Starting train neural network... 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 100/100 [01:19<00:00, 1.25it/s] Training time: 79.83818292617798 Traceback (most recent call last): File "src/scFEA.py", line 370, in <module> main(args) File "src/scFEA.py", line 299, in main fluxStatuTest[i, :] = out_m_batch.detach().numpy() TypeError: can't convert cuda:0 device type tensor to numpy. Use Tensor.cpu() to copy the tensor to host memory first.

[seekning]

sorry. when i running at this part :
Starting train neural network...
100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 100/100 [01:19<00:00, 1.25it/s]
Training time: 79.83818292617798
Traceback (most recent call last):
File "src/scFEA.py", line 370, in
main(args)
File "src/scFEA.py", line 299, in main
fluxStatuTest[i, :] = out_m_batch.detach().numpy()
TypeError: can't convert cuda:0 device type tensor to numpy. Use Tensor.cpu() to copy the tensor to host memory first.

how could i slove this bug ,holp for your request.

[skymoswu]

I editted line 299 in src/scFEA.py to out_m_batch.cpu().detach().numpy() to avoid the error.

[accelerator819]

Hello, I met many issues when I tried to build a conda environment for scFEA, most of them are issues related to package version. Can I see your conda environment with package version?

[skymoswu]

Hello, I met many issues when I tried to build a conda environment for scFEA, most of them are issues related to package version. Can I see your conda environment with package version?

My conda environment is composed of the following packages:

