Mim install fails to install dependencies

[alexh-deeplite]

Checklist

1. I have searched related issues but cannot get the expected help. ✅
2. I have read the FAQ documentation but cannot get the expected help. ✅
3. The bug has not been fixed in the latest version. ✅

Describe the bug
mim install mmpretrain prints the following warnings with pip>=24.1:

Ignoring mmcv: markers 'extra == "mim"' don't match your environment
Ignoring mmdet: markers 'extra == "mim"' don't match your environment
Ignoring mmengine: markers 'extra == "mim"' don't match your environment

Followed by failed import of mmcv when importing the package. Basically, mim is failing to install its dependencies

Reproduction

1. What command or script did you run?

conda create -n mm python=3.8
conda deactivate
conda activate mm
pip install --upgrade pip
pip install openmim
pip install torch
mim install mmpretrain
python -c "import mmpretrain"
pip list

Output:

(mm) $ pip install --upgrade pip
Requirement already satisfied: pip in miniconda3/envs/mm/lib/python3.8/site-packages (24.0)
Collecting pip
  Downloading pip-24.1.2-py3-none-any.whl.metadata (3.6 kB)
Downloading pip-24.1.2-py3-none-any.whl (1.8 MB)
   ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1.8/1.8 MB 60.8 MB/s eta 0:00:00
Installing collected packages: pip
  Attempting uninstall: pip
    Found existing installation: pip 24.0
    Uninstalling pip-24.0:
      Successfully uninstalled pip-24.0
Successfully installed pip-24.1.2
(mm) $ pip install torch
Collecting torch
... omitted for space

(mm) $ mim install mmpretrain
Looking in links: https://download.openmmlab.com/mmcv/dist/cu121/torch2.3.0/index.html
Collecting mmpretrain
  Using cached mmpretrain-1.2.0-py2.py3-none-any.whl.metadata (20 kB)
Ignoring mmcv: markers 'extra == "mim"' don't match your environment
Ignoring mmengine: markers 'extra == "mim"' don't match your environment
... continues installing other required packages (omitted for space)

(mm) $ pip list
Package                  Version
------------------------ -----------
aliyun-python-sdk-core   2.15.1
aliyun-python-sdk-kms    2.16.3
certifi                  2024.7.4
cffi                     1.16.0
charset-normalizer       3.3.2
click                    8.1.7
colorama                 0.4.6
contourpy                1.1.1
crcmod                   1.7
cryptography             42.0.8
cycler                   0.12.1
einops                   0.8.0
filelock                 3.14.0
fonttools                4.53.1
fsspec                   2024.6.1
idna                     3.7
importlib_metadata       8.0.0
importlib_resources      6.4.0
Jinja2                   3.1.4
jmespath                 0.10.0
kiwisolver               1.4.5
Markdown                 3.6
markdown-it-py           3.0.0
MarkupSafe               2.1.5
mat4py                   0.6.0
matplotlib               3.7.5
mdurl                    0.1.2
mmpretrain               1.2.0
model-index              0.1.11
modelindex               0.0.2
mpmath                   1.3.0
networkx                 3.1
numpy                    1.24.4
nvidia-cublas-cu12       12.1.3.1
nvidia-cuda-cupti-cu12   12.1.105
nvidia-cuda-nvrtc-cu12   12.1.105
nvidia-cuda-runtime-cu12 12.1.105
nvidia-cudnn-cu12        8.9.2.26
nvidia-cufft-cu12        11.0.2.54
nvidia-curand-cu12       10.3.2.106
nvidia-cusolver-cu12     11.4.5.107
nvidia-cusparse-cu12     12.1.0.106
nvidia-ml-py             12.535.133
nvidia-nccl-cu12         2.20.5
nvidia-nvjitlink-cu12    12.5.82
nvidia-nvtx-cu12         12.1.105
nvitop                   1.3.2
opendatalab              0.0.10
openmim                  0.3.9
openxlab                 0.1.1
ordered-set              4.1.0
oss2                     2.17.0
packaging                24.1
pandas                   2.0.3
pillow                   10.4.0
pip                      24.1.2
psutil                   5.9.7
pycparser                2.22
pycryptodome             3.20.0
Pygments                 2.18.0
pyparsing                3.1.2
python-dateutil          2.9.0.post0
pytz                     2023.4
PyYAML                   6.0.1
requests                 2.28.2
rich                     13.4.2
setuptools               60.2.0
six                      1.16.0
sympy                    1.13.0
tabulate                 0.9.0
torch                    2.3.1
tqdm                     4.65.2
triton                   2.3.1
typing_extensions        4.12.2
tzdata                   2024.1
urllib3                  1.26.19
wheel                    0.43.0
zipp                     3.19.2

(mm) $ python -c "import mmpretrain"
Traceback (most recent call last):
  File "<string>", line 1, in <module>
  File "miniconda3/envs/mm/lib/python3.8/site-packages/mmpretrain/__init__.py", line 2, in <module>
    import mmcv
ModuleNotFoundError: No module named 'mmcv'

4. Did you make any modifications on the code or config? Did you understand what you have modified? No
5. What dataset did you use? N/A

Environment

1. Please run python mmdet/utils/collect_env.py to collect necessary environment information and paste it here. N/A, see pip list above, python=3.8.12
2. You may add addition that may be helpful for locating the problem, such as
   • How you installed PyTorch [e.g., pip, conda, source]: yes, torch==2.3.1, CUDA Version: 12.2
   • Other environment variables that may be related (such as $PATH, $LD_LIBRARY_PATH, $PYTHONPATH, etc.)

Error traceback
If applicable, paste the error trackback here.

Traceback (most recent call last):
  File "<string>", line 1, in <module>
  File "/home/alex/miniconda3/envs/mm/lib/python3.8/site-packages/mmpretrain/__init__.py", line 2, in <module>
    import mmcv
ModuleNotFoundError: No module named 'mmcv'

Bug fix
Reverting to pip<=24.0 resolved this issue. I believe the problem is related to this part of openmim, where we hack the pip installer to accept mim extras. This was working in previous pip versions but no longer works

The earliest version of pip where the bug is observed is 24.1b1

@ice-tong seemed to address this issue with the patched_requires code but I'm afraid the fix is no longer working