conda CPU installation for LTS fails with UnsatisfiableError
Labels: triaged, module: lts

### 🐛 Describe the bug

In a totally empty conda environment on Linux, copy pasting the installation command from [here](https://pytorch.org/get-started/locally):

```sh                                                                                                                                                                                                                      
conda install pytorch torchvision torchaudio cpuonly -c pytorch-lts
```

Output:
```
Collecting package metadata (current_repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment: failed with repodata from current_repodata.json, will retry with next repodata source.
Collecting package metadata (repodata.json): doneSolving environment: failed with initial frozen solve. Retrying with flexible solve.Solving environment: | Found conflicts! Looking for incompatible packages.This can take several minutes.  Press CTRL-C to abort.failed                                                                                                                                                                                                                                                                                                                                                            
UnsatisfiableError: The following specifications were found to be incompatible with each other:
Output in format: Requested package -> Available versions
Package typing conflicts for:pytorch -> typing_extensions -> typing[version='>=3.6.2|>=3.7.4']pytorch -> typing
Package pytorch conflicts for:torchvision -> pytorch[version='*|*|1.10|1.10|1.8.1|1.8.2|>=1.11.0,<1.12.0a0|>=1.10.2,<1.11.0a0|1.10.0.*|>=1.8.0|>=1.8.0|1.7.1.*|1.3.1.*|1.2.0.*|1.1.*|>=0.4|>=0.3',build='cpu*|cuda*|cuda*|cpu*|cuda*|cpu*']torchvision -> pytorch-cpu -> pytorch[version='1.10.0|1.10.0|1.10.0|1.10.0|1.10.0|1.10.0|1.10.0|1.10.0|1.10.0|1.10.0|1.10.0|1.10.0|1.10.0|1.10.0|1.10.0|1.10.0|1.10.0|1.10.0|1.10.0|1.10.0|1.10.0|1.10.0|1.10.0|1.10.0|1.10.0|1.10.0|1.10.0|1.10.0|1.10.0|1.10.0|1.10.1|1.10.1|1.10.1|1.10.2|1.10.2|1.10.2|1.10.2|1.10.2|1.10.2|1.11.0|1.9.1|1.9.1|1.9.1|1.9.1|1.9.0|1.9.0|1.9.0|1.9.0|1.9.0|1.9.0|1.9.0|1.9.0|1.9.0|1.9.0|1.9.0|1.9.0|1.8.0|1.8.0|1.8.0|1.8.0|1.8.0|1.8.0|1.8.0|1.8.0|1.8.0|1.8.0|1.8.0|1.8.0|1.8.0|1.8.0|1.8.0|1.8.0|1.7.1|1.7.1|1.7.1|1.7.1|1.7.1|1.7.1|1.7.1|1.7.1|1.6.0|1.6.0|1.6.0|1.6|1.11.0|1.11.0|1.11.0|1.11.0|1.11.0|1.11.0|1.11.0|1.11.0|1.11.0|1.11.0|1.11.0|1.11.0|1.11.0|1.11.0|1.11.0|1.11.0|1.11.0|1.11.0|1.10.2|1.10.2|1.10.2|1