Conda recipe issue

[meiyasan]

Solution to issue cannot be found in the documentation.

• I checked the documentation.

Issue

Since few days, it takes much longer to resolve the following libtorch recipe. Of course, including more packages make the dependency resolution event longer (>15min)

channels:
  - conda-forge
dependencies:
    - libtorch

Additionally, here is the recent warning message I receive.

Collecting package metadata (repodata.json): | WARNING conda.models.version:get_matcher(563): Using .* with relational operator is superfluous and deprecated and will be removed in a future version of conda. Your spec was 1.9.0.*, but conda is ignoring the .* and treating it as 1.9.0
WARNING conda.models.version:get_matcher(563): Using .* with relational operator is superfluous and deprecated and will be removed in a future version of conda. Your spec was 1.8.0.*, but conda is ignoring the .* and treating it as 1.8.0
WARNING conda.models.version:get_matcher(563): Using .* with relational operator is superfluous and deprecated and will be removed in a future version of conda. Your spec was 1.6.0.*, but conda is ignoring the .* and treating it as 1.6.0
WARNING conda.models.version:get_matcher(563): Using .* with relational operator is superfluous and deprecated and will be removed in a future version of conda. Your spec was 1.7.1.*, but conda is ignoring the .* and treating it as 1.7.1
done
Solving environment: - 

