将docker run -p 8501:8501 -v /mnt/hgfs/data_input_test/tensorflow-yolov4-tflite-master/models/:/models/yolov4 -it tensorflow/serving:latest -e MODEL_NAME=yolov4 --model_base_path=/models/yolov4这行命令装换成k8s yaml文件

要将上述Docker命令转换为Kubernetes YAML文件，您可以按照以下步骤进行操作：

1. 创建一个Deployment YAML文件来定义Pod的部署。创建一个`deployment.yaml`文件，并添加以下内容：

apiVersion: apps/v1
kind: Deployment
metadata:
  name: yolov4-deployment
spec:
  replicas: 1
  selector:
    matchLabels:
      app: yolov4-app
  template:
    metadata:
      labels:
        app: yolov4-app
    spec:
      containers:
        - name: tensorflow-serving
          image: tensorflow/serving:latest
          ports:
            - containerPort: 8501
          volumeMounts:
            - name: models-volume
              mountPath: /models/yolov4
          env:
            - name: MODEL_NAME
              value: yolov4
          args: ["--model_base_path=/models/yolov4"]
    volumes:
      - name: models-volume
        hostPath:
          path: /mnt/hgfs/data_input_test/tensorflow-yolov4-tflite-master/models/

2. 创建一个Service YAML文件来公开Pod。创建一个`service.yaml`文件，并添加以下内容：

apiVersion: v1
kind: Service
metadata:
  name: yolov4-service
spec:
  selector:
    app: yolov4-app
  ports:
    - protocol: TCP
      port: 8501
      targetPort: 8501
  type: NodePort

现在，您可以使用kubectl命令将这两个YAML文件应用于Kubernetes集群：

kubectl apply -f deployment.yaml
kubectl apply -f service.yaml

这将在Kubernetes集群中创建一个名为`yolov4-deployment`的部署和一个名为`yolov4-service`的服务。