel.cuda.o nvcc warning : The 'compute_20', 'sm_20', and 'sm_21' architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning). /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include/torch/csrc/jit/argument_spec.h(59): error: static assertion failed with "ArgumentInfo is to be a POD struct"

1 error detected in the compilation of "/tmp/tmpxft_00003cd3_00000000-7_nms_kernel.cpp1.ii". [4/7] /usr/local/cuda-8.0/bin/nvcc -DTORCH_EXTENSION_NAME=enclib_gpu -DTORCH_API_INCLUDE_EXTENSION_H -isystem /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include -isystem /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include/torch/csrc/api/include -isystem /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include/TH -isystem /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include/THC -isystem /usr/local/cuda-8.0/include -isystem /data_2/Anaconda3/envs/pytorch1.0.0/include/python3.6m -D_GLIBCXX_USE_CXX11_ABI=0 -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --compiler-options '-fPIC' --expt-extended-lambda -std=c++11 -c /data_2/pytorch_project/PyTorch-Encoding/encoding/lib/gpu/encoding_kernel.cu -o encoding_kernel.cuda.o FAILED: encoding_kernel.cuda.o /usr/local/cuda-8.0/bin/nvcc -DTORCH_EXTENSION_NAME=enclib_gpu -DTORCH_API_INCLUDE_EXTENSION_H -isystem /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include -isystem /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include/torch/csrc/api/include -isystem /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include/TH -isystem /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include/THC -isystem /usr/local/cuda-8.0/include -isystem /data_2/Anaconda3/envs/pytorch1.0.0/include/python3.6m -D_GLIBCXX_USE_CXX11_ABI=0 -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --compiler-options '-fPIC' --expt-extended-lambda -std=c++11 -c /data_2/pytorch_project/PyTorch-Encoding/encoding/lib/gpu/encoding_kernel.cu -o encoding_kernel.cuda.o nvcc warning : The 'compute_20', 'sm_20', and 'sm_21' architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning). /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include/torch/csrc/jit/argument_spec.h(59): error: static assertion failed with "ArgumentInfo is to be a POD struct"

1 error detected in the compilation of "/tmp/tmpxft_00003cce_00000000-7_encoding_kernel.cpp1.ii". [5/7] /usr/local/cuda-8.0/bin/nvcc -DTORCH_EXTENSION_NAME=enclib_gpu -DTORCH_API_INCLUDE_EXTENSION_H -isystem /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include -isystem /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include/torch/csrc/api/include -isystem /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include/TH -isystem /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include/THC -isystem /usr/local/cuda-8.0/include -isystem /data_2/Anaconda3/envs/pytorch1.0.0/include/python3.6m -D_GLIBCXX_USE_CXX11_ABI=0 -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --compiler-options '-fPIC' --expt-extended-lambda -std=c++11 -c /data_2/pytorch_project/PyTorch-Encoding/encoding/lib/gpu/roi_align_kernel.cu -o roi_align_kernel.cuda.o FAILED: roi_align_kernel.cuda.o /usr/local/cuda-8.0/bin/nvcc -DTORCH_EXTENSION_NAME=enclib_gpu -DTORCH_API_INCLUDE_EXTENSION_H -isystem /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include -isystem /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include/torch/csrc/api/include -isystem /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include/TH -isystem /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include/THC -isystem /usr/local/cuda-8.0/include -isystem /data_2/Anaconda3/envs/pytorch1.0.0/include/python3.6m -D_GLIBCXX_USE_CXX11_ABI=0 -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --compiler-options '-fPIC' --expt-extended-lambda -std=c++11 -c /data_2/pytorch_project/PyTorch-Encoding/encoding/lib/gpu/roi_align_kernel.cu -o roi_align_kernel.cuda.o nvcc warning : The 'compute_20', 'sm_20', and 'sm_21' architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning). /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include/torch/csrc/jit/argument_spec.h(59): error: static assertion failed with "ArgumentInfo is to be a POD struct"

