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Deformable Convolutional Networks v2 with Pytorch

License: BSD 3-Clause "New" or "Revised" License

Python 20.05% Shell 0.03% Cuda 33.36% C 6.71% C++ 39.84%

cnn deformable-convolutional-networks pytorch

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dcnv2's Issues

RuntimeError: Jacobian mismatch for output 0 with respect to input 1

Does anyone have same issue? How to fix it?

What is deformable group?

Hello
Thanks for your great implementation.
I have a question regarding the deformable group variable ?
I am not sure what exactly is useful for?
I appreciate your guide. Thanks

正在创建库 build\temp.win-amd64-3.7\Release\Users\anymy\Desktop\DCNv2-master\src_ext.cp37-win_amd64.lib 和对象 build\temp.win-amd64-3.7\Release\Users\anymy\Desktop\DCNv2-master\src_ext.cp37-win_amd64.exp
dcn_v2_cuda.obj : error LNK2001: 无法解析的外部符号 "struct THCState * state" (?state@@3PEAUTHCState@@ea)
build\lib.win-amd64-3.7_ext.cp37-win_amd64.pyd : fatal error LNK1120: 1 个无法解析的外部命令
error: command 'C:\Program Files (x86)\Microsoft Visual Studio\2017\Community\VC\Tools\MSVC\14.16.27023\bin\HostX86\x64\link.exe' failed with exit status 1120

python test.py Segment error (vomiting)

cffi.VerificationError: LinkError: command 'gcc' failed with exit status 1

I followed all the instruction from this link https://github.com/xingyizhou/CenterNet/blob/master/readme/INSTALL.md

But I m getting this error while "./make.sh"

cffi.VerificationError: LinkError: command 'gcc' failed with exit status 1

system info.:-
ubuntu 18.04
rtx 2080ti
anconda version = conda 4.8.1
cuda 10.1
pytorch version = 0.4.0/0.4.1

fatal error: cuda_runtime_api.h: No such file or directory

python=3.6
pytorch=1.0.0
cuda=10.0

when running make.sh, give this error message:

ModuleNotFoundError: No module named '_ext'

When i run the dcn_v2.py,a problem has occured : 'ModuleNotFoundError: No module named '_ext' ' .
the code in dcn_v2.py writes : import _ext as _backend,however i can't find a file named _ext.How to solve it?

Onnx support

Will there be onnx support for this? I'm currently unable to convert my model to onnx because of no support for DCNv2

Thanks.

No module named _ext in dcn_v2.py

When I successful sh 'make.sh', I got this import error , is there anyone who have met the same problem before?

meet error when compiling

I got "invalid command name develop". It seems that the develop option does not work

Jacobian mismatch for output 0 with respect to input 1

Zero offset passed
/usr/local/lib/python3.6/dist-packages/torch/autograd/gradcheck.py:216: UserWarning: At least one of the inputs that requires gradient is not of double precision floating point. This check will likely fail if all the inputs are not of double precision floating point. 
  'At least one of the inputs that requires gradient '
check_gradient_dpooling: True
Traceback (most recent call last):
  File "test.py", line 265, in <module>
    check_gradient_dconv()
  File "test.py", line 97, in check_gradient_dconv
    eps=1e-3, atol=1e-4, rtol=1e-2))
  File "/usr/local/lib/python3.6/dist-packages/torch/autograd/gradcheck.py", line 263, in gradcheck
    'numerical:%s\nanalytical:%s\n' % (i, j, n, a))
  File "/usr/local/lib/python3.6/dist-packages/torch/autograd/gradcheck.py", line 201, in fail_test
    raise RuntimeError(msg)
RuntimeError: Jacobian mismatch for output 0 with respect to input 1,

DCNv2 Tensorflow

Is it possible to use it with tensorflow ?

error in modulated_deformable_im2col_cuda: invalid device function

I compile it success, but when I use this api, I encounter the problem.
Do anyone can figure it?
I use pytorch1.3 cuda10.0 RTX2080Ti ubuntu18.06

pytorch 1.3 test error

in build progress warning this message：
/home/chenjun/Deformable-Convolution-V2-PyTorch-pytorch_1.0.0/src/cuda/deform_conv_cuda.cu:219:2309: warning: 鈥[01mT* at::Tensor::data() const [with T = float]鈥is deprecated [-Wdeprecated-declarations]
/home/chenjun/anaconda3/envs/torch13/lib/python3.7/site-packages/torch/include/ATen/core/TensorBody.h:303:1: note: declared here
when run test.py:
ImportError: /home/chenjun/anaconda3/envs/torch13/lib/python3.7/site-packages/DCN-1.0-py3.7-linux-x86_64.egg/DCN.cpython-37m-x86_64-linux-gnu.so: undefined symbol: cudaSetupArgument

Purpose of 'THCudaBlas_SgemmBatched' calls

In the 'dcn_v2_cuda_forward' function, I see two calls to 'THCudaBlas_SgemmBatched' function, one before and one after kernel call to 'modulated_deformable_im2col_cuda'. Can anybody, please explain the purpose of these calls. I am unable to find a clear description of this function. I tracked the function definition to here:

https://github.com/pytorch/pytorch/blob/master/aten/src/THC/THCBlas.cu

But, then again there is no description or comments as to why it is required twice. Any help in this regards is greatly appreciated.

3D Deformable Conv.....

Could you please write a 3D version of deformable convolution ... I am dealing with medical data which require 3D conv but my modified 3D deformable conv from your code can not pass gradient check if threshold is small.

cant compile on windows 10

Creating library build\temp.win-amd64-3.6\Release\Users\user\yolact\yolact\external\DCNv2\src_ext.cp36-win_amd64.lib and object build\temp.win-amd64-3.6\Release\Users\user\yolact\yolact\external\DCNv2\src_ext.cp36-win_amd64.exp
dcn_v2_cuda.obj : error LNK2001: unresolved external symbol "struct THCState * state" (?state@@3PEAUTHCState@@ea)
build\lib.win-amd64-3.6_ext.cp36-win_amd64.pyd : fatal error LNK1120: 1 unresolved externals
error: command 'C:\Program Files (x86)\Microsoft Visual Studio\2017\Community\VC\Tools\MSVC\14.16.27023\bin\HostX86\x64\link.exe' failed with exit status 1120

is it possible to make conv_offset_mask conv shared when using groups != 1, i.e., when using group convolution.

@CharlesShang

Segmentation Fault when testing

I successfully built up the dependencies but failed in test phase, anyone knows what caused this?
`Installed /home/yuankunhao/DCNv2

Processing dependencies for DCNv2==0.1

Finished processing dependencies for DCNv2==0.1

(yuankunhao) [root@localhost DCNv2]# python test.py

Segmentation fault

(yuankunhao) [root@localhost DCNv2]# python test.py

Segmentation fault
`

ImportError:~/DCNv2/_ext/dcn_v2/_dcn_v2.so: undefined symbol: THCudaTensor__nDimension

After I have runned '. mask.sh', and then 'python test.py', This error produced.Why?

failed in inference on non-default gpu

the centernet project uses this DCNv2( pytorch 0.4 version)
as I compiled DCNv2( pytorch 1.0 version) and use it in the centernet project,it also works fine.
things goes well as i only run it on gpu 0

but,strange bug happened when i tried to use model inference on different gpu.
say i wrote code like this:
...
torch.cuda.synchronize()
model = centernet_model.to( 1 ) # not on gpu 0
x = x.to( 1 )
y = model(x)
torch.cuda.synchronize()
...

firstly, there would be error says" illegal memory access torch.cuda.synchronize()"

well, if i remove the all the synchronize function
this code would run as usual for about 10 images,
then suddenly it got a cuda runtime error says:

"GPU program failed to execute at /pytorch/aten/src/THC/THCBlas.cu:416"

as the author of centernet developed his project in py0.4 enviroment, i decided to change to another machine and set-up all the pytorch0.4 env, and compile DCNv2 pytorch0.4 version.

Still, everything works fine except try to inference on a non-default gpu.
but this time,the error message is "argument not on same gpu".

and the error message is from dcn_v2_cuda.c:20

this problem really drived me mad, and i realy don't know where the bug is. is it here(DCNv2),or is it in the centernet project.

Failed to import DCNv2 module

ImportError: Failed to import DCNv2 module.

[Solved] dcn_v2_cuda.obj : error LNK2001: unresolved external symbol state caused by extern THCState *state;

First thank you for your job.

When compiling the DCNv2 on Win10 with Pytorch 1.0.1 using make.sh, error occurs at the last step:

dcn_v2_cuda.obj : error LNK2001: unresolved external symbol state caused by extern THCState *state;

The original error info is in Chinese:

... 
C:\Program Files (x86)\Microsoft Visual Studio 14.0\VC\BIN\x86_amd64\link.exe /nologo /INCREMENTAL:NO /LTCG /DLL /MANIFEST:EMBED,ID=2 /MANIFESTUAC:NO /LIBPATH:D:\Programs\Python\Python37\lib\site-packages\torch\lib /LIBPATH:D:\Programs\Nvidia\CudaToolkit\v10.1\lib/x64 /LIBPATH:D:\Programs\Python\Python37\libs /LIBPATH:D:\Programs\Python\Python37\PCbuild\amd64 "/LIBPATH:C:\Program Files (x86)\Microsoft Visual Studio 14.0\VC\LIB\amd64" "/LIBPATH:C:\Program Files (x86)\Microsoft Visual Studio 14.0\VC\ATLMFC\LIB\amd64" "/LIBPATH:C:\Program Files (x86)\Windows Kits\10\lib\10.0.17763.0\ucrt\x64" "/LIBPATH:C:\Program Files (x86)\Windows Kits\10\lib\10.0.17763.0\um\x64" cudart.lib c10.lib caffe2.lib torch.lib torch_python.lib caffe2_gpu.lib _C.lib /EXPORT:PyInit__ext build\temp.win-amd64-3.7\Release\Projects\Python\201904\centernet\CenterNet-master\src\lib\models\networks\DCNv2\src\vision.obj build\temp.win-amd64-3.7\Release\Projects\Python\201904\centernet\CenterNet-master\src\lib\models\networks\DCNv2\src\cpu\dcn_v2_cpu.obj build\temp.win-amd64-3.7\Release\Projects\Python\201904\centernet\CenterNet-master\src\lib\models\networks\DCNv2\src\cuda\dcn_v2_cuda.obj build\temp.win-amd64-3.7\Release\Projects\Python\201904\centernet\CenterNet-master\src\lib\models\networks\DCNv2\src\cuda\dcn_v2_im2col_cuda.obj build\temp.win-amd64-3.7\Release\Projects\Python\201904\centernet\CenterNet-master\src\lib\models\networks\DCNv2\src\cuda\dcn_v2_psroi_pooling_cuda.obj /OUT:build\lib.win-amd64-3.7\_ext.cp37-win_amd64.pyd /IMPLIB:build\temp.win-amd64-3.7\Release\Projects\Python\201904\centernet\CenterNet-master\src\lib\models\networks\DCNv2\src\_ext.cp37-win_amd64.lib
vision.obj : warning LNK4197: 多次指定导出“PyInit__ext”；使用第一个规范
  正在创建库 build\temp.win-amd64-3.7\Release\Projects\Python\201904\centernet\CenterNet-master\src\lib\models\networks\DCNv2\src\_ext.cp37-win_amd64.lib 和对象 build\temp.win-amd64-3.7\Release\Projects\Python\201904\centernet\CenterNet-master\src\lib\models\networks\DCNv2\src\_ext.cp37-win_amd64.exp
dcn_v2_cuda.obj : error LNK2001: 无法解析的外部符号 "struct THCState * state" (?state@@3PEAUTHCState@@EA)
build\lib.win-amd64-3.7\_ext.cp37-win_amd64.pyd : fatal error LNK1120: 1 个无法解析的外部命令
error: command 'C:\\Program Files (x86)\\Microsoft Visual Studio 14.0\\VC\\BIN\\x86_amd64\\link.exe' failed with exit status 1120

I want to know: does DCNv2 support Pytorch 1.0.1 + Cuda 10.1 + Win10 64 ?

