cudf instllation issue on centos7

I’m new to rapids ai libraries. I’ve an existing conda environment yaml file where I’m using python 3.8.5, tensorflow 2.7.0, opencv-python-headless 4.5.5.62, numpy 1.22.2, pandas 1.4.1, pandas-profiling 3.1.0, seaborn 0.11.2, matplotlib 3.5.1, jupyterlab 3.2.9.

I’ve added below 2 channels to the file:

• rapidsai
• nvidia

And the below packages:

• cudf=22.02
• cudatoolkit=11.5

The installation is going on for hours and while trying to find incompatible packages, it seems to be in some sort of loop as I keep seeing below message multiple times in the terminal:

Found conflicts! Looking for incompatible packages.

Is there any known issue/limitations that I should be aware of?

Since we don’t get interactive shell on GPU h/w easily, I’m trying the conda environment update on non-GPU machine and once installed, I’ll try cudf package on GPU machine.

EDIT1:
This is what I have as working without tensorflow and tensorflow-hub

    name: cudf-env
        channels:
          - default
          - rmg
          - rapidsai
          - nvidia
          - numba
          - conda-forge
          - anaconda
        dependencies:
          - glibc=2.19
          - libgcc-ng=11.2.0
          - python=3.8.5
          - cudf=22.02
          - cudatoolkit=11.2
          - pytest=6.1.2
          - pandas=1.3.5
          - numpy=1.21.5
          - requests=2.25.0
          - scikit-learn=0.24.2
          - dill=0.3.4
          - tqdm=4.62.3
          - ruamel.yaml=0.17.19
          - yappi=1.3.3
          - black=22.1.0
          - pillow=9.0.1
          - jupyterlab=3.2.9
          - matplotlib=3.5.1
          - seaborn=0.11.2
          - plotly=5.6.0
          - pandas-profiling=3.1.0
          - black=22.1.0
        #  - pip
        #  - pip:
        #      - tensorflow==2.7.0
        #      - tensorflow-hub==0.12.0
        #      - opencv-python-headless==4.5.5.62
        #      - opencv-contrib-python-headless==4.5.5.62

Now, if I uncomment the pip section, the anaconda crashes while creating the environment. Since pip may not be supported with cudf, I tried following as well, the conda create env hangs while solving the environment (strangely, it’s not resolving from conda-forge channel):

    name: cudf-env
        channels:
          - default
          - rmg
          - rapidsai
          - nvidia
          - numba
          - conda-forge
          - anaconda
        dependencies:
          - glibc=2.19
          - libgcc-ng=11.2.0
          - python=3.8.5
          - cudf=22.02
          - cudatoolkit=11.2
          - pytest=6.1.2
          - pandas=1.3.5
          - numpy=1.21.5
          - requests=2.25.0
          - scikit-learn=0.24.2
          - dill=0.3.4
          - tqdm=4.62.3
          - ruamel.yaml=0.17.19
          - yappi=1.3.3
          - black=22.1.0
          - pillow=9.0.1
          - jupyterlab=3.2.9
          - matplotlib=3.5.1
          - seaborn=0.11.2
          - plotly=5.6.0
          - pandas-profiling=3.1.0
          - black=22.1.0
          - tensorflow
          - tensorflow-hub

My system details are following:

$ cat /etc/os-release
NAME="CentOS Linux"
VERSION="7 (Core)"

$ uname -r
3.10.0-1127.10.1.el7.x86_64

EDIT2: I forgot to mention that if I comment out glibc, cudf and cudatoolkit, the tensorflow installation through pip works fine.