feat: add kep md

[LY-today]

What would you like to be added?

What is your proposal:
The NodeResourcesFit plug-in of native k8s can only adopt a type of strategy for all resources, such as MostRequestedPriority and LeastRequestedPriority. However, in industrial practice, this design does not apply to some scenarios. For example: In AI scenarios, businesses that apply for GPUs prefer to occupy the entire GPU machine first to prevent GPU fragmentation; businesses that apply for CPU & MEM are prioritized and dispersed to non-GPU machines to prevent excessive consumption of CPU & MEM on GPU machines, resulting in real tasks of applying for GPUs. Pending due to insufficient non-GPU resources
. It is therefore hoped that both strategies can be extended to address this business need.

Why is this needed:
There are related descriptions above

Is there a suggested solution, if so, please add it:

plugin-one

config：

resources: 
  nvidia.com/gpu:
    type: MostAllocated
    weight: 2
  cpu:
    type: LeastAllocated
    weight: 1
  memory:
    type: LeastAllocated
    weight: 1

config description：

node score:

finalScoreNode = [(weight1 * resource1) + (weight2 * resource2) + … + (weightN* resourceN)] /(weight1+weight2+ … +weightN)

plugin-two

config：

resources: 
- nvidia.com/gpu 

config description：

node score:

finalScoreNode = (allocatablesResourcesNum - requestsResourcesNum) * framework.MaxNodeScore / allocatablesResourcesNum

Why is this needed?

It’s introduced above