The installation script should be more generic

I think it is better to make the installation script move the file into python site-packages and make the library available for the system
if I run the build command from inside the repo then deleted the repo folder the DCN will not be available anymore

Model url dosn't exist

The script is trying to download the model from the following link:
http://dl.yf.io/dla/models/imagenet/dla34-ba72cf86.pth

But the address doesn't exist. Any other versions of the link?

RuntimeError: Backward is not reentrant, i.e., running backward with same input and grad_output multiple times gives different values, although analytical gradient matches numerical gradient

HI, I encountered this problem, could anyone help me out here, thks :-)

xxzx@DeskPC:~/Desktop/DCNv2$ python3 test.py 
torch.Size([2, 64, 128, 128])
torch.Size([20, 32, 7, 7])
torch.Size([20, 32, 7, 7])
torch.Size([20, 32, 7, 7])
0.971507, 1.943014
0.971507, 1.943014
Zero offset passed
/usr/local/lib/python3.5/dist-packages/torch/autograd/gradcheck.py:170: UserWarning: At least one of the inputs that requires gradient is not of double precision floating point. This check will likely fail if all the inputs are not of double precision floating point. 
  'At least one of the inputs that requires gradient '
check_gradient_dpooling: True
Traceback (most recent call last):
  File "test.py", line 265, in <module>
    check_gradient_dconv()
  File "test.py", line 97, in check_gradient_dconv
    eps=1e-3, atol=1e-4, rtol=1e-2))
  File "/usr/local/lib/python3.5/dist-packages/torch/autograd/gradcheck.py", line 208, in gradcheck
    return fail_test('Backward is not reentrant, i.e., running backward with same '
  File "/usr/local/lib/python3.5/dist-packages/torch/autograd/gradcheck.py", line 185, in fail_test
    raise RuntimeError(msg)
RuntimeError: Backward is not reentrant, i.e., running backward with same input and grad_output multiple times gives different values, although analytical gradient matches numerical gradient

There are two issues in latest pytorch. Does someone modify the project in latest pytorch?

When I do ./make.sh, I got two issues:

ImportError: torch.utils.ffi is deprecated. Please use cpp extensions instead.
It only change the from torch.utils.ffi import create_extension to from torch.utils.cpp_extension import BuildExtension.
And then change the call ffi = create_extension(...) to ffi = BuildExtension(...).
TypeError: dist must be a Distribution instance
This problem I can't solve it, sadly.

Segmentation fault (core dumped)

My current environment is : Python 3.6+ Pytorch 1.2.0+ Cuda 10.0 + CentOS 7.
I compile the code successfully but when I run the test.py, the command line returns the Segmentation fault (core dumped) error. Could you help me?

pytorch_0.4 ,compile error: dcn_v2_im2col_cuda_double.cu(248): error: no instance of overloaded function "atomicAdd" matches the argument list argument types are: (double *, double)

@CharlesShang Thank you for your code , when I run make.sh error produced as follows:

dcn_v2_im2col_cuda_double.cu(248): error: no instance of overloaded function "atomicAdd" matches the argument list
argument types are: (double *, double)

1 error detected in the compilation of "/tmp/tmpxft_00002005_00000000-5_dcn_v2_im2col_cuda_double.cpp4.ii".
dcn_v2_psroi_pooling_cuda_double.cu(247): error: no instance of overloaded function "atomicAdd" matches the argument list
argument types are: (double *, double)

dcn_v2_psroi_pooling_cuda_double.cu(248): error: no instance of overloaded function "atomicAdd" matches the argument list
argument types are: (double *, double)

dcn_v2_psroi_pooling_cuda_double.cu(249): error: no instance of overloaded function "atomicAdd" matches the argument list
argument types are: (double *, double)

dcn_v2_psroi_pooling_cuda_double.cu(250): error: no instance of overloaded function "atomicAdd" matches the argument list
argument types are: (double *, double)

dcn_v2_psroi_pooling_cuda_double.cu(265): error: no instance of overloaded function "atomicAdd" matches the argument list
argument types are: (double *, double)

dcn_v2_psroi_pooling_cuda_double.cu(266): error: no instance of overloaded function "atomicAdd" matches the argument list
argument types are: (double *, double)

6 errors detected in the compilation of "/tmp/tmpxft_00002154_00000000-5_dcn_v2_psroi_pooling_cuda_double.cpp4.ii".

Apex training not supported !

When I try to apply apex for mix-precision training , error appears as follow"

expected scalar type Float but found Half (data<float> at /home/bit530/anaconda3/envs/torch1.1/lib/python3.7/site-packages/torch/include/ATen/core/TensorMethods.h:1821)

thus I convert all variable to type torch.float16 , but it doesn't work.
It seems that your variable define in cuda source code restricts input to be float32 type, right?

int matrices_size = batch * sizeof(float *);
    auto input_b = static_cast<const float **>(THCudaMalloc(state, matrices_size));
    auto output_b = static_cast<float **>(THCudaMalloc(state, matrices_size));
    auto columns_b = static_cast<float **>(THCudaMalloc(state, matrices_size));
    auto ones_b = static_cast<const float **>(THCudaMalloc(state, matrices_size));
    auto weight_b = static_cast<const float **>(THCudaMalloc(state, matrices_size));
    auto bias_b = static_cast<const float **>(THCudaMalloc(state, matrices_size));

fatal error: cusparse.h: No such file or directory

Hello. I run your code with pytorch1.0.1. When I run ./make.sh, it tells me fatal error: cusparse.h: No such file or directory. I think I've correctly installed the pytorch. Is there anyone encountered the same problem?

PyTorch 1.4 support

I got the same error when compiling as in #44 . Maybe because I'm using PyTorch 1.4? Anayways, I have a fix for it, will create a PR.

My system:

Windows 7
Visual Studio 2017
Anaconda Python 3.7
Cuda 10.0
PyTorch 1.4

Can‘t compiled on Win10_64？

platform: win10 64, python 3.6, pytorch 1.0.0

I met the following error, can you give me some advice?

