No module named 'amp_C' error for py3.9 pytorch2.1.0 cuda12.1

[rocke2020]

Describe the Bug
python
import amp_C
ModuleNotFoundError: No module named 'amp_C'
Minimal Steps/Code to Reproduce the Bug
python 3.9, torch 2.1.0, cuda 12.1, pip 23.3.1
git clone https://github.com/NVIDIA/apex

cd apex

if pip >= 23.1 (ref: https://pip.pypa.io/en/stable/news/#v23-1) which supports multiple --config-settings with the same key...
As my pip version is 23.3.1
pip install -v --disable-pip-version-check --no-cache-dir --no-build-isolation --config-settings "--build-option=--cpp_ext" --config-settings "--build-option=--cuda_ext" ./

2. from can't install apex #1594
   I installed apex-0.1 successfully, when I run "import amp_C" in python, the No module named 'amp_C' error.
3. I had seen several No module named 'amp_C' issues, but none solved my problem.
   So, create a new No module named 'amp_C' issue on this exact env, pytorch 2.1 pip23.3.1
   thanks!!

Expected Behavior
apex can run normally in py3.9 pytorch2.1.0 cuda12.1, pip23.3.1 no error, to use deepspeed.

Environment
pip 23.3.1
PyTorch version: 2.1.0
Is debug build: False
CUDA used to build PyTorch: 12.1
ROCM used to build PyTorch: N/A

OS: Ubuntu 20.04.6 LTS (x86_64)
GCC version: (Ubuntu 9.4.0-1ubuntu1~20.04.1) 9.4.0
Clang version: Could not collect
CMake version: version 3.16.3
Libc version: glibc-2.31

Python version: 3.9.18 (main, Sep 11 2023, 13:41:44) [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-5.15.0-72-generic-x86_64-with-glibc2.31
Is CUDA available: True
CUDA runtime version: 12.1.105
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration:
GPU 0: NVIDIA GeForce RTX 3090
GPU 1: NVIDIA GeForce RTX 3090

Nvidia driver version: 530.30.02
cuDNN version: Probably one of the following:
/usr/local/cuda-11.4/targets/x86_64-linux/lib/libcudnn.so.8.5.0
numpy==1.26.2

[rocke2020]

strictly follow #1737 (comment)
I install apex successfully. The key is pip install with global option, even with pip 23.3
pip install -v --disable-pip-version-check --no-cache-dir --global-option="--cpp_ext" --global-option="--cuda_ext" ./

successful env
PyTorch 1.8.1
Python 3.8(ubuntu20.04)
Cuda 11.1