Google collab

[DikshuSharma]

the google collab notebook is not working on cell # Install DPVO

[RohaanA]

The notebook is completely functional, I just ran it multiple times today. Can you please share your error?

[2022yingjie]

The notebook is completely functional, I just ran it multiple times today. Can you please share your error?

Hi, could you pls show us which GPU you selected, I have a similar problem, that is the colab cannot be configured well. Thank you

[mnauf]

it fails here while installing DPVO

/content/WHAM/third-party/DPVO --2024-05-18 14:29:13-- https://gitlab.com/libeigen/eigen/-/archive/3.4.0/eigen-3.4.0.zip Resolving gitlab.com (gitlab.com)... 172.65.251.78, 2606:4700:90:0:f22e:fbec:5bed:a9b9 Connecting to gitlab.com (gitlab.com)|172.65.251.78|:443... connected. HTTP request sent, awaiting response... 200 OK Length: unspecified [application/zip] Saving to: ‘eigen-3.4.0.zip’

eigen-3.4.0.zip [ <=> ] 3.53M --.-KB/s in 0.09s

2024-05-18 14:29:13 (37.6 MB/s) - ‘eigen-3.4.0.zip’ saved [3700486]

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inflating: thirdparty/eigen-3.4.0/unsupported/test/levenberg_marquardt.cpp
inflating: thirdparty/eigen-3.4.0/unsupported/test/matrix_exponential.cpp
inflating: thirdparty/eigen-3.4.0/unsupported/test/matrix_function.cpp
inflating: thirdparty/eigen-3.4.0/unsupported/test/matrix_functions.h
inflating: thirdparty/eigen-3.4.0/unsupported/test/matrix_power.cpp
inflating: thirdparty/eigen-3.4.0/unsupported/test/matrix_square_root.cpp
inflating: thirdparty/eigen-3.4.0/unsupported/test/minres.cpp
inflating: thirdparty/eigen-3.4.0/unsupported/test/mpreal_support.cpp
inflating: thirdparty/eigen-3.4.0/unsupported/test/openglsupport.cpp
inflating: thirdparty/eigen-3.4.0/unsupported/test/polynomialsolver.cpp
inflating: thirdparty/eigen-3.4.0/unsupported/test/polynomialutils.cpp
inflating: thirdparty/eigen-3.4.0/unsupported/test/sparse_extra.cpp
inflating: thirdparty/eigen-3.4.0/unsupported/test/special_functions.cpp
inflating: thirdparty/eigen-3.4.0/unsupported/test/special_packetmath.cpp
inflating: thirdparty/eigen-3.4.0/unsupported/test/splines.cpp
Channels:

• rusty1s
• conda-forge
• pytorch
• iopath Platform: linux-64 Collecting package metadata (repodata.json): done Solving environment: done

==> WARNING: A newer version of conda exists. <== current version: 23.11.0 latest version: 24.5.0

Please update conda by running

$ conda update -n base -c conda-forge conda

Package Plan

environment location: /usr/local/envs/wham

added / updated specs:

• pytorch-scatter=2.0.9

The following packages will be downloaded:

package                    |            build
---------------------------|-----------------
pytorch-scatter-2.0.9      |py39_torch_1.11.0_cu113         4.7 MB  rusty1s
------------------------------------------------------------
                                       Total:         4.7 MB

The following NEW packages will be INSTALLED:

pytorch-scatter rusty1s/linux-64::pytorch-scatter-2.0.9-py39_torch_1.11.0_cu113

Downloading and Extracting Packages:

Preparing transaction: done Verifying transaction: done Executing transaction: done Channels:

• conda-forge
• pytorch
• iopath
• rusty1s Platform: linux-64 Collecting package metadata (repodata.json): done Solving environment: done

==> WARNING: A newer version of conda exists. <== current version: 23.11.0 latest version: 24.5.0

Please update conda by running

$ conda update -n base -c conda-forge conda

Package Plan

environment location: /usr/local/envs/wham

added / updated specs:

• cudatoolkit-dev=11.3.1

The following packages will be downloaded:

package                    |            build
---------------------------|-----------------
cudatoolkit-dev-11.3.1     |   py39h3811e60_0           8 KB  conda-forge
------------------------------------------------------------
                                       Total:           8 KB

The following NEW packages will be INSTALLED:

cudatoolkit-dev conda-forge/linux-64::cudatoolkit-dev-11.3.1-py39h3811e60_0

Downloading and Extracting Packages:

Preparing transaction: done Verifying transaction: done Executing transaction: done Channels:

• conda-forge
• pytorch
• iopath
• rusty1s Platform: linux-64 Collecting package metadata (repodata.json): done Solving environment: done

==> WARNING: A newer version of conda exists. <== current version: 23.11.0 latest version: 24.5.0

Please update conda by running

$ conda update -n base -c conda-forge conda

Package Plan

environment location: /usr/local/envs/wham

added / updated specs:

• gxx=9.5

The following packages will be downloaded:

package                    |            build
---------------------------|-----------------
binutils_impl_linux-64-2.40|       ha885e6a_0         5.5 MB  conda-forge
gcc-9.5.0                  |      h1fea6ba_13          26 KB  conda-forge
gcc_impl_linux-64-9.5.0    |      h99780fb_19        43.5 MB  conda-forge
gxx-9.5.0                  |      h1fea6ba_13          26 KB  conda-forge
gxx_impl_linux-64-9.5.0    |      h99780fb_19        10.6 MB  conda-forge
kernel-headers_linux-64-2.6.32|      he073ed8_17         694 KB  conda-forge
libgcc-devel_linux-64-9.5.0|      h0a57e50_19         4.0 MB  conda-forge
libsanitizer-9.5.0         |      h2f262e1_19         6.9 MB  conda-forge
libstdcxx-devel_linux-64-9.5.0|      h0a57e50_19         9.9 MB  conda-forge
sysroot_linux-64-2.12      |      he073ed8_17        14.4 MB  conda-forge
------------------------------------------------------------
                                       Total:        95.6 MB

The following NEW packages will be INSTALLED:

binutils_impl_lin~ conda-forge/linux-64::binutils_impl_linux-64-2.40-ha885e6a_0 gcc conda-forge/linux-64::gcc-9.5.0-h1fea6ba_13 gcc_impl_linux-64 conda-forge/linux-64::gcc_impl_linux-64-9.5.0-h99780fb_19 gxx conda-forge/linux-64::gxx-9.5.0-h1fea6ba_13 gxx_impl_linux-64 conda-forge/linux-64::gxx_impl_linux-64-9.5.0-h99780fb_19 kernel-headers_li~ conda-forge/noarch::kernel-headers_linux-64-2.6.32-he073ed8_17 libgcc-devel_linu~ conda-forge/linux-64::libgcc-devel_linux-64-9.5.0-h0a57e50_19 libsanitizer conda-forge/linux-64::libsanitizer-9.5.0-h2f262e1_19 libstdcxx-devel_l~ conda-forge/linux-64::libstdcxx-devel_linux-64-9.5.0-h0a57e50_19 sysroot_linux-64 conda-forge/noarch::sysroot_linux-64-2.12-he073ed8_17

Downloading and Extracting Packages: gcc_impl_linux-64-9. | 43.5 MB | : 0% 0/1 [00:00<?, ?it/s] sysroot_linux-64-2.1 | 14.4 MB | : 0% 0/1 [00:00<?, ?it/s]

gxx_impl_linux-64-9. | 10.6 MB | : 0% 0/1 [00:00<?, ?it/s]

libstdcxx-devel_linu | 9.9 MB | : 0% 0/1 [00:00<?, ?it/s]

libsanitizer-9.5.0 | 6.9 MB | : 0% 0/1 [00:00<?, ?it/s]

binutils_impl_linux- | 5.5 MB | : 0% 0/1 [00:00<?, ?it/s]

libgcc-devel_linux-6 | 4.0 MB | : 0% 0/1 [00:00<?, ?it/s]

kernel-headers_linux | 694 KB | : 0% 0/1 [00:00<?, ?it/s]

gcc-9.5.0 | 26 KB | : 0% 0/1 [00:00<?, ?it/s]

gxx-9.5.0 | 26 KB | : 0% 0/1 [00:00<?, ?it/s]

libsanitizer-9.5.0 | 6.9 MB | : 0% 0.0022566352362077564/1 [00:00<01:01, 61.43s/it] sysroot_linux-64-2.1 | 14.4 MB | : 0% 0.0010830876433013733/1 [00:00<02:23, 144.11s/it]

gxx_impl_linux-64-9. | 10.6 MB | : 0% 0.0014739590816220136/1 [00:00<01:51, 111.56s/it]

gcc_impl_linux-64-9. | 43.5 MB | : 0% 0.0003594543008068656/1 [00:00<08:29, 509.69s/it]

libsanitizer-9.5.0 | 6.9 MB | : 46% 0.45809695295017455/1 [00:00<00:00, 2.32it/s]

gxx_impl_linux-64-9. | 10.6 MB | : 15% 0.1518177854070674/1 [00:00<00:01, 1.42s/it]

libstdcxx-devel_linu | 9.9 MB | : 24% 0.2421299030360704/1 [00:00<00:00, 1.11it/s]
gcc_impl_linux-64-9. | 43.5 MB | : 6% 0.06470177414523581/1 [00:00<00:03, 3.65s/it]

gxx_impl_linux-64-9. | 10.6 MB | : 47% 0.4716669061190443/1 [00:00<00:00, 1.69it/s]

libstdcxx-devel_linu | 9.9 MB | : 50% 0.5000852899307074/1 [00:00<00:00, 1.70it/s] gcc_impl_linux-64-9. | 43.5 MB | : 17% 0.16606788697277192/1 [00:00<00:01, 1.87s/it]

gxx_impl_linux-64-9. | 10.6 MB | : 95% 0.9492296485645767/1 [00:00<00:00, 2.80it/s]

libstdcxx-devel_linu | 9.9 MB | : 95% 0.9511115798998582/1 [00:00<00:00, 2.71it/s] sysroot_linux-64-2.1 | 14.4 MB | : 68% 0.6801790399932625/1 [00:00<00:00, 1.84it/s]

gcc_impl_linux-64-9. | 43.5 MB | : 25% 0.24874237615835104/1 [00:00<00:01, 1.60s/it]

gcc_impl_linux-64-9. | 43.5 MB | : 44% 0.43709642978114865/1 [00:00<00:00, 1.27s/it]

gcc_impl_linux-64-9. | 43.5 MB | : 52% 0.5197709189667278/1 [00:00<00:00, 1.30s/it]

kernel-headers_linux | 694 KB | : 2% 0.023055695885464526/1 [00:00<00:35, 36.07s/it]

libgcc-devel_linux-6 | 4.0 MB | : 70% 0.6952193466966525/1 [00:00<00:00, 1.09it/s]

gcc-9.5.0 | 26 KB | : 61% 0.6095691643723491/1 [00:00<00:00, 1.46s/it]

gcc_impl_linux-64-9. | 43.5 MB | : 96% 0.9575862573494901/1 [00:01<00:00, 1.24it/s]

libsanitizer-9.5.0 | 6.9 MB | : 100% 1.0/1 [00:02<00:00, 2.83s/it]

libsanitizer-9.5.0 | 6.9 MB | : 100% 1.0/1 [00:02<00:00, 2.83s/it]

libstdcxx-devel_linu | 9.9 MB | : 100% 1.0/1 [00:05<00:00, 2.71it/s]

binutils_impl_linux- | 5.5 MB | : 100% 1.0/1 [00:05<00:00, 6.46s/it]

binutils_impl_linux- | 5.5 MB | : 100% 1.0/1 [00:05<00:00, 6.46s/it]

kernel-headers_linux | 694 KB | : 100% 1.0/1 [00:06<00:00, 5.91s/it]

kernel-headers_linux | 694 KB | : 100% 1.0/1 [00:06<00:00, 5.91s/it]

gcc-9.5.0 | 26 KB | : 100% 1.0/1 [00:06<00:00, 7.19s/it]

gcc-9.5.0 | 26 KB | : 100% 1.0/1 [00:06<00:00, 7.19s/it]

gxx-9.5.0 | 26 KB | : 100% 1.0/1 [00:06<00:00, 7.24s/it]

gxx-9.5.0 | 26 KB | : 100% 1.0/1 [00:06<00:00, 7.24s/it]

gxx_impl_linux-64-9. | 10.6 MB | : 100% 1.0/1 [00:06<00:00, 2.80it/s]

libgcc-devel_linux-6 | 4.0 MB | : 100% 1.0/1 [00:07<00:00, 1.09it/s]
sysroot_linux-64-2.1 | 14.4 MB | : 100% 1.0/1 [00:08<00:00, 12.22s/it]

Preparing transaction: done Verifying transaction: done Executing transaction: done Processing /content/WHAM/third-party/DPVO error: subprocess-exited-with-error

× python setup.py egg_info did not run successfully. │ exit code: 1 ╰─> See above for output.

note: This error originates from a subprocess, and is likely not a problem with pip. Preparing metadata (setup.py) ... error error: metadata-generation-failed

× Encountered error while generating package metadata. ╰─> See above for output.

note: This is an issue with the package mentioned above, not pip. hint: See above for details. /content/WHAM

[mnauf]

also, it fails to install WHAM

/content/WHAM Channels:

• pytorch
• conda-forge Platform: linux-64 Collecting package metadata (repodata.json): done Solving environment: done

==> WARNING: A newer version of conda exists. <== current version: 23.11.0 latest version: 24.5.0

Please update conda by running

$ conda update -n base -c conda-forge conda

Package Plan

environment location: /usr/local/envs/wham

added / updated specs:

• cudatoolkit=11.3
• pytorch==1.11.0
• torchaudio==0.11.0
• torchvision==0.12.0

The following packages will be downloaded:

package                    |            build
---------------------------|-----------------
_openmp_mutex-4.5          |       2_kmp_llvm           6 KB  conda-forge
blas-2.122                 |              mkl          14 KB  conda-forge
blas-devel-3.9.0           |   22_linux64_mkl          14 KB  conda-forge
brotli-python-1.1.0        |   py39h3d6467e_1         342 KB  conda-forge
certifi-2024.2.2           |     pyhd8ed1ab_0         157 KB  conda-forge
cudatoolkit-11.3.1         |      hb98b00a_13       603.5 MB  conda-forge
ffmpeg-4.3                 |       hf484d3e_0         9.9 MB  pytorch
freetype-2.12.1            |       h267a509_2         620 KB  conda-forge
gmp-6.3.0                  |       h59595ed_1         556 KB  conda-forge
gnutls-3.6.13              |       h85f3911_1         2.0 MB  conda-forge
idna-3.7                   |     pyhd8ed1ab_0          51 KB  conda-forge
jpeg-9e                    |       h0b41bf4_3         235 KB  conda-forge
lame-3.100                 |    h166bdaf_1003         496 KB  conda-forge
lcms2-2.15                 |       hfd0df8a_0         235 KB  conda-forge
lerc-4.0.0                 |       h27087fc_0         275 KB  conda-forge
libblas-3.9.0              |   22_linux64_mkl          15 KB  conda-forge
libcblas-3.9.0             |   22_linux64_mkl          14 KB  conda-forge
libdeflate-1.17            |       h0b41bf4_0          63 KB  conda-forge
libgfortran-ng-13.2.0      |       h69a702a_7          24 KB  conda-forge
libgfortran5-13.2.0        |       hca663fb_7         1.4 MB  conda-forge
libhwloc-2.10.0            |default_h5622ce7_1001         2.3 MB  conda-forge
liblapack-3.9.0            |   22_linux64_mkl          14 KB  conda-forge
liblapacke-3.9.0           |   22_linux64_mkl          14 KB  conda-forge
libpng-1.6.43              |       h2797004_0         281 KB  conda-forge
libstdcxx-ng-13.2.0        |       hc0a3c3a_7         3.7 MB  conda-forge
libtiff-4.5.0              |       h6adf6a1_2         397 KB  conda-forge
libuv-1.48.0               |       hd590300_0         879 KB  conda-forge
libwebp-base-1.4.0         |       hd590300_0         429 KB  conda-forge
libxcb-1.13                |    h7f98852_1004         391 KB  conda-forge
libxml2-2.12.7             |       hc051c1a_0         689 KB  conda-forge
llvm-openmp-18.1.5         |       ha31de31_0        56.7 MB  conda-forge
mkl-2024.1.0               |     ha957f24_692       121.0 MB  conda-forge
mkl-devel-2024.1.0         |     ha770c72_692          34 KB  conda-forge
mkl-include-2024.1.0       |     ha957f24_692         673 KB  conda-forge
nettle-3.6                 |       he412f7d_0         6.5 MB  conda-forge
numpy-1.26.4               |   py39h474f0d3_0         6.7 MB  conda-forge
openh264-2.1.1             |       h780b84a_0         1.5 MB  conda-forge
openjpeg-2.5.0             |       hfec8fc6_2         344 KB  conda-forge
pillow-9.4.0               |   py39h2320bf1_1        44.1 MB  conda-forge
pthread-stubs-0.4          |    h36c2ea0_1001           5 KB  conda-forge
python_abi-3.9             |           4_cp39           6 KB  conda-forge
pytorch-1.11.0             |py3.9_cuda11.3_cudnn8.2.0_0        1.02 GB  pytorch
pytorch-mutex-1.0          |             cuda           3 KB  pytorch
tbb-2021.12.0              |       h297d8ca_1         190 KB  conda-forge
torchaudio-0.11.0          |       py39_cu113         5.3 MB  pytorch
torchvision-0.12.0         |       py39_cu113         9.2 MB  pytorch
typing_extensions-4.11.0   |     pyha770c72_0          37 KB  conda-forge
urllib3-2.2.1              |     pyhd8ed1ab_0          92 KB  conda-forge
xorg-libxau-1.0.11         |       hd590300_0          14 KB  conda-forge
xorg-libxdmcp-1.1.3        |       h7f98852_0          19 KB  conda-forge
zlib-1.2.13                |       hd590300_5          91 KB  conda-forge
zstd-1.5.6                 |       ha6fb4c9_0         542 KB  conda-forge
------------------------------------------------------------
                                       Total:        1.88 GB