D:\YX\python\pytorch_projects\C_Extension\DCNv2-master_1.0\DCNv2-master>python setup.py install
running install
running bdist_egg
running egg_info
creating DCNv2.egg-info
writing DCNv2.egg-info\PKG-INFO
writing dependency_links to DCNv2.egg-info\dependency_links.txt
writing top-level names to DCNv2.egg-info\top_level.txt
writing manifest file 'DCNv2.egg-info\SOURCES.txt'
reading manifest file 'DCNv2.egg-info\SOURCES.txt'
writing manifest file 'DCNv2.egg-info\SOURCES.txt'
installing library code to build\bdist.win-amd64\egg
running install_lib
running build_ext
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\utils\cpp_extension.py:184: UserWarning: Error checking compiler version for cl: [WinError 2] 系统找不到指定的文件。
warnings.warn('Error checking compiler version for {}: {}'.format(compiler, error))
building 'ext' extension
creating build
creating build\temp.win-amd64-3.6
creating build\temp.win-amd64-3.6\Release
creating build\temp.win-amd64-3.6\Release\YX
creating build\temp.win-amd64-3.6\Release\YX\python
creating build\temp.win-amd64-3.6\Release\YX\python\pytorch_projects
creating build\temp.win-amd64-3.6\Release\YX\python\pytorch_projects\C_Extension
creating build\temp.win-amd64-3.6\Release\YX\python\pytorch_projects\C_Extension\DCNv2-master_1.0
creating build\temp.win-amd64-3.6\Release\YX\python\pytorch_projects\C_Extension\DCNv2-master_1.0\DCNv2-master
creating build\temp.win-amd64-3.6\Release\YX\python\pytorch_projects\C_Extension\DCNv2-master_1.0\DCNv2-master\src
creating build\temp.win-amd64-3.6\Release\YX\python\pytorch_projects\C_Extension\DCNv2-master_1.0\DCNv2-master\src\cpu
creating build\temp.win-amd64-3.6\Release\YX\python\pytorch_projects\C_Extension\DCNv2-master_1.0\DCNv2-master\src\cuda
C:\Program Files (x86)\Microsoft Visual Studio 14.0\VC\BIN\x86_amd64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -DWITH_CUDA -ID:\YX\python\pytorch_projects\C_Extension\DCNv2-master_1.0\DCNv2-master\src -IC:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include -IC:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include -IC:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\TH -IC:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\THC "-IC:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v9.0\include" -IG:\python\anaconda3\include -IG:\python\anaconda3\include "-IC:\Program Files (x86)\Microsoft Visual Studio 14.0\VC\INCLUDE" "-IC:\Program Files (x86)\Microsoft Visual Studio 14.0\VC\ATLMFC\INCLUDE" "-IC:\Program Files (x86)\Windows Kits\10\include\10.0.10240.0\ucrt" "-IC:\Program Files (x86)\Windows Kits\NETFXSDK\4.6.1\include\um" "-IC:\Program Files (x86)\Windows Kits\8.1\include\shared" "-IC:\Program Files (x86)\Windows Kits\8.1\include\um" "-IC:\Program Files (x86)\Windows Kits\8.1\include\winrt" /EHsc /TpD:\YX\python\pytorch_projects\C_Extension\DCNv2-master_1.0\DCNv2-master\src\vision.cpp /Fobuild\temp.win-amd64-3.6\Release\YX\python\pytorch_projects\C_Extension\DCNv2-master_1.0\DCNv2-master\src\vision.obj -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=ext -D_GLIBCXX_USE_CXX11_ABI=0
vision.cpp
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/util/Exception.h(27): warning C4275: 非 dll 接口 class“std::exception”用作 dll 接口 class“c10::Error”的基
C:\Program Files (x86)\Microsoft Visual Studio 14.0\VC\INCLUDE\vcruntime_exception.h(43): note: 参见“std::exception”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/util/Exception.h(27): note: 参见“c10::Error”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/util/Exception.h(28): warning C4251: “c10::Error::msg_stack”: class“std::vector<std::string,std::allocator<Ty>>”需要有 dll 接口由 class“c10::Error”的客户端使用
with
[
Ty=std::string
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/util/Exception.h(28): note: 参见“std::vector<std::string,std::allocator<Ty>>”的声明
with
[
Ty=std::string
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/util/Exception.h(29): warning C4251: “c10::Error::backtrace”: class“std::basic_string<char,std::char_traits,std::allocator>”需要有 dll 接口由 class“c10::Error”的客户端使用
C:\Program Files (x86)\Microsoft Visual Studio 14.0\VC\INCLUDE\xstring(2633): note: 参见“std::basic_string<char,std::char_traits,std::allocator>”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/util/Exception.h(34): warning C4251: “c10::Error::msg”: class“std::basic_string<char,std::char_traits,std::allocator>”需要有 dll 接口由 class“c10::Error”的客户端使用
C:\Program Files (x86)\Microsoft Visual Studio 14.0\VC\INCLUDE\xstring(2633): note: 参见“std::basic_string<char,std::char_traits,std::allocator>”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/util/Exception.h(35): warning C4251: “c10::Error::msg_without_backtrace”: class“std::basic_string<char,std::char_traits,std::allocator>”需要有 dll 接口由 class“c10::Error”的客户端使用
C:\Program Files (x86)\Microsoft Visual Studio 14.0\VC\INCLUDE\xstring(2633): note: 参见“std::basic_string<char,std::char_traits,std::allocator>”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/core/Allocator.h(126): warning C4251: “c10::InefficientStdFunctionContext::ptr”: class“std::unique_ptr<void,std::function<void (void *)>>”需要有 dll 接口由 struct“c10::InefficientStdFunctionContext”的客户端使用
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/core/Allocator.h(126): note: 参见“std::unique_ptr<void,std::function<void (void *)>>”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/core/TensorTypeIdRegistration.h(32): warning C4251: “c10::TensorTypeIdCreator::last_id”: struct“std::atomic”需要有 dll 接口由 class“c10::TensorTypeIdCreator”的客户端使用
C:\Program Files (x86)\Microsoft Visual Studio 14.0\VC\INCLUDE\xxatomic(180): note: 参见“std::atomic”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/core/TensorTypeIdRegistration.h(45): warning C4251: “c10::TensorTypeIdRegistry::registeredTypeIds_”: class“std::unordered_set<c10::TensorTypeId,std::hashc10::TensorTypeId,std::equal_to<Kty>,std::allocator<Kty>>”需要有 dll 接口由 class“c10::TensorTypeIdRegistry”的客户端使用
with
[
Kty=c10::TensorTypeId
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/core/TensorTypeIdRegistration.h(45): note: 参见“std::unordered_set<c10::TensorTypeId,std::hashc10::TensorTypeId,std::equal_to<Kty>,std::allocator<Kty>>”的声明
with
[
Kty=c10::TensorTypeId
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/core/TensorTypeIdRegistration.h(46): warning C4251: “c10::TensorTypeIdRegistry::mutex”: class“std::mutex”需要有 dll 接口由 class“c10::TensorTypeIdRegistry”的客户端使用
C:\Program Files (x86)\Microsoft Visual Studio 14.0\VC\INCLUDE\mutex(78): note: 参见“std::mutex”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/Half-inl.h(168): warning C4244: “参数”: 从“int”转换到“float”，可能丢失数据
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/Half-inl.h(171): warning C4244: “参数”: 从“int”转换到“float”，可能丢失数据
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/Half-inl.h(174): warning C4244: “参数”: 从“int”转换到“float”，可能丢失数据
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/Half-inl.h(177): warning C4244: “参数”: 从“int”转换到“float”，可能丢失数据
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/Half-inl.h(181): warning C4244: “参数”: 从“int”转换到“float”，可能丢失数据
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/Half-inl.h(184): warning C4244: “参数”: 从“int”转换到“float”，可能丢失数据
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/Half-inl.h(187): warning C4244: “参数”: 从“int”转换到“float”，可能丢失数据
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/Half-inl.h(190): warning C4244: “参数”: 从“int”转换到“float”，可能丢失数据
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/Half-inl.h(196): warning C4244: “参数”: 从“int64_t”转换到“float”，可能丢失数据
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/Half-inl.h(199): warning C4244: “参数”: 从“int64_t”转换到“float”，可能丢失数据
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/Half-inl.h(202): warning C4244: “参数”: 从“int64_t”转换到“float”，可能丢失数据
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/Half-inl.h(205): warning C4244: “参数”: 从“int64_t”转换到“float”，可能丢失数据
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/Half-inl.h(209): warning C4244: “参数”: 从“int64_t”转换到“float”，可能丢失数据
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/Half-inl.h(212): warning C4244: “参数”: 从“int64_t”转换到“float”，可能丢失数据
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/Half-inl.h(215): warning C4244: “参数”: 从“int64_t”转换到“float”，可能丢失数据
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/Half-inl.h(218): warning C4244: “参数”: 从“int64_t”转换到“float”，可能丢失数据
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/util/typeid.h(433): warning C4068: 未知的杂注
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/util/typeid.h(434): warning C4068: 未知的杂注
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/util/typeid.h(435): warning C4068: 未知的杂注
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/util/typeid.h(436): warning C4068: 未知的杂注
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/util/typeid.h(438): warning C4068: 未知的杂注
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/util/intrusive_ptr.h(58): warning C4251: “c10::intrusive_ptr_target::refcount”: struct“std::atomic”需要有 dll 接口由 class“c10::intrusive_ptr_target”的客户端使用
C:\Program Files (x86)\Microsoft Visual Studio 14.0\VC\INCLUDE\xxatomic(180): note: 参见“std::atomic ”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/util/intrusive_ptr.h(59): warning C4251: “c10::intrusive_ptr_target::weakcount”: struct“std::atomic”需要有 dll 接口由 class“c10::intrusive_ptr_target”的客户端使用
C:\Program Files (x86)\Microsoft Visual Studio 14.0\VC\INCLUDE\xxatomic(180): note: 参见“std::atomic ”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/util/intrusive_ptr.h(75): warning C4068: 未知的杂注
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/util/intrusive_ptr.h(76): warning C4068: 未知的杂注
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/util/intrusive_ptr.h(77): warning C4068: 未知的杂注
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/util/intrusive_ptr.h(78): warning C4068: 未知的杂注
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/util/intrusive_ptr.h(79): warning C4068: 未知的杂注
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/util/intrusive_ptr.h(86): warning C4068: 未知的杂注
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/util/intrusive_ptr.h(80): warning C4297: “c10::intrusive_ptr_target::~intrusive_ptr_target”: 假定函数不引发异常，但确实发生了
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/util/intrusive_ptr.h(80): note: 析构函数或释放器具有一个(可能是隐含的)非引发异常规范
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/util/intrusive_ptr.h(83): warning C4297: “c10::intrusive_ptr_target::~intrusive_ptr_target”: 假定函数不引发异常，但确实发生了
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/util/intrusive_ptr.h(83): note: 析构函数或释放器具有一个(可能是隐含的)非引发异常规范
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/util/intrusive_ptr.h(699): warning C4267: “return”: 从“size_t”转换到“uint32_t”，可能丢失数据
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/util/intrusive_ptr.h(733): warning C4267: “return”: 从“size_t”转换到“uint32_t”，可能丢失数据
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/core/StorageImpl.h(215): warning C4251: “c10::StorageImpl::data_ptr”: class“c10::DataPtr”需要有 dll 接口由 struct“c10::StorageImpl”的客户端使用
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/core/Allocator.h(19): note: 参见“c10::DataPtr”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/core/Storage.h(184): warning C4251: “c10::Storage::storage_impl”: class“c10::intrusive_ptr<c10::StorageImpl,c10::detail::intrusive_target_default_null_type>”需要有 dll 接口由 struct“c10::Storage”的客户端使用
with
[
TTarget=c10::StorageImpl
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/core/Storage.h(10): note: 参见“c10::intrusive_ptr<c10::StorageImpl,c10::detail::intrusive_target_default_null_type>”的声明
with
[
TTarget=c10::StorageImpl
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/util/logging_is_not_google_glog.h(47): warning C4251: “c10::MessageLogger::stream”: class“std::basic_stringstream<char,std::char_traits,std::allocator>”需要有 dll 接口由 class“c10::MessageLogger”的客户端使用
C:\Program Files (x86)\Microsoft Visual Studio 14.0\VC\INCLUDE\iosfwd(687): note: 参见“std::basic_stringstream<char,std::char_traits,std::allocator>”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/TensorImpl.h(115): warning C4251: “at::PlacementDeleteContext::data_ptr_”: class“c10::DataPtr”需要有 dll 接口由 struct“at::PlacementDeleteContext”的客户端使用
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/core/Allocator.h(19): note: 参见“c10::DataPtr”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/TensorImpl.h(1434): warning C4251: “at::TensorImpl::sizes_”: class“c10::SmallVector<int64_t,5>”需要有 dll 接口由 struct“at::TensorImpl”的客户端使用
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/TensorImpl.h(1434): note: 参见“c10::SmallVector<int64_t,5>”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/TensorImpl.h(1435): warning C4251: “at::TensorImpl::strides_”: class“c10::SmallVector<int64_t,5>”需要有 dll 接口由 struct“at::TensorImpl”的客户端使用
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/TensorImpl.h(1434): note: 参见“c10::SmallVector<int64_t,5>”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/TensorImpl.h(454): warning C4244: “参数”: 从“int64_t”转换到“c10::DeviceIndex”，可能丢失数据
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/TensorImpl.h(1006): warning C4244: “参数”: 从“float”转换到“const std::size_t”，可能丢失数据
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/TensorImpl.h(1382): warning C4244: “初始化”: 从“int64_t”转换到“int”，可能丢失数据
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/LegacyTypeDispatch.h(138): warning C4251: “at::LegacyTypeDispatch::type_registry”: class“std::unique_ptrat::Type,at::LegacyTypeDeleter”需要有 dll 接口由 class“at::LegacyTypeDispatch”的客户端使用
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/LegacyTypeDispatch.h(51): note: 参见“std::unique_ptrat::Type,at::LegacyTypeDeleter”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/Tensor.h(692): warning C4251: “at::Tensor::impl_”: class“c10::intrusive_ptrat::TensorImpl,at::UndefinedTensorImpl”需要有 dll 接口由 class“at::Tensor”的客户端使用
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/Tensor.h(44): note: 参见“c10::intrusive_ptrat::TensorImpl,at::UndefinedTensorImpl”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/Tensor.h(693): warning C4522: “at::Tensor”: 指定了多个赋值运算符
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/Tensor.h(720): warning C4251: “at::WeakTensor::weak_impl_”: class“c10::weak_intrusive_ptr<TTarget,NullType>”需要有 dll 接口由 struct“at::WeakTensor”的客户端使用
with
[
TTarget=at::TensorImpl,
NullType=at::UndefinedTensorImpl
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/util/intrusive_ptr.h(163): note: 参见“c10::weak_intrusive_ptr<TTarget,NullType>”的声明
with
[
TTarget=at::TensorImpl,
NullType=at::UndefinedTensorImpl
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/LegacyTHDispatch.h(86): warning C4251: “at::LegacyTHDispatch::dispatcher_registry”: class“std::unique_ptrat::LegacyTHDispatcher,at::LegacyTHDispatcherDeleter”需要有 dll 接口由 class“at::LegacyTHDispatch”的客户端使用
