场景：一个有3张k100服务器，已经部署了hami模式dcu，现在想让k8s集群独占其中两张卡，集群中的业务pod都使用指定的这两张k100，另外一张卡供其余业务使用，具体该怎么操作

源码中的示例：

apiVersion: v1
kind: Pod
metadata:
  name: alexnet-tf-gpu-pod
  labels:
    purpose: demo-tf-amdgpu
spec:
  containers:
    - name: alexnet-tf-gpu-container
      image: rocm/tensorflow:latest
      workingDir: /root
      env:
      - name: HIP_VISIBLE_DEVICES
        value: "0" # # 0,1,2,...,n for running on GPU and select the GPUs, -1 for running on CPU 
      command: ["/bin/bash", "-c", "--"]
      args: ["python3 benchmarks/scripts/tf_cnn_benchmarks/tf_cnn_benchmarks.py --model=alexnet; trap : TERM INT; sleep infinity & wait"]
      resources:
        limits:
          dcu/gpu: 1 # requesting a GPU

env中的HIP_VISIBLE_DEVICES这个参数是否是通用的，能否加入到dcu-device-plugin中，让GPU注册的时候就只注册指定的GPU