The following NEW packages will be INSTALLED:

blas conda-forge/linux-64::blas-2.122-mkl blas-devel conda-forge/linux-64::blas-devel-3.9.0-22_linux64_mkl brotli-python conda-forge/linux-64::brotli-python-1.1.0-py39h3d6467e_1 certifi conda-forge/noarch::certifi-2024.2.2-pyhd8ed1ab_0 charset-normalizer conda-forge/noarch::charset-normalizer-3.3.2-pyhd8ed1ab_0 cudatoolkit conda-forge/linux-64::cudatoolkit-11.3.1-hb98b00a_13 ffmpeg pytorch/linux-64::ffmpeg-4.3-hf484d3e_0 freetype conda-forge/linux-64::freetype-2.12.1-h267a509_2 gmp conda-forge/linux-64::gmp-6.3.0-h59595ed_1 gnutls conda-forge/linux-64::gnutls-3.6.13-h85f3911_1 icu conda-forge/linux-64::icu-73.2-h59595ed_0 idna conda-forge/noarch::idna-3.7-pyhd8ed1ab_0 jpeg conda-forge/linux-64::jpeg-9e-h0b41bf4_3 lame conda-forge/linux-64::lame-3.100-h166bdaf_1003 lcms2 conda-forge/linux-64::lcms2-2.15-hfd0df8a_0 lerc conda-forge/linux-64::lerc-4.0.0-h27087fc_0 libblas conda-forge/linux-64::libblas-3.9.0-22_linux64_mkl libcblas conda-forge/linux-64::libcblas-3.9.0-22_linux64_mkl libdeflate conda-forge/linux-64::libdeflate-1.17-h0b41bf4_0 libgfortran-ng conda-forge/linux-64::libgfortran-ng-13.2.0-h69a702a_7 libgfortran5 conda-forge/linux-64::libgfortran5-13.2.0-hca663fb_7 libhwloc conda-forge/linux-64::libhwloc-2.10.0-default_h5622ce7_1001 libiconv conda-forge/linux-64::libiconv-1.17-hd590300_2 liblapack conda-forge/linux-64::liblapack-3.9.0-22_linux64_mkl liblapacke conda-forge/linux-64::liblapacke-3.9.0-22_linux64_mkl libpng conda-forge/linux-64::libpng-1.6.43-h2797004_0 libstdcxx-ng conda-forge/linux-64::libstdcxx-ng-13.2.0-hc0a3c3a_7 libtiff conda-forge/linux-64::libtiff-4.5.0-h6adf6a1_2 libuv conda-forge/linux-64::libuv-1.48.0-hd590300_0 libwebp-base conda-forge/linux-64::libwebp-base-1.4.0-hd590300_0 libxcb conda-forge/linux-64::libxcb-1.13-h7f98852_1004 libxml2 conda-forge/linux-64::libxml2-2.12.7-hc051c1a_0 llvm-openmp conda-forge/linux-64::llvm-openmp-18.1.5-ha31de31_0 mkl conda-forge/linux-64::mkl-2024.1.0-ha957f24_692 mkl-devel conda-forge/linux-64::mkl-devel-2024.1.0-ha770c72_692 mkl-include conda-forge/linux-64::mkl-include-2024.1.0-ha957f24_692 nettle conda-forge/linux-64::nettle-3.6-he412f7d_0 numpy conda-forge/linux-64::numpy-1.26.4-py39h474f0d3_0 openh264 conda-forge/linux-64::openh264-2.1.1-h780b84a_0 openjpeg conda-forge/linux-64::openjpeg-2.5.0-hfec8fc6_2 pillow conda-forge/linux-64::pillow-9.4.0-py39h2320bf1_1 pthread-stubs conda-forge/linux-64::pthread-stubs-0.4-h36c2ea0_1001 pysocks conda-forge/noarch::pysocks-1.7.1-pyha2e5f31_6 python_abi conda-forge/linux-64::python_abi-3.9-4_cp39 pytorch pytorch/linux-64::pytorch-1.11.0-py3.9_cuda11.3_cudnn8.2.0_0 pytorch-mutex pytorch/noarch::pytorch-mutex-1.0-cuda requests conda-forge/noarch::requests-2.31.0-pyhd8ed1ab_0 tbb conda-forge/linux-64::tbb-2021.12.0-h297d8ca_1 torchaudio pytorch/linux-64::torchaudio-0.11.0-py39_cu113 torchvision pytorch/linux-64::torchvision-0.12.0-py39_cu113 typing_extensions conda-forge/noarch::typing_extensions-4.11.0-pyha770c72_0 urllib3 conda-forge/noarch::urllib3-2.2.1-pyhd8ed1ab_0 xorg-libxau conda-forge/linux-64::xorg-libxau-1.0.11-hd590300_0 xorg-libxdmcp conda-forge/linux-64::xorg-libxdmcp-1.1.3-h7f98852_0 zlib conda-forge/linux-64::zlib-1.2.13-hd590300_5 zstd conda-forge/linux-64::zstd-1.5.6-ha6fb4c9_0

The following packages will be DOWNGRADED:

_openmp_mutex 4.5-2_gnu --> 4.5-2_kmp_llvm

Downloading and Extracting Packages: pytorch-1.11.0 | 1.02 GB | : 0% 0/1 [00:00<?, ?it/s] cudatoolkit-11.3.1 | 603.5 MB | : 0% 0/1 [00:00<?, ?it/s]

mkl-2024.1.0 | 121.0 MB | : 0% 0/1 [00:00<?, ?it/s]

llvm-openmp-18.1.5 | 56.7 MB | : 0% 0/1 [00:00<?, ?it/s]

pillow-9.4.0 | 44.1 MB | : 0% 0/1 [00:00<?, ?it/s]

ffmpeg-4.3 | 9.9 MB | : 0% 0/1 [00:00<?, ?it/s]

torchvision-0.12.0 | 9.2 MB | : 0% 0/1 [00:00<?, ?it/s]

numpy-1.26.4 | 6.7 MB | : 0% 0/1 [00:00<?, ?it/s]

nettle-3.6 | 6.5 MB | : 0% 0/1 [00:00<?, ?it/s]

torchaudio-0.11.0 | 5.3 MB | : 0% 0/1 [00:00<?, ?it/s]

libstdcxx-ng-13.2.0 | 3.7 MB | : 0% 0/1 [00:00<?, ?it/s]

libhwloc-2.10.0 | 2.3 MB | : 0% 0/1 [00:00<?, ?it/s]

gnutls-3.6.13 | 2.0 MB | : 0% 0/1 [00:00<?, ?it/s]

openh264-2.1.1 | 1.5 MB | : 0% 0/1 [00:00<?, ?it/s]

libgfortran5-13.2.0 | 1.4 MB | : 0% 0/1 [00:00<?, ?it/s]

libuv-1.48.0 | 879 KB | : 0% 0/1 [00:00<?, ?it/s]

libxml2-2.12.7 | 689 KB | : 0% 0/1 [00:00<?, ?it/s]

mkl-include-2024.1.0 | 673 KB | : 0% 0/1 [00:00<?, ?it/s]

freetype-2.12.1 | 620 KB | : 0% 0/1 [00:00<?, ?it/s]

... (more hidden) ...

pillow-9.4.0 | 44.1 MB | : 0% 0.00035460850152238814/1 [00:00<07:28, 448.59s/it] cudatoolkit-11.3.1 | 603.5 MB | : 0% 2.5889303500845355e-05/1 [00:00<1:52:27, 6747.60s/it]

llvm-openmp-18.1.5 | 56.7 MB | : 0% 0.00027538904543591487/1 [00:00<10:19, 619.70s/it]

pytorch-1.11.0 | 1.02 GB | : 0% 1.4941751582323194e-05/1 [00:00<4:13:14, 15194.48s/it] cudatoolkit-11.3.1 | 603.5 MB | : 0% 0.004530628112647937/1 [00:00<00:49, 49.53s/it]

pillow-9.4.0 | 44.1 MB | : 1% 0.01170208055023881/1 [00:00<00:18, 18.99s/it]

mkl-2024.1.0 | 121.0 MB | : 2% 0.01627641085738685/1 [00:00<00:13, 14.08s/it]

pytorch-1.11.0 | 1.02 GB | : 0% 0.0028239910490590837/1 [00:00<01:31, 91.88s/it]

pillow-9.4.0 | 44.1 MB | : 5% 0.04680832220095524/1 [00:00<00:05, 5.89s/it] cudatoolkit-11.3.1 | 603.5 MB | : 1% 0.011753743789383791/1 [00:00<00:25, 25.58s/it]

mkl-2024.1.0 | 121.0 MB | : 4% 0.03939924850399198/1 [00:00<00:07, 7.54s/it]

pytorch-1.11.0 | 1.02 GB | : 1% 0.006335302670905034/1 [00:00<00:51, 51.82s/it]

pillow-9.4.0 | 44.1 MB | : 10% 0.1017726399369254/1 [00:00<00:02, 3.30s/it]

mkl-2024.1.0 | 121.0 MB | : 7% 0.06536399915744243/1 [00:00<00:05, 5.63s/it]

llvm-openmp-18.1.5 | 56.7 MB | : 15% 0.15229014212606093/1 [00:00<00:02, 2.42s/it] pytorch-1.11.0 | 1.02 GB | : 1% 0.009891439547497953/1 [00:00<00:41, 41.45s/it]

pillow-9.4.0 | 44.1 MB | : 19% 0.18652407180077615/1 [00:00<00:01, 2.06s/it]

llvm-openmp-18.1.5 | 56.7 MB | : 21% 0.21370189925826993/1 [00:00<00:01, 2.11s/it]

mkl-2024.1.0 | 121.0 MB | : 10% 0.0950749078653708/1 [00:00<00:04, 4.78s/it] pytorch-1.11.0 | 1.02 GB | : 1% 0.013447576424090875/1 [00:00<00:35, 36.03s/it]

pillow-9.4.0 | 44.1 MB | : 27% 0.2726939376707165/1 [00:00<00:01, 1.71s/it]

llvm-openmp-18.1.5 | 56.7 MB | : 28% 0.2817229934809409/1 [00:00<00:01, 1.92s/it]

mkl-2024.1.0 | 121.0 MB | : 13% 0.12646512880461688/1 [00:00<00:03, 4.31s/it] pytorch-1.11.0 | 1.02 GB | : 2% 0.016525577250049453/1 [00:00<00:35, 35.99s/it]

pillow-9.4.0 | 44.1 MB | : 35% 0.35425389302086574/1 [00:00<00:00, 1.52s/it]

llvm-openmp-18.1.5 | 56.7 MB | : 34% 0.34065624920422666/1 [00:00<00:01, 1.85s/it]

mkl-2024.1.0 | 121.0 MB | : 16% 0.1600513734309707/1 [00:00<00:03, 3.80s/it] pytorch-1.11.0 | 1.02 GB | : 2% 0.019797820846578232/1 [00:00<00:33, 34.16s/it]

pillow-9.4.0 | 44.1 MB | : 42% 0.4216295083101195/1 [00:00<00:00, 1.56s/it]

llvm-openmp-18.1.5 | 56.7 MB | : 40% 0.39628483638228146/1 [00:00<00:01, 1.93s/it]

pytorch-1.11.0 | 1.02 GB | : 2% 0.02287582167253681/1 [00:00<00:37, 38.47s/it] cudatoolkit-11.3.1 | 603.5 MB | : 4% 0.04129343908384834/1 [00:01<00:22, 23.23s/it]

pillow-9.4.0 | 44.1 MB | : 49% 0.48687747259023895/1 [00:01<00:00, 1.65s/it]

llvm-openmp-18.1.5 | 56.7 MB | : 45% 0.44943492215141306/1 [00:01<00:01, 2.25s/it]

mkl-2024.1.0 | 121.0 MB | : 21% 0.2130142976494517/1 [00:01<00:03, 4.79s/it] pytorch-1.11.0 | 1.02 GB | : 3% 0.0256400457152666/1 [00:01<00:40, 42.06s/it]

pillow-9.4.0 | 44.1 MB | : 55% 0.5485793518551345/1 [00:01<00:00, 1.79s/it]

llvm-openmp-18.1.5 | 56.7 MB | : 50% 0.5039619531477242/1 [00:01<00:01, 2.14s/it]

mkl-2024.1.0 | 121.0 MB | : 24% 0.23639549102395185/1 [00:01<00:03, 4.69s/it] pytorch-1.11.0 | 1.02 GB | : 3% 0.028329561000084776/1 [00:01<00:39, 40.80s/it]

pillow-9.4.0 | 44.1 MB | : 61% 0.6148911416398211/1 [00:01<00:00, 1.76s/it]

llvm-openmp-18.1.5 | 56.7 MB | : 56% 0.5573874279622917/1 [00:01<00:00, 2.15s/it]

mkl-2024.1.0 | 121.0 MB | : 26% 0.2596475065345045/1 [00:01<00:03, 4.63s/it] pytorch-1.11.0 | 1.02 GB | : 3% 0.03101907628490295/1 [00:01<00:39, 40.81s/it]

pillow-9.4.0 | 44.1 MB | : 67% 0.6734015443910151/1 [00:01<00:00, 1.75s/it]

llvm-openmp-18.1.5 | 56.7 MB | : 61% 0.6102621246859873/1 [00:01<00:00, 2.08s/it]

mkl-2024.1.0 | 121.0 MB | : 29% 0.28625814650769255/1 [00:01<00:03, 4.54s/it] pytorch-1.11.0 | 1.02 GB | : 3% 0.0336936498181388/1 [00:01<00:38, 39.82s/it]

pillow-9.4.0 | 44.1 MB | : 75% 0.7496423722183285/1 [00:01<00:00, 1.62s/it]

llvm-openmp-18.1.5 | 56.7 MB | : 66% 0.6606583200007597/1 [00:01<00:00, 2.09s/it]

mkl-2024.1.0 | 121.0 MB | : 31% 0.3105435849298253/1 [00:01<00:03, 4.42s/it] pytorch-1.11.0 | 1.02 GB | : 4% 0.036622233128274145/1 [00:01<00:37, 38.50s/it]

pillow-9.4.0 | 44.1 MB | : 83% 0.8333299785776122/1 [00:01<00:00, 1.48s/it]

mkl-2024.1.0 | 121.0 MB | : 33% 0.3336664225764304/1 [00:01<00:02, 4.43s/it]

pytorch-1.11.0 | 1.02 GB | : 4% 0.039789884463726666/1 [00:01<00:35, 36.50s/it] cudatoolkit-11.3.1 | 603.5 MB | : 7% 0.0702117910942926/1 [00:01<00:20, 22.36s/it]