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/LegacyTHDispatch.h(61): note: 参见“std::unique_ptrat::LegacyTHDispatcher,at::LegacyTHDispatcherDeleter”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/Context.h(128): warning C4251: “at::Context::generator_registry”: class“std::unique_ptr<at::Generator,std::default_delete<_Ty>>”需要有 dll 接口由 class“at::Context”的客户端使用
with
[
_Ty=at::Generator
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/Type.h(104): note: 参见“std::unique_ptr<at::Generator,std::default_delete<_Ty>>”的声明
with
[
Ty=at::Generator
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/Context.h(145): warning C4251: “at::Context::thc_init”: struct“std::once_flag”需要有 dll 接口由 class“at::Context”的客户端使用
C:\Program Files (x86)\Microsoft Visual Studio 14.0\VC\INCLUDE\mutex(452): note: 参见“std::once_flag”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/Context.h(146): warning C4251: “at::Context::thh_init”: struct“std::once_flag”需要有 dll 接口由 class“at::Context”的客户端使用
C:\Program Files (x86)\Microsoft Visual Studio 14.0\VC\INCLUDE\mutex(452): note: 参见“std::once_flag”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/Context.h(147): warning C4251: “at::Context::complex_init”: struct“std::once_flag”需要有 dll 接口由 class“at::Context”的客户端使用
C:\Program Files (x86)\Microsoft Visual Studio 14.0\VC\INCLUDE\mutex(452): note: 参见“std::once_flag”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/Context.h(151): warning C4251: “at::Context::next_id”: struct“std::atomic”需要有 dll 接口由 class“at::Context”的客户端使用
C:\Program Files (x86)\Microsoft Visual Studio 14.0\VC\INCLUDE\xxatomic(180): note: 参见“std::atomic ”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/Context.h(152): warning C4251: “at::Context::thc_state”: class“std::unique_ptr<THCState,void (__cdecl *)(THCState *)>”需要有 dll 接口由 class“at::Context”的客户端使用
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/detail/CUDAHooksInterface.h(57): note: 参见“std::unique_ptr<THCState,void (__cdecl *)(THCState *)>”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/Context.h(153): warning C4251: “at::Context::thh_state”: class“std::unique_ptr<THHState,void (__cdecl *)(THHState *)>”需要有 dll 接口由 class“at::Context”的客户端使用
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/detail/HIPHooksInterface.h(33): note: 参见“std::unique_ptr<THHState,void (__cdecl *)(THHState *)>”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/Context.h(161): warning C4996: 'getenv': This function or variable may be unsafe. Consider using _dupenv_s instead. To disable deprecation, use _CRT_SECURE_NO_WARNINGS. See online help for details.
C:\Program Files (x86)\Windows Kits\10\include\10.0.10240.0\ucrt\stdlib.h(1183): note: 参见“getenv”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/Context.h(164): warning C4996: 'getenv': This function or variable may be unsafe. Consider using _dupenv_s instead. To disable deprecation, use _CRT_SECURE_NO_WARNINGS. See online help for details.
C:\Program Files (x86)\Windows Kits\10\include\10.0.10240.0\ucrt\stdlib.h(1183): note: 参见“getenv”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/Stream.h(102): warning C4244: “参数”: 从“unsigned __int64”转换到“c10::DeviceIndex”，可能丢失数据
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/Stream.h(102): warning C4244: “参数”: 从“unsigned _int64”转换到“c10::StreamId”，可能丢失数据
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/TensorGeometry.h(56): warning C4251: “at::TensorGeometry::sizes”: class“std::vector<int64_t,std::allocator<_Ty>>”需要有 dll 接口由 struct“at::TensorGeometry”的客户端使用
with
[
_Ty=int64_t
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/util/typeid.h(580): note: 参见“std::vector<int64_t,std::allocator<_Ty>>”的声明
with
[
Ty=int64_t
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/TensorGeometry.h(57): warning C4251: “at::TensorGeometry::strides”: class“std::vector<int64_t,std::allocator<Ty>>”需要有 dll 接口由 struct“at::TensorGeometry”的客户端使用
with
[
Ty=int64_t
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/util/typeid.h(580): note: 参见“std::vector<int64_t,std::allocator<Ty>>”的声明
with
[
Ty=int64_t
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/autograd/variable.h(351): warning C4251: “torch::autograd::Variable::Impl::name”: class“std::basic_string<char,std::char_traits,std::allocator>”需要有 dll 接口由 struct“torch::autograd::Variable::Impl”的客户端使用
C:\Program Files (x86)\Microsoft Visual Studio 14.0\VC\INCLUDE\xstring(2633): note: 参见“std::basic_string<char,std::char_traits,std::allocator>”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/autograd/variable.h(355): warning C4251: “torch::autograd::Variable::Impl::grad_fn”: class“std::shared_ptrtorch::autograd::Function”需要有 dll 接口由 struct“torch::autograd::Variable::Impl”的客户端使用
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/autograd/edge.h(17): note: 参见“std::shared_ptrtorch::autograd::Function”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/autograd/variable.h(356): warning C4251: “torch::autograd::Variable::Impl::grad_accumulator”: class“std::weak_ptrtorch::autograd::Function”需要有 dll 接口由 struct“torch::autograd::Variable::Impl”的客户端使用
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/autograd/variable.h(153): note: 参见“std::weak_ptrtorch::autograd::Function”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/autograd/variable.h(358): warning C4251: “torch::autograd::Variable::Impl::version_counter”: struct“torch::autograd::VariableVersion”需要有 dll 接口由 struct“torch::autograd::Variable::Impl”的客户端使用
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/autograd/variable_version.h(19): note: 参见“torch::autograd::VariableVersion”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/autograd/variable.h(359): warning C4251: “torch::autograd::Variable::Impl::hooks”: class“std::vector<std::shared_ptrtorch::autograd::FunctionPreHook,std::allocator<_Ty>>”需要有 dll 接口由 struct“torch::autograd::Variable::Impl”的客户端使用
with
[
_Ty=std::shared_ptrtorch::autograd::FunctionPreHook
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/autograd/variable.h(245): note: 参见“std::vector<std::shared_ptrtorch::autograd::FunctionPreHook,std::allocator<Ty>>”的声明
with
[
Ty=std::shared_ptrtorch::autograd::FunctionPreHook
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/autograd/variable.h(376): warning C4251: “torch::autograd::Variable::Impl::mutex”: class“std::mutex”需要有 dll 接口由 struct“torch::autograd::Variable::Impl”的客户端使用
C:\Program Files (x86)\Microsoft Visual Studio 14.0\VC\INCLUDE\mutex(78): note: 参见“std::mutex”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/thread_pool.h(51): warning C4251: “c10::ThreadPool::tasks”: class“std::queue<c10::ThreadPool::task_element_t,std::deque<_Ty,std::allocator<_Ty>>>”需要有 dll 接口由 class“c10::ThreadPool”的客户端使用
with
[
_Ty=c10::ThreadPool::task_element_t
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/thread_pool.h(51): note: 参见“std::queue<c10::ThreadPool::task_element_t,std::deque<_Ty,std::allocator<Ty>>>”的声明
with
[
Ty=c10::ThreadPool::task_element_t
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/thread_pool.h(52): warning C4251: “c10::ThreadPool::threads”: class“std::vector<std::thread,std::allocator<Ty>>”需要有 dll 接口由 class“c10::ThreadPool”的客户端使用
with
[
Ty=std::thread
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/thread_pool.h(52): note: 参见“std::vector<std::thread,std::allocator<Ty>>”的声明
with
[
Ty=std::thread
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/thread_pool.h(53): warning C4251: “c10::ThreadPool::mutex”: class“std::mutex”需要有 dll 接口由 class“c10::ThreadPool”的客户端使用
C:\Program Files (x86)\Microsoft Visual Studio 14.0\VC\INCLUDE\mutex(78): note: 参见“std::mutex”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/thread_pool.h(54): warning C4251: “c10::ThreadPool::condition”: class“std::condition_variable”需要有 dll 接口由 class“c10::ThreadPool”的客户端使用
C:\Program Files (x86)\Microsoft Visual Studio 14.0\VC\INCLUDE\mutex(536): note: 参见“std::condition_variable”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/thread_pool.h(55): warning C4251: “c10::ThreadPool::completed”: class“std::condition_variable”需要有 dll 接口由 class“c10::ThreadPool”的客户端使用
C:\Program Files (x86)\Microsoft Visual Studio 14.0\VC\INCLUDE\mutex(536): note: 参见“std::condition_variable”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/ivalue.h(24): warning C4251: “c10::ivalue::ConstantString::str”: class“std::basic_string<char,std::char_traits,std::allocator> ”需要有 dll 接口由 struct“c10::ivalue::ConstantString”的客户端使用
C:\Program Files (x86)\Microsoft Visual Studio 14.0\VC\INCLUDE\xstring(2633): note: 参见“std::basic_string<char,std::char_traits,std::allocator>”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/ivalue.h(43): warning C4251: “c10::ivalue::List::elements”: class“std::vector<T,std::allocator<_Ty>>”需要有 dll 接口由 struct“c10::ivalue::List”的客户端使用
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/util/ArrayRef.h(214): note: 参见“std::vector<T,std::allocator<Ty>>”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/ivalue.h(65): note: 参见对正在编译的类模板实例化“c10::ivalue::List”的引用
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/ivalue.h(43): warning C4251: “c10::ivalue::Listc10::IValue::elements”: class“std::vector<Elem,std::allocator<_Ty>>”需要有 dll 接口由 struct“c10::ivalue::Listc10::IValue”的客户端使用
with
[
Elem=c10::IValue,
_Ty=c10::IValue
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/ivalue.h(43): note: 参见“std::vector<Elem,std::allocator<Ty>>”的声明
with
[
Elem=c10::IValue,
Ty=c10::IValue
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/ivalue.h(69): note: 参见对正在编译的类模板实例化“c10::ivalue::Listc10::IValue”的引用
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/ivalue.h(570): warning C4251: “c10::ivalue::Future::mutex”: class“std::mutex”需要有 dll 接口由 struct“c10::ivalue::Future”的客户端使用
C:\Program Files (x86)\Microsoft Visual Studio 14.0\VC\INCLUDE\mutex(78): note: 参见“std::mutex”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/ivalue.h(572): warning C4251: “c10::ivalue::Future::completed”: struct“std::atomic”需要有 dll 接口由 struct“c10::ivalue::Future”的客户端使用
C:\Program Files (x86)\Microsoft Visual Studio 14.0\VC\INCLUDE\xxatomic(180): note: 参见“std::atomic”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/ivalue.h(573): warning C4251: “c10::ivalue::Future::callbacks”: class“std::vector<std::function<void (void)>,std::allocator<_Ty>>”需要有 dll 接口由 struct“c10::ivalue::Future”的客户端使用
with
[
_Ty=std::function<void (void)>
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/ivalue.h(573): note: 参见“std::vector<std::function<void (void)>,std::allocator<_Ty>>”的声明
with
[
Ty=std::function<void (void)>
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/ivalue.h(43): warning C4251: “c10::ivalue::List<int64_t>::elements”: class“std::vector<int64_t,std::allocator<_Ty>>”需要有 dll 接口由 struct“c10::ivalue::List<int64_t>”的客户端使用
with
[
_Ty=int64_t
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/util/typeid.h(580): note: 参见“std::vector<int64_t,std::allocator<_Ty>>”的声明
with
[
Ty=int64_t
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/ivalue.h(622): note: 参见对正在编译的类模板实例化“c10::ivalue::List<int64_t>”的引用
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/ivalue.h(43): warning C4251: “c10::ivalue::List::elements”: class“std::vector<T,std::allocator<_Ty>>”需要有 dll 接口由 struct“c10::ivalue::List”的客户端使用
with
[
T=double,
_Ty=double
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/util/ArrayRef.h(214): note: 参见“std::vector<T,std::allocator<_Ty>>”的声明
with
[
T=double,
Ty=double
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/ivalue.h(636): note: 参见对正在编译的类模板实例化“c10::ivalue::List”的引用
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/ivalue.h(43): warning C4251: “c10::ivalue::List::elements”: class“std::vector<bool,std::allocator<_Ty>>”需要有 dll 接口由 struct“c10::ivalue::List”的客户端使用
with
[
_Ty=bool
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/ivalue.h(296): note: 参见“std::vector<bool,std::allocator<_Ty>>”的声明
with
[
Ty=bool
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/ivalue.h(643): note: 参见对正在编译的类模板实例化“c10::ivalue::List”的引用
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/ivalue.h(43): warning C4251: “c10::ivalue::Listat::Tensor::elements”: class“std::vector<at::Tensor,std::allocator<_Ty>>”需要有 dll 接口由 struct“c10::ivalue::Listat::Tensor”的客户端使用
with
[
_Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/Type.h(224): note: 参见“std::vector<at::Tensor,std::allocator<_Ty>>”的声明
with
[
Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/ivalue.h(650): note: 参见对正在编译的类模板实例化“c10::ivalue::Listat::Tensor”的引用
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/jit/scope.h(24): warning C4251: “torch::jit::Scope::parent”: class“c10::intrusive_ptr<torch::jit::Scope,c10::detail::intrusive_target_default_null_type>”需要有 dll 接口由 struct“torch::jit::Scope”的客户端使用
with
[
TTarget=torch::jit::Scope
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/jit/scope.h(20): note: 参见“c10::intrusive_ptr<torch::jit::Scope,c10::detail::intrusive_target_default_null_type>”的声明
with
[
TTarget=torch::jit::Scope
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/jit/constants.h(16): warning C4275: 非 dll 接口 class“std::runtime_error”用作 dll 接口 struct“torch::jit::constant_not_supported_error”的基
C:\Program Files (x86)\Microsoft Visual Studio 14.0\VC\INCLUDE\stdexcept(156): note: 参见“std::runtime_error”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/jit/constants.h(16): note: 参见“torch::jit::constant_not_supported_error”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/jit_type.h(52): warning C4251: “std::enable_shared_from_thisc10::Type::_Wptr”: class“std::weak_ptr<_Ty>”需要有 dll 接口由 class“std::enable_shared_from_thisc10::Type”的客户端使用
with
[
_Ty=c10::Type
]
C:\Program Files (x86)\Microsoft Visual Studio 14.0\VC\INCLUDE\memory(1161): note: 参见“std::weak_ptr<_Ty>”的声明
with
[
Ty=c10::Type
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/jit_type.h(213): warning C4251: “c10::SingleElementTypec10::TypeKind::OptionalType,c10::OptionalType::elem”: class“std::shared_ptrc10::Type”需要有 dll 接口由 struct“c10::SingleElementTypec10::TypeKind::OptionalType,c10::OptionalType”的客户端使用
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/jit_type.h(50): note: 参见“std::shared_ptrc10::Type”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/jit_type.h(361): warning C4244: “参数”: 从“int64_t”转换到“int”，可能丢失数据
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/jit_type.h(476): warning C4251: “c10::CompleteTensorType::sizes”: class“std::vector<int64_t,std::allocator<_Ty>>”需要有 dll 接口由 struct “c10::CompleteTensorType”的客户端使用
with
[
_Ty=int64_t
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/util/typeid.h(580): note: 参见“std::vector<int64_t,std::allocator<_Ty>>”的声明
with
[
Ty=int64_t
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/jit_type.h(477): warning C4251: “c10::CompleteTensorType::strides”: class“std::vector<int64_t,std::allocator<_Ty>>”需要有 dll 接口由 struct“c10::CompleteTensorType”的客户端使用
with
[
_Ty=int64_t