1 error detected in the compilation of "/tmp/tmpxft_00003cd2_00000000-7_roi_align_kernel.cpp1.ii". [6/7] /usr/local/cuda-8.0/bin/nvcc -DTORCH_EXTENSION_NAME=enclib_gpu -DTORCH_API_INCLUDE_EXTENSION_H -isystem /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include -isystem /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include/torch/csrc/api/include -isystem /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include/TH -isystem /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include/THC -isystem /usr/local/cuda-8.0/include -isystem /data_2/Anaconda3/envs/pytorch1.0.0/include/python3.6m -D_GLIBCXX_USE_CXX11_ABI=0 -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --compiler-options '-fPIC' --expt-extended-lambda -std=c++11 -c /data_2/pytorch_project/PyTorch-Encoding/encoding/lib/gpu/activation_kernel.cu -o activation_kernel.cuda.o FAILED: activation_kernel.cuda.o /usr/local/cuda-8.0/bin/nvcc -DTORCH_EXTENSION_NAME=enclib_gpu -DTORCH_API_INCLUDE_EXTENSION_H -isystem /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include -isystem /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include/torch/csrc/api/include -isystem /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include/TH -isystem /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include/THC -isystem /usr/local/cuda-8.0/include -isystem /data_2/Anaconda3/envs/pytorch1.0.0/include/python3.6m -D_GLIBCXX_USE_CXX11_ABI=0 -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --compiler-options '-fPIC' --expt-extended-lambda -std=c++11 -c /data_2/pytorch_project/PyTorch-Encoding/encoding/lib/gpu/activation_kernel.cu -o activation_kernel.cuda.o nvcc warning : The 'compute_20', 'sm_20', and 'sm_21' architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning). /data_2/Anaconda3/envs/pytorch1.0.0/lib/python3.6/site-packages/torch/lib/include/torch/csrc/jit/argument_spec.h(59): error: static assertion failed with "ArgumentInfo is to be a POD struct"

1 error detected in the compilation of "/tmp/tmpxft_00003ccc_00000000-7_activation_kernel.cpp1.ii". ninja: build stopped: subcommand failed.

opened by zhenxingsh 15
Can not pip install torch-encoding
my pythoch is 0.40, and when I use pip install torch-encoding, it went wrong like this:

Complete output from command python setup.py egg_info: fatal: Not a git repository (or any of the parent directories): .git error in torch-encoding setup command: '/tmp/pip-build-lhdbv8pg/torch-encoding/build.py' does not name an existing file

Command "python setup.py egg_info" failed with error code 1 in /tmp/pip-build-lhdbv8pg/torch-encoding/
enhancement
opened by irfanICMLL 15
Make compatible with pytorch 1.11 and newer; bugfix
The current version is incompatible with pytorch 1.11 and newer due to breaking changes.

Two commits feature in this PR

The first commit enables compatibility with newer pytorch versions (Issue #411)

https://github.com/zhanghang1989/PyTorch-Encoding/commit/45d5f8cc3d932faafd98f5b427b30800a2f667fd

THCudaCheck is deprecated https://github.com/pytorch/pytorch/pull/66391 in favour of C10_CUDA_CHECK

The other commit fixed this bug https://github.com/zhanghang1989/PyTorch-Encoding/commit/00167dc4b4338f332f74b9e0dda34a5cdb5f5e84

Missing "common.h" include

Tested this out, and it compiles and runs on pytorch 1.11 and 1.13
opened by krrish94 0
CVE-2007-4559 Patch

Patching CVE-2007-4559

Hi, we are security researchers from the Advanced Research Center at Trellix. We have began a campaign to patch a widespread bug named CVE-2007-4559. CVE-2007-4559 is a 15 year old bug in the Python tarfile package. By using extract() or extractall() on a tarfile object without sanitizing input, a maliciously crafted .tar file could perform a directory path traversal attack. We found at least one unsantized extractall() in your codebase and are providing a patch for you via pull request. The patch essentially checks to see if all tarfile members will be extracted safely and throws an exception otherwise. We encourage you to use this patch or your own solution to secure against CVE-2007-4559. Further technical information about the vulnerability can be found in this blog.

If you have further questions you may contact us through this projects lead researcher Kasimir Schulz.

opened by TrellixVulnTeam 0
Which index matches which class in ADE20k?
When I output with any model, I got probabilities per class on each pixel. E.g. when I run

model = encoding.models.get_model('DeepLab_ResNeSt101_ADE', pretrained=True).eval() img = torch.randn(1,3,256,256) output = model.evaluate(img) print(output.shape)

I got torch.Size([1, 150, 256, 256]), since there are 150 classes in ADE20k dataset.

However, I did not find anywhere in the code, which prediction of the output[0, :, x, y] corresponds to which of the 150 classes in ADE dataset. Where can I find list of classes?
opened by 8ToThePowerOfMol 0
What changes need to be made in this repo if I wanted to use this on CamVid dataset

Recently,I came across the paper Fast FCN in which the author uses the pytorch-encoding repository.In order to test their model on CamVid dataset,what changes should I make apart from writign the CamVid.py file in datasets.

opened by sparshgarg23 0
Package has issues with Pytorch 1.10

Hi,

As I was configuring different combinations of pytorch and CUDA I realized if your device's current nvvc version and torch's compiled cuda version differ- which is totally ok for torch itself since you can run any code on the new cuda 11.5 machines while torch lags behind at 11.3 - you will receive an error for mismatched versions for installing extensions through distutils and cppextensions.

