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Pytorch-based tools for visualizing and understanding the neurons of a GAN. https://gandissect.csail.mit.edu/

License: MIT License

HTML 6.72% Python 79.38% C 0.68% C++ 0.15% Cuda 3.35% Shell 1.73% Jupyter Notebook 7.99%

pytorch gan image-manipulation deep-learning interactive-visualizations generative-adversarial-network interpretable-ml

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liao1995 ideaplexus shafiahmed shyamalschandra shubhampachori12110095 ml-lab mtlong jerofad hephaex linhanxiao samangel93 expert68 showkeyjar o7s8r6 tangxinofchina pandinosaurus shimion100 jackylee1 buaazb cclauss visionandy tuchang avatarworld hhsummerwind devhttps kekedan daiiyu leochencipher syzer tobyclh ex082 scapeqin eight-diagram anastasiianovikova stjordanis trendingtechnology hbcbh1999 zedzero hhy5277 dantodor esmaeilinia jaynoel unax127 sigmind benzei codeaudit fytrace murari023 nhu2000 dataxujing maihau nikolayvoronchikhin gridl nunofernandes-plight amseej ashritdeebadi maximr kjeanclaude yaya319 iamarocks mengjutsai iamsile siangfrank fluctlux baiti01 eyebies tony32769 stc-cqupt quixoticblink asankagp amirunpri2018 avnishxlr8 haifengzeng gauthamn letsdodatascience ttklm20 xeransis piegu jin7788 skymysky albo-ai awesomemachinelearning zhenzhenpeng nicolepcx hpp340 hello-anmol marcosgodoy arthur-qiu yyht cannoneyed vigneshgig dengpingling yuhonghong66 duhuajiang a415432669 cedrickchee qinhuaping nanshuiyu charlottesean bigdatasciencegroup

gandissect's Issues

GANPaint non-GAN images?

Is it possible to paint images that have not been generated from the GAN itself?

would you mind providing more details of implementation of getting the casual α in the paper

hello , i am very interested in the implementation of getting the casual α in the published paper while this git has not included , would you mind instruct some details about the prcoess to get the casula α？ thank you very much.

Excuse me, but I just find nothing in my directory "dissect" and thus no "dissect.json" found

some doubts about gan painting

Hello, what an excellent job you have done from gan dissection to gan painting and gan rewritting, i have carefully read the paper "GAN Dissection: Visualizing and Understanding Generative Adversarial Networks" and the paper "Semantic Photo Manipulation with a Generative Image Prior". 
 In particular,  i have doubts about how to intervention the middle layer in gan to draw/remove the user-specified semantic concepts in the **user-marked area** in output image, for example , in gan-painting(https://ganpaint.io/), we could choose some marked region and use the gan dissection to find the units in the middle layer associated with most matched concept , then choose some way to edit the units in the middle layer like insert value k in the units

The question is hou to ensure that **the position of the middle layer editor will  correspond exactly to the position that calibrated by the user in the output image**。gan dissection , in my opinion , would find the agreement between the concept in the output image and the unit(feature map) in the middle layer, wheras , it would not ensure the concept just appears in the are drawn by the user.
 It is clear to understand the match between the concept and the unit,  but i have doubts about the match between the location area of the concept and the editing area in the unit. would you mind giving me more details on this issue ?

What is the difference between the fullablated.py and evalablate.py ?

Very appreciate if someone knowns it. 😁

enhancement - docker container for localhost site

maybe able to leverage this repo https://github.com/anibali/docker-pytorch

this would allow users to get up and running with a single command.

I used miniconda with docker the other week. There was a couple of gotchas.

https://hub.docker.com/r/continuumio/miniconda/

RuntimeError: CUDA error: out of memory

I have the problem:
RuntimeError: CUDA error: out of memory

although I have change the batch_size to 1

Support for pytorch 1.0.1

Will there be plan to have the script support pytorch 1.0.1? I got the following error when executing ./travis.sh with pytorch 1.0.1: "ImportError: torch.utils.ffi is deprecated. Please use cpp extensions instead"

Custom dataset

I'm trying to train on my own dataset. I created a data loader class like this

I call the dissect model like this

But I keep getting an indexing error.

Can anybody help me with this issue?

stylegan2

Dear CSAILVision team,

Thank you for sharing with us the great implementation.