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/util/typeid.h(580): note: 参见“std::vector<int64_t,std::allocator<_Ty>>”的声明
with
[
Ty=int64_t
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/jit_type.h(445): warning C4800: “std::size_t”: 将值强制为布尔值“true”或“false”(性能警告)
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/jit_type.h(463): warning C4267: “参数”: 从“size_t”转换到“int”，可能丢失数据
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/jit_type.h(482): warning C4251: “c10::SingleElementTypec10::TypeKind::ListType,c10::ListType::elem”: class“std::shared_ptrc10::Type”需要有 dll 接口由 struct“c10::SingleElementTypec10::TypeKind::ListType,c10::ListType”的客户端使用
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/jit_type.h(50): note: 参见“std::shared_ptrc10::Type”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/jit_type.h(516): warning C4251: “c10::SingleElementTypec10::TypeKind::FutureType,c10::FutureType::elem”: class“std::shared_ptrc10::Type ”需要有 dll 接口由 struct“c10::SingleElementTypec10::TypeKind::FutureType,c10::FutureType”的客户端使用
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/jit_type.h(50): note: 参见“std::shared_ptrc10::Type”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/jit_type.h(622): warning C4251: “c10::TupleType::elements”: class“std::vector<c10::TypePtr,std::allocator<_Ty>>”需要有 dll 接口由 struct“c10::TupleType”的客户端使用
with
[
_Ty=c10::TypePtr
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/jit_type.h(148): note: 参见“std::vector<c10::TypePtr,std::allocator<_Ty>>”的声明
with
[
_Ty=c10::TypePtr
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/jit/tracing_state.h(29): warning C4251: “std::enable_shared_from_thistorch::jit::tracer::TracingState::_Wptr”: class“std::weak_ptr<_Ty>”需要有 dll 接口由 class“std::enable_shared_from_thistorch::jit::tracer::TracingState”的客户端使用
with
[
_Ty=torch::jit::tracer::TracingState
]
C:\Program Files (x86)\Microsoft Visual Studio 14.0\VC\INCLUDE\memory(1161): note: 参见“std::weak_ptr<_Ty>”的声明
with
[
_Ty=torch::jit::tracer::TracingState
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/jit/tracing_state.h(47): warning C4251: “torch::jit::tracer::TracingState::value_map”: class“std::unordered_map<torch::jit::tracer::TracingState::WeakTensor,torch::jit::Value *,torch::jit::tracer::TracingState::WeakTensorHasher,torch::jit::tracer::TracingState::WeakTensorEq,std::allocator<std::pair<const _Kty,_Ty>>>”需要有 dll 接口由 struct“torch::jit::tracer::TracingState”的客户端使用
with
[
_Kty=torch::jit::tracer::TracingState::WeakTensor,
_Ty=torch::jit::Value *
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/jit/tracing_state.h(47): note: 参见“std::unordered_map<torch::jit::tracer::TracingState::WeakTensor,torch::jit::Value *,torch::jit::tracer::TracingState::WeakTensorHasher,torch::jit::tracer::TracingState::WeakTensorEq,std::allocator<std::pair<const _Kty,_Ty>>> ”的声明
with
[
_Kty=torch::jit::tracer::TracingState::WeakTensor,
_Ty=torch::jit::Value *
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/jit/tracing_state.h(48): warning C4251: “torch::jit::tracer::TracingState::graph”: class“std::shared_ptrtorch::jit::Graph”需要有 dll 接口由 struct“torch::jit::tracer::TracingState”的客户端使用
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/jit/tracing_state.h(48): note: 参见“std::shared_ptrtorch::jit::Graph”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/jit/tracing_state.h(52): warning C4251: “torch::jit::tracer::TracingState::lookup_var_name_fn”: class“std::function<std::string (const torch::autograd::Variable &)>”需要有 dll 接口由 struct“torch::jit::tracer::TracingState”的客户端使用
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/jit/tracing_state.h(51): note: 参见“std::function<std::string (const torch::autograd::Variable &)>”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/jit/tracing_state.h(145): warning C4251: “torch::jit::tracer::NoWarn::state”: class“std::shared_ptr<_Ty>”需要有 dll 接口由 struct“torch::jit::tracer::NoWarn”的客户端使用
with
[
_Ty=torch::jit::tracer::TracingState
]
C:\Program Files (x86)\Microsoft Visual Studio 14.0\VC\INCLUDE\memory(1124): note: 参见“std::shared_ptr<Ty>”的声明
with
[
Ty=torch::jit::tracer::TracingState
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/serialize/input-archive.h(78): warning C4251: “torch::serialize::InputArchive::module”: class“std::shared_ptrtorch::jit::script::Module”需要有 dll 接口由 class“torch::serialize::InputArchive”的客户端使用
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/serialize/input-archive.h(78): note: 参见“std::shared_ptrtorch::jit::script::Module”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/serialize/output-archive.h(66): warning C4251: “torch::serialize::OutputArchive::module”: class“std::shared_ptrtorch::jit::script::Module”需要有 dll 接口由 class“torch::serialize::OutputArchive”的客户端使用
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/serialize/input-archive.h(78): note: 参见“std::shared_ptrtorch::jit::script::Module”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/jit/script/lexer.h(384): warning C4267: “参数”: 从“size_t”转换到“int”，可能丢失数据
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/jit/script/lexer.h(458): warning C4267: “初始化”: 从“size_t”转换到“int”，可能丢失数据
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/jit/interpreter.h(42): warning C4251: “torch::jit::Code::pImpl”: class“std::shared_ptrtorch::jit::CodeImpl”需要有 dll 接口由 struct“torch::jit::Code”的客户端使用
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/jit/interpreter.h(42): note: 参见“std::shared_ptrtorch::jit::CodeImpl”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/jit/argument_spec.h(189): warning C4267: “初始化”: 从“size_t”转换到“int32_t”，可能丢失数据
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/jit/argument_spec.h(192): warning C4267: “初始化”: 从“size_t”转换到“int32_t”，可能丢失数据
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/jit/argument_spec.h(192): warning C4267: “初始化”: 从“size_t”转换到“const int32_t”，可能丢失数据
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/jit/argument_spec.h(196): warning C4244: “+=”: 从“int64_t”转换到“int32_t”，可能丢失数据
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/jit/argument_spec.h(215): warning C4244: “+=”: 从“int64_t”转换到“int32_t”，可能丢失数据
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/jit/argument_spec.h(276): warning C4800: “const unsigned int”: 将值强制为布尔值“true”或“false”(性能警告)
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/jit/argument_spec.h(367): warning C4267: “参数”: 从“size_t”转换到“const int”，可能丢失数据
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/jit/graph_executor.h(41): warning C4251: “torch::jit::GraphExecutor::pImpl”: class“std::shared_ptrtorch::jit::GraphExecutorImpl”需要有 dll 接口由 struct“torch::jit::GraphExecutor”的客户端使用
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/jit/graph_executor.h(41): note: 参见“std::shared_ptrtorch::jit::GraphExecutorImpl”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/jit/script/module.h(56): warning C4267: “初始化”: 从“size_t”转换到“int”，可能丢失数据
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/jit/script/compiler.h(93): warning C4275: 非 dll 接口 struct“torch::jit::script::SugaredValue”用作 dll 接口 struct“torch::jit::script::SimpleValue”的基
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/jit/script/compiler.h(35): note: 参见“torch::jit::script::SugaredValue”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/jit/script/compiler.h(93): note: 参见“torch::jit::script::SimpleValue”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/jit/script/compiler.h(122): warning C4275: 非 dll 接口 struct“torch::jit::script::SugaredValue”用作 dll 接口 struct“torch::jit::script::BuiltinFunction”的基
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/jit/script/compiler.h(35): note: 参见“torch::jit::script::SugaredValue”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/jit/script/compiler.h(122): note: 参见“torch::jit::script::BuiltinFunction”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/jit/script/compiler.h(130): warning C4251: “torch::jit::script::BuiltinFunction::self”: class“c10::optionaltorch::jit::NamedValue”需要有 dll 接口由 struct“torch::jit::script::BuiltinFunction”的客户端使用
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/jit/script/module.h(479): note: 参见“c10::optionaltorch::jit::NamedValue”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/jit/script/compiler.h(143): warning C4275: 非 dll 接口 struct“torch::jit::script::SugaredValue”用作 dll 接口 struct“torch::jit::script::BuiltinModule”的基
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/jit/script/compiler.h(35): note: 参见“torch::jit::script::SugaredValue”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/jit/script/compiler.h(143): note: 参见“torch::jit::script::BuiltinModule”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/jit/script/compiler.h(157): warning C4251: “torch::jit::script::BuiltinModule::name”: class“std::basic_string<char,std::char_traits,std::allocator>”需要有 dll 接口由 struct“torch::jit::script::BuiltinModule”的客户端使用
C:\Program Files (x86)\Microsoft Visual Studio 14.0\VC\INCLUDE\xstring(2633): note: 参见“std::basic_string<char,std::char_traits,std::allocator>”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/jit/script/compiler.h(160): warning C4251: “torch::jit::script::BuiltinModule::version”: class“c10::optional<int64_t>”需要有 dll 接口由 struct“torch::jit::script::BuiltinModule”的客户端使用
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/jit/script/compiler.h(145): note: 参见“c10::optional<int64_t>”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/jit/script/compiler.h(167): warning C4275: 非 dll 接口 struct“torch::jit::script::SugaredValue”用作 dll 接口 struct“torch::jit::script::ForkValue”的基
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/jit/script/compiler.h(35): note: 参见“torch::jit::script::SugaredValue”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/jit/script/compiler.h(167): note: 参见“torch::jit::script::ForkValue”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/jit/script/compiler.h(173): warning C4275: 非 dll 接口 struct“torch::jit::script::SugaredValue”用作 dll 接口 struct“torch::jit::script::AnnotateValue”的基
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/jit/script/compiler.h(35): note: 参见“torch::jit::script::SugaredValue”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/jit/script/compiler.h(173): note: 参见“torch::jit::script::AnnotateValue”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/nn/module.h(61): warning C4251: “std::enable_shared_from_thistorch::nn::Module::_Wptr”: class“std::weak_ptr<_Ty>”需要有 dll 接口由 class“std::enable_shared_from_thistorch::nn::Module”的客户端使用
with
[
Ty=torch::nn::Module
]
C:\Program Files (x86)\Microsoft Visual Studio 14.0\VC\INCLUDE\memory(1161): note: 参见“std::weak_ptr<Ty>”的声明
with
[
Ty=torch::nn::Module
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/nn/module.h(483): warning C4251: “torch::nn::Module::parameters”: class“torch::OrderedDictstd::string,at::Tensor”需要有 dll 接口由 class“torch::nn::Module”的客户端使用
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/nn/module.h(209): note: 参见“torch::OrderedDictstd::string,at::Tensor”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/nn/module.h(486): warning C4251: “torch::nn::Module::buffers”: class“torch::OrderedDictstd::string,at::Tensor”需要有 dll 接口由 class“torch::nn::Module”的客户端使用
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/nn/module.h(209): note: 参见“torch::OrderedDictstd::string,at::Tensor”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/nn/module.h(489): warning C4251: “torch::nn::Module::children”: class“torch::OrderedDict<std::string,std::shared_ptr<_Ty>>”需要有 dll 接口由 class“torch::nn::Module”的客户端使用
with
[
_Ty=torch::nn::Module
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/nn/module.h(245): note: 参见“torch::OrderedDict<std::string,std::shared_ptr<Ty>>”的声明
with
[
Ty=torch::nn::Module
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/nn/module.h(492): warning C4251: “torch::nn::Module::name”: class“c10::optionalstd::string”需要有 dll 接口由 class“torch::nn::Module”的客户端使用
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/jit/named_value.h(70): note: 参见“c10::optionalstd::string”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/nn/pimpl.h(123): error C2872: “std”: 不明确的符号
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/jit/argument_spec.h(380): note: 可能是“std”
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/nn/pimpl.h(123): note: 或 “std”
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/nn/modules/batchnorm.h(92): note: 参见对正在编译的类模板实例化“torch::nn::ModuleHoldertorch::nn::BatchNormImpl”的引用
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/jit/stack.h(30): note: 参见对正在编译的类模板实例化“c10::ArrayRefc10::IValue”的引用
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/nn/pimpl.h(129): error C2872: “std”: 不明确的符号
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch/csrc/jit/argument_spec.h(380): note: 可能是“std”
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/nn/pimpl.h(129): note: 或 “std”
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/nn/modules/conv.h(106): warning C4251: “torch::nn::ConvImpl<1,torch::nn::Conv1dImpl>::options”: struct“torch::nn::ConvOptions<1>”需要有 dll 接口由 class“torch::nn::ConvImpl<1,torch::nn::Conv1dImpl>”的客户端使用
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/nn/modules/conv.h(87): note: 参见“torch::nn::ConvOptions<1>”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/nn/modules/conv.h(126): warning C4251: “torch::nn::ConvImpl<2,torch::nn::Conv2dImpl>::options”: struct“torch::nn::ConvOptions<2>”需要有 dll 接口由 class“torch::nn::ConvImpl<2,torch::nn::Conv2dImpl>”的客户端使用
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/nn/modules/conv.h(87): note: 参见“torch::nn::ConvOptions<2>”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/nn/modules/conv.h(146): warning C4251: “torch::nn::ConvImpl<3,torch::nn::Conv3dImpl>::options”: struct“torch::nn::ConvOptions<3>”需要有 dll 接口由 class“torch::nn::ConvImpl<3,torch::nn::Conv3dImpl>”的客户端使用
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/nn/modules/conv.h(87): note: 参见“torch::nn::ConvOptions<3>”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/nn/modules/functional.h(89): warning C4251: “torch::nn::FunctionalImpl::function”: class“std::function<at::Tensor (at::Tensor)>”需要有 dll 接口由 class“torch::nn::FunctionalImpl”的客户端使用
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/data/transforms/tensor.h(39): note: 参见“std::function<at::Tensor (at::Tensor)>”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/nn/modules/rnn.h(174): warning C4251: “torch::nn::detail::RNNImplBasetorch::nn::RNNImpl::w_ih”: class“std::vector<at::Tensor,std::allocator<_Ty>>”需要有 dll 接口由 class“torch::nn::detail::RNNImplBasetorch::nn::RNNImpl”的客户端使用
with
[
_Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/Type.h(224): note: 参见“std::vector<at::Tensor,std::allocator<_Ty>>”的声明
with
[
_Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/nn/modules/rnn.h(174): warning C4251: “torch::nn::detail::RNNImplBasetorch::nn::RNNImpl::w_hh”: class“std::vector<at::Tensor,std::allocator<_Ty>>”需要有 dll 接口由 class“torch::nn::detail::RNNImplBasetorch::nn::RNNImpl”的客户端使用