Installed packages

(base) conda list
# packages in environment at /opt/conda:
#
# Name                    Version                   Build  Channel
_libgcc_mutex             0.1                 conda_forge    conda-forge
_openmp_mutex             4.5                       2_gnu    conda-forge
archspec                  0.2.5              pyhd8ed1ab_0    conda-forge
boltons                   24.0.0             pyhd8ed1ab_1    conda-forge
brotli-python             1.1.0           py312h2ec8cdc_2    conda-forge
bzip2                     1.0.8                h4bc722e_7    conda-forge
c-ares                    1.34.5               hb9d3cd8_0    conda-forge
ca-certificates           2025.4.26            hbd8a1cb_0    conda-forge
certifi                   2025.4.26          pyhd8ed1ab_0    conda-forge
cffi                      1.17.1          py312h06ac9bb_0    conda-forge
charset-normalizer        3.4.2              pyhd8ed1ab_0    conda-forge
colorama                  0.4.6              pyhd8ed1ab_1    conda-forge
conda                     25.3.0          py312h7900ff3_0    conda-forge
conda-libmamba-solver     25.3.0             pyhd8ed1ab_0    conda-forge
conda-package-handling    2.4.0              pyh7900ff3_2    conda-forge
conda-package-streaming   0.11.0             pyhd8ed1ab_1    conda-forge
cpp-expected              1.1.0                hff21bea_1    conda-forge
distro                    1.9.0              pyhd8ed1ab_1    conda-forge
fmt                       11.1.4               h07f6e7f_1    conda-forge
frozendict                2.4.6           py312h66e93f0_0    conda-forge
h2                        4.2.0              pyhd8ed1ab_0    conda-forge
hpack                     4.1.0              pyhd8ed1ab_0    conda-forge
hyperframe                6.1.0              pyhd8ed1ab_0    conda-forge
icu                       75.1                 he02047a_0    conda-forge
idna                      3.10               pyhd8ed1ab_1    conda-forge
jsonpatch                 1.33               pyhd8ed1ab_1    conda-forge
jsonpointer               3.0.0           py312h7900ff3_1    conda-forge
keyutils                  1.6.1                h166bdaf_0    conda-forge
krb5                      1.21.3               h659f571_0    conda-forge
ld_impl_linux-64          2.43                 h712a8e2_4    conda-forge
libarchive                3.7.7                h75ea233_4    conda-forge
libcurl                   8.13.0               h332b0f4_0    conda-forge
libedit                   3.1.20250104    pl5321h7949ede_0    conda-forge
libev                     4.33                 hd590300_2    conda-forge
libexpat                  2.7.0                h5888daf_0    conda-forge
libffi                    3.4.6                h2dba641_1    conda-forge
libgcc                    15.1.0               h767d61c_2    conda-forge
libgcc-ng                 15.1.0               h69a702a_2    conda-forge
libgomp                   15.1.0               h767d61c_2    conda-forge
libiconv                  1.18                 h4ce23a2_1    conda-forge
liblzma                   5.8.1                hb9d3cd8_1    conda-forge
libmamba                  2.1.1                h430c389_0    conda-forge
libmambapy                2.1.1           py312h07448e0_0    conda-forge
libnghttp2                1.64.0               h161d5f1_0    conda-forge
libnsl                    2.0.1                hd590300_0    conda-forge
libsolv                   0.7.32               h7955e40_2    conda-forge
libsqlite                 3.49.2               hee588c1_0    conda-forge
libssh2                   1.11.1               hcf80075_0    conda-forge
libstdcxx                 15.1.0               h8f9b012_2    conda-forge
libstdcxx-ng              15.1.0               h4852527_2    conda-forge
libuuid                   2.38.1               h0b41bf4_0    conda-forge
libxcrypt                 4.4.36               hd590300_1    conda-forge
libxml2                   2.13.8               h4bc477f_0    conda-forge
libzlib                   1.3.1                hb9d3cd8_2    conda-forge
lz4-c                     1.10.0               h5888daf_1    conda-forge
lzo                       2.10              hd590300_1001    conda-forge
mamba                     2.1.1                had4a41a_0    conda-forge
menuinst                  2.2.0           py312h7900ff3_0    conda-forge
ncurses                   6.5                  h2d0b736_3    conda-forge
nlohmann_json             3.11.3               he02047a_1    conda-forge
openssl                   3.5.0                h7b32b05_1    conda-forge
packaging                 25.0               pyh29332c3_1    conda-forge
pip                       25.1.1             pyh8b19718_0    conda-forge
platformdirs              4.3.8              pyhe01879c_0    conda-forge
pluggy                    1.5.0              pyhd8ed1ab_1    conda-forge
pybind11-abi              4                    hd8ed1ab_3    conda-forge
pycosat                   0.6.6           py312h66e93f0_2    conda-forge
pycparser                 2.22               pyh29332c3_1    conda-forge
pysocks                   1.7.1              pyha55dd90_7    conda-forge
python                    3.12.10         h9e4cc4f_0_cpython    conda-forge
python_abi                3.12                    7_cp312    conda-forge
readline                  8.2                  h8c095d6_2    conda-forge
reproc                    14.2.5.post0         hb9d3cd8_0    conda-forge
reproc-cpp                14.2.5.post0         h5888daf_0    conda-forge
requests                  2.32.3             pyhd8ed1ab_1    conda-forge
ruamel.yaml               0.18.10         py312h66e93f0_0    conda-forge
ruamel.yaml.clib          0.2.8           py312h66e93f0_1    conda-forge
setuptools                80.1.0             pyhff2d567_0    conda-forge
simdjson                  3.12.3               h84d6215_0    conda-forge
tk                        8.6.13          noxft_h4845f30_101    conda-forge
tqdm                      4.67.1             pyhd8ed1ab_1    conda-forge
truststore                0.10.1             pyh29332c3_0    conda-forge
tzdata                    2025b                h78e105d_0    conda-forge
urllib3                   2.4.0              pyhd8ed1ab_0    conda-forge
wheel                     0.45.1             pyhd8ed1ab_1    conda-forge
yaml-cpp                  0.8.0                h3f2d84a_0    conda-forge
zstandard                 0.23.0          py312h66e93f0_2    conda-forge
zstd                      1.5.7                hb8e6e7a_2    conda-forge

Environment info

(base) conda info

     active environment : base
    active env location : /opt/conda
            shell level : 1
       user config file : /root/.condarc
 populated config files : /opt/conda/.condarc
                          /root/.condarc
          conda version : 25.3.0
    conda-build version : not installed
         python version : 3.12.10.final.0
                 solver : classic
       virtual packages : __archspec=1=x86_64_v2
                          __conda=25.3.0=0
                          __glibc=2.35=0
                          __linux=6.12.5=0
                          __unix=0=0
       base environment : /opt/conda  (writable)
      conda av data dir : /opt/conda/etc/conda
  conda av metadata url : None
           channel URLs : https://conda.anaconda.org/conda-forge/linux-64
                          https://conda.anaconda.org/conda-forge/noarch
          package cache : /opt/conda/pkgs
                          /root/.conda/pkgs
       envs directories : /opt/conda/envs
                          /root/.conda/envs
               platform : linux-64
             user-agent : conda/25.3.0 requests/2.32.3 CPython/3.12.10 Linux/6.12.5-linuxkit ubuntu/22.04.5 glibc/2.35
                UID:GID : 0:0
             netrc file : None
           offline mode : False

[h-vetinari]

Thanks for the issue. Since you're on a non-CUDA system, the only relevant change merged recently (3 days ago) would be 91d7940.