• _libgcc_mutex=0.1=conda_forge
• _openmp_mutex=4.5=2_gnu
• blas=1.0=mkl
• bottleneck=1.3.7=py310ha9d4c09_0
• brotli=1.0.9=h5eee18b_8
• brotli-bin=1.0.9=h5eee18b_8
• brotli-python=1.0.9=py310h6a678d5_8
• bzip2=1.0.8=h5eee18b_6
• ca-certificates=2024.8.30=hbcca054_0
• certifi=2024.8.30=pyhd8ed1ab_0
• charset-normalizer=3.3.2=pyhd3eb1b0_0
• contourpy=1.2.0=py310hdb19cb5_0
• cuda-cudart=12.4.99=hd3aeb46_0
• cuda-cudart_linux-64=12.4.99=h59595ed_0
• cuda-cupti=12.4.127=h6a678d5_1
• cuda-libraries=12.4.0=ha770c72_0
• cuda-nvrtc=12.4.99=hd3aeb46_0
• cuda-nvtx=12.4.127=h6a678d5_1
• cuda-opencl=12.4.99=h59595ed_0
• cuda-runtime=12.4.0=ha804496_0
• cuda-version=12.4=hbda6634_3
• cycler=0.11.0=pyhd3eb1b0_0
• decorator=5.1.1=pyhd3eb1b0_0
• deprecated=1.2.13=py310h06a4308_0
• ffmpeg=4.3=hf484d3e_0
• filelock=3.13.1=py310h06a4308_0
• fonttools=4.51.0=py310h5eee18b_0
• freetype=2.12.1=h4a9f257_0
• future=0.18.3=py310h06a4308_0
• gmp=6.2.1=h295c915_3
• gmpy2=2.1.2=py310heeb90bb_0
• gnutls=3.6.15=he1e5248_0
• gputil=1.4.0=pyh9f0ad1d_0
• graphtools=1.5.3=pyhd8ed1ab_0
• idna=3.7=py310h06a4308_0
• intel-openmp=2023.1.0=hdb19cb5_46306
• jinja2=3.1.4=py310h06a4308_0
• joblib=1.4.2=py310h06a4308_0
• jpeg=9e=h5eee18b_3
• kiwisolver=1.4.4=py310h6a678d5_0
• lame=3.100=h7b6447c_0
• lcms2=2.12=h3be6417_0
• ld_impl_linux-64=2.38=h1181459_1
• lerc=3.0=h295c915_0
• libbrotlicommon=1.0.9=h5eee18b_8
• libbrotlidec=1.0.9=h5eee18b_8
• libbrotlienc=1.0.9=h5eee18b_8
• libcublas=12.4.2.65=hd3aeb46_0
• libcufft=11.2.0.44=hd3aeb46_0
• libcufile=1.9.0.20=hd3aeb46_0
• libcurand=10.3.5.119=hd3aeb46_0
• libcusolver=11.6.0.99=hd3aeb46_0
• libcusparse=12.3.0.142=hd3aeb46_0
• libdeflate=1.17=h5eee18b_1
• libffi=3.4.4=h6a678d5_1
• libgcc=14.1.0=h77fa898_1
• libgcc-ng=14.1.0=h69a702a_1
• libgfortran-ng=11.2.0=h00389a5_1
• libgfortran5=11.2.0=h1234567_1
• libgomp=14.1.0=h77fa898_1
• libiconv=1.16=h5eee18b_3
• libidn2=2.3.4=h5eee18b_0
• libjpeg-turbo=2.0.0=h9bf148f_0
• libllvm14=14.0.6=hdb19cb5_3
• libnpp=12.2.5.2=hd3aeb46_0
• libnvfatbin=12.4.99=hd3aeb46_0
• libnvjitlink=12.4.99=hd3aeb46_0
• libnvjpeg=12.3.1.89=h59595ed_0
• libopenblas=0.3.21=h043d6bf_0
• libpng=1.6.39=h5eee18b_0
• libstdcxx=14.1.0=hc0a3c3a_1
• libstdcxx-ng=14.1.0=h4852527_1
• libtasn1=4.19.0=h5eee18b_0
• libtiff=4.5.1=h6a678d5_0
• libunistring=0.9.10=h27cfd23_0
• libuuid=1.41.5=h5eee18b_0
• libwebp-base=1.3.2=h5eee18b_0
• llvm-openmp=14.0.6=h9e868ea_0
• llvmlite=0.43.0=py310h6a678d5_0
• lz4-c=1.9.4=h6a678d5_1
• magic-impute=3.0.0=pyh7cba7a3_0
• markupsafe=2.1.3=py310h5eee18b_0
• matplotlib-base=3.9.2=py310hbfdbfaf_0
• mkl=2023.1.0=h213fc3f_46344
• mkl-service=2.4.0=py310h5eee18b_1
• mkl_fft=1.3.8=py310h5eee18b_0
• mkl_random=1.2.4=py310hdb19cb5_0
• mpc=1.1.0=h10f8cd9_1
• mpfr=4.0.2=hb69a4c5_1
• mpmath=1.3.0=py310h06a4308_0
• ncurses=6.4=h6a678d5_0
• nettle=3.7.3=hbbd107a_1
• networkx=3.3=py310h06a4308_0
• numba=0.60.0=py310h5dc88bb_0
• numexpr=2.8.7=py310h85018f9_0
• numpy=1.26.4=py310h5f9d8c6_0
• numpy-base=1.26.4=py310hb5e798b_0
• ocl-icd=2.3.2=h5eee18b_1
• openh264=2.1.1=h4ff587b_0
• openjpeg=2.5.2=he7f1fd0_0
• openssl=3.3.2=hb9d3cd8_0
• packaging=24.1=py310h06a4308_0
• pandas=2.2.2=py310h6a678d5_0
• pillow=10.4.0=py310h5eee18b_0
• pip=24.2=py310h06a4308_0
• pybind11-abi=4=hd3eb1b0_1
• pygsp=0.5.1=py_0
• pynndescent=0.5.10=py310h06a4308_0
• pyparsing=3.1.2=py310h06a4308_0
• pysocks=1.7.1=py310h06a4308_0
• python=3.10.14=h955ad1f_1
• python-dateutil=2.9.0post0=py310h06a4308_2
• python-tzdata=2023.3=pyhd3eb1b0_0
• python_abi=3.10=2_cp310
• pytorch=2.4.0=py3.10_cuda12.4_cudnn9.1.0_0
• pytorch-cuda=12.4=hc786d27_6
• pytorch-mutex=1.0=cuda
• pytz=2024.1=py310h06a4308_0
• pyyaml=6.0.1=py310h5eee18b_0
• readline=8.2=h5eee18b_0
• requests=2.32.3=py310h06a4308_0
• scikit-learn=1.5.1=py310h1128e8f_0
• scipy=1.13.1=py310h5f9d8c6_0
• scprep=1.2.3=pyhdfd78af_0
• setuptools=72.1.0=py310h06a4308_0
• six=1.16.0=pyhd3eb1b0_1
• sqlite=3.45.3=h5eee18b_0
• sympy=1.13.2=py310h06a4308_0
• tasklogger=1.2.0=pyhd8ed1ab_0
• tbb=2021.8.0=hdb19cb5_0
• threadpoolctl=3.5.0=py310h2f386ee_0
• tk=8.6.14=h39e8969_0
• torchtriton=3.0.0=py310
• torchvision=0.19.0=py310_cu124
• tqdm=4.66.5=py310h2f386ee_0
• typing_extensions=4.11.0=py310h06a4308_0
• tzdata=2024a=h04d1e81_0
• umap-learn=0.5.3=py310h06a4308_0
• unicodedata2=15.1.0=py310h5eee18b_0
• urllib3=2.2.2=py310h06a4308_0
• wheel=0.43.0=py310h06a4308_0
• wrapt=1.14.1=py310h5eee18b_0
• xz=5.4.6=h5eee18b_1
• yaml=0.2.5=h7b6447c_0
• zlib=1.2.13=h5eee18b_1
• zstd=1.5.5=hc292b87_2

[accelerator819]

Really thx!