pillow-9.4.0 | 44.1 MB | : 90% 0.9021240278729554/1 [00:01<00:00, 1.48s/it]

mkl-2024.1.0 | 121.0 MB | : 36% 0.3589852839101433/1 [00:01<00:02, 4.29s/it]

pytorch-1.11.0 | 1.02 GB | : 4% 0.04282306003493827/1 [00:01<00:33, 35.47s/it] cudatoolkit-11.3.1 | 603.5 MB | : 8% 0.0752343159734566/1 [00:01<00:20, 21.65s/it]

pillow-9.4.0 | 44.1 MB | : 97% 0.9723365111743884/1 [00:01<00:00, 1.47s/it]

mkl-2024.1.0 | 121.0 MB | : 38% 0.38262483301253847/1 [00:01<00:02, 4.30s/it]

pytorch-1.11.0 | 1.02 GB | : 5% 0.046812507707418564/1 [00:01<00:30, 31.67s/it] cudatoolkit-11.3.1 | 603.5 MB | : 8% 0.08121474508215187/1 [00:01<00:18, 20.09s/it]

mkl-2024.1.0 | 121.0 MB | : 41% 0.4078145164823038/1 [00:01<00:02, 4.20s/it]

pytorch-1.11.0 | 1.02 GB | : 5% 0.05001004254603573/1 [00:01<00:30, 31.61s/it] cudatoolkit-11.3.1 | 603.5 MB | : 9% 0.08833430354488435/1 [00:01<00:16, 17.91s/it]

mkl-2024.1.0 | 121.0 MB | : 44% 0.44114240538076266/1 [00:02<00:02, 3.77s/it] pytorch-1.11.0 | 1.02 GB | : 5% 0.053879956205857435/1 [00:02<00:28, 30.00s/it]

mkl-2024.1.0 | 121.0 MB | : 48% 0.4806708317487021/1 [00:02<00:01, 3.29s/it] pytorch-1.11.0 | 1.02 GB | : 6% 0.05821306416473116/1 [00:02<00:27, 28.68s/it]

mkl-2024.1.0 | 121.0 MB | : 51% 0.5132236534634759/1 [00:02<00:01, 3.26s/it] pytorch-1.11.0 | 1.02 GB | : 6% 0.06170943403499479/1 [00:02<00:27, 29.83s/it]

mkl-2024.1.0 | 121.0 MB | : 55% 0.5510727676000976/1 [00:02<00:01, 3.05s/it] pytorch-1.11.0 | 1.02 GB | : 7% 0.06540004667582862/1 [00:02<00:27, 29.37s/it]

mkl-2024.1.0 | 121.0 MB | : 60% 0.5955099527980426/1 [00:02<00:01, 2.78s/it] pytorch-1.11.0 | 1.02 GB | : 7% 0.06882170778818063/1 [00:02<00:27, 29.44s/it]

mkl-2024.1.0 | 121.0 MB | : 63% 0.6316797547033468/1 [00:02<00:01, 2.97s/it] pytorch-1.11.0 | 1.02 GB | : 7% 0.07273644670274931/1 [00:02<00:26, 28.40s/it]

ffmpeg-4.3 | 9.9 MB | : 0% 0.0015713236502815128/1 [00:02<27:46, 1668.63s/it] cudatoolkit-11.3.1 | 603.5 MB | : 14% 0.13672141178796432/1 [00:02<00:13, 15.27s/it]

pytorch-1.11.0 | 1.02 GB | : 8% 0.07626270007617758/1 [00:02<00:26, 28.90s/it]

ffmpeg-4.3 | 9.9 MB | : 35% 0.3504051740127774/1 [00:02<00:03, 5.53s/it]

pytorch-1.11.0 | 1.02 GB | : 8% 0.07972918644327656/1 [00:02<00:29, 31.64s/it]

mkl-2024.1.0 | 121.0 MB | : 70% 0.6973021095886842/1 [00:02<00:01, 3.72s/it] cudatoolkit-11.3.1 | 603.5 MB | : 14% 0.14332318418067988/1 [00:02<00:15, 18.38s/it]

ffmpeg-4.3 | 9.9 MB | : 93% 0.9333662482672186/1 [00:02<00:00, 1.69s/it]

pytorch-1.11.0 | 1.02 GB | : 8% 0.08294166303347605/1 [00:02<00:31, 34.35s/it] cudatoolkit-11.3.1 | 603.5 MB | : 15% 0.1490964988613684/1 [00:02<00:16, 18.82s/it]

pytorch-1.11.0 | 1.02 GB | : 9% 0.08591507159835836/1 [00:03<00:32, 35.04s/it] cudatoolkit-11.3.1 | 603.5 MB | : 15% 0.1546368098105493/1 [00:03<00:15, 18.91s/it]

pytorch-1.11.0 | 1.02 GB | : 9% 0.08894824716956998/1 [00:03<00:31, 34.92s/it] cudatoolkit-11.3.1 | 603.5 MB | : 16% 0.16009945284922766/1 [00:03<00:16, 19.13s/it]

torchvision-0.12.0 | 9.2 MB | : 0% 0.001706616712573309/1 [00:03<31:51, 1914.60s/it]

pytorch-1.11.0 | 1.02 GB | : 9% 0.09290781133888562/1 [00:03<00:28, 31.93s/it]

numpy-1.26.4 | 6.7 MB | : 0% 0.0023274608416504116/1 [00:03<23:26, 1410.19s/it] cudatoolkit-11.3.1 | 603.5 MB | : 17% 0.1654326493704018/1 [00:03<00:16, 19.66s/it]

torchvision-0.12.0 | 9.2 MB | : 21% 0.21332708907166364/1 [00:03<00:08, 11.22s/it]

numpy-1.26.4 | 6.7 MB | : 39% 0.3933408822389196/1 [00:03<00:03, 6.11s/it]

mkl-2024.1.0 | 121.0 MB | : 84% 0.8381059812914753/1 [00:03<00:00, 4.16s/it] pytorch-1.11.0 | 1.02 GB | : 10% 0.09609040442592046/1 [00:03<00:33, 37.04s/it]

torchvision-0.12.0 | 9.2 MB | : 42% 0.4181210945804607/1 [00:03<00:02, 5.01s/it]

numpy-1.26.4 | 6.7 MB | : 76% 0.7610796952196847/1 [00:03<00:00, 2.77s/it] cudatoolkit-11.3.1 | 603.5 MB | : 18% 0.17547769912872982/1 [00:03<00:18, 22.17s/it]

pytorch-1.11.0 | 1.02 GB | : 10% 0.09891439547497954/1 [00:03<00:35, 39.11s/it]

torchvision-0.12.0 | 9.2 MB | : 69% 0.6911797685921902/1 [00:03<00:00, 2.58s/it]

mkl-2024.1.0 | 121.0 MB | : 89% 0.8856434352241607/1 [00:03<00:00, 4.58s/it] cudatoolkit-11.3.1 | 603.5 MB | : 18% 0.18006010584837945/1 [00:03<00:18, 23.10s/it]

pytorch-1.11.0 | 1.02 GB | : 10% 0.10155908550505074/1 [00:03<00:36, 40.82s/it] cudatoolkit-11.3.1 | 603.5 MB | : 18% 0.184487176747024/1 [00:03<00:19, 23.55s/it]

pytorch-1.11.0 | 1.02 GB | : 10% 0.10408424152246337/1 [00:03<00:36, 40.70s/it]

mkl-2024.1.0 | 121.0 MB | : 93% 0.9299514425581582/1 [00:03<00:00, 4.72s/it] pytorch-1.11.0 | 1.02 GB | : 11% 0.10684846556519316/1 [00:03<00:35, 39.52s/it]

nettle-3.6 | 6.5 MB | : 0% 0.002418919541397422/1 [00:03<26:50, 1613.98s/it]

mkl-2024.1.0 | 121.0 MB | : 95% 0.9525575687489732/1 [00:03<00:00, 4.67s/it] cudatoolkit-11.3.1 | 603.5 MB | : 19% 0.19297886829530128/1 [00:04<00:19, 24.26s/it]

pytorch-1.11.0 | 1.02 GB | : 11% 0.10941844683735275/1 [00:04<00:37, 42.16s/it]

torchaudio-0.11.0 | 5.3 MB | : 0% 0.0029263126121323022/1 [00:04<23:00, 1384.36s/it] cudatoolkit-11.3.1 | 603.5 MB | : 20% 0.19766483222895428/1 [00:04<00:18, 23.48s/it]

mkl-2024.1.0 | 121.0 MB | : 97% 0.9741302720282082/1 [00:04<00:00, 4.81s/it]

pytorch-1.11.0 | 1.02 GB | : 11% 0.1118390105936891/1 [00:04<00:39, 44.52s/it]

torchaudio-0.11.0 | 5.3 MB | : 44% 0.4418732044319776/1 [00:04<00:03, 6.66s/it]

mkl-2024.1.0 | 121.0 MB | : 100% 0.9950570859877056/1 [00:04<00:00, 5.06s/it] pytorch-1.11.0 | 1.02 GB | : 11% 0.1143492248595194/1 [00:04<00:38, 43.82s/it]

torchaudio-0.11.0 | 5.3 MB | : 81% 0.8105885935606477/1 [00:04<00:00, 3.18s/it] pytorch-1.11.0 | 1.02 GB | : 12% 0.11720309941174313/1 [00:04<00:36, 41.03s/it]

libstdcxx-ng-13.2.0 | 3.7 MB | : 0% 0.004269219304042208/1 [00:04<17:07, 1031.95s/it] pytorch-1.11.0 | 1.02 GB | : 12% 0.11983284769023202/1 [00:04<00:35, 40.39s/it]

libhwloc-2.10.0 | 2.3 MB | : 1% 0.006789530762367667/1 [00:04<10:55, 659.84s/it]

libstdcxx-ng-13.2.0 | 3.7 MB | : 96% 0.9563051241054548/1 [00:04<00:00, 3.34s/it]
pytorch-1.11.0 | 1.02 GB | : 12% 0.12234306195606232/1 [00:04<00:35, 40.84s/it] pytorch-1.11.0 | 1.02 GB | : 13% 0.1253015287693623/1 [00:04<00:33, 38.55s/it]

gnutls-3.6.13 | 2.0 MB | : 1% 0.007814829000532786/1 [00:04<09:52, 596.67s/it]

openh264-2.1.1 | 1.5 MB | : 1% 0.01033460034793491/1 [00:04<07:26, 451.46s/it] pytorch-1.11.0 | 1.02 GB | : 13% 0.12791633529626886/1 [00:04<00:35, 41.19s/it] cudatoolkit-11.3.1 | 603.5 MB | : 23% 0.23093258722754056/1 [00:04<00:16, 20.86s/it]

libgfortran5-13.2.0 | 1.4 MB | : 1% 0.011367034351560782/1 [00:04<07:00, 425.03s/it]

pytorch-1.11.0 | 1.02 GB | : 13% 0.131113870134886/1 [00:04<00:33, 38.09s/it]
cudatoolkit-11.3.1 | 603.5 MB | : 24% 0.2362657837487147/1 [00:04<00:15, 20.22s/it]

libxml2-2.12.7 | 689 KB | : 2% 0.023211500346387443/1 [00:04<03:28, 213.05s/it]

pytorch-1.11.0 | 1.02 GB | : 13% 0.13417692920926227/1 [00:04<00:31, 36.51s/it] cudatoolkit-11.3.1 | 603.5 MB | : 24% 0.241236530020877/1 [00:05<00:15, 20.70s/it]

freetype-2.12.1 | 620 KB | : 3% 0.025802712560553852/1 [00:05<03:10, 195.04s/it]

pytorch-1.11.0 | 1.02 GB | : 14% 0.1369560950035744/1 [00:05<00:33, 38.73s/it] pytorch-1.11.0 | 1.02 GB | : 14% 0.13958584328206328/1 [00:05<00:33, 38.99s/it] pytorch-1.11.0 | 1.02 GB | : 14% 0.14226041681529913/1 [00:05<00:33, 39.32s/it] pytorch-1.11.0 | 1.02 GB | : 15% 0.1456671361760688/1 [00:05<00:31, 36.69s/it] pytorch-1.11.0 | 1.02 GB | : 15% 0.14914856429475012/1 [00:05<00:28, 34.04s/it] pytorch-1.11.0 | 1.02 GB | : 15% 0.1521070311080501/1 [00:05<00:29, 34.49s/it] pytorch-1.11.0 | 1.02 GB | : 16% 0.15502067266660313/1 [00:05<00:33, 40.20s/it] pytorch-1.11.0 | 1.02 GB | : 16% 0.15791937247357382/1 [00:05<00:32, 38.91s/it] pytorch-1.11.0 | 1.02 GB | : 16% 0.16077324702579757/1 [00:06<00:32, 38.77s/it] pytorch-1.11.0 | 1.02 GB | : 16% 0.16403054887074403/1 [00:06<00:30, 36.51s/it] pytorch-1.11.0 | 1.02 GB | : 17% 0.1678257537726541/1 [00:06<00:27, 33.12s/it] pytorch-1.11.0 | 1.02 GB | : 17% 0.1715611916682349/1 [00:06<00:25, 31.04s/it] pytorch-1.11.0 | 1.02 GB | : 18% 0.1751621537995748/1 [00:06<00:24, 30.02s/it] pytorch-1.11.0 | 1.02 GB | : 18% 0.1787033489245854/1 [00:06<00:24, 30.11s/it] pytorch-1.11.0 | 1.02 GB | : 18% 0.1828870393676359/1 [00:06<00:22, 28.01s/it] pytorch-1.11.0 | 1.02 GB | : 19% 0.18783275914138486/1 [00:06<00:20, 25.19s/it] pytorch-1.11.0 | 1.02 GB | : 19% 0.19270377015722223/1 [00:06<00:19, 23.66s/it] pytorch-1.11.0 | 1.02 GB | : 20% 0.19696216935818434/1 [00:06<00:19, 24.28s/it] pytorch-1.11.0 | 1.02 GB | : 20% 0.20111597629807018/1 [00:07<00:19, 24.38s/it] pytorch-1.11.0 | 1.02 GB | : 21% 0.2061513465813131/1 [00:07<00:18, 23.56s/it] pytorch-1.11.0 | 1.02 GB | : 21% 0.21064881380759237/1 [00:07<00:18, 23.22s/it] pytorch-1.11.0 | 1.02 GB | : 21% 0.2149669800148838/1 [00:07<00:18, 23.72s/it] pytorch-1.11.0 | 1.02 GB | : 22% 0.21959892300540398/1 [00:07<00:18, 23.66s/it] pytorch-1.11.0 | 1.02 GB | : 22% 0.22448487577282367/1 [00:07<00:17, 22.65s/it] pytorch-1.11.0 | 1.02 GB | : 23% 0.22892257599277366/1 [00:07<00:17, 23.26s/it] pytorch-1.11.0 | 1.02 GB | : 23% 0.23380852876019334/1 [00:07<00:17, 22.45s/it] pytorch-1.11.0 | 1.02 GB | : 24% 0.23903814181400646/1 [00:07<00:16, 21.37s/it] pytorch-1.11.0 | 1.02 GB | : 24% 0.24374479356243825/1 [00:07<00:16, 21.54s/it] pytorch-1.11.0 | 1.02 GB | : 25% 0.2486606298330226/1 [00:08<00:15, 21.17s/it] pytorch-1.11.0 | 1.02 GB | : 25% 0.25412931091215285/1 [00:08<00:15, 20.25s/it] pytorch-1.11.0 | 1.02 GB | : 26% 0.26010601154508217/1 [00:08<00:14, 19.11s/it] pytorch-1.11.0 | 1.02 GB | : 27% 0.2656792848852887/1 [00:08<00:13, 18.75s/it] cudatoolkit-11.3.1 | 603.5 MB | : 47% 0.4686999505793043/1 [00:08<00:06, 11.62s/it]