Is there a easy way to apply this mehtod for stylegan or stylegan2?

Thank you for your help.

Best Wishes,

Alex

change the gan model and dataset

hello, I am interested in your work. could you tell me which .py files should change if I want to change the gan model as my own encode-decode gan model and own dataset?

GanImageSegmenter

Is there any code provided for GanImageSegmenter as used in ablate.py?

'EasyDict' object has no attribute 'settings' when trying to run the server

Hi, i have been trying to run the server however i have been given this bug:
'EasyDict' object has no attribute 'settings'.
This happens when the config is passed from server.py into serverstate.py and config.settings is passed into GanTester.
If i print each key in config.keys(), i get the following list:
netname
meta
default_ranking
quantile_threshold
iou_threshold
iqr_threshold
segcolors
layers,
none of them being settings. Am i missing something here?
i have tried importing and running server.py in google colab as well as using the command line interface and getting the same bug for both.

Edit1: I have realised why i don't have a settings attribute. In the main file, the settings is created by creating a dictionary of all the arguments passed in when running netdissect on the command line. The generate_report() function in dissection.py will pass the settings into dissect.json which is the config that is passed into load_projects() but only if there is a value for settings. The value for settings is defaulted to None and since i'm importing dissection.py into google colab, the settings value doesn't change and isn't passed into the top_record dictionary which stores the report. Therefore, config.settings doesn't exist and so i get the bug from above. I am going to work on editing the dissection code so that it adds a settings field to the report. If i can get that working, i will post the updated version here so that people are able to dissect a model and load the server to view the dissection without using the command line.

cannot import prroi_pool2d?

Windows10
cudatoolkit 9.0
python 3.6
pytorch 1.1.0
torchvision 0.3.0

C:\Users\86189\Anaconda3\envs\py36\lib\site-packages\torch\utils\cpp_extension.py:184: UserWarning: Error checking compiler version for cl: Command 'cl' returned non-zero exit status 1.
warnings.warn('Error checking compiler version for {}: {}'.format(compiler, error))
Traceback (most recent call last):
File "C:\Users\86189\Anaconda3\envs\py36\lib\site-packages\torch\utils\cpp_extension.py", line 949, in _build_extension_module
check=True)
File "C:\Users\86189\Anaconda3\envs\py36\lib\subprocess.py", line 438, in run
output=stdout, stderr=stderr)
subprocess.CalledProcessError: Command '['ninja', '-v']' returned non-zero exit status 1.