with
[
_Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/Type.h(224): note: 参见“std::vector<at::Tensor,std::allocator<_Ty>>”的声明
with
[
_Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/nn/modules/rnn.h(174): warning C4251: “torch::nn::detail::RNNImplBasetorch::nn::RNNImpl::b_ih”: class“std::vector<at::Tensor,std::allocator<_Ty>>”需要有 dll 接口由 class“torch::nn::detail::RNNImplBasetorch::nn::RNNImpl”的客户端使用
with
[
_Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/Type.h(224): note: 参见“std::vector<at::Tensor,std::allocator<_Ty>>”的声明
with
[
_Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/nn/modules/rnn.h(174): warning C4251: “torch::nn::detail::RNNImplBasetorch::nn::RNNImpl::b_hh”: class“std::vector<at::Tensor,std::allocator<_Ty>>”需要有 dll 接口由 class“torch::nn::detail::RNNImplBasetorch::nn::RNNImpl”的客户端使用
with
[
_Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/Type.h(224): note: 参见“std::vector<at::Tensor,std::allocator<Ty>>”的声明
with
[
Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/nn/modules/rnn.h(174): warning C4251: “torch::nn::detail::RNNImplBasetorch::nn::RNNImpl::cudnn_mode”: class“c10::optional<torch::nn::detail::RNNImplBasetorch::nn::RNNImpl::CuDNNMode>”需要有 dll 接口由 class“torch::nn::detail::RNNImplBasetorch::nn::RNNImpl”的客户端使用
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/nn/modules/rnn.h(64): note: 参见“c10::optional<torch::nn::detail::RNNImplBasetorch::nn::RNNImpl::CuDNNMode>”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/nn/modules/rnn.h(174): warning C4251: “torch::nn::detail::RNNImplBasetorch::nn::RNNImpl::flat_weights”: class“std::vector<at::Tensor,std::allocator<_Ty>>”需要有 dll 接口由 class“torch::nn::detail::RNNImplBasetorch::nn::RNNImpl”的客户端使用
with
[
_Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/Type.h(224): note: 参见“std::vector<at::Tensor,std::allocator<_Ty>>”的声明
with
[
_Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/nn/modules/rnn.h(202): warning C4251: “torch::nn::detail::RNNImplBasetorch::nn::LSTMImpl::w_ih”: class“std::vector<at::Tensor,std::allocator<_Ty>>”需要有 dll 接口由 class“torch::nn::detail::RNNImplBasetorch::nn::LSTMImpl”的客户端使用
with
[
_Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/Type.h(224): note: 参见“std::vector<at::Tensor,std::allocator<_Ty>>”的声明
with
[
_Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/nn/modules/rnn.h(202): warning C4251: “torch::nn::detail::RNNImplBasetorch::nn::LSTMImpl::w_hh”: class“std::vector<at::Tensor,std::allocator<_Ty>>”需要有 dll 接口由 class“torch::nn::detail::RNNImplBasetorch::nn::LSTMImpl”的客户端使用
with
[
_Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/Type.h(224): note: 参见“std::vector<at::Tensor,std::allocator<_Ty>>”的声明
with
[
_Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/nn/modules/rnn.h(202): warning C4251: “torch::nn::detail::RNNImplBasetorch::nn::LSTMImpl::b_ih”: class“std::vector<at::Tensor,std::allocator<_Ty>>”需要有 dll 接口由 class“torch::nn::detail::RNNImplBasetorch::nn::LSTMImpl”的客户端使用
with
[
_Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/Type.h(224): note: 参见“std::vector<at::Tensor,std::allocator<_Ty>>”的声明
with
[
_Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/nn/modules/rnn.h(202): warning C4251: “torch::nn::detail::RNNImplBasetorch::nn::LSTMImpl::b_hh”: class“std::vector<at::Tensor,std::allocator<_Ty>>”需要有 dll 接口由 class“torch::nn::detail::RNNImplBasetorch::nn::LSTMImpl”的客户端使用
with
[
_Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/Type.h(224): note: 参见“std::vector<at::Tensor,std::allocator<Ty>>”的声明
with
[
Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/nn/modules/rnn.h(202): warning C4251: “torch::nn::detail::RNNImplBasetorch::nn::LSTMImpl::cudnn_mode”: class“c10::optional<torch::nn::detail::RNNImplBasetorch::nn::LSTMImpl::CuDNNMode>”需要有 dll 接口由 class“torch::nn::detail::RNNImplBasetorch::nn::LSTMImpl”的客户端使用
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/nn/modules/rnn.h(64): note: 参见“c10::optional<torch::nn::detail::RNNImplBasetorch::nn::LSTMImpl::CuDNNMode>”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/nn/modules/rnn.h(202): warning C4251: “torch::nn::detail::RNNImplBasetorch::nn::LSTMImpl::flat_weights”: class“std::vector<at::Tensor,std::allocator<_Ty>>”需要有 dll 接口由 class“torch::nn::detail::RNNImplBasetorch::nn::LSTMImpl”的客户端使用
with
[
_Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/Type.h(224): note: 参见“std::vector<at::Tensor,std::allocator<_Ty>>”的声明
with
[
_Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/nn/modules/rnn.h(228): warning C4251: “torch::nn::detail::RNNImplBasetorch::nn::GRUImpl::w_ih”: class“std::vector<at::Tensor,std::allocator<_Ty>>”需要有 dll 接口由 class“torch::nn::detail::RNNImplBasetorch::nn::GRUImpl”的客户端使用
with
[
_Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/Type.h(224): note: 参见“std::vector<at::Tensor,std::allocator<_Ty>>”的声明
with
[
_Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/nn/modules/rnn.h(228): warning C4251: “torch::nn::detail::RNNImplBasetorch::nn::GRUImpl::w_hh”: class“std::vector<at::Tensor,std::allocator<_Ty>>”需要有 dll 接口由 class“torch::nn::detail::RNNImplBasetorch::nn::GRUImpl”的客户端使用
with
[
_Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/Type.h(224): note: 参见“std::vector<at::Tensor,std::allocator<_Ty>>”的声明
with
[
_Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/nn/modules/rnn.h(228): warning C4251: “torch::nn::detail::RNNImplBasetorch::nn::GRUImpl::b_ih”: class“std::vector<at::Tensor,std::allocator<_Ty>>”需要有 dll 接口由 class“torch::nn::detail::RNNImplBasetorch::nn::GRUImpl”的客户端使用
with
[
_Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/Type.h(224): note: 参见“std::vector<at::Tensor,std::allocator<_Ty>>”的声明
with
[
_Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/nn/modules/rnn.h(228): warning C4251: “torch::nn::detail::RNNImplBasetorch::nn::GRUImpl::b_hh”: class“std::vector<at::Tensor,std::allocator<_Ty>>”需要有 dll 接口由 class“torch::nn::detail::RNNImplBasetorch::nn::GRUImpl”的客户端使用
with
[
_Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/Type.h(224): note: 参见“std::vector<at::Tensor,std::allocator<Ty>>”的声明
with
[
Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/nn/modules/rnn.h(228): warning C4251: “torch::nn::detail::RNNImplBasetorch::nn::GRUImpl::cudnn_mode”: class“c10::optional<torch::nn::detail::RNNImplBasetorch::nn::GRUImpl::CuDNNMode>”需要有 dll 接口由 class“torch::nn::detail::RNNImplBasetorch::nn::GRUImpl”的客户端使用
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/nn/modules/rnn.h(64): note: 参见“c10::optional<torch::nn::detail::RNNImplBasetorch::nn::GRUImpl::CuDNNMode>”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/nn/modules/rnn.h(228): warning C4251: “torch::nn::detail::RNNImplBasetorch::nn::GRUImpl::flat_weights”: class“std::vector<at::Tensor,std::allocator<_Ty>>”需要有 dll 接口由 class“torch::nn::detail::RNNImplBasetorch::nn::GRUImpl”的客户端使用
with
[
_Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/Type.h(224): note: 参见“std::vector<at::Tensor,std::allocator<_Ty>>”的声明
with
[
Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/optim/optimizer.h(80): warning C4251: “torch::optim::detail::OptimizerBase::parameters”: class“std::vector<at::Tensor,std::allocator<_Ty>>”需要有 dll 接口由 class“torch::optim::detail::OptimizerBase”的客户端使用
with
[
_Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/Type.h(224): note: 参见“std::vector<at::Tensor,std::allocator<_Ty>>”的声明
with
[
_Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/optim/adagrad.h(28): warning C4275: 非 dll 接口 class“torch::optim::Optimizer”用作 dll 接口 class“torch::optim::Adagrad”的基
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/optim/optimizer.h(97): note: 参见“torch::optim::Optimizer”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/optim/adagrad.h(28): note: 参见“torch::optim::Adagrad”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/optim/adagrad.h(44): warning C4251: “torch::optim::Adagrad::sum_buffers”: class“std::vector<at::Tensor,std::allocator<_Ty>>”需要有 dll 接口由 class“torch::optim::Adagrad”的客户端使用
with
[
_Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/Type.h(224): note: 参见“std::vector<at::Tensor,std::allocator<_Ty>>”的声明
with
[
_Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/optim/adagrad.h(45): warning C4251: “torch::optim::Adagrad::step_buffers”: class“std::vector<int64_t,std::allocator<_Ty>>”需要有 dll 接口由 class“torch::optim::Adagrad”的客户端使用
with
[
_Ty=int64_t
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/util/typeid.h(580): note: 参见“std::vector<int64_t,std::allocator<_Ty>>”的声明
with
[
_Ty=int64_t
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/optim/adam.h(31): warning C4275: 非 dll 接口 class“torch::optim::Optimizer”用作 dll 接口 class“torch::optim::Adam”的基
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/optim/optimizer.h(97): note: 参见“torch::optim::Optimizer”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/optim/adam.h(31): note: 参见“torch::optim::Adam”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/optim/adam.h(45): warning C4251: “torch::optim::Adam::step_buffers”: class“std::vector<int64_t,std::allocator<_Ty>>”需要有 dll 接口由 class“torch::optim::Adam”的客户端使用
with
[
_Ty=int64_t
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\c10/util/typeid.h(580): note: 参见“std::vector<int64_t,std::allocator<_Ty>>”的声明
with
[
_Ty=int64_t
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/optim/adam.h(46): warning C4251: “torch::optim::Adam::exp_average_buffers”: class“std::vector<at::Tensor,std::allocator<_Ty>>”需要有 dll 接口由 class“torch::optim::Adam”的客户端使用
with
[
_Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/Type.h(224): note: 参见“std::vector<at::Tensor,std::allocator<_Ty>>”的声明
with
[
_Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/optim/adam.h(47): warning C4251: “torch::optim::Adam::exp_average_sq_buffers”: class“std::vector<at::Tensor,std::allocator<_Ty>>”需要有 dll 接口由 class“torch::optim::Adam”的客户端使用
with
[
_Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/Type.h(224): note: 参见“std::vector<at::Tensor,std::allocator<_Ty>>”的声明
with
[
_Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/optim/adam.h(48): warning C4251: “torch::optim::Adam::max_exp_average_sq_buffers”: class“std::vector<at::Tensor,std::allocator<_Ty>>”需要有 dll 接口由 class“torch::optim::Adam”的客户端使用
with
[
_Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/Type.h(224): note: 参见“std::vector<at::Tensor,std::allocator<_Ty>>”的声明
with
[
_Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/optim/lbfgs.h(22): warning C4305: “初始化”: 从“double”到“float”截断
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/optim/lbfgs.h(23): warning C4305: “初始化”: 从“double”到“float”截断
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/optim/lbfgs.h(27): warning C4275: 非 dll 接口 class“torch::optim::LossClosureOptimizer”用作 dll 接口 class“torch::optim::LBFGS”的基
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/optim/optimizer.h(107): note: 参见“torch::optim::LossClosureOptimizer”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/optim/lbfgs.h(27): note: 参见“torch::optim::LBFGS”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/optim/lbfgs.h(48): warning C4251: “torch::optim::LBFGS::ro”: class“std::vector<at::Tensor,std::allocator<_Ty>>”需要有 dll 接口由 class“torch::optim::LBFGS”的客户端使用
with
[
_Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/Type.h(224): note: 参见“std::vector<at::Tensor,std::allocator<_Ty>>”的声明
with
[
_Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/optim/lbfgs.h(49): warning C4251: “torch::optim::LBFGS::al”: class“std::vector<at::Tensor,std::allocator<_Ty>>”需要有 dll 接口由 class“torch::optim::LBFGS”的客户端使用
with
[
_Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/Type.h(224): note: 参见“std::vector<at::Tensor,std::allocator<_Ty>>”的声明
with
[
_Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/optim/lbfgs.h(50): warning C4251: “torch::optim::LBFGS::old_dirs”: class“std::deque<at::Tensor,std::allocator<_Ty>>”需要有 dll 接口由 class“torch::optim::LBFGS”的客户端使用
with
[
_Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/optim/lbfgs.h(50): note: 参见“std::deque<at::Tensor,std::allocator<_Ty>>”的声明
with
[
_Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/optim/lbfgs.h(51): warning C4251: “torch::optim::LBFGS::old_stps”: class“std::deque<at::Tensor,std::allocator<_Ty>>”需要有 dll 接口由 class“torch::optim::LBFGS”的客户端使用
with
[
_Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/optim/lbfgs.h(50): note: 参见“std::deque<at::Tensor,std::allocator<_Ty>>”的声明
with
[
_Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/optim/rmsprop.h(34): warning C4275: 非 dll 接口 class“torch::optim::Optimizer”用作 dll 接口 class“torch::optim::RMSprop”的基
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/optim/optimizer.h(97): note: 参见“torch::optim::Optimizer”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/optim/rmsprop.h(34): note: 参见“torch::optim::RMSprop”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/optim/rmsprop.h(50): warning C4251: “torch::optim::RMSprop::square_average_buffers”: class“std::vector<at::Tensor,std::allocator<_Ty>>”需要有 dll 接口由 class“torch::optim::RMSprop”的客户端使用
with
[
_Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/Type.h(224): note: 参见“std::vector<at::Tensor,std::allocator<_Ty>>”的声明
with
[
_Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/optim/rmsprop.h(51): warning C4251: “torch::optim::RMSprop::momentum_buffers”: class“std::vector<at::Tensor,std::allocator<_Ty>>”需要有 dll 接口由 class“torch::optim::RMSprop”的客户端使用
with
[
_Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/Type.h(224): note: 参见“std::vector<at::Tensor,std::allocator<_Ty>>”的声明
with
[
_Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/optim/rmsprop.h(52): warning C4251: “torch::optim::RMSprop::grad_average_buffers”: class“std::vector<at::Tensor,std::allocator<_Ty>>”需要有 dll 接口由 class“torch::optim::RMSprop”的客户端使用
with
[
_Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/Type.h(224): note: 参见“std::vector<at::Tensor,std::allocator<_Ty>>”的声明
with
[
_Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/optim/sgd.h(31): warning C4275: 非 dll 接口 class“torch::optim::Optimizer”用作 dll 接口 class“torch::optim::SGD”的基
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/optim/optimizer.h(97): note: 参见“torch::optim::Optimizer”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/optim/sgd.h(31): note: 参见“torch::optim::SGD”的声明
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\torch\csrc\api\include\torch/optim/sgd.h(45): warning C4251: “torch::optim::SGD::momentum_buffers”: class“std::vector<at::Tensor,std::allocator<_Ty>> ”需要有 dll 接口由 class“torch::optim::SGD”的客户端使用
with
[
_Ty=at::Tensor
]
C:\Users\Administrator\AppData\Roaming\Python\Python36\site-packages\torch\lib\include\ATen/core/Type.h(224): note: 参见“std::vector<at::Tensor,std::allocator<_Ty>>”的声明
with
[
_Ty=at::Tensor
]
error: command 'C:\Program Files (x86)\Microsoft Visual Studio 14.0\VC\BIN\x86_amd64\cl.exe' failed with exit status 2