pillow-9.4.0 | 44.1 MB | : 100% 1.0/1 [00:08<00:00, 1.47s/it]
pytorch-1.11.0 | 1.02 GB | : 28% 0.27607874398658566/1 [00:08<00:14, 20.50s/it] pytorch-1.11.0 | 1.02 GB | : 28% 0.28099458025717/1 [00:08<00:15, 20.90s/it]
pytorch-1.11.0 | 1.02 GB | : 29% 0.28580582426667805/1 [00:08<00:15, 21.79s/it] pytorch-1.11.0 | 1.02 GB | : 29% 0.29088601980466794/1 [00:08<00:15, 21.15s/it] cudatoolkit-11.3.1 | 603.5 MB | : 51% 0.5126858772272406/1 [00:08<00:06, 12.48s/it] pytorch-1.11.0 | 1.02 GB | : 30% 0.295652438559429/1 [00:09<00:16, 22.86s/it]
pytorch-1.11.0 | 1.02 GB | : 30% 0.30165902269552297/1 [00:09<00:14, 20.77s/it] pytorch-1.11.0 | 1.02 GB | : 31% 0.30655991721452497/1 [00:09<00:14, 20.81s/it] pytorch-1.11.0 | 1.02 GB | : 32% 0.3201867946576037/1 [00:09<00:11, 17.45s/it] pytorch-1.11.0 | 1.02 GB | : 33% 0.32703011688230776/1 [00:09<00:11, 16.51s/it] cudatoolkit-11.3.1 | 603.5 MB | : 58% 0.5773314680688514/1 [00:09<00:04, 9.78s/it] pytorch-1.11.0 | 1.02 GB | : 33% 0.33314129327947795/1 [00:09<00:11, 17.40s/it] pytorch-1.11.0 | 1.02 GB | : 34% 0.33896857639658395/1 [00:09<00:11, 17.91s/it]

ffmpeg-4.3 | 9.9 MB | : 100% 1.0/1 [00:09<00:00, 1.69s/it]
pytorch-1.11.0 | 1.02 GB | : 34% 0.34461655849470213/1 [00:09<00:12, 18.46s/it] pytorch-1.11.0 | 1.02 GB | : 35% 0.3549114253349228/1 [00:10<00:14, 22.79s/it] pytorch-1.11.0 | 1.02 GB | : 36% 0.3596778440896839/1 [00:10<00:14, 22.38s/it] pytorch-1.11.0 | 1.02 GB | : 36% 0.36426496182545715/1 [00:10<00:14, 22.23s/it] pytorch-1.11.0 | 1.02 GB | : 37% 0.36885207956123034/1 [00:10<00:14, 23.07s/it] cudatoolkit-11.3.1 | 603.5 MB | : 65% 0.650882979314753/1 [00:10<00:04, 13.90s/it] pytorch-1.11.0 | 1.02 GB | : 37% 0.3732598962780157/1 [00:10<00:15, 25.12s/it] pytorch-1.11.0 | 1.02 GB | : 38% 0.378728577357146/1 [00:10<00:14, 22.87s/it] pytorch-1.11.0 | 1.02 GB | : 38% 0.3832260445834253/1 [00:10<00:14, 23.00s/it] pytorch-1.11.0 | 1.02 GB | : 39% 0.38882920142679644/1 [00:10<00:13, 21.31s/it] pytorch-1.11.0 | 1.02 GB | : 39% 0.39361056193313987/1 [00:11<00:12, 21.23s/it] pytorch-1.11.0 | 1.02 GB | : 40% 0.3983919224394833/1 [00:11<00:12, 21.25s/it] pytorch-1.11.0 | 1.02 GB | : 40% 0.4031433994426621/1 [00:11<00:13, 22.00s/it] pytorch-1.11.0 | 1.02 GB | : 41% 0.4077305171784353/1 [00:11<00:13, 22.46s/it] pytorch-1.11.0 | 1.02 GB | : 41% 0.41221304265313224/1 [00:11<00:13, 23.38s/it] pytorch-1.11.0 | 1.02 GB | : 42% 0.4166955681278292/1 [00:11<00:13, 23.08s/it] pytorch-1.11.0 | 1.02 GB | : 42% 0.4210585595898676/1 [00:11<00:14, 24.60s/it] pytorch-1.11.0 | 1.02 GB | : 43% 0.4293960569728039/1 [00:11<00:14, 25.88s/it] pytorch-1.11.0 | 1.02 GB | : 43% 0.4333107958873726/1 [00:12<00:14, 25.82s/it] pytorch-1.11.0 | 1.02 GB | : 44% 0.4372255348019413/1 [00:12<00:15, 26.88s/it] pytorch-1.11.0 | 1.02 GB | : 44% 0.44241032260100743/1 [00:12<00:13, 24.84s/it] cudatoolkit-11.3.1 | 603.5 MB | : 78% 0.7811579545310069/1 [00:12<00:03, 14.13s/it] pytorch-1.11.0 | 1.02 GB | : 45% 0.446459537279817/1 [00:12<00:14, 25.99s/it]
pytorch-1.11.0 | 1.02 GB | : 45% 0.4512110142829958/1 [00:12<00:13, 24.72s/it] pytorch-1.11.0 | 1.02 GB | : 46% 0.45536482122288163/1 [00:12<00:13, 25.19s/it] pytorch-1.11.0 | 1.02 GB | : 46% 0.459772637939667/1 [00:12<00:13, 24.44s/it]
pytorch-1.11.0 | 1.02 GB | : 46% 0.4638965613763882/1 [00:12<00:14, 26.23s/it] pytorch-1.11.0 | 1.02 GB | : 47% 0.46787106729728617/1 [00:12<00:14, 27.77s/it] pytorch-1.11.0 | 1.02 GB | : 47% 0.47206969949191896/1 [00:13<00:14, 26.78s/it] pytorch-1.11.0 | 1.02 GB | : 48% 0.47586490439382906/1 [00:13<00:14, 26.74s/it] pytorch-1.11.0 | 1.02 GB | : 48% 0.4796899927989038/1 [00:13<00:13, 26.76s/it] pytorch-1.11.0 | 1.02 GB | : 49% 0.48768382989544673/1 [00:13<00:13, 25.88s/it] cudatoolkit-11.3.1 | 603.5 MB | : 87% 0.8657900876752703/1 [00:13<00:01, 14.18s/it] pytorch-1.11.0 | 1.02 GB | : 49% 0.4917778698290033/1 [00:13<00:13, 25.97s/it] pytorch-1.11.0 | 1.02 GB | : 50% 0.4961707447942063/1 [00:13<00:12, 25.27s/it] pytorch-1.11.0 | 1.02 GB | : 50% 0.5007279790268149/1 [00:13<00:12, 25.05s/it] pytorch-1.11.0 | 1.02 GB | : 51% 0.505359922017335/1 [00:13<00:11, 23.96s/it]

pytorch-1.11.0 | 1.02 GB | : 51% 0.5095585542119678/1 [00:15<00:49, 100.93s/it] pytorch-1.11.0 | 1.02 GB | : 51% 0.5126066715347618/1 [00:16<01:41, 209.24s/it] pytorch-1.11.0 | 1.02 GB | : 52% 0.5181948866265507/1 [00:16<01:05, 136.93s/it] cudatoolkit-11.3.1 | 603.5 MB | : 92% 0.9216850939335954/1 [00:16<00:05, 69.39s/it] pytorch-1.11.0 | 1.02 GB | : 52% 0.5213924214651678/1 [00:17<00:54, 113.19s/it] pytorch-1.11.0 | 1.02 GB | : 53% 0.526158840219929/1 [00:17<00:39, 82.34s/it]
pytorch-1.11.0 | 1.02 GB | : 53% 0.5314631620316537/1 [00:17<00:28, 60.36s/it] pytorch-1.11.0 | 1.02 GB | : 54% 0.5366031245759728/1 [00:17<00:21, 47.15s/it]

llvm-openmp-18.1.5 | 56.7 MB | : 100% 1.0/1 [00:17<00:00, 1.57s/it]
pytorch-1.11.0 | 1.02 GB | : 55% 0.5491243124019597/1 [00:17<00:13, 29.60s/it] cudatoolkit-11.3.1 | 603.5 MB | : 98% 0.9766480852658902/1 [00:17<00:00, 17.87s/it] pytorch-1.11.0 | 1.02 GB | : 56% 0.5603903930950314/1 [00:17<00:10, 24.18s/it] pytorch-1.11.0 | 1.02 GB | : 70% 0.7046380628707795/1 [00:20<00:05, 17.19s/it]

pytorch-1.11.0 | 1.02 GB | : 73% 0.7251082625385623/1 [00:20<00:04, 15.60s/it]

pytorch-1.11.0 | 1.02 GB | : 77% 0.7660934871288748/1 [00:21<00:04, 18.89s/it]

libhwloc-2.10.0 | 2.3 MB | : 100% 1.0/1 [00:21<00:00, 20.11s/it]

pytorch-1.11.0 | 1.02 GB | : 78% 0.7825294138694303/1 [00:21<00:04, 19.09s/it]

pytorch-1.11.0 | 1.02 GB | : 82% 0.8217365700214464/1 [00:22<00:03, 20.77s/it]

openh264-2.1.1 | 1.5 MB | : 100% 1.0/1 [00:22<00:00, 21.21s/it]

pytorch-1.11.0 | 1.02 GB | : 86% 0.8574772398063635/1 [00:23<00:02, 19.57s/it]

pytorch-1.11.0 | 1.02 GB | : 86% 0.8627217946117589/1 [00:23<00:02, 20.48s/it]

libuv-1.48.0 | 879 KB | : 100% 1.0/1 [00:23<00:00, 21.93s/it]

pytorch-1.11.0 | 1.02 GB | : 87% 0.8737189237763487/1 [00:23<00:02, 20.84s/it]

libgfortran5-13.2.0 | 1.4 MB | : 100% 1.0/1 [00:23<00:00, 22.12s/it]

pytorch-1.11.0 | 1.02 GB | : 88% 0.8786198182953507/1 [00:23<00:02, 22.36s/it]

libxml2-2.12.7 | 689 KB | : 100% 1.0/1 [00:23<00:00, 22.30s/it]

pytorch-1.11.0 | 1.02 GB | : 90% 0.9017048244900401/1 [00:24<00:01, 18.62s/it]

mkl-include-2024.1.0 | 673 KB | : 100% 1.0/1 [00:24<00:00, 22.74s/it]

pytorch-1.11.0 | 1.02 GB | : 91% 0.9127168954062123/1 [00:24<00:01, 19.00s/it]

freetype-2.12.1 | 620 KB | : 100% 1.0/1 [00:24<00:00, 22.92s/it]

pytorch-1.11.0 | 1.02 GB | : 92% 0.9180361589695193/1 [00:24<00:01, 19.04s/it]

... (more hidden) ...

pytorch-1.11.0 | 1.02 GB | : 100% 0.9968240150631096/1 [00:26<00:00, 22.96s/it]

gnutls-3.6.13 | 2.0 MB | : 100% 1.0/1 [00:26<00:00, 25.50s/it]

gnutls-3.6.13 | 2.0 MB | : 100% 1.0/1 [00:26<00:00, 25.50s/it]

mkl-2024.1.0 | 121.0 MB | : 100% 1.0/1 [00:38<00:00, 5.06s/it]
pytorch-1.11.0 | 1.02 GB | : 100% 1.0/1 [03:27<00:00, 22.96s/it]

Preparing transaction: done Verifying transaction: done Executing transaction: \ By downloading and using the CUDA Toolkit conda packages, you accept the terms and conditions of the CUDA End User License Agreement (EULA): https://docs.nvidia.com/cuda/eula/index.htmldone Channels:

• fvcore
• iopath
• conda-forge
• pytorch Platform: linux-64 Collecting package metadata (repodata.json): done Solving environment: done

==> WARNING: A newer version of conda exists. <== current version: 23.11.0 latest version: 24.5.0

Please update conda by running

$ conda update -n base -c conda-forge conda

Package Plan

environment location: /usr/local/envs/wham

added / updated specs:

• fvcore
• iopath

The following packages will be downloaded:

package                    |            build
---------------------------|-----------------
fvcore-0.1.5.post20221221  |     pyhd8ed1ab_0          59 KB  conda-forge
iopath-0.1.9               |             py39          42 KB  iopath
portalocker-2.8.2          |   py39hf3d152e_1          35 KB  conda-forge
pyyaml-6.0.1               |   py39hd1e30aa_1         174 KB  conda-forge
tabulate-0.9.0             |     pyhd8ed1ab_1          35 KB  conda-forge
termcolor-2.4.0            |     pyhd8ed1ab_0          12 KB  conda-forge
tqdm-4.66.4                |     pyhd8ed1ab_0          87 KB  conda-forge
yacs-0.1.8                 |     pyhd8ed1ab_0          17 KB  conda-forge
yaml-0.2.5                 |       h7f98852_2          87 KB  conda-forge
------------------------------------------------------------
                                       Total:         548 KB

The following NEW packages will be INSTALLED:

colorama conda-forge/noarch::colorama-0.4.6-pyhd8ed1ab_0 fvcore conda-forge/noarch::fvcore-0.1.5.post20221221-pyhd8ed1ab_0 iopath iopath/linux-64::iopath-0.1.9-py39 portalocker conda-forge/linux-64::portalocker-2.8.2-py39hf3d152e_1 pyyaml conda-forge/linux-64::pyyaml-6.0.1-py39hd1e30aa_1 tabulate conda-forge/noarch::tabulate-0.9.0-pyhd8ed1ab_1 termcolor conda-forge/noarch::termcolor-2.4.0-pyhd8ed1ab_0 tqdm conda-forge/noarch::tqdm-4.66.4-pyhd8ed1ab_0 yacs conda-forge/noarch::yacs-0.1.8-pyhd8ed1ab_0 yaml conda-forge/linux-64::yaml-0.2.5-h7f98852_2

Downloading and Extracting Packages: pyyaml-6.0.1 | 174 KB | : 0% 0/1 [00:00<?, ?it/s] tqdm-4.66.4 | 87 KB | : 0% 0/1 [00:00<?, ?it/s]

yaml-0.2.5 | 87 KB | : 0% 0/1 [00:00<?, ?it/s]

fvcore-0.1.5.post202 | 59 KB | : 0% 0/1 [00:00<?, ?it/s]

iopath-0.1.9 | 42 KB | : 0% 0/1 [00:00<?, ?it/s]

tabulate-0.9.0 | 35 KB | : 0% 0/1 [00:00<?, ?it/s]

portalocker-2.8.2 | 35 KB | : 0% 0/1 [00:00<?, ?it/s]

yacs-0.1.8 | 17 KB | : 0% 0/1 [00:00<?, ?it/s]

termcolor-2.4.0 | 12 KB | : 0% 0/1 [00:00<?, ?it/s] tqdm-4.66.4 | 87 KB | : 18% 0.18315968340562536/1 [00:00<00:00, 1.11it/s]

yaml-0.2.5 | 87 KB | : 18% 0.1837987009344746/1 [00:00<00:00, 1.04it/s]

pyyaml-6.0.1 | 174 KB | : 9% 0.09184319836763065/1 [00:00<00:01, 2.10s/it]

tabulate-0.9.0 | 35 KB | : 46% 0.45622633103141014/1 [00:00<00:00, 2.04it/s]

portalocker-2.8.2 | 35 KB | : 46% 0.46111845993639355/1 [00:00<00:00, 1.92it/s]

yacs-0.1.8 | 17 KB | : 93% 0.9277988561073673/1 [00:00<00:00, 3.55it/s]

termcolor-2.4.0 | 12 KB | : 100% 1.0/1 [00:00<00:00, 3.71it/s]

fvcore-0.1.5.post202 | 59 KB | : 100% 1.0/1 [00:00<00:00, 4.02it/s]

fvcore-0.1.5.post202 | 59 KB | : 100% 1.0/1 [00:00<00:00, 4.02it/s] tqdm-4.66.4 | 87 KB | : 100% 1.0/1 [00:00<00:00, 3.66it/s]
tqdm-4.66.4 | 87 KB | : 100% 1.0/1 [00:00<00:00, 3.66it/s]

yaml-0.2.5 | 87 KB | : 100% 1.0/1 [00:00<00:00, 3.24it/s]

pyyaml-6.0.1 | 174 KB | : 100% 1.0/1 [00:00<00:00, 2.98it/s]

tabulate-0.9.0 | 35 KB | : 100% 1.0/1 [00:00<00:00, 2.80it/s]

tabulate-0.9.0 | 35 KB | : 100% 1.0/1 [00:00<00:00, 2.80it/s]

yacs-0.1.8 | 17 KB | : 100% 1.0/1 [00:00<00:00, 3.55it/s]

portalocker-2.8.2 | 35 KB | : 100% 1.0/1 [00:00<00:00, 2.50it/s]

portalocker-2.8.2 | 35 KB | : 100% 1.0/1 [00:00<00:00, 2.50it/s]

termcolor-2.4.0 | 12 KB | : 100% 1.0/1 [00:00<00:00, 3.71it/s]

iopath-0.1.9 | 42 KB | : 100% 1.0/1 [00:00<00:00, 1.94it/s]