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "C:\Users\86189\Anaconda3\envs\py36\lib\runpy.py", line 193, in run_module_as_main
"main", mod_spec)
File "C:\Users\86189\Anaconda3\envs\py36\lib\runpy.py", line 85, in run_code
exec(code, run_globals)
File "C:\Users\86189\Desktop\GANDissection\netdissect_main.py", line 410, in
main()
File "C:\Users\86189\Desktop\GANDissection\netdissect_main.py", line 220, in main
segrunner = GeneratorSegRunner(autoimport_eval(args.segmenter))
File "C:\Users\86189\Desktop\GANDissection\netdissect\autoeval.py", line 36, in autoimport_eval
return eval(term, {}, AutoImportDict())
File "", line 1, in
File "C:\Users\86189\Desktop\GANDissection\netdissect\segmenter.py", line 68, in init
segarch, segvocab, epoch)
File "C:\Users\86189\Desktop\GANDissection\netdissect\segmenter.py", line 502, in load_unified_parsing_segmentation_model
weights=os.path.join(segmodel_dir, 'decoder_epoch_%d.pth' % epoch))
File "C:\Users\86189\Desktop\GANDissection\netdissect\upsegmodel\models.py", line 215, in build_decoder
fpn_dim=512)
File "C:\Users\86189\Desktop\GANDissection\netdissect\upsegmodel\models.py", line 271, in init
from .prroi_pool import PrRoIPool2D
File "C:\Users\86189\Desktop\GANDissection\netdissect\upsegmodel\prroi_pool_init_.py", line 12, in
from .prroi_pool import *
File "C:\Users\86189\Desktop\GANDissection\netdissect\upsegmodel\prroi_pool\prroi_pool.py", line 14, in
from .functional import prroi_pool2d
File "C:\Users\86189\Desktop\GANDissection\netdissect\upsegmodel\prroi_pool\functional.py", line 22, in
verbose=False
File "C:\Users\86189\Anaconda3\envs\py36\lib\site-packages\torch\utils\cpp_extension.py", line 644, in load
is_python_module)
File "C:\Users\86189\Anaconda3\envs\py36\lib\site-packages\torch\utils\cpp_extension.py", line 813, in jit_compile
with_cuda=with_cuda)
File "C:\Users\86189\Anaconda3\envs\py36\lib\site-packages\torch\utils\cpp_extension.py", line 866, in write_ninja_file_and_build
build_extension_module(name, build_directory, verbose)
File "C:\Users\86189\Anaconda3\envs\py36\lib\site-packages\torch\utils\cpp_extension.py", line 962, in build_extension_module
raise RuntimeError(message)
RuntimeError: Error building extension 'prroi_pooling': b'[1/3] cl /showIncludes -DTORCH_EXTENSION_NAME=prroi_pooling -DTORCH_API_INCLUDE_EXTENSION_H -IC:\Users\86189\Anaconda3\envs\py36\lib\site-packages\torch\include -IC:\Users\86189\Anaconda3\envs\py36\lib\site-packages\torch\include\torch\csrc\api\include -IC:\Users\86189\Anaconda3\envs\py36\lib\site-packages\torch\include\TH
-IC:\Users\86189\Anaconda3\envs\py36\lib\site-packages\torch\include\THC "-IC:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1\include" -IC:\Users\86189\Anaconda3\envs\py36\Include -D_GLIBCXX_USE_CXX11_ABI=0 -fPIC -std=c++11 -c C:\Users\86189\Desktop\GANDissection\netdissect\upsegmodel\prroi_pool\src\prroi_pooling_gpu.c /Foprroi_pooling_gpu.o\r\nFAILED: prroi_pooling_gpu.o \r\ncl /showIncludes -DTORCH_EXTENSION_NAME=prroi_pooling -DTORCH_API_INCLUDE_EXTENSION_H -IC:\Users\86189\Anaconda3\envs\py36\lib\site-packages\torch\include -IC:\Users\86189\Anaconda3\envs\py36\lib\site-packages\torch\include\torch\csrc\api\include -IC:\Users\86189\Anaconda3\envs\py36\lib\site-packages\torch\include\TH -IC:\Users\86189\Anaconda3\envs\py36\lib\site-packages\torch\include\THC "-IC:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1\include" -IC:\Users\86189\Anaconda3\envs\py36\Include -D_GLIBCXX_USE_CXX11_ABI=0 -fPIC -std=c++11 -c C:\Users\86189\Desktop\GANDissection\netdissect\upsegmodel\prroi_pool\src\prroi_pooling_gpu.c /Foprroi_pooling_gpu.o\r\nTraceback (most recent call last):\n File "c:\users\86189\anaconda3\envs\pytorch\lib\runpy.py", line 193, in run_module_as_main\n "main", mod_spec)\n File "c:\users\86189\anaconda3\envs\pytorch\lib\runpy.py", line
85, in run_code\n exec(code, run_globals)\n File "C:\Users\86189\Anaconda3\envs\pytorch\Scripts\cl.exe\main.py", line 4, in \n File "c:\users\86189\anaconda3\envs\pytorch\lib\site-packages\cl\bin\cl.py", line 5, in \n from kombu import Connection\n File "c:\users\86189\anaconda3\envs\pytorch\lib\site-packages\kombu\init.py", line 81, in getattr\n