why you not support CPU

it is difficult to rrealize by code?

CUDA error occurred when running on a GPU with the index not being 0

It works well on GPU 0, but CUDA error occurred when I run my model on GPU 1 or 2.

Traceback (most recent call last): File "train_task.py", line 906, in <module> main()
File "train_task.py", line 547, in main model(image_tensors)

File "/home/eezywu/anaconda3/lib/python3.6/site-packages/torch/nn/modules/module.py", line 489, in __call__ result = self.forward(*input, **kwargs)

File "/home/eezywu/Project8/models.py", line 737, in forward out = self.layer2(out)

File "/home/eezywu/anaconda3/lib/python3.6/site-packages/torch/nn/modules/module.py", line 489, in __call__ result = self.forward(*input, **kwargs)

File "/home/eezywu/anaconda3/lib/python3.6/site-packages/torch/nn/modules/container.py", line 92, in forward input = module(input)

File "/home/eezywu/anaconda3/lib/python3.6/site-packages/torch/nn/modules/module.py", line 489, in __call__ result = self.forward(*input, **kwargs)

File "/home/eezywu/anaconda3/lib/python3.6/site-packages/torch/nn/modules/batchnorm.py", line 67, in forward self.num_batches_tracked += 1

RuntimeError: CUDA error: an illegal memory access was encountered

When I repalce the DCN module with a conventional nn.Conv2d, there is no error. So I think the DCN module causes it.

fatal error: cuda_runtime_api.h: No such file or directory in Anaconda3

Hey, I've tried everything to run your make.sh
Still I have the same problem:
fatal error: cuda_runtime_api.h: No such file or directory