Preparing transaction: done Verifying transaction: done Executing transaction: done Looking in links: https://dl.fbaipublicfiles.com/pytorch3d/packaging/wheels/py39_cu113_pyt1110/download.html Collecting pytorch3d Downloading https://dl.fbaipublicfiles.com/pytorch3d/packaging/wheels/py39_cu113_pyt1110/pytorch3d-0.7.2-cp39-cp39-linux_x86_64.whl (19.6 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 19.6/19.6 MB 58.7 MB/s eta 0:00:00 Requirement already satisfied: fvcore in /usr/local/envs/wham/lib/python3.9/site-packages (from pytorch3d) (0.1.5.post20221221) Requirement already satisfied: iopath in /usr/local/envs/wham/lib/python3.9/site-packages (from pytorch3d) (0.1.9) Requirement already satisfied: numpy in /usr/local/envs/wham/lib/python3.9/site-packages (from fvcore->pytorch3d) (1.26.4) Requirement already satisfied: yacs>=0.1.6 in /usr/local/envs/wham/lib/python3.9/site-packages (from fvcore->pytorch3d) (0.1.8) Requirement already satisfied: pyyaml>=5.1 in /usr/local/envs/wham/lib/python3.9/site-packages (from fvcore->pytorch3d) (6.0.1) Requirement already satisfied: tqdm in /usr/local/envs/wham/lib/python3.9/site-packages (from fvcore->pytorch3d) (4.66.4) Requirement already satisfied: termcolor>=1.1 in /usr/local/envs/wham/lib/python3.9/site-packages (from fvcore->pytorch3d) (2.4.0) Requirement already satisfied: Pillow in /usr/local/envs/wham/lib/python3.9/site-packages (from fvcore->pytorch3d) (9.4.0) Requirement already satisfied: tabulate in /usr/local/envs/wham/lib/python3.9/site-packages (from fvcore->pytorch3d) (0.9.0) Requirement already satisfied: portalocker in /usr/local/envs/wham/lib/python3.9/site-packages (from iopath->pytorch3d) (2.8.2) Installing collected packages: pytorch3d Successfully installed pytorch3d-0.7.2 WARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv Collecting chumpy@ git+https://github.com/mattloper/chumpy (from -r requirements.txt (line 1)) Cloning https://github.com/mattloper/chumpy to /tmp/pip-install-apea3dsa/chumpy_c950a9336dde460fbdf58cf7d076db18 Running command git clone --filter=blob:none --quiet https://github.com/mattloper/chumpy /tmp/pip-install-apea3dsa/chumpy_c950a9336dde460fbdf58cf7d076db18 Resolved https://github.com/mattloper/chumpy to commit 51d5afd92a8ded3637553be8cef41f328a1c863a Preparing metadata (setup.py) ... done Collecting numpy==1.22.3 (from -r requirements.txt (line 2)) Downloading numpy-1.22.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (2.0 kB) Requirement already satisfied: yacs in /usr/local/envs/wham/lib/python3.9/site-packages (from -r requirements.txt (line 3)) (0.1.8) Collecting joblib (from -r requirements.txt (line 4)) Downloading joblib-1.4.2-py3-none-any.whl.metadata (5.4 kB) Collecting scikit-image (from -r requirements.txt (line 5)) Downloading scikit_image-0.22.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (13 kB) Collecting opencv-python (from -r requirements.txt (line 6)) Downloading opencv_python-4.9.0.80-cp37-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (20 kB) Collecting matplotlib (from -r requirements.txt (line 8)) Downloading matplotlib-3.9.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (11 kB) Collecting tensorboard (from -r requirements.txt (line 9)) Downloading tensorboard-2.16.2-py3-none-any.whl.metadata (1.6 kB) Collecting smplx (from -r requirements.txt (line 10)) Downloading smplx-0.1.28-py3-none-any.whl.metadata (10 kB) Collecting progress (from -r requirements.txt (line 11)) Downloading progress-1.6.tar.gz (7.8 kB) Preparing metadata (setup.py) ... done Collecting einops (from -r requirements.txt (line 12)) Downloading einops-0.8.0-py3-none-any.whl.metadata (12 kB) Collecting mmcv==1.3.9 (from -r requirements.txt (line 13)) Downloading mmcv-1.3.9.tar.gz (313 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 313.3/313.3 kB 3.0 MB/s eta 0:00:00 error: subprocess-exited-with-error

× python setup.py egg_info did not run successfully. │ exit code: 1 ╰─> See above for output.

note: This error originates from a subprocess, and is likely not a problem with pip. Preparing metadata (setup.py) ... error error: metadata-generation-failed

× Encountered error while generating package metadata. ╰─> See above for output.

note: This is an issue with the package mentioned above, not pip. hint: See above for details.

[RohaanA]

Hey, were you able to fix it? Looks like mm-cv failed to install

On Sat, May 18, 2024 at 7:44 PM Muhammad Naufil @.***> wrote:

also, it fails to install WHAM

/content/WHAM Channels:

• pytorch
• conda-forge Platform: linux-64 Collecting package metadata (repodata.json): done Solving environment: done

==> WARNING: A newer version of conda exists. <== current version: 23.11.0 latest version: 24.5.0

Please update conda by running

$ conda update -n base -c conda-forge conda

Package Plan

environment location: /usr/local/envs/wham

added / updated specs:

• cudatoolkit=11.3
• pytorch==1.11.0
• torchaudio==0.11.0
• torchvision==0.12.0

The following packages will be downloaded:

package	build
_openmp_mutex-4.5	2_kmp_llvm 6 KB conda-forge
blas-2.122	mkl 14 KB conda-forge
blas-devel-3.9.0	22_linux64_mkl 14 KB conda-forge
brotli-python-1.1.0	py39h3d6467e_1 342 KB conda-forge
certifi-2024.2.2	pyhd8ed1ab_0 157 KB conda-forge
cudatoolkit-11.3.1	hb98b00a_13 603.5 MB conda-forge
ffmpeg-4.3	hf484d3e_0 9.9 MB pytorch
freetype-2.12.1	h267a509_2 620 KB conda-forge
gmp-6.3.0	h59595ed_1 556 KB conda-forge
gnutls-3.6.13	h85f3911_1 2.0 MB conda-forge
idna-3.7	pyhd8ed1ab_0 51 KB conda-forge
jpeg-9e	h0b41bf4_3 235 KB conda-forge
lame-3.100	h166bdaf_1003 496 KB conda-forge
lcms2-2.15	hfd0df8a_0 235 KB conda-forge
lerc-4.0.0	h27087fc_0 275 KB conda-forge
libblas-3.9.0	22_linux64_mkl 15 KB conda-forge
libcblas-3.9.0	22_linux64_mkl 14 KB conda-forge
libdeflate-1.17	h0b41bf4_0 63 KB conda-forge
libgfortran-ng-13.2.0	h69a702a_7 24 KB conda-forge
libgfortran5-13.2.0	hca663fb_7 1.4 MB conda-forge
libhwloc-2.10.0	default_h5622ce7_1001 2.3 MB conda-forge
liblapack-3.9.0	22_linux64_mkl 14 KB conda-forge
liblapacke-3.9.0	22_linux64_mkl 14 KB conda-forge
libpng-1.6.43	h2797004_0 281 KB conda-forge
libstdcxx-ng-13.2.0	hc0a3c3a_7 3.7 MB conda-forge
libtiff-4.5.0	h6adf6a1_2 397 KB conda-forge
libuv-1.48.0	hd590300_0 879 KB conda-forge
libwebp-base-1.4.0	hd590300_0 429 KB conda-forge
libxcb-1.13	h7f98852_1004 391 KB conda-forge
libxml2-2.12.7	hc051c1a_0 689 KB conda-forge
llvm-openmp-18.1.5	ha31de31_0 56.7 MB conda-forge
mkl-2024.1.0	ha957f24_692 121.0 MB conda-forge
mkl-devel-2024.1.0	ha770c72_692 34 KB conda-forge
mkl-include-2024.1.0	ha957f24_692 673 KB conda-forge
nettle-3.6	he412f7d_0 6.5 MB conda-forge
numpy-1.26.4	py39h474f0d3_0 6.7 MB conda-forge
openh264-2.1.1	h780b84a_0 1.5 MB conda-forge
openjpeg-2.5.0	hfec8fc6_2 344 KB conda-forge
pillow-9.4.0	py39h2320bf1_1 44.1 MB conda-forge
pthread-stubs-0.4	h36c2ea0_1001 5 KB conda-forge
python_abi-3.9	4_cp39 6 KB conda-forge
pytorch-1.11.0	py3.9_cuda11.3_cudnn8.2.0_0 1.02 GB pytorch
pytorch-mutex-1.0	cuda 3 KB pytorch
tbb-2021.12.0	h297d8ca_1 190 KB conda-forge
torchaudio-0.11.0	py39_cu113 5.3 MB pytorch
torchvision-0.12.0	py39_cu113 9.2 MB pytorch
typing_extensions-4.11.0	pyha770c72_0 37 KB conda-forge
urllib3-2.2.1	pyhd8ed1ab_0 92 KB conda-forge
xorg-libxau-1.0.11	hd590300_0 14 KB conda-forge
xorg-libxdmcp-1.1.3	h7f98852_0 19 KB conda-forge
zlib-1.2.13	hd590300_5 91 KB conda-forge
zstd-1.5.6	ha6fb4c9_0 542 KB conda-forge

---

                                   Total:        1.88 GB

The following NEW packages will be INSTALLED:

blas conda-forge/linux-64::blas-2.122-mkl blas-devel conda-forge/linux-64::blas-devel-3.9.0-22_linux64_mkl brotli-python conda-forge/linux-64::brotli-python-1.1.0-py39h3d6467e_1 certifi conda-forge/noarch::certifi-2024.2.2-pyhd8ed1ab_0 charset-normalizer conda-forge/noarch::charset-normalizer-3.3.2-pyhd8ed1ab_0 cudatoolkit conda-forge/linux-64::cudatoolkit-11.3.1-hb98b00a_13 ffmpeg pytorch/linux-64::ffmpeg-4.3-hf484d3e_0 freetype conda-forge/linux-64::freetype-2.12.1-h267a509_2 gmp conda-forge/linux-64::gmp-6.3.0-h59595ed_1 gnutls conda-forge/linux-64::gnutls-3.6.13-h85f3911_1 icu conda-forge/linux-64::icu-73.2-h59595ed_0 idna conda-forge/noarch::idna-3.7-pyhd8ed1ab_0 jpeg conda-forge/linux-64::jpeg-9e-h0b41bf4_3 lame conda-forge/linux-64::lame-3.100-h166bdaf_1003 lcms2 conda-forge/linux-64::lcms2-2.15-hfd0df8a_0 lerc conda-forge/linux-64::lerc-4.0.0-h27087fc_0 libblas conda-forge/linux-64::libblas-3.9.0-22_linux64_mkl libcblas conda-forge/linux-64::libcblas-3.9.0-22_linux64_mkl libdeflate conda-forge/linux-64::libdeflate-1.17-h0b41bf4_0 libgfortran-ng conda-forge/linux-64::libgfortran-ng-13.2.0-h69a702a_7 libgfortran5 conda-forge/linux-64::libgfortran5-13.2.0-hca663fb_7 libhwloc conda-forge/linux-64::libhwloc-2.10.0-default_h5622ce7_1001 libiconv conda-forge/linux-64::libiconv-1.17-hd590300_2 liblapack conda-forge/linux-64::liblapack-3.9.0-22_linux64_mkl liblapacke conda-forge/linux-64::liblapacke-3.9.0-22_linux64_mkl libpng conda-forge/linux-64::libpng-1.6.43-h2797004_0 libstdcxx-ng conda-forge/linux-64::libstdcxx-ng-13.2.0-hc0a3c3a_7 libtiff conda-forge/linux-64::libtiff-4.5.0-h6adf6a1_2 libuv conda-forge/linux-64::libuv-1.48.0-hd590300_0 libwebp-base conda-forge/linux-64::libwebp-base-1.4.0-hd590300_0 libxcb conda-forge/linux-64::libxcb-1.13-h7f98852_1004 libxml2 conda-forge/linux-64::libxml2-2.12.7-hc051c1a_0 llvm-openmp conda-forge/linux-64::llvm-openmp-18.1.5-ha31de31_0 mkl conda-forge/linux-64::mkl-2024.1.0-ha957f24_692 mkl-devel conda-forge/linux-64::mkl-devel-2024.1.0-ha770c72_692 mkl-include conda-forge/linux-64::mkl-include-2024.1.0-ha957f24_692 nettle conda-forge/linux-64::nettle-3.6-he412f7d_0 numpy conda-forge/linux-64::numpy-1.26.4-py39h474f0d3_0 openh264 conda-forge/linux-64::openh264-2.1.1-h780b84a_0 openjpeg conda-forge/linux-64::openjpeg-2.5.0-hfec8fc6_2 pillow conda-forge/linux-64::pillow-9.4.0-py39h2320bf1_1 pthread-stubs conda-forge/linux-64::pthread-stubs-0.4-h36c2ea0_1001 pysocks conda-forge/noarch::pysocks-1.7.1-pyha2e5f31_6 python_abi conda-forge/linux-64::python_abi-3.9-4_cp39 pytorch pytorch/linux-64::pytorch-1.11.0-py3.9_cuda11.3_cudnn8.2.0_0 pytorch-mutex pytorch/noarch::pytorch-mutex-1.0-cuda requests conda-forge/noarch::requests-2.31.0-pyhd8ed1ab_0 tbb conda-forge/linux-64::tbb-2021.12.0-h297d8ca_1 torchaudio pytorch/linux-64::torchaudio-0.11.0-py39_cu113 torchvision pytorch/linux-64::torchvision-0.12.0-py39_cu113 typing_extensions conda-forge/noarch::typing_extensions-4.11.0-pyha770c72_0 urllib3 conda-forge/noarch::urllib3-2.2.1-pyhd8ed1ab_0 xorg-libxau conda-forge/linux-64::xorg-libxau-1.0.11-hd590300_0 xorg-libxdmcp conda-forge/linux-64::xorg-libxdmcp-1.1.3-h7f98852_0 zlib conda-forge/linux-64::zlib-1.2.13-hd590300_5 zstd conda-forge/linux-64::zstd-1.5.6-ha6fb4c9_0

The following packages will be DOWNGRADED:

_openmp_mutex 4.5-2_gnu --> 4.5-2_kmp_llvm

Downloading and Extracting Packages: pytorch-1.11.0 | 1.02 GB | : 0% 0/1 [00:00<?, ?it/s] cudatoolkit-11.3.1 | 603.5 MB | : 0% 0/1 [00:00<?, ?it/s]

mkl-2024.1.0 | 121.0 MB | : 0% 0/1 [00:00<?, ?it/s]

llvm-openmp-18.1.5 | 56.7 MB | : 0% 0/1 [00:00<?, ?it/s]

pillow-9.4.0 | 44.1 MB | : 0% 0/1 [00:00<?, ?it/s]

ffmpeg-4.3 | 9.9 MB | : 0% 0/1 [00:00<?, ?it/s]

torchvision-0.12.0 | 9.2 MB | : 0% 0/1 [00:00<?, ?it/s]

numpy-1.26.4 | 6.7 MB | : 0% 0/1 [00:00<?, ?it/s]

nettle-3.6 | 6.5 MB | : 0% 0/1 [00:00<?, ?it/s]

torchaudio-0.11.0 | 5.3 MB | : 0% 0/1 [00:00<?, ?it/s]

libstdcxx-ng-13.2.0 | 3.7 MB | : 0% 0/1 [00:00<?, ?it/s]

libhwloc-2.10.0 | 2.3 MB | : 0% 0/1 [00:00<?, ?it/s]

gnutls-3.6.13 | 2.0 MB | : 0% 0/1 [00:00<?, ?it/s]

openh264-2.1.1 | 1.5 MB | : 0% 0/1 [00:00<?, ?it/s]

libgfortran5-13.2.0 | 1.4 MB | : 0% 0/1 [00:00<?, ?it/s]

libuv-1.48.0 | 879 KB | : 0% 0/1 [00:00<?, ?it/s]

libxml2-2.12.7 | 689 KB | : 0% 0/1 [00:00<?, ?it/s]

mkl-include-2024.1.0 | 673 KB | : 0% 0/1 [00:00<?, ?it/s]

freetype-2.12.1 | 620 KB | : 0% 0/1 [00:00<?, ?it/s]