module = import(object_origins[name], None, None, [name])\n File "c:\users\86189\anaconda3\envs\pytorch\lib\site-packages\kombu\connection.py", line 23, in \n from kombu import exceptions\n File "c:\users\86189\anaconda3\envs\pytorch\lib\site-packages\kombu\exceptions.py", line 6, in \n from amqp import ChannelError, ConnectionError, ResourceError\n File "c:\users\86189\anaconda3\envs\pytorch\lib\site-packages\amqp\init.py", line 33, in \n from .connection import Connection # noqa\n File "c:\users\86189\anaconda3\envs\pytorch\lib\site-packages\amqp\connection.py", line 21, in \n from .transport
import Transport\n File "c:\users\86189\anaconda3\envs\pytorch\lib\site-packages\amqp\transport.py", line 8, in \n import ssl\n File "c:\users\86189\anaconda3\envs\pytorch\lib\ssl.py", line 98, in \n import ssl # if we can't import it, let the error propagate\nImportError: DLL load failed: \xd5\xd2\xb2\xbb\xb5\xbd\xd6\xb8\xb6\xa8\xb5\xc4\xc4\xa3\xbf\xe9\xa1\xa3\n[2/3] C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1\bin\nvcc -DTORCH_EXTENSION_NAME=prroi_pooling -DTORCH_API_INCLUDE_EXTENSION_H -IC:\Users\86189\Anaconda3\envs\py36\lib\site-packages\torch\include -IC:\Users\86189\Anaconda3\envs\py36\lib\site-packages\torch\include\torch\csrc\api\include -IC:\Users\86189\Anaconda3\envs\py36\lib\site-packages\torch\include\TH -IC:\Users\86189\Anaconda3\envs\py36\lib\site-packages\torch\include\THC "-IC:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1\include" -IC:\Users\86189\Anaconda3\envs\py36\Include -D_GLIBCXX_USE_CXX11_ABI=0 -D__CUDA_NO_HALF_OPERATORS -D__CUDA_NO_HALF_CONVERSIONS -D__CUDA_NO_HALF2_OPERATORS -c C:\Users\86189\Desktop\GANDissection\netdissect\upsegmodel\prroi_pool\src\prroi_pooling_gpu_impl.cu -o prroi_pooling_gpu_impl.cuda.o\r\nFAILED: prroi_pooling_gpu_impl.cuda.o \r\nC:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1\bin\nvcc -DTORCH_EXTENSION_NAME=prroi_pooling -DTORCH_API_INCLUDE_EXTENSION_H -IC:\Users\86189\Anaconda3\envs\py36\lib\site-packages\torch\include -IC:\Users\86189\Anaconda3\envs\py36\lib\site-packages\torch\include\torch\csrc\api\include -IC:\Users\86189\Anaconda3\envs\py36\lib\site-packages\torch\include\TH -IC:\Users\86189\Anaconda3\envs\py36\lib\site-packages\torch\include\THC "-IC:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1\include" -IC:\Users\86189\Anaconda3\envs\py36\Include -D_GLIBCXX_USE_CXX11_ABI=0 -D__CUDA_NO_HALF_OPERATORS -D__CUDA_NO_HALF_CONVERSIONS -D__CUDA_NO_HALF2_OPERATORS -c C:\Users\86189\Desktop\GANDissection\netdissect\upsegmodel\prroi_pool\src\prroi_pooling_gpu_impl.cu -o prroi_pooling_gpu_impl.cuda.o\r\nTraceback (most recent call last):\r\n File "c:\users\86189\anaconda3\envs\pytorch\lib\runpy.py", line 193, in _run_module_as_main\r\n "main", mod_spec)\r\n File "c:\users\86189\anaconda3\envs\pytorch\lib\runpy.py", line 85, in _run_code\r\n exec(code, run_globals)\r\n File "C:\Users\86189\Anaconda3\envs\pytorch\Scripts\cl.exe\main.py", line 4, in \r\n File "c:\users\86189\anaconda3\envs\pytorch\lib\site-packages\cl\bin\cl.py", line 5, in \r\n from kombu import Connection\r\n File "c:\users\86189\anaconda3\envs\pytorch\lib\site-packages\kombu\init.py", line 81, in getattr\r\n module = import(object_origins[name], None, None, [name])\r\n File "c:\users\86189\anaconda3\envs\pytorch\lib\site-packages\kombu\connection.py", line 23, in \r\n from kombu import exceptions\r\n File "c:\users\86189\anaconda3\envs\pytorch\lib\site-packages\kombu\exceptions.py", line 6, in \r\n from amqp import ChannelError, ConnectionError, ResourceError\r\n File "c:\users\86189\anaconda3\envs\pytorch\lib\site-packages\amqp\init.py", line 33, in \r\n from .connection import Connection # noqa\r\n
File "c:\users\86189\anaconda3\envs\pytorch\lib\site-packages\amqp\connection.py", line 21, in \r\n from .transport import Transport\r\n File "c:\users\86189\anaconda3\envs\pytorch\lib\site-packages\amqp\transport.py", line 8, in \r\n import ssl\r\n File "c:\users\86189\anaconda3\envs\pytorch\lib\ssl.py", line 98, in \r\n import _ssl # if we can't import it, let the error propagate\r\nImportError: DLL load failed: \xd5\xd2\xb2\xbb\xb5\xbd\xd6\xb8\xb6\xa8\xb5\xc4\xc4\xa3\xbf\xe9\xa1\xa3\r\nninja: build stopped: subcommand failed.\r\n'