Could you try if

channels:
  - conda-forge
dependencies:
  - libtorch =*=cpu*

goes faster?

[meiyasan]

@h-vetinari Thanks! Yes, it definitely works much better. Resolution took about 1-2 seconds.
Would you consider rolling back the commit?

[h-vetinari]

Would you consider rolling back the commit?

This commit actually solved another issue, but I think I have a way to fix it. I'll try to include it with the next PR, but currently both #399 and #396 are blocked on an issue we haven't fully debugged yet.

[baszalmstra]

Im not entirely sure what causes this since libtorch doesnt depend on the packages that were affected in #394. It (libtorch) only has a constraint on pytorch-cpu and pytorch-gpu which should as far as I understand not result in any explosion that would cause a solver slowdown. But I see you are also using the classic solver, I am not too familiar with the internals of that implementation.

So I tried this locally with:

conda create --dry-run -n foobar libtorch --platform linux-64 --override-channels -c conda-forge --solver classic

But it runs in ~25 seconds vs ~24 seconds when solving libtorch =*=cpu*. (It only takes 4 seconds to solve this with the (now default) libmamba solver) (and (shameless plug) just 2.7s with the new conda-rattler-solver plugin).

So it seems Im not able to reproduce this, would you be able to provide a reproducer that I can try?

[meiyasan]

Sorry for the confusion, there were couple of issues in my approach. I just noticed that my test yesterday wasn't running on classic solver so it appeared lighting fast. Perhaps my initial issue was about conda recipe. I have no issue anymore, I believe pinning on libtorch on cpu didn't change anything as you already guessed. Thanks for the time!

Here is the conda info after fixing the solver configuration 🙏

(base) conda info

     active environment : base
    active env location : /opt/conda
            shell level : 1
       user config file : /root/.condarc
 populated config files : /opt/conda/.condarc
                          /root/.condarc
          conda version : 25.3.0
    conda-build version : not installed
         python version : 3.12.10.final.0
                 solver : libmamba (default)
       virtual packages : __archspec=1=x86_64_v2
                          __conda=25.3.0=0
                          __glibc=2.35=0
                          __linux=6.12.5=0
                          __unix=0=0
       base environment : /opt/conda  (writable)
      conda av data dir : /opt/conda/etc/conda
  conda av metadata url : None
           channel URLs : https://conda.anaconda.org/conda-forge/linux-64
                          https://conda.anaconda.org/conda-forge/noarch
          package cache : /opt/conda/pkgs
                          /root/.conda/pkgs
       envs directories : /opt/conda/envs
                          /root/.conda/envs
               platform : linux-64
             user-agent : conda/25.3.0 requests/2.32.3 CPython/3.12.10 Linux/6.12.5-linuxkit ubuntu/22.04.5 glibc/2.35 solver/libmamba conda-libmamba-solver/25.3.0 libmambapy/2.1.1
                UID:GID : 0:0
             netrc file : None
           offline mode : False

[meiyasan]

For the records, what drove my concern toward pytorch was due to the warnings triggered by libtorch dependencies using the classic solver.

WARNING conda.models.version:get_matcher(563): Using .* with relational operator is superfluous and deprecated and will be removed in a future version of conda. Your spec was 1.8.0.*, but conda is ignoring the .* and treating it as 1.8.0
WARNING conda.models.version:get_matcher(563): Using .* with relational operator is superfluous and deprecated and will be removed in a future version of conda. Your spec was 1.6.0.*, but conda is ignoring the .* and treating it as 1.6.0
WARNING conda.models.version:get_matcher(563): Using .* with relational operator is superfluous and deprecated and will be removed in a future version of conda. Your spec was 1.7.1.*, but conda is ignoring the .* and treating it as 1.7.1

This is not visible anymore while switching back to libmamba.

P.S. thanks for pointing at [conda-rattler-solver](https://github.com/conda-incubator/conda-rattler-solver)!!