Of course I realize reverting the torch version back to 1.9 is totally fine and you can easily install the package. Any plans for a change in the structure of extensions(Sorry I am not familiar how exactly you could bypass this mismatch issue).

opened by codtiger 2

Releases(v1.2.1)

v1.2.1(Jun 29, 2020)

Change model zoo to wasabi to save model
Source code(tar.gz)
Source code(zip)

v1.2.0(May 10, 2020)

ResNeSt

Split-Attention Network, A New ResNet Variant. It significantly boosts the performance of downstream models such as Mask R-CNN, Cascade R-CNN and DeepLabV3.

| | crop size | PyTorch | Gluon | |-------------|-----------|---------|-------| | ResNeSt-50 | 224 | 81.03 | 81.04 | | ResNeSt-101 | 256 | 82.83 | 82.81 | | ResNeSt-200 | 320 | 83.84 | 83.88 | | ResNeSt-269 | 416 | 84.54 | 84.53 |

Semantic Segmentation

PyTorch models and training: Please visit PyTorch Encoding Toolkit.
Training with Gluon: Please visit GluonCV Toolkit.

Results on ADE20K

Method	Backbone	pixAcc%	mIoU%
Deeplab-V3	ResNet-50	80.39	42.1
	ResNet-101	81.11	44.14
	ResNeSt-50 (ours)	81.17	45.12
	ResNeSt-101 (ours)	82.07	46.91
	ResNeSt-200 (ours)	82.45	48.36
	ResNeSt-269 (ours)	82.62	47.60

Source code(tar.gz)
Source code(zip)

v1.0.1(Mar 16, 2020)
Compatible with stable PyTorch 14..0.

Source code(tar.gz)
Source code(zip)
v1.0.0(Dec 17, 2018)
Compatible with stable PyTorch 1.0.

Inplace ABN with SyncBN.

ImageNet training script

Source code(tar.gz)
Source code(zip)
v0.4.3(Jun 15, 2018)
Segmentation examples and pretrained models.

Pypi install through pip install torch-encoding

Source code(tar.gz)
Source code(zip)
v0.1.0(Nov 20, 2017)

Make the compilation easier to the users.
Source code(tar.gz)
Source code(zip)
0.0.1(Oct 6, 2017)

Memory efficient implementation of Encoding Layer.
Source code(tar.gz)
Source code(zip)

A CV toolkit for my papers.

Related tags

Overview

PyTorch-Encoding

Citations

Comments

segmentation

recognition

Patching CVE-2007-4559

Releases(v1.2.1)

v1.2.1(Jun 29, 2020)

v1.2.0(May 10, 2020)

ResNeSt

Semantic Segmentation

Results on ADE20K

v1.0.1(Mar 16, 2020)

v1.0.0(Dec 17, 2018)

v0.4.3(Jun 15, 2018)

v0.1.0(Nov 20, 2017)

0.0.1(Oct 6, 2017)

Owner

Hang Zhang

Robustness via Cross-Domain Ensembles

Ludwig is a toolbox that allows to train and evaluate deep learning models without the need to write code.

CLUES: Few-Shot Learning Evaluation in Natural Language Understanding

This is an official implementation for "PlaneRecNet".

Open-World Entity Segmentation

(NeurIPS 2021) Pytorch implementation of paper "Re-ranking for image retrieval and transductive few-shot classification"

This repository is an implementation of our NeurIPS 2021 paper (Stylized Dialogue Generation with Multi-Pass Dual Learning) in PyTorch.

Towards Long-Form Video Understanding

Gesture-Volume-Control - This Python program can adjust the system's volume by using hand gestures

Orange Chicken: Data-driven Model Generalizability in Crosslinguistic Low-resource Morphological Segmentation

ESGD-M - A stochastic non-convex second order optimizer, suitable for training deep learning models, for PyTorch

Benchmarks for semi-supervised domain generalization.

Implementation of the paper NAST: Non-Autoregressive Spatial-Temporal Transformer for Time Series Forecasting.

Official code repository for ICCV 2021 paper: Gravity-Aware Monocular 3D Human Object Reconstruction

Code for Multimodal Neural SLAM for Interactive Instruction Following

alfred-py: A deep learning utility library for **human**

Data Consistency for Magnetic Resonance Imaging

vit for few-shot classification

Neural Contours: Learning to Draw Lines from 3D Shapes (CVPR2020)

This is the code of paper ``Contrastive Coding for Active Learning under Class Distribution Mismatch'' with python.

alfred-py: A deep learning utility library for human