Failed at 'Making images:'

I met a problem when run 'Dissecting a GAN'. When the program is at the stage of 'Making Images:', it shuts down without releasing any error. Do you have specific requirements about the GPUs?

How to train own dataset

Thanks to your share.I am interested in your job,And I want to know how to train own dataset.Could you help me ?Thanks!

Lack of paint_select

package.json under folder client indicates a url git+ssh://[email protected]/HendrikStrobelt/paint_widget_js.git which is currently not available.
Could the team republic it?

Which part code can ablate "artifact" units and improve results?

Thank you for this amazing work.
I am wondering which part code can ablate "artifact" units and improve results, as what Fig. 1 (f) and (g) in your paper do?

CreateProcess failed: The system cannot find the file specified.;subprocess.CalledProcessError: Command '['ninja', '-v']' returned non-zero exit status 3221226356.

hi,CSAILVision team,
i have installed ninja, but i still cause a problem.
PS D:\Users\wei22\Desktop\gandissect\gandissect-master> python -m netdissect --gan --model "netdissect.proggan.from_pth_file('models/karras/livingroom_lsun.pth')" --outdir "dissect/livingroom" --layer layer1 layer4 layer7 --size 1000
D:\Users\wei22\Desktop\gandissect\gandissect-master\netdissect\upsegmodel\prroi_pool\src
Using C:\Users\wei22\AppData\Local\torch_extensions\torch_extensions\Cache\py36_cu113 as PyTorch extensions root...
Detected CUDA files, patching ldflags
Emitting ninja build file C:\Users\wei22\AppData\Local\torch_extensions\torch_extensions\Cache\py36_cu113_prroi_pooling\build.ninja...
Building extension module prroi_pooling...
Allowing ninja to set a default number of workers... (overridable by setting the environment variable MAX_JOBS=N)
[1/3] C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA\v11.3\bin\nvcc --generate-dependencies-with-compile --dependency-output prroi_pooling_gpu_impl.cuda.o.d -Xcudafe --diag_suppre
ss=dll_interface_conflict_dllexport_assumed -Xcudafe --diag_suppress=dll_interface_conflict_none_assumed -Xcudafe --diag_suppress=field_without_dll_interface -Xcudafe --diag_suppress=
base_class_has_different_dll_interface -Xcompiler /EHsc -Xcompiler /wd4190 -Xcompiler /wd4018 -Xcompiler /wd4275 -Xcompiler /wd4267 -Xcompiler /wd4244 -Xcompiler /wd4251 -Xcompiler /w
d4819 -Xcompiler /MD -DTORCH_EXTENSION_NAME=prroi_pooling -DTORCH_API_INCLUDE_EXTENSION_H -ID:\Users\wei22\Desktop\gandissect\venv\lib\site-packages\torch\include -ID:\Users\wei22\De
sktop\gandissect\venv\lib\site-packages\torch\include\torch\csrc\api\include -ID:\Users\wei22\Desktop\gandissect\venv\lib\site-packages\torch\include\TH -ID:\Users\wei22\Desktop\gandi
ssect\venv\lib\site-packages\torch\include\THC "-IC:/Program Files/NVIDIA GPU Computing Toolkit/CUDA\v11.3\include" -IC:\Users\wei22.conda\envs\netd\Include -D_GLIBCXX_USE_CXX11_ABI=
0 -D__CUDA_NO_HALF_OPERATORS -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_BFLOAT16_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr -gencode=arch=compute_61,code=c
ompute_61 -gencode=arch=compute_61,code=sm_61 -c D:\Users\wei22\Desktop\gandissect\gandissect-master\netdissect\upsegmodel\prroi_pool\src\prroi_pooling_gpu_impl.cu -o prroi_pooling_gpu_impl.cuda.o
FAILED: prroi_pooling_gpu_impl.cuda.o
C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA\v11.3\bin\nvcc --generate-dependencies-with-compile --dependency-output prroi_pooling_gpu_impl.cuda.o.d -Xcudafe --diag_suppress=dll
interface_conflict_dllexport_assumed -Xcudafe --diag_suppress=dll_interface_conflict_none_assumed -Xcudafe --diag_suppress=field_without_dll_interface -Xcudafe --diag_suppress=base_c
lass_has_different_dll_interface -Xcompiler /EHsc -Xcompiler /wd4190 -Xcompiler /wd4018 -Xcompiler /wd4275 -Xcompiler /wd4267 -Xcompiler /wd4244 -Xcompiler /wd4251 -Xcompiler /wd4819
-Xcompiler /MD -DTORCH_EXTENSION_NAME=prroi_pooling -DTORCH_API_INCLUDE_EXTENSION_H -ID:\Users\wei22\Desktop\gandissect\venv\lib\site-packages\torch\include -ID:\Users\wei22\Desktop
gandissect\venv\lib\site-packages\torch\include\torch\csrc\api\include -ID:\Users\wei22\Desktop\gandissect\venv\lib\site-packages\torch\include\TH -ID:\Users\wei22\Desktop\gandissect
venv\lib\site-packages\torch\include\THC "-IC:/Program Files/NVIDIA GPU Computing Toolkit/CUDA\v11.3\include" -IC:\Users\wei22.conda\envs\netd\Include -D_GLIBCXX_USE_CXX11_ABI=0 -D
CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_BFLOAT16_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr -gencode=arch=compute_61,code=compute
_61 -gencode=arch=compute_61,code=sm_61 -c D:\Users\wei22\Desktop\gandissect\gandissect-master\netdissect\upsegmodel\prroi_pool\src\prroi_pooling_gpu_impl.cu -o prroi_pooling_gpu_impl.cuda.o
CreateProcess failed: The system cannot find the file specified.
Traceback (most recent call last):
File "D:\Users\wei22\Desktop\gandissect\venv\lib\site-packages\torch\utils\cpp_extension.py", line 1723, in _run_ninja_build
env=env)
File "C:\Users\wei22.conda\envs\netd\lib\subprocess.py", line 438, in run
output=stdout, stderr=stderr)
subprocess.CalledProcessError: Command '['ninja', '-v']' returned non-zero exit status 3221226356.