... (more hidden) ...

pillow-9.4.0 | 44.1 MB | : 0% 0.00035460850152238814/1 [00:00<07:28, 448.59s/it] cudatoolkit-11.3.1 | 603.5 MB | : 0% 2.5889303500845355e-05/1 [00:00<1:52:27, 6747.60s/it]

llvm-openmp-18.1.5 | 56.7 MB | : 0% 0.00027538904543591487/1 [00:00<10:19, 619.70s/it]

pytorch-1.11.0 | 1.02 GB | : 0% 1.4941751582323194e-05/1 [00:00<4:13:14, 15194.48s/it] cudatoolkit-11.3.1 | 603.5 MB | : 0% 0.004530628112647937/1 [00:00<00:49, 49.53s/it]

pillow-9.4.0 | 44.1 MB | : 1% 0.01170208055023881/1 [00:00<00:18, 18.99s/it]

mkl-2024.1.0 | 121.0 MB | : 2% 0.01627641085738685/1 [00:00<00:13, 14.08s/it]

pytorch-1.11.0 | 1.02 GB | : 0% 0.0028239910490590837/1 [00:00<01:31, 91.88s/it]

pillow-9.4.0 | 44.1 MB | : 5% 0.04680832220095524/1 [00:00<00:05, 5.89s/it] cudatoolkit-11.3.1 | 603.5 MB | : 1% 0.011753743789383791/1 [00:00<00:25, 25.58s/it]

mkl-2024.1.0 | 121.0 MB | : 4% 0.03939924850399198/1 [00:00<00:07, 7.54s/it]

pytorch-1.11.0 | 1.02 GB | : 1% 0.006335302670905034/1 [00:00<00:51, 51.82s/it]

pillow-9.4.0 | 44.1 MB | : 10% 0.1017726399369254/1 [00:00<00:02, 3.30s/it]

mkl-2024.1.0 | 121.0 MB | : 7% 0.06536399915744243/1 [00:00<00:05, 5.63s/it]

llvm-openmp-18.1.5 | 56.7 MB | : 15% 0.15229014212606093/1 [00:00<00:02, 2.42s/it] pytorch-1.11.0 | 1.02 GB | : 1% 0.009891439547497953/1 [00:00<00:41, 41.45s/it]

pillow-9.4.0 | 44.1 MB | : 19% 0.18652407180077615/1 [00:00<00:01, 2.06s/it]

llvm-openmp-18.1.5 | 56.7 MB | : 21% 0.21370189925826993/1 [00:00<00:01, 2.11s/it]

mkl-2024.1.0 | 121.0 MB | : 10% 0.0950749078653708/1 [00:00<00:04, 4.78s/it] pytorch-1.11.0 | 1.02 GB | : 1% 0.013447576424090875/1 [00:00<00:35, 36.03s/it]

pillow-9.4.0 | 44.1 MB | : 27% 0.2726939376707165/1 [00:00<00:01, 1.71s/it]

llvm-openmp-18.1.5 | 56.7 MB | : 28% 0.2817229934809409/1 [00:00<00:01, 1.92s/it]

mkl-2024.1.0 | 121.0 MB | : 13% 0.12646512880461688/1 [00:00<00:03, 4.31s/it] pytorch-1.11.0 | 1.02 GB | : 2% 0.016525577250049453/1 [00:00<00:35, 35.99s/it]

pillow-9.4.0 | 44.1 MB | : 35% 0.35425389302086574/1 [00:00<00:00, 1.52s/it]

llvm-openmp-18.1.5 | 56.7 MB | : 34% 0.34065624920422666/1 [00:00<00:01, 1.85s/it]

mkl-2024.1.0 | 121.0 MB | : 16% 0.1600513734309707/1 [00:00<00:03, 3.80s/it] pytorch-1.11.0 | 1.02 GB | : 2% 0.019797820846578232/1 [00:00<00:33, 34.16s/it]

pillow-9.4.0 | 44.1 MB | : 42% 0.4216295083101195/1 [00:00<00:00, 1.56s/it]

llvm-openmp-18.1.5 | 56.7 MB | : 40% 0.39628483638228146/1 [00:00<00:01, 1.93s/it]

pytorch-1.11.0 | 1.02 GB | : 2% 0.02287582167253681/1 [00:00<00:37, 38.47s/it] cudatoolkit-11.3.1 | 603.5 MB | : 4% 0.04129343908384834/1 [00:01<00:22, 23.23s/it]

pillow-9.4.0 | 44.1 MB | : 49% 0.48687747259023895/1 [00:01<00:00, 1.65s/it]

llvm-openmp-18.1.5 | 56.7 MB | : 45% 0.44943492215141306/1 [00:01<00:01, 2.25s/it]

mkl-2024.1.0 | 121.0 MB | : 21% 0.2130142976494517/1 [00:01<00:03, 4.79s/it] pytorch-1.11.0 | 1.02 GB | : 3% 0.0256400457152666/1 [00:01<00:40, 42.06s/it]

pillow-9.4.0 | 44.1 MB | : 55% 0.5485793518551345/1 [00:01<00:00, 1.79s/it]

llvm-openmp-18.1.5 | 56.7 MB | : 50% 0.5039619531477242/1 [00:01<00:01, 2.14s/it]

mkl-2024.1.0 | 121.0 MB | : 24% 0.23639549102395185/1 [00:01<00:03, 4.69s/it] pytorch-1.11.0 | 1.02 GB | : 3% 0.028329561000084776/1 [00:01<00:39, 40.80s/it]

pillow-9.4.0 | 44.1 MB | : 61% 0.6148911416398211/1 [00:01<00:00, 1.76s/it]

llvm-openmp-18.1.5 | 56.7 MB | : 56% 0.5573874279622917/1 [00:01<00:00, 2.15s/it]

mkl-2024.1.0 | 121.0 MB | : 26% 0.2596475065345045/1 [00:01<00:03, 4.63s/it] pytorch-1.11.0 | 1.02 GB | : 3% 0.03101907628490295/1 [00:01<00:39, 40.81s/it]

pillow-9.4.0 | 44.1 MB | : 67% 0.6734015443910151/1 [00:01<00:00, 1.75s/it]

llvm-openmp-18.1.5 | 56.7 MB | : 61% 0.6102621246859873/1 [00:01<00:00, 2.08s/it]

mkl-2024.1.0 | 121.0 MB | : 29% 0.28625814650769255/1 [00:01<00:03, 4.54s/it] pytorch-1.11.0 | 1.02 GB | : 3% 0.0336936498181388/1 [00:01<00:38, 39.82s/it]

pillow-9.4.0 | 44.1 MB | : 75% 0.7496423722183285/1 [00:01<00:00, 1.62s/it]

llvm-openmp-18.1.5 | 56.7 MB | : 66% 0.6606583200007597/1 [00:01<00:00, 2.09s/it]

mkl-2024.1.0 | 121.0 MB | : 31% 0.3105435849298253/1 [00:01<00:03, 4.42s/it] pytorch-1.11.0 | 1.02 GB | : 4% 0.036622233128274145/1 [00:01<00:37, 38.50s/it]

pillow-9.4.0 | 44.1 MB | : 83% 0.8333299785776122/1 [00:01<00:00, 1.48s/it]

mkl-2024.1.0 | 121.0 MB | : 33% 0.3336664225764304/1 [00:01<00:02, 4.43s/it]

pytorch-1.11.0 | 1.02 GB | : 4% 0.039789884463726666/1 [00:01<00:35, 36.50s/it] cudatoolkit-11.3.1 | 603.5 MB | : 7% 0.0702117910942926/1 [00:01<00:20, 22.36s/it]

pillow-9.4.0 | 44.1 MB | : 90% 0.9021240278729554/1 [00:01<00:00, 1.48s/it]

mkl-2024.1.0 | 121.0 MB | : 36% 0.3589852839101433/1 [00:01<00:02, 4.29s/it]

pytorch-1.11.0 | 1.02 GB | : 4% 0.04282306003493827/1 [00:01<00:33, 35.47s/it] cudatoolkit-11.3.1 | 603.5 MB | : 8% 0.0752343159734566/1 [00:01<00:20, 21.65s/it]

pillow-9.4.0 | 44.1 MB | : 97% 0.9723365111743884/1 [00:01<00:00, 1.47s/it]

mkl-2024.1.0 | 121.0 MB | : 38% 0.38262483301253847/1 [00:01<00:02, 4.30s/it]

pytorch-1.11.0 | 1.02 GB | : 5% 0.046812507707418564/1 [00:01<00:30, 31.67s/it] cudatoolkit-11.3.1 | 603.5 MB | : 8% 0.08121474508215187/1 [00:01<00:18, 20.09s/it]

mkl-2024.1.0 | 121.0 MB | : 41% 0.4078145164823038/1 [00:01<00:02, 4.20s/it]

pytorch-1.11.0 | 1.02 GB | : 5% 0.05001004254603573/1 [00:01<00:30, 31.61s/it] cudatoolkit-11.3.1 | 603.5 MB | : 9% 0.08833430354488435/1 [00:01<00:16, 17.91s/it]

mkl-2024.1.0 | 121.0 MB | : 44% 0.44114240538076266/1 [00:02<00:02, 3.77s/it] pytorch-1.11.0 | 1.02 GB | : 5% 0.053879956205857435/1 [00:02<00:28, 30.00s/it]

mkl-2024.1.0 | 121.0 MB | : 48% 0.4806708317487021/1 [00:02<00:01, 3.29s/it] pytorch-1.11.0 | 1.02 GB | : 6% 0.05821306416473116/1 [00:02<00:27, 28.68s/it]

mkl-2024.1.0 | 121.0 MB | : 51% 0.5132236534634759/1 [00:02<00:01, 3.26s/it] pytorch-1.11.0 | 1.02 GB | : 6% 0.06170943403499479/1 [00:02<00:27, 29.83s/it]

mkl-2024.1.0 | 121.0 MB | : 55% 0.5510727676000976/1 [00:02<00:01, 3.05s/it] pytorch-1.11.0 | 1.02 GB | : 7% 0.06540004667582862/1 [00:02<00:27, 29.37s/it]

mkl-2024.1.0 | 121.0 MB | : 60% 0.5955099527980426/1 [00:02<00:01, 2.78s/it] pytorch-1.11.0 | 1.02 GB | : 7% 0.06882170778818063/1 [00:02<00:27, 29.44s/it]

mkl-2024.1.0 | 121.0 MB | : 63% 0.6316797547033468/1 [00:02<00:01, 2.97s/it] pytorch-1.11.0 | 1.02 GB | : 7% 0.07273644670274931/1 [00:02<00:26, 28.40s/it]

ffmpeg-4.3 | 9.9 MB | : 0% 0.0015713236502815128/1 [00:02<27:46, 1668.63s/it] cudatoolkit-11.3.1 | 603.5 MB | : 14% 0.13672141178796432/1 [00:02<00:13, 15.27s/it]

pytorch-1.11.0 | 1.02 GB | : 8% 0.07626270007617758/1 [00:02<00:26, 28.90s/it]

ffmpeg-4.3 | 9.9 MB | : 35% 0.3504051740127774/1 [00:02<00:03, 5.53s/it]

pytorch-1.11.0 | 1.02 GB | : 8% 0.07972918644327656/1 [00:02<00:29, 31.64s/it]

mkl-2024.1.0 | 121.0 MB | : 70% 0.6973021095886842/1 [00:02<00:01, 3.72s/it] cudatoolkit-11.3.1 | 603.5 MB | : 14% 0.14332318418067988/1 [00:02<00:15, 18.38s/it]

ffmpeg-4.3 | 9.9 MB | : 93% 0.9333662482672186/1 [00:02<00:00, 1.69s/it]

pytorch-1.11.0 | 1.02 GB | : 8% 0.08294166303347605/1 [00:02<00:31, 34.35s/it] cudatoolkit-11.3.1 | 603.5 MB | : 15% 0.1490964988613684/1 [00:02<00:16, 18.82s/it]

pytorch-1.11.0 | 1.02 GB | : 9% 0.08591507159835836/1 [00:03<00:32, 35.04s/it] cudatoolkit-11.3.1 | 603.5 MB | : 15% 0.1546368098105493/1 [00:03<00:15, 18.91s/it]

pytorch-1.11.0 | 1.02 GB | : 9% 0.08894824716956998/1 [00:03<00:31, 34.92s/it] cudatoolkit-11.3.1 | 603.5 MB | : 16% 0.16009945284922766/1 [00:03<00:16, 19.13s/it]

torchvision-0.12.0 | 9.2 MB | : 0% 0.001706616712573309/1 [00:03<31:51, 1914.60s/it]

pytorch-1.11.0 | 1.02 GB | : 9% 0.09290781133888562/1 [00:03<00:28, 31.93s/it]

numpy-1.26.4 | 6.7 MB | : 0% 0.0023274608416504116/1 [00:03<23:26, 1410.19s/it] cudatoolkit-11.3.1 | 603.5 MB | : 17% 0.1654326493704018/1 [00:03<00:16, 19.66s/it]

torchvision-0.12.0 | 9.2 MB | : 21% 0.21332708907166364/1 [00:03<00:08, 11.22s/it]

numpy-1.26.4 | 6.7 MB | : 39% 0.3933408822389196/1 [00:03<00:03, 6.11s/it]

mkl-2024.1.0 | 121.0 MB | : 84% 0.8381059812914753/1 [00:03<00:00, 4.16s/it] pytorch-1.11.0 | 1.02 GB | : 10% 0.09609040442592046/1 [00:03<00:33, 37.04s/it]

torchvision-0.12.0 | 9.2 MB | : 42% 0.4181210945804607/1 [00:03<00:02, 5.01s/it]

numpy-1.26.4 | 6.7 MB | : 76% 0.7610796952196847/1 [00:03<00:00, 2.77s/it] cudatoolkit-11.3.1 | 603.5 MB | : 18% 0.17547769912872982/1 [00:03<00:18, 22.17s/it]

pytorch-1.11.0 | 1.02 GB | : 10% 0.09891439547497954/1 [00:03<00:35, 39.11s/it]

torchvision-0.12.0 | 9.2 MB | : 69% 0.6911797685921902/1 [00:03<00:00, 2.58s/it]

mkl-2024.1.0 | 121.0 MB | : 89% 0.8856434352241607/1 [00:03<00:00, 4.58s/it] cudatoolkit-11.3.1 | 603.5 MB | : 18% 0.18006010584837945/1 [00:03<00:18, 23.10s/it]

pytorch-1.11.0 | 1.02 GB | : 10% 0.10155908550505074/1 [00:03<00:36, 40.82s/it] cudatoolkit-11.3.1 | 603.5 MB | : 18% 0.184487176747024/1 [00:03<00:19, 23.55s/it]

pytorch-1.11.0 | 1.02 GB | : 10% 0.10408424152246337/1 [00:03<00:36, 40.70s/it]

mkl-2024.1.0 | 121.0 MB | : 93% 0.9299514425581582/1 [00:03<00:00, 4.72s/it] pytorch-1.11.0 | 1.02 GB | : 11% 0.10684846556519316/1 [00:03<00:35, 39.52s/it]

nettle-3.6 | 6.5 MB | : 0% 0.002418919541397422/1 [00:03<26:50, 1613.98s/it]

mkl-2024.1.0 | 121.0 MB | : 95% 0.9525575687489732/1 [00:03<00:00, 4.67s/it] cudatoolkit-11.3.1 | 603.5 MB | : 19% 0.19297886829530128/1 [00:04<00:19, 24.26s/it]

pytorch-1.11.0 | 1.02 GB | : 11% 0.10941844683735275/1 [00:04<00:37, 42.16s/it]

torchaudio-0.11.0 | 5.3 MB | : 0% 0.0029263126121323022/1 [00:04<23:00, 1384.36s/it] cudatoolkit-11.3.1 | 603.5 MB | : 20% 0.19766483222895428/1 [00:04<00:18, 23.48s/it]

mkl-2024.1.0 | 121.0 MB | : 97% 0.9741302720282082/1 [00:04<00:00, 4.81s/it]

pytorch-1.11.0 | 1.02 GB | : 11% 0.1118390105936891/1 [00:04<00:39, 44.52s/it]