.10.2|1.10.2|1.10.2|1.10.2|1.10.2|1.10.2|1.10.2|1.10.2|1.10.2|1.10.2|1.10.2|1.10.2|1.10.2|1.10.2|1.10.2|1.10.2|1.10.2|1.10.2|1.10.2|1.10.2|1.10.2|1.10.1|1.10.1|1.10.1|1.10.1|1.10.1|1.10.1|1.10.1|1.10.1|1.10.1|1.10.1|1.10.1|1.10.1|1.9.1|1.9.1|1.9.1|1.9.1|1.9.1|1.9.1|1.9.1|1.9.1|1.9.1|1.9.1|1.9.1|1.9.1|1.9.1|1.9.1|1.9.1|1.9.1|1.9.0|1.9.0|1.9.0|1.9.0|1.9.0|1.9.0|1.9.0|1.9.0|1.9.0|1.9.0|1.9.0|1.9.0|1.9.0|1.9.0|1.9.0|1.9.0|1.8.0|1.8.0|1.8.0|1.8.0|1.8.0|1.8.0|1.8.0|1.8.0|1.8.0|1.8.0|1.8.0|1.8.0|1.8.0|1.8.0|1.8.0|1.8.0|1.7.1|1.7.1|1.7.1|1.7.1|1.7.1|1.7.1|1.7.1|1.7.1|1.7.1|1.7.1|1.7.1|1.7.1|1.7.1|1.7.1|1.7.1|1.7.1|1.6.0|1.6.0|1.6.0|1.6.0|1.6.0|1.6.0|1.6.0|1.6.0|1.6.0|1.6.0|1.6.0|1.6.0|1.6.0|1.6.0|1.6.0|1.6.0',build='cuda92py36h7ecc001_1|cuda100py36hd82b6f9_1|cuda102py36h8620ce9_1|cuda101py36h42dc283_1|cuda92py37hc3ec645_1|cuda102py37h4d98c68_1|cuda100py37h50b9e00_1|cuda101py37h7589291_1|cuda92py38hb6ed0dd_1|cuda100py38h679e3f5_1|cuda102py39h09d0254_1|cuda92py39hde86683_1|cuda100py39h2b73809_1|cuda102py38h9f8c3ab_1|cuda92py36h7ecc001_1|cuda102py36h8620ce9_1|cuda100py36hd82b6f9_1|cuda92py37hc3ec645_1|cuda102py37h4d98c68_1|cuda100py37h50b9e00_1|cuda101py38h2499a06_1|cuda92py39hde86683_1|cuda102py39h09d0254_1|cuda100py39h2b73809_1|cuda92py38hb6ed0dd_1|cuda100py38h679e3f5_1|cuda101py36h42dc283_1|cuda101py39h41d04a9_1|cuda102py36hf4eb8d7_0|cuda102py38h540557e_0|cuda102py39hf89b2ab_0|cuda110py36h7ef7e1d_0|cuda110py38h65e529b_0|cuda111py38he2736ed_1|cuda112py39h716d6ff_1|cuda111py37h50e976f_1|cuda102py38hf03d9dd_1|cuda112py39hbeb36f3_1|cuda110py38hc2289b8_1|cuda112py36h755b813_1|cuda112py37hcb91bf2_1|cuda111py36hc5445e6_1|cuda110py37h00edf66_1|cuda102py37h92fd811_1|cuda110py39hd6acddb_1|cuda112py38h4f2a933_3|cuda112py36h36e649e_3|cuda111py36h8a2106e_3|cuda111py37he371307_3|cuda112py37h3bec1eb_3|cuda111py38h2f85826_3|cuda102py37h98b7ee3_3|cuda102py39h2fcd037_3|cuda110py36he570edd_3|cuda110py38hf84197b_0|cuda112py37h3bec1eb_0|cuda112py38h4f2a933_0|cuda102py37h98b7ee3_0|cuda110py39h5cf7045_0|cuda111py39hb4a4491_0|cuda112py37haf94430_1|cuda102py38h17946ce_1|cuda111py39h7295ad4_1|cuda102py39h06ffc54_1|cuda111py38h9575ccd_1|cuda110py37h7b7832c_1|cuda102py39hfe0cb5b_0|cuda112py38h6425f36_0|cuda112py37hc1ee5ce_0|cuda111py39h930882a_0|cuda110py39he47eb21_0|cuda112py38h6425f36_0|cuda111py39h930882a_0|cuda110py39he47eb21_0|cuda102py39hfe0cb5b_0|cuda111py37hc0ce48b_1|cuda110py38hf0a79ac_1|cuda111py38hc64aeea_1|cuda102py39hfe0cb5b_1|cuda111py39h930882a_1|cuda102py39hfe0cb5b_0|cuda112py38habe9d5a_1|cuda102py310hdf4a2db_1|cuda110py38h386aa8f_1|cuda110py37h0def887_1|cuda111py37hdb2541a