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
File "C:\Users\wei22.conda\envs\netd\lib\runpy.py", line 193, in _run_module_as_main
"main", mod_spec)
File "C:\Users\wei22.conda\envs\netd\lib\runpy.py", line 85, in run_code
exec(code, run_globals)
File "D:\Users\wei22\Desktop\gandissect\gandissect-master\netdissect_main.py", line 409, in
File "D:\Users\wei22\Desktop\gandissect\gandissect-master\netdissect\upsegmodel\prroi_pool\prroi_pool.py", line 14, in
from .functional import prroi_pool2d
File "D:\Users\wei22\Desktop\gandissect\gandissect-master\netdissect\upsegmodel\prroi_pool\functional.py", line 23, in
verbose=True
File "D:\Users\wei22\Desktop\gandissect\venv\lib\site-packages\torch\utils\cpp_extension.py", line 1136, in load
keep_intermediates=keep_intermediates)
File "D:\Users\wei22\Desktop\gandissect\venv\lib\site-packages\torch\utils\cpp_extension.py", line 1347, in _jit_compile
is_standalone=is_standalone)
File "D:\Users\wei22\Desktop\gandissect\venv\lib\site-packages\torch\utils\cpp_extension.py", line 1452, in _write_ninja_file_and_build_library
error_prefix=f"Error building extension '{name}'")
File "D:\Users\wei22\Desktop\gandissect\venv\lib\site-packages\torch\utils\cpp_extension.py", line 1733, in _run_ninja_build
raise RuntimeError(message) from e
RuntimeError: Error building extension '_prroi_pooling'

My environment:
window 11
ninja 1.10.2
torch 1.10.2+cu113

Do you have any idea why that's happening?
Can you upload the pre-trained models elsewhere?

Thanks!