Does Hami support RKE2 when using Operator-gpu

[zopidev]

Hi everyone,
I have a k8s rke2 cluster with gpu operator installed.
I want to install Hami but when it deployed devicePlugin in Hami chart, it shown the error:
could not load NVML library: libnvidia-ml.so.1
But when deploy devicePlugin in gpu operator it's normal.
This is my value config in gpu-operator chart:

    hostPaths:
      rootFS: "/"
      driverInstallDir: "/run/nvidia/driver"
    daemonsets:
      labels: {}
      annotations: {}
      priorityClassName: system-node-critical
      nodeSelector:
        gpu: "true"
      tolerations:
      - key: nvidia.com/gpu
        operator: Exists
        effect: NoSchedule
      updateStrategy: "RollingUpdate"
      rollingUpdate:
        maxUnavailable: "1"
    nfd:
      enabled: true
    node-feature-discovery:
      master:
        enable: true
        nodeSelector: { gpu: "true" }
        tolerations:
          - key: "nvidia.com/gpu"
            operator: "Exists"
            effect: "NoSchedule"
      worker:
        enable: true
        nodeSelector: { gpu: "true" }
        tolerations:
          - key: "nvidia.com/gpu"
            operator: "Exists"
            effect: "NoSchedule"
    driver:
      enabled: true  # Let GPU Operator manage driver installation
    gfd: # NVIDIA GPU Feature Discovery to automate map label nvidia.com/gpu.present=true on GPU nodes
      enabled: true
      nodeSelector: { gpu: "true" }
      tolerations:
        - key: nvidia.com/gpu
          operator: Exists
          effect: NoSchedule
    dcgmExporter:
      enabled: true
      serviceMonitor:
        enabled: true
    # Toolkit configuration
    toolkit:
      enabled: true
      env:
      - name: CONTAINERD_CONFIG
        value: /var/lib/rancher/rke2/agent/etc/containerd/config.toml
      - name: CONTAINERD_SOCKET
        value: /run/k3s/containerd/containerd.sock
      - name: CONTAINERD_RUNTIME_CLASS
        value: nvidia
      - name: CONTAINERD_SET_AS_DEFAULT
        value: "false"  # Dont set nviidia as default runtime

In hamy chart:

    scheduler:
      kubeScheduler:
        imageTag: v1.30.9+rke2r1
    devicePlugin:
      enabled: true
      nvidianodeSelector:
        gpu: "true"
      tolerations:
        - key: nvidia.com/gpu
          operator: Exists
          effect: NoSchedule