torchaudio-0.11.0 | 5.3 MB | : 44% 0.4418732044319776/1 [00:04<00:03, 6.66s/it]

mkl-2024.1.0 | 121.0 MB | : 100% 0.9950570859877056/1 [00:04<00:00, 5.06s/it] pytorch-1.11.0 | 1.02 GB | : 11% 0.1143492248595194/1 [00:04<00:38, 43.82s/it]

torchaudio-0.11.0 | 5.3 MB | : 81% 0.8105885935606477/1 [00:04<00:00, 3.18s/it] pytorch-1.11.0 | 1.02 GB | : 12% 0.11720309941174313/1 [00:04<00:36, 41.03s/it]

libstdcxx-ng-13.2.0 | 3.7 MB | : 0% 0.004269219304042208/1 [00:04<17:07, 1031.95s/it] pytorch-1.11.0 | 1.02 GB | : 12% 0.11983284769023202/1 [00:04<00:35, 40.39s/it]

libhwloc-2.10.0 | 2.3 MB | : 1% 0.006789530762367667/1 [00:04<10:55, 659.84s/it]

libstdcxx-ng-13.2.0 | 3.7 MB | : 96% 0.9563051241054548/1 [00:04<00:00, 3.34s/it] pytorch-1.11.0 | 1.02 GB | : 12% 0.12234306195606232/1 [00:04<00:35, 40.84s/it] pytorch-1.11.0 | 1.02 GB | : 13% 0.1253015287693623/1 [00:04<00:33, 38.55s/it]

gnutls-3.6.13 | 2.0 MB | : 1% 0.007814829000532786/1 [00:04<09:52, 596.67s/it]

openh264-2.1.1 | 1.5 MB | : 1% 0.01033460034793491/1 [00:04<07:26, 451.46s/it] pytorch-1.11.0 | 1.02 GB | : 13% 0.12791633529626886/1 [00:04<00:35, 41.19s/it] cudatoolkit-11.3.1 | 603.5 MB | : 23% 0.23093258722754056/1 [00:04<00:16, 20.86s/it]

libgfortran5-13.2.0 | 1.4 MB | : 1% 0.011367034351560782/1 [00:04<07:00, 425.03s/it]

pytorch-1.11.0 | 1.02 GB | : 13% 0.131113870134886/1 [00:04<00:33, 38.09s/it] cudatoolkit-11.3.1 | 603.5 MB | : 24% 0.2362657837487147/1 [00:04<00:15, 20.22s/it]

libxml2-2.12.7 | 689 KB | : 2% 0.023211500346387443/1 [00:04<03:28, 213.05s/it]

pytorch-1.11.0 | 1.02 GB | : 13% 0.13417692920926227/1 [00:04<00:31, 36.51s/it] cudatoolkit-11.3.1 | 603.5 MB | : 24% 0.241236530020877/1 [00:05<00:15, 20.70s/it]

freetype-2.12.1 | 620 KB | : 3% 0.025802712560553852/1 [00:05<03:10, 195.04s/it]

pytorch-1.11.0 | 1.02 GB | : 14% 0.1369560950035744/1 [00:05<00:33, 38.73s/it] pytorch-1.11.0 | 1.02 GB | : 14% 0.13958584328206328/1 [00:05<00:33, 38.99s/it] pytorch-1.11.0 | 1.02 GB | : 14% 0.14226041681529913/1 [00:05<00:33, 39.32s/it] pytorch-1.11.0 | 1.02 GB | : 15% 0.1456671361760688/1 [00:05<00:31, 36.69s/it] pytorch-1.11.0 | 1.02 GB | : 15% 0.14914856429475012/1 [00:05<00:28, 34.04s/it] pytorch-1.11.0 | 1.02 GB | : 15% 0.1521070311080501/1 [00:05<00:29, 34.49s/it] pytorch-1.11.0 | 1.02 GB | : 16% 0.15502067266660313/1 [00:05<00:33, 40.20s/it] pytorch-1.11.0 | 1.02 GB | : 16% 0.15791937247357382/1 [00:05<00:32, 38.91s/it] pytorch-1.11.0 | 1.02 GB | : 16% 0.16077324702579757/1 [00:06<00:32, 38.77s/it] pytorch-1.11.0 | 1.02 GB | : 16% 0.16403054887074403/1 [00:06<00:30, 36.51s/it] pytorch-1.11.0 | 1.02 GB | : 17% 0.1678257537726541/1 [00:06<00:27, 33.12s/it] pytorch-1.11.0 | 1.02 GB | : 17% 0.1715611916682349/1 [00:06<00:25, 31.04s/it] pytorch-1.11.0 | 1.02 GB | : 18% 0.1751621537995748/1 [00:06<00:24, 30.02s/it] pytorch-1.11.0 | 1.02 GB | : 18% 0.1787033489245854/1 [00:06<00:24, 30.11s/it] pytorch-1.11.0 | 1.02 GB | : 18% 0.1828870393676359/1 [00:06<00:22, 28.01s/it] pytorch-1.11.0 | 1.02 GB | : 19% 0.18783275914138486/1 [00:06<00:20, 25.19s/it] pytorch-1.11.0 | 1.02 GB | : 19% 0.19270377015722223/1 [00:06<00:19, 23.66s/it] pytorch-1.11.0 | 1.02 GB | : 20% 0.19696216935818434/1 [00:06<00:19, 24.28s/it] pytorch-1.11.0 | 1.02 GB | : 20% 0.20111597629807018/1 [00:07<00:19, 24.38s/it] pytorch-1.11.0 | 1.02 GB | : 21% 0.2061513465813131/1 [00:07<00:18, 23.56s/it] pytorch-1.11.0 | 1.02 GB | : 21% 0.21064881380759237/1 [00:07<00:18, 23.22s/it] pytorch-1.11.0 | 1.02 GB | : 21% 0.2149669800148838/1 [00:07<00:18, 23.72s/it] pytorch-1.11.0 | 1.02 GB | : 22% 0.21959892300540398/1 [00:07<00:18, 23.66s/it] pytorch-1.11.0 | 1.02 GB | : 22% 0.22448487577282367/1 [00:07<00:17, 22.65s/it] pytorch-1.11.0 | 1.02 GB | : 23% 0.22892257599277366/1 [00:07<00:17, 23.26s/it] pytorch-1.11.0 | 1.02 GB | : 23% 0.23380852876019334/1 [00:07<00:17, 22.45s/it] pytorch-1.11.0 | 1.02 GB | : 24% 0.23903814181400646/1 [00:07<00:16, 21.37s/it] pytorch-1.11.0 | 1.02 GB | : 24% 0.24374479356243825/1 [00:07<00:16, 21.54s/it] pytorch-1.11.0 | 1.02 GB | : 25% 0.2486606298330226/1 [00:08<00:15, 21.17s/it] pytorch-1.11.0 | 1.02 GB | : 25% 0.25412931091215285/1 [00:08<00:15, 20.25s/it] pytorch-1.11.0 | 1.02 GB | : 26% 0.26010601154508217/1 [00:08<00:14, 19.11s/it] pytorch-1.11.0 | 1.02 GB | : 27% 0.2656792848852887/1 [00:08<00:13, 18.75s/it] cudatoolkit-11.3.1 | 603.5 MB | : 47% 0.4686999505793043/1 [00:08<00:06, 11.62s/it]

pillow-9.4.0 | 44.1 MB | : 100% 1.0/1 [00:08<00:00, 1.47s/it] pytorch-1.11.0 | 1.02 GB | : 28% 0.27607874398658566/1 [00:08<00:14, 20.50s/it] pytorch-1.11.0 | 1.02 GB | : 28% 0.28099458025717/1 [00:08<00:15, 20.90s/it] pytorch-1.11.0 | 1.02 GB | : 29% 0.28580582426667805/1 [00:08<00:15, 21.79s/it] pytorch-1.11.0 | 1.02 GB | : 29% 0.29088601980466794/1 [00:08<00:15, 21.15s/it] cudatoolkit-11.3.1 | 603.5 MB | : 51% 0.5126858772272406/1 [00:08<00:06, 12.48s/it] pytorch-1.11.0 | 1.02 GB | : 30% 0.295652438559429/1 [00:09<00:16, 22.86s/it] pytorch-1.11.0 | 1.02 GB | : 30% 0.30165902269552297/1 [00:09<00:14, 20.77s/it] pytorch-1.11.0 | 1.02 GB | : 31% 0.30655991721452497/1 [00:09<00:14, 20.81s/it] pytorch-1.11.0 | 1.02 GB | : 32% 0.3201867946576037/1 [00:09<00:11, 17.45s/it] pytorch-1.11.0 | 1.02 GB | : 33% 0.32703011688230776/1 [00:09<00:11, 16.51s/it] cudatoolkit-11.3.1 | 603.5 MB | : 58% 0.5773314680688514/1 [00:09<00:04, 9.78s/it] pytorch-1.11.0 | 1.02 GB | : 33% 0.33314129327947795/1 [00:09<00:11, 17.40s/it] pytorch-1.11.0 | 1.02 GB | : 34% 0.33896857639658395/1 [00:09<00:11, 17.91s/it]

ffmpeg-4.3 | 9.9 MB | : 100% 1.0/1 [00:09<00:00, 1.69s/it] pytorch-1.11.0 | 1.02 GB | : 34% 0.34461655849470213/1 [00:09<00:12, 18.46s/it] pytorch-1.11.0 | 1.02 GB | : 35% 0.3549114253349228/1 [00:10<00:14, 22.79s/it] pytorch-1.11.0 | 1.02 GB | : 36% 0.3596778440896839/1 [00:10<00:14, 22.38s/it] pytorch-1.11.0 | 1.02 GB | : 36% 0.36426496182545715/1 [00:10<00:14, 22.23s/it] pytorch-1.11.0 | 1.02 GB | : 37% 0.36885207956123034/1 [00:10<00:14, 23.07s/it] cudatoolkit-11.3.1 | 603.5 MB | : 65% 0.650882979314753/1 [00:10<00:04, 13.90s/it] pytorch-1.11.0 | 1.02 GB | : 37% 0.3732598962780157/1 [00:10<00:15, 25.12s/it] pytorch-1.11.0 | 1.02 GB | : 38% 0.378728577357146/1 [00:10<00:14, 22.87s/it] pytorch-1.11.0 | 1.02 GB | : 38% 0.3832260445834253/1 [00:10<00:14, 23.00s/it] pytorch-1.11.0 | 1.02 GB | : 39% 0.38882920142679644/1 [00:10<00:13, 21.31s/it] pytorch-1.11.0 | 1.02 GB | : 39% 0.39361056193313987/1 [00:11<00:12, 21.23s/it] pytorch-1.11.0 | 1.02 GB | : 40% 0.3983919224394833/1 [00:11<00:12, 21.25s/it] pytorch-1.11.0 | 1.02 GB | : 40% 0.4031433994426621/1 [00:11<00:13, 22.00s/it] pytorch-1.11.0 | 1.02 GB | : 41% 0.4077305171784353/1 [00:11<00:13, 22.46s/it] pytorch-1.11.0 | 1.02 GB | : 41% 0.41221304265313224/1 [00:11<00:13, 23.38s/it] pytorch-1.11.0 | 1.02 GB | : 42% 0.4166955681278292/1 [00:11<00:13, 23.08s/it] pytorch-1.11.0 | 1.02 GB | : 42% 0.4210585595898676/1 [00:11<00:14, 24.60s/it] pytorch-1.11.0 | 1.02 GB | : 43% 0.4293960569728039/1 [00:11<00:14, 25.88s/it] pytorch-1.11.0 | 1.02 GB | : 43% 0.4333107958873726/1 [00:12<00:14, 25.82s/it] pytorch-1.11.0 | 1.02 GB | : 44% 0.4372255348019413/1 [00:12<00:15, 26.88s/it] pytorch-1.11.0 | 1.02 GB | : 44% 0.44241032260100743/1 [00:12<00:13, 24.84s/it] cudatoolkit-11.3.1 | 603.5 MB | : 78% 0.7811579545310069/1 [00:12<00:03, 14.13s/it] pytorch-1.11.0 | 1.02 GB | : 45% 0.446459537279817/1 [00:12<00:14, 25.99s/it] pytorch-1.11.0 | 1.02 GB | : 45% 0.4512110142829958/1 [00:12<00:13, 24.72s/it] pytorch-1.11.0 | 1.02 GB | : 46% 0.45536482122288163/1 [00:12<00:13, 25.19s/it] pytorch-1.11.0 | 1.02 GB | : 46% 0.459772637939667/1 [00:12<00:13, 24.44s/it] pytorch-1.11.0 | 1.02 GB | : 46% 0.4638965613763882/1 [00:12<00:14, 26.23s/it] pytorch-1.11.0 | 1.02 GB | : 47% 0.46787106729728617/1 [00:12<00:14, 27.77s/it] pytorch-1.11.0 | 1.02 GB | : 47% 0.47206969949191896/1 [00:13<00:14, 26.78s/it] pytorch-1.11.0 | 1.02 GB | : 48% 0.47586490439382906/1 [00:13<00:14, 26.74s/it] pytorch-1.11.0 | 1.02 GB | : 48% 0.4796899927989038/1 [00:13<00:13, 26.76s/it] pytorch-1.11.0 | 1.02 GB | : 49% 0.48768382989544673/1 [00:13<00:13, 25.88s/it] cudatoolkit-11.3.1 | 603.5 MB | : 87% 0.8657900876752703/1 [00:13<00:01, 14.18s/it] pytorch-1.11.0 | 1.02 GB | : 49% 0.4917778698290033/1 [00:13<00:13, 25.97s/it] pytorch-1.11.0 | 1.02 GB | : 50% 0.4961707447942063/1 [00:13<00:12, 25.27s/it] pytorch-1.11.0 | 1.02 GB | : 50% 0.5007279790268149/1 [00:13<00:12, 25.05s/it] pytorch-1.11.0 | 1.02 GB | : 51% 0.505359922017335/1 [00:13<00:11, 23.96s/it]

pytorch-1.11.0 | 1.02 GB | : 51% 0.5095585542119678/1 [00:15<00:49, 100.93s/it] pytorch-1.11.0 | 1.02 GB | : 51% 0.5126066715347618/1 [00:16<01:41, 209.24s/it] pytorch-1.11.0 | 1.02 GB | : 52% 0.5181948866265507/1 [00:16<01:05, 136.93s/it] cudatoolkit-11.3.1 | 603.5 MB | : 92% 0.9216850939335954/1 [00:16<00:05, 69.39s/it] pytorch-1.11.0 | 1.02 GB | : 52% 0.5213924214651678/1 [00:17<00:54, 113.19s/it] pytorch-1.11.0 | 1.02 GB | : 53% 0.526158840219929/1 [00:17<00:39, 82.34s/it] pytorch-1.11.0 | 1.02 GB | : 53% 0.5314631620316537/1 [00:17<00:28, 60.36s/it] pytorch-1.11.0 | 1.02 GB | : 54% 0.5366031245759728/1 [00:17<00:21, 47.15s/it]

llvm-openmp-18.1.5 | 56.7 MB | : 100% 1.0/1 [00:17<00:00, 1.57s/it] pytorch-1.11.0 | 1.02 GB | : 55% 0.5491243124019597/1 [00:17<00:13, 29.60s/it] cudatoolkit-11.3.1 | 603.5 MB | : 98% 0.9766480852658902/1 [00:17<00:00, 17.87s/it] pytorch-1.11.0 | 1.02 GB | : 56% 0.5603903930950314/1 [00:17<00:10, 24.18s/it] pytorch-1.11.0 | 1.02 GB | : 70% 0.7046380628707795/1 [00:20<00:05, 17.19s/it]

pytorch-1.11.0 | 1.02 GB | : 73% 0.7251082625385623/1 [00:20<00:04, 15.60s/it]

pytorch-1.11.0 | 1.02 GB | : 77% 0.7660934871288748/1 [00:21<00:04, 18.89s/it]

libhwloc-2.10.0 | 2.3 MB | : 100% 1.0/1 [00:21<00:00, 20.11s/it]

pytorch-1.11.0 | 1.02 GB | : 78% 0.7825294138694303/1 [00:21<00:04, 19.09s/it]

pytorch-1.11.0 | 1.02 GB | : 82% 0.8217365700214464/1 [00:22<00:03, 20.77s/it]

openh264-2.1.1 | 1.5 MB | : 100% 1.0/1 [00:22<00:00, 21.21s/it]

pytorch-1.11.0 | 1.02 GB | : 86% 0.8574772398063635/1 [00:23<00:02, 19.57s/it]

pytorch-1.11.0 | 1.02 GB | : 86% 0.8627217946117589/1 [00:23<00:02, 20.48s/it]

libuv-1.48.0 | 879 KB | : 100% 1.0/1 [00:23<00:00, 21.93s/it]

pytorch-1.11.0 | 1.02 GB | : 87% 0.8737189237763487/1 [00:23<00:02, 20.84s/it]

libgfortran5-13.2.0 | 1.4 MB | : 100% 1.0/1 [00:23<00:00, 22.12s/it]

pytorch-1.11.0 | 1.02 GB | : 88% 0.8786198182953507/1 [00:23<00:02, 22.36s/it]

libxml2-2.12.7 | 689 KB | : 100% 1.0/1 [00:23<00:00, 22.30s/it]

pytorch-1.11.0 | 1.02 GB | : 90% 0.9017048244900401/1 [00:24<00:01, 18.62s/it]

mkl-include-2024.1.0 | 673 KB | : 100% 1.0/1 [00:24<00:00, 22.74s/it]

pytorch-1.11.0 | 1.02 GB | : 91% 0.9127168954062123/1 [00:24<00:01, 19.00s/it]

freetype-2.12.1 | 620 KB | : 100% 1.0/1 [00:24<00:00, 22.92s/it]

pytorch-1.11.0 | 1.02 GB | : 92% 0.9180361589695193/1 [00:24<00:01, 19.04s/it]