_1|cuda102py37haad9b4f_1|cuda110py310hfdf97d1_1|cuda111py39h9f128c5_1|cuda112py39ha0cca9b_1|cuda111py38h2d04dd0_1|cuda110py39h0a9da28_1|cuda112py310h51fe464_1|cuda111py310h385535d_1|cpu_py37hf1c21f6_1|cpu_py39h714fb45_1|cpu_py38h36eccb8_1|cpu_py36h63cae03_1|cpu_py37hf1c21f6_1|cpu_py36h63cae03_2|cpu_py39h714fb45_2|cpu_py36h2ecc29a_0|cpu_py39h0fbb4fb_0|cpu_py38hd248515_1|cpu_py37hd5260e0_2|cpu_py38h91ab35c_2|cpu_py39hfbcbfe4_2|cpu_py38h91ab35c_3|cpu_py36h95c28ec_3|cpu_py39hfbcbfe4_0|cpu_py37hd5260e0_0|cpu_py36h95c28ec_0|cpu_py36h3564fbe_1|cpu_py38hfb3baa6_1|cpu_py37hff829bd_1|cpu_py39h818de69_2|cpu_py37hf3cc979_3|cpu_py36ha8b20dc_3|cpu_py38h1ee18c8_3|cpu_py38h1ee18c8_0|cpu_py39h5e9ed0b_0|cpu_py39h5e9ed0b_0|cpu_py37h76afcab_1|cpu_py39h5e9ed0b_1|cpu_py37hd754017_0|cpu_py39h5d22d69_1|cpu_py310h75c9ab6_1|cpu_py38h39c826d_1|cpu_py37h14e09b7_1|cpu_py310h2272b30_0|cpu_py39h7613f69_0|cpu_py38hde1b6bc_0|cpu_py38hb2150b6_1|cpu_py38hb2150b6_0|cpu_py37h76afcab_0|cpu_py37h76afcab_0|cpu_py38hb2150b6_0|cpu_py39hc70245e_1|cpu_py38h7c5583f_1|cpu_py37h2761dfd_1|cpu_py37hf3cc979_0|cpu_py39hc5866cc_0|cpu_py39hc5866cc_3|cpu_py38h4bbe6ce_2|cpu_py37hb06efa0_2|cpu_py36h1c7b8ea_2|cpu_py39h818de69_1|cpu_py38h91ab35c_0|cpu_py39hfbcbfe4_3|cpu_py37hd5260e0_3|cpu_py36h95c28ec_2|cpu_py39h0fbb4fb_1|cpu_py37ha70c682_1|cpu_py36h2d15a6b_1|cpu_py38he614459_0|cpu_py37hafa7651_0|cpu_py37hf1c21f6_2|cpu_py38h36eccb8_2|cpu_py38h36eccb8_1|cpu_py36h63cae03_1|cuda102py39hbbcd3cb_1|cuda112py37hfcfbd4c_1|cuda102py38hfdb21e3_1|cuda110py38hade5236_0|cuda112py39h4de5995_1|cuda110py39he47eb21_1|cuda102py38h9fb240c_1|cuda110py37h4121e64_1|cuda112py38h6425f36_1|cuda112py37hc1ee5ce_1|cuda102py37hc804c4d_1|cuda102py38h9fb240c_0|cuda102py37hc804c4d_0|cuda110py37h4121e64_0|cuda110py38hf0a79ac_0|cuda111py37hc0ce48b_0|cuda111py38hc64aeea_0|cuda112py37hc1ee5ce_0|cuda112py39h4de5995_0|cuda110py37h4121e64_0|cuda110py38hf0a79ac_0|cuda111py37hc0ce48b_0|cuda111py38hc64aeea_0|cuda112py39h4de5995_0|cuda102py37hc804c4d_0|cuda102py38h9fb240c_0|cuda102py37h689c94d_1|cuda111py37h07fa5b8_1|cuda110py39h423d6c6_1|cuda110py38h68479e5_1|cuda112py39h3ad47f5_1|cuda112py38had345c2_1|cuda112py39h4e14dd4_0|cuda110py37h4a33b93_0|cuda102py38ha031fbe_0|cuda111py38h2f85826_0|cuda111py37he371307_0|cuda102py39h2fcd037_0|cuda110py39h5cf7045_3|cuda110py38hf84197b_3|cuda110py37h4a33b93_3|cuda102py38ha031fbe_3|cuda102py36h3d4679f_3|cuda111py39hb4a4491_3|cuda112py39h4e14dd4_3|cuda112py38h3d13190_1|cuda111py37h78388d7_1|cuda102py39h9bf10ef_1|cuda111py38h5169e65_1|cuda110py36h768fbb7_1|cuda102py36he3537ca_1|cuda111py39hc274426_1|cuda112py37h946b90b_1|cuda112py36h5fea6e2_1|cuda111py36h3cb1cac_1|cuda111py39h37e5b68_1|cuda112py38h3bc52bc_1|cuda110py39hbc72f07_0|cuda110py37h5fb8b0b_0|cuda102py37h4454d97_0|cuda102py38h9f8c3ab_1|cuda101py37h7589291_1|cuda101py39h41d04a9_1|cuda101py38h2499a06_1']torchaudio -> pytorch[version='1.8.1|1.8.2']