The specific traceback is as follows:
running build running build_ext building '_ext' extension gcc -pthread -B /home/ryluo/anaconda3/envs/pytorch/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DWITH_CUDA -I/data/zp/EDVR-master/codes/models/modules/DCNv2/src -I/home/ryluo/anaconda3/envs/pytorch/lib/python3.6/site-packages/torch/include -I/home/ryluo/anaconda3/envs/pytorch/lib/python3.6/site-packages/torch/include/torch/csrc/api/include -I/home/ryluo/anaconda3/envs/pytorch/lib/python3.6/site-packages/torch/include/TH -I/home/ryluo/anaconda3/envs/pytorch/lib/python3.6/site-packages/torch/include/THC -I/usr/local/cuda-9.0::/usr/local/cuda-9.0/include -I/home/ryluo/anaconda3/envs/pytorch/include/python3.6m -c /data/zp/EDVR-master/codes/models/modules/DCNv2/src/vision.cpp -o build/temp.linux-x86_64-3.6/data/zp/EDVR-master/codes/models/modules/DCNv2/src/vision.o -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=_ext -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++11 cc1plus: warning: command line option ‘-Wstrict-prototypes’ is valid for C/ObjC but not for C++ gcc -pthread -B /home/ryluo/anaconda3/envs/pytorch/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -DWITH_CUDA -I/data/zp/EDVR-master/codes/models/modules/DCNv2/src -I/home/ryluo/anaconda3/envs/pytorch/lib/python3.6/site-packages/torch/include -I/home/ryluo/anaconda3/envs/pytorch/lib/python3.6/site-packages/torch/include/torch/csrc/api/include -I/home/ryluo/anaconda3/envs/pytorch/lib/python3.6/site-packages/torch/include/TH -I/home/ryluo/anaconda3/envs/pytorch/lib/python3.6/site-packages/torch/include/THC -I/usr/local/cuda-9.0::/usr/local/cuda-9.0/include -I/home/ryluo/anaconda3/envs/pytorch/include/python3.6m -c /data/zp/EDVR-master/codes/models/modules/DCNv2/src/cpu/dcn_v2_cpu.cpp -o build/temp.linux-x86_64-3.6/data/zp/EDVR-master/codes/models/modules/DCNv2/src/cpu/dcn_v2_cpu.o -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=_ext -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++11 cc1plus: warning: command line option ‘-Wstrict-prototypes’ is valid for C/ObjC but not for C++ In file included from /home/ryluo/anaconda3/envs/pytorch/lib/python3.6/site-packages/torch/include/ATen/cuda/CUDAContext.h:5:0, from /data/zp/EDVR-master/codes/models/modules/DCNv2/src/cpu/dcn_v2_cpu.cpp:4: /home/ryluo/anaconda3/envs/pytorch/lib/python3.6/site-packages/torch/include/c10/cuda/CUDAStream.h:6:30: fatal error: cuda_runtime_api.h: No such file or directory compilation terminated. error: command 'gcc' failed with exit status 1

So what exactly happened? I've tried setting my environment variable, or exporting it again in my single terminal, etc.
I've checked my ~/.bashrc, no problem found there.
I ran it in Anaconda3.

Pre-built pyd file for different PC ???

@CharlesShang
Hello, I had tried to build the DCNv2 pyd file in my PC and then use it in another PC but it didnt work.
The error: DLL load failed: The specified module could not be found ... always occurs.

Can you give me some advises to cope with this problem ?

DCNv2 test.py error

when i python test.py ,it will occur Segmentation fault.and i have successfully installed 👍
Installed /home/ptt/local_big_disk/DCNv2-master
Processing dependencies for DCNv2==0.1
Finished processing dependencies for DCNv2==0.1

Higher order gradients through DCN layer

When I try to get higher order derivatives on architectures using your implementation of DCNv2, I get the following error:

"RuntimeError: DCNv2FunctionLegacyBackward is not differentiable twice".

Is there a way around this?

import error with _ZN3c105ErrorC1ENS_14SourceLocationERKSs

>>> from dcn_v2 import DCN
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/admin/PassengerRec/DCNv2/dcn_v2.py", line 13, in <module>
    import _ext as _backend
ImportError: /home/admin/PassengerRec/DCNv2/_ext.cpython-36m-x86_64-linux-gnu.so: undefined symbol: _ZN3c105ErrorC1ENS_14SourceLocationERKSs

When i tried to import the DCN, after succeeded compile the project, i encountered the error!
Environment:
Ubuntu 16.04
GPU: 2080
python:3.6
conda install:
pytorch:1.0.1
cuda=10.0
cudnn=7.3

But when I use the 1080Ti, there is nothing happen.
Can you give me some advice?
@CharlesShang

torchscript support for DCVv2

Hello!
Allow me to ask for your advice, please.
Situation description: I know that deformable convolution is supported natively in Pytorch since 1.4, but this does not mean DCN may be extracted to a static graph via jit. Moreover, DCN added to Pytorch is version 1, not this one (version two).
Question: Can you confirm I understand the situation correctly and how hard is to add DCNv2 support to torchscript from your point of view?

Test Runtime Error

Give following error on a freshly cloned repo

error in modulated_deformable_im2col_cuda: a PTX JIT compilation failed
Traceback (most recent call last):
  File "test.py", line 255, in <module>
    example_dconv()
  File "test.py", line 177, in example_dconv
    targert.data.uniform_(-0.01, 0.01)
RuntimeError: Creating MTGP constants failed. at /opt/conda/conda-bld/pytorch_1549630534704/work/aten/src/THC/THCTensorRandom.cu:35

Does anyone encounter this issue?
I am using PyTorch 1.0.0 and CUDA 10.

Deform Pool: Multiple Forward-Backward Gives Buffer / Retain_graph Related Bugs

Hi,

When I want to run deformable pooling (no matter modulated or not) two times (forward -> backward -> forward -> backward), the second backward yields follow bug:

Trying to backward through the graph a second time, but the buffers have already been freed. Specify retain_graph=True when calling backward the first time.

This doesn't happen on Deform Convs, so it's related to pooling only. What is your opinion?

erro when test

I do the make.sh successfully, but when I do python test.py in DCVv2, I met this error:
Traceback (most recent call last):
File "test.py", line 11, in
from dcn_v2 import dcn_v2_conv, DCNv2, DCN
File "/home/data/CenterNet-master/src/lib/models/networks/DCNv2-master/dcn_v2.py", line 13, in
import _ext as _backend
ImportError: libcudart.so.10.0: cannot open shared object file: No such file or directory

RuntimeError: Backward is not reentrant

(pytorch) wuwenfu@wuwenfu:~/DCNv2-master$ python test.py
torch.Size([2, 64, 128, 128])
torch.Size([20, 32, 7, 7])
torch.Size([20, 32, 7, 7])
torch.Size([20, 32, 7, 7])
0.971507, 1.943014
0.971507, 1.943014
Zero offset passed
/home/wuwenfu/.conda/envs/pytorch/lib/python3.7/site-packages/torch/autograd/gradcheck.py:239: UserWarning: At least one of the inputs that requires gradient is not of double precision floating point. This check will likely fail if all the inputs are not of double precision floating point.
'At least one of the inputs that requires gradient '
check_gradient_dpooling: True
Traceback (most recent call last):
File "test.py", line 265, in
check_gradient_dconv()
File "test.py", line 97, in check_gradient_dconv
eps=1e-3, atol=1e-4, rtol=1e-2))
File "/home/wuwenfu/.conda/envs/pytorch/lib/python3.7/site-packages/torch/autograd/gradcheck.py", line 289, in gradcheck
return fail_test('Backward is not reentrant, i.e., running backward with same '
File "/home/wuwenfu/.conda/envs/pytorch/lib/python3.7/site-packages/torch/autograd/gradcheck.py", line 224, in fail_test
raise RuntimeError(msg)
RuntimeError: Backward is not reentrant, i.e., running backward with same input and grad_output multiple times gives different values, although analytical gradient matches numerical gradient
how can I fix it? thanks.

Does it support stride=(2,1) for DCNv2?

Build process is not working (error: command '/usr/bin/nvcc' failed with exit status 1: During Build Process)

$ ./make.sh
running build
running build_ext
building '_ext' extension

(...)

/usr/include/c++/6/type_traits:1558:8: note: provided for ‘template<class _From, class _To> struct std::is_convertible’
     struct is_convertible
        ^~~~~~~~~~~~~~
/usr/include/c++/6/tuple:502:1: error: body of constexpr function ‘static constexpr bool std::_TC<<anonymous>, _Elements>::_NonNestedTuple() [with _SrcTuple = std::tuple<at::Tensor, at::Tensor, at::Tensor, at::Tensor>&&; bool <anonymous> = true; _Elements = {at::Tensor, at::Tensor, at::Tensor, at::Tensor}]’ not a return-statement
     }
 ^
error: command '/usr/bin/nvcc' failed with exit status 1

error: command '/usr/bin/nvcc' failed with exit status 1
Anyone please let me know how to solve this error? I used export TORCH_CUDA_ARCH_LIST="7.0" to solvenvcc fatal unsupported gpu architecture 'compute_75' error.

I'm using CUDA 9.2, Python 3.7.5, and PyTorch 1.0.1. My GPU is RTX 2080 Ti.

torch/extension.h: No such file or directory

When I compiling in my Ubuntu system. It released an error, said:
DCNv2-master/src/cpu/vision.h:2:29: fatal error: torch/extension.h: No such file or directory
There is no file named "torch" in above mentioned path, How can I solve the question

When I use apex on 2080ti, I get the following error, how can I solve it?

RuntimeError: expected scalar type Float but found Half (data at /usr/local/lib/python3.5/dist-packages/torch/include/ATen/core/TensorMethods.h:1386)
frame #0: std::function<std::string ()>::operator()() const + 0x11 (0x7f9f2dbdd441 in /usr/local/lib/python3.5/dist-packages/torch/lib/libc10.so)
frame #1: c10::Error::Error(c10::SourceLocation, std::string const&) + 0x2a (0x7f9f2dbdcd7a in /usr/local/lib/python3.5/dist-packages/torch/lib/libc10.so)
frame #2: float* at::Tensor::data() const + 0xcf (0x7f9f1c69fa2f in /home/yyz/bigdisk/CenterNet-master0/src/lib/models/networks/DCNv2/_ext.cpython-35m-x86_64-linux-gnu.so)
frame #3: dcn_v2_cuda_forward(at::Tensor const&, at::Tensor const&, at::Tensor const&, at::Tensor const&, at::Tensor const&, int, int, int, int, int, int, int, int, int) + 0xbc0 (0x7f9f1c6a4b50 in /home/yyz/bigdisk/CenterNet-master0/src/lib/models/networks/DCNv2/_ext.cpython-35m-x86_64-linux-gnu.so)
frame #4: dcn_v2_forward(at::Tensor const&, at::Tensor const&, at::Tensor const&, at::Tensor const&, at::Tensor const&, int, int, int, int, int, int, int, int, int) + 0x8b (0x7f9f1c689c0b in /home/yyz/bigdisk/CenterNet-master0/src/lib/models/networks/DCNv2/_ext.cpython-35m-x86_64-linux-gnu.so)
frame #5: + 0x1f91c (0x7f9f1c69591c in /home/yyz/bigdisk/CenterNet-master0/src/lib/models/networks/DCNv2/_ext.cpython-35m-x86_64-linux-gnu.so)
frame #6: + 0x1f99e (0x7f9f1c69599e in /home/yyz/bigdisk/CenterNet-master0/src/lib/models/networks/DCNv2/_ext.cpython-35m-x86_64-linux-gnu.so)
frame #7: + 0x1cdc0 (0x7f9f1c692dc0 in /home/yyz/bigdisk/CenterNet-master0/src/lib/models/networks/DCNv2/_ext.cpython-35m-x86_64-linux-gnu.so)

frame #11: python3() [0x4e3423]
frame #14: THPFunction_apply(_object*, _object*) + 0x6b1 (0x7f9f2e3bf491 in /usr/local/lib/python3.5/dist-packages/torch/lib/libtorch_python.so)
frame #18: python3() [0x4e3537]
frame #22: python3() [0x4e3423]
frame #24: python3() [0x4f08be]
frame #26: python3() [0x55fbf6]
frame #30: python3() [0x4e3537]
frame #34: python3() [0x4e3423]
frame #36: python3() [0x4f08be]
frame #38: python3() [0x55fbf6]
frame #42: python3() [0x4e3537]
frame #46: python3() [0x4e3423]
frame #48: python3() [0x4f08be]
frame #50: python3() [0x55fbf6]
frame #54: python3() [0x4e3537]
frame #58: python3() [0x4e3423]
frame #60: python3() [0x4f08be]
frame #62: python3() [0x55fbf6]

Confusion about why a single conv layer is able to learn the offsets

Hi, I was confused that why a single conv layer is able to learn the offsets, since a conv layer is local connected to the input. So how could it learn the offsets that point to the other positions?
Thanks!

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