... (more hidden) ...

pytorch-1.11.0 | 1.02 GB | : 100% 0.9968240150631096/1 [00:26<00:00, 22.96s/it]

gnutls-3.6.13 | 2.0 MB | : 100% 1.0/1 [00:26<00:00, 25.50s/it]

gnutls-3.6.13 | 2.0 MB | : 100% 1.0/1 [00:26<00:00, 25.50s/it]

mkl-2024.1.0 | 121.0 MB | : 100% 1.0/1 [00:38<00:00, 5.06s/it] pytorch-1.11.0 | 1.02 GB | : 100% 1.0/1 [03:27<00:00, 22.96s/it]

Preparing transaction: done Verifying transaction: done Executing transaction: \ By downloading and using the CUDA Toolkit conda packages, you accept the terms and conditions of the CUDA End User License Agreement (EULA): https://docs.nvidia.com/cuda/eula/index.htmldone Channels:

• fvcore
• iopath
• conda-forge
• pytorch Platform: linux-64 Collecting package metadata (repodata.json): done Solving environment: done

==> WARNING: A newer version of conda exists. <== current version: 23.11.0 latest version: 24.5.0

Please update conda by running

$ conda update -n base -c conda-forge conda

Package Plan

environment location: /usr/local/envs/wham

added / updated specs:

• fvcore
• iopath

The following packages will be downloaded:

package	build
fvcore-0.1.5.post20221221	pyhd8ed1ab_0 59 KB conda-forge
iopath-0.1.9	py39 42 KB iopath
portalocker-2.8.2	py39hf3d152e_1 35 KB conda-forge
pyyaml-6.0.1	py39hd1e30aa_1 174 KB conda-forge
tabulate-0.9.0	pyhd8ed1ab_1 35 KB conda-forge
termcolor-2.4.0	pyhd8ed1ab_0 12 KB conda-forge
tqdm-4.66.4	pyhd8ed1ab_0 87 KB conda-forge
yacs-0.1.8	pyhd8ed1ab_0 17 KB conda-forge
yaml-0.2.5	h7f98852_2 87 KB conda-forge

---

                                   Total:         548 KB

The following NEW packages will be INSTALLED:

colorama conda-forge/noarch::colorama-0.4.6-pyhd8ed1ab_0 fvcore conda-forge/noarch::fvcore-0.1.5.post20221221-pyhd8ed1ab_0 iopath iopath/linux-64::iopath-0.1.9-py39 portalocker conda-forge/linux-64::portalocker-2.8.2-py39hf3d152e_1 pyyaml conda-forge/linux-64::pyyaml-6.0.1-py39hd1e30aa_1 tabulate conda-forge/noarch::tabulate-0.9.0-pyhd8ed1ab_1 termcolor conda-forge/noarch::termcolor-2.4.0-pyhd8ed1ab_0 tqdm conda-forge/noarch::tqdm-4.66.4-pyhd8ed1ab_0 yacs conda-forge/noarch::yacs-0.1.8-pyhd8ed1ab_0 yaml conda-forge/linux-64::yaml-0.2.5-h7f98852_2

Downloading and Extracting Packages: pyyaml-6.0.1 | 174 KB | : 0% 0/1 [00:00<?, ?it/s] tqdm-4.66.4 | 87 KB | : 0% 0/1 [00:00<?, ?it/s]

yaml-0.2.5 | 87 KB | : 0% 0/1 [00:00<?, ?it/s]

fvcore-0.1.5.post202 | 59 KB | : 0% 0/1 [00:00<?, ?it/s]

iopath-0.1.9 | 42 KB | : 0% 0/1 [00:00<?, ?it/s]

tabulate-0.9.0 | 35 KB | : 0% 0/1 [00:00<?, ?it/s]

portalocker-2.8.2 | 35 KB | : 0% 0/1 [00:00<?, ?it/s]

yacs-0.1.8 | 17 KB | : 0% 0/1 [00:00<?, ?it/s]

termcolor-2.4.0 | 12 KB | : 0% 0/1 [00:00<?, ?it/s] tqdm-4.66.4 | 87 KB | : 18% 0.18315968340562536/1 [00:00<00:00, 1.11it/s]

yaml-0.2.5 | 87 KB | : 18% 0.1837987009344746/1 [00:00<00:00, 1.04it/s]

pyyaml-6.0.1 | 174 KB | : 9% 0.09184319836763065/1 [00:00<00:01, 2.10s/it]

tabulate-0.9.0 | 35 KB | : 46% 0.45622633103141014/1 [00:00<00:00, 2.04it/s]

portalocker-2.8.2 | 35 KB | : 46% 0.46111845993639355/1 [00:00<00:00, 1.92it/s]

yacs-0.1.8 | 17 KB | : 93% 0.9277988561073673/1 [00:00<00:00, 3.55it/s]

termcolor-2.4.0 | 12 KB | : 100% 1.0/1 [00:00<00:00, 3.71it/s]

fvcore-0.1.5.post202 | 59 KB | : 100% 1.0/1 [00:00<00:00, 4.02it/s]

fvcore-0.1.5.post202 | 59 KB | : 100% 1.0/1 [00:00<00:00, 4.02it/s] tqdm-4.66.4 | 87 KB | : 100% 1.0/1 [00:00<00:00, 3.66it/s] tqdm-4.66.4 | 87 KB | : 100% 1.0/1 [00:00<00:00, 3.66it/s]

yaml-0.2.5 | 87 KB | : 100% 1.0/1 [00:00<00:00, 3.24it/s]

pyyaml-6.0.1 | 174 KB | : 100% 1.0/1 [00:00<00:00, 2.98it/s]

tabulate-0.9.0 | 35 KB | : 100% 1.0/1 [00:00<00:00, 2.80it/s]

tabulate-0.9.0 | 35 KB | : 100% 1.0/1 [00:00<00:00, 2.80it/s]

yacs-0.1.8 | 17 KB | : 100% 1.0/1 [00:00<00:00, 3.55it/s]

portalocker-2.8.2 | 35 KB | : 100% 1.0/1 [00:00<00:00, 2.50it/s]

portalocker-2.8.2 | 35 KB | : 100% 1.0/1 [00:00<00:00, 2.50it/s]

termcolor-2.4.0 | 12 KB | : 100% 1.0/1 [00:00<00:00, 3.71it/s]

iopath-0.1.9 | 42 KB | : 100% 1.0/1 [00:00<00:00, 1.94it/s]

Preparing transaction: done Verifying transaction: done Executing transaction: done Looking in links: https://dl.fbaipublicfiles.com/pytorch3d/packaging/wheels/py39_cu113_pyt1110/download.html Collecting pytorch3d Downloading https://dl.fbaipublicfiles.com/pytorch3d/packaging/wheels/py39_cu113_pyt1110/pytorch3d-0.7.2-cp39-cp39-linux_x86_64.whl (19.6 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 19.6/19.6 MB 58.7 MB/s eta 0:00:00 Requirement already satisfied: fvcore in /usr/local/envs/wham/lib/python3.9/site-packages (from pytorch3d) (0.1.5.post20221221) Requirement already satisfied: iopath in /usr/local/envs/wham/lib/python3.9/site-packages (from pytorch3d) (0.1.9) Requirement already satisfied: numpy in /usr/local/envs/wham/lib/python3.9/site-packages (from fvcore->pytorch3d) (1.26.4) Requirement already satisfied: yacs>=0.1.6 in /usr/local/envs/wham/lib/python3.9/site-packages (from fvcore->pytorch3d) (0.1.8) Requirement already satisfied: pyyaml>=5.1 in /usr/local/envs/wham/lib/python3.9/site-packages (from fvcore->pytorch3d) (6.0.1) Requirement already satisfied: tqdm in /usr/local/envs/wham/lib/python3.9/site-packages (from fvcore->pytorch3d) (4.66.4) Requirement already satisfied: termcolor>=1.1 in /usr/local/envs/wham/lib/python3.9/site-packages (from fvcore->pytorch3d) (2.4.0) Requirement already satisfied: Pillow in /usr/local/envs/wham/lib/python3.9/site-packages (from fvcore->pytorch3d) (9.4.0) Requirement already satisfied: tabulate in /usr/local/envs/wham/lib/python3.9/site-packages (from fvcore->pytorch3d) (0.9.0) Requirement already satisfied: portalocker in /usr/local/envs/wham/lib/python3.9/site-packages (from iopath->pytorch3d) (2.8.2) Installing collected packages: pytorch3d Successfully installed pytorch3d-0.7.2 WARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv Collecting chumpy@ git+https://github.com/mattloper/chumpy (from -r requirements.txt (line 1)) Cloning https://github.com/mattloper/chumpy to /tmp/pip-install-apea3dsa/chumpy_c950a9336dde460fbdf58cf7d076db18 Running command git clone --filter=blob:none --quiet https://github.com/mattloper/chumpy /tmp/pip-install-apea3dsa/chumpy_c950a9336dde460fbdf58cf7d076db18 Resolved https://github.com/mattloper/chumpy to commit 51d5afd92a8ded3637553be8cef41f328a1c863a Preparing metadata (setup.py) ... done Collecting numpy==1.22.3 (from -r requirements.txt (line 2)) Downloading numpy-1.22.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (2.0 kB) Requirement already satisfied: yacs in /usr/local/envs/wham/lib/python3.9/site-packages (from -r requirements.txt (line 3)) (0.1.8) Collecting joblib (from -r requirements.txt (line 4)) Downloading joblib-1.4.2-py3-none-any.whl.metadata (5.4 kB) Collecting scikit-image (from -r requirements.txt (line 5)) Downloading scikit_image-0.22.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (13 kB) Collecting opencv-python (from -r requirements.txt (line 6)) Downloading opencv_python-4.9.0.80-cp37-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (20 kB) Collecting matplotlib (from -r requirements.txt (line 8)) Downloading matplotlib-3.9.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (11 kB) Collecting tensorboard (from -r requirements.txt (line 9)) Downloading tensorboard-2.16.2-py3-none-any.whl.metadata (1.6 kB) Collecting smplx (from -r requirements.txt (line 10)) Downloading smplx-0.1.28-py3-none-any.whl.metadata (10 kB) Collecting progress (from -r requirements.txt (line 11)) Downloading progress-1.6.tar.gz (7.8 kB) Preparing metadata (setup.py) ... done Collecting einops (from -r requirements.txt (line 12)) Downloading einops-0.8.0-py3-none-any.whl.metadata (12 kB) Collecting mmcv==1.3.9 (from -r requirements.txt (line 13)) Downloading mmcv-1.3.9.tar.gz (313 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 313.3/313.3 kB 3.0 MB/s eta 0:00:00 error: subprocess-exited-with-error

× python setup.py egg_info did not run successfully. │ exit code: 1 ╰─> See above for output.

note: This error originates from a subprocess, and is likely not a problem with pip. Preparing metadata (setup.py) ... error error: metadata-generation-failed

× Encountered error while generating package metadata. ╰─> See above for output.

note: This is an issue with the package mentioned above, not pip. hint: See above for details.

— Reply to this email directly, view it on GitHub https://github.com/yohanshin/WHAM/issues/75#issuecomment-2118845642, or unsubscribe https://github.com/notifications/unsubscribe-auth/ASBW2WA63SHYHDKZ3DLJLCTZC5SM5AVCNFSM6AAAAABFC27X7CVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDCMJYHA2DKNRUGI . You are receiving this because you commented.Message ID: @.***>

[mnauf]

@RohaanA Nope. There are 2 issues with the colab notebook. Please scroll down slowly. I have written 2 comments

[mnauf]

@RohaanA Alright, now I have problem with installing DPVO only:

....
  inflating: thirdparty/eigen-3.4.0/unsupported/test/levenberg_marquardt.cpp  
  inflating: thirdparty/eigen-3.4.0/unsupported/test/matrix_exponential.cpp  
  inflating: thirdparty/eigen-3.4.0/unsupported/test/matrix_function.cpp  
  inflating: thirdparty/eigen-3.4.0/unsupported/test/matrix_functions.h  
  inflating: thirdparty/eigen-3.4.0/unsupported/test/matrix_power.cpp  
  inflating: thirdparty/eigen-3.4.0/unsupported/test/matrix_square_root.cpp  
  inflating: thirdparty/eigen-3.4.0/unsupported/test/minres.cpp  
  inflating: thirdparty/eigen-3.4.0/unsupported/test/mpreal_support.cpp  
  inflating: thirdparty/eigen-3.4.0/unsupported/test/openglsupport.cpp  
  inflating: thirdparty/eigen-3.4.0/unsupported/test/polynomialsolver.cpp  
  inflating: thirdparty/eigen-3.4.0/unsupported/test/polynomialutils.cpp  
  inflating: thirdparty/eigen-3.4.0/unsupported/test/sparse_extra.cpp  
  inflating: thirdparty/eigen-3.4.0/unsupported/test/special_functions.cpp  
  inflating: thirdparty/eigen-3.4.0/unsupported/test/special_packetmath.cpp  
  inflating: thirdparty/eigen-3.4.0/unsupported/test/splines.cpp  
Channels:
 - rusty1s
 - conda-forge
 - pytorch
 - iopath
Platform: linux-64
Collecting package metadata (repodata.json): done
Solving environment: done

==> WARNING: A newer version of conda exists. <==
    current version: 23.11.0
    latest version: 24.5.0

Please update conda by running

    $ conda update -n base -c conda-forge conda

# All requested packages already installed.

Channels:
 - conda-forge
 - pytorch
 - iopath
 - rusty1s
Platform: linux-64
Collecting package metadata (repodata.json): done
Solving environment: done

==> WARNING: A newer version of conda exists. <==
    current version: 23.11.0
    latest version: 24.5.0

Please update conda by running

    $ conda update -n base -c conda-forge conda

# All requested packages already installed.

Channels:
 - conda-forge
 - pytorch
 - iopath
 - rusty1s
Platform: linux-64
Collecting package metadata (repodata.json): done
Solving environment: done

==> WARNING: A newer version of conda exists. <==
    current version: 23.11.0
    latest version: 24.5.0

Please update conda by running

    $ conda update -n base -c conda-forge conda

# All requested packages already installed.

Processing /content/WHAM/third-party/DPVO
  error: subprocess-exited-with-error

  × python setup.py egg_info did not run successfully.
  │ exit code: 1
  ╰─> See above for output.

  note: This error originates from a subprocess, and is likely not a problem with pip.
  Preparing metadata (setup.py) ... error
error: metadata-generation-failed

× Encountered error while generating package metadata.
╰─> See above for output.

note: This is an issue with the package mentioned above, not pip.
hint: See above for details.
/content/WHAM

[RohaanA]

Hmm, I've got 2 exams scheduled in the next 3 days so I won't be able to look into this until then. Maybe @yohanshin can look into it as he was the author of the notebook as well.

Have u tried using the docker image instead?

[elizabethjcobs]

Hi, I am having the same issues :(

[rizwansabirawan]

Has anybody solved it yet?

[david02871]

Same issue here