pytorch

Package nccl conflicts for:
pytorch -> nccl[version='<2|>=2.10.3.1,<3.0a0|>=2.11.4.1,<3.0a0|>=2.12.10.1,<3.0a0|>=2.12.7.1,<3.0a0|>=2.8.4.1,<3.0a0|>=2.7.8.1,<3.0a0']
torchvision -> pytorch[version='>=1.11.0,<1.12.0a0'] -> nccl[version='<2|>=2.10.3.1,<3.0a0|>=2.11.4.1,<3.0a0|>=2.12.10.1,<3.0a0|>=2.12.7.1,<3.0a0|>=2.8.4.1,<3.0a0|>=2.7.8.1,<3.0a0']The following specifications were found to be incompatible with your system:

  - feature:/linux-64::__glibc==2.31=0
  - feature:|@/linux-64::__glibc==2.31=0
  - torchvision -> __glibc[version='>=2.17|>=2.17,<3.0.a0']

Your installed version is: 2.31

Note that strict channel priority may have removed packages required for satisfiability.
```

Perhaps relevant:
```
➜  conda info

     active environment : lts-scratch
    active env location : /home/azureuser/miniconda3/envs/lts-scratch
            shell level : 1
       user config file : /home/azureuser/.condarc
 populated config files : /home/azureuser/.condarc
          conda version : 4.12.0
    conda-build version : 3.21.4
         python version : 3.9.10.final.0
       virtual packages : __linux=5.4.0=0
                          __glibc=2.31=0
                          __unix=0=0
                          __archspec=1=x86_64
       base environment : /home/azureuser/miniconda3  (writable)
      conda av data dir : /home/azureuser/miniconda3/etc/conda
  conda av metadata url : None
           channel URLs : https://conda.anaconda.org/conda-forge/linux-64
                          https://conda.anaconda.org/conda-forge/noarch
                          https://repo.anaconda.com/pkgs/main/linux-64
                          https://repo.anaconda.com/pkgs/main/noarch
                          https://repo.anaconda.com/pkgs/r/linux-64
                          https://repo.anaconda.com/pkgs/r/noarch
          package cache : /home/azureuser/miniconda3/pkgs
                          /home/azureuser/.conda/pkgs
       envs directories : /home/azureuser/miniconda3/envs
                          /home/azureuser/.conda/envs
               platform : linux-64
             user-agent : conda/4.12.0 requests/2.27.1 CPython/3.9.10 Linux/5.4.0-1041-azure ubuntu/20.04.2 glibc/2.31
                UID:GID : 1000:1000
             netrc file : None
           offline mode : False
```