From PVC (API)

If you have already pre-loaded a model onto a Persistant Volume Claim (PVC), you can add the model to HPE Machine Learning Inferencing Software by following the steps below.

Before You Start

PVC Syntax & URL Options

Review the following PVC syntax and URL options to ensure you have the correct information for adding your model.

Option Description Example Default
PVC Name Name of the Persistent Volume Claim (PVC) to be mounted pvc://my-model-pvc Required, no default
Path Optional path within the PVC to be mounted pvc://my-model-pvc/models If not specified, the entire PVC is mounted
ContainerPath Directory in container where the PVC is mounted pvc://my-model-pvc?containerPath=/mnt/models /mnt/models
readOnly Whether the volume is read-only pvc://my-model-pvc?readOnly If not specified, the volume is read-write
PVC Name
The PVC Name (e.g., <my-model-pvc>) must already exist in the Kubernetes namespace where the packaged model will be deployed.

How to Add a Packaged Model From a Registry

  1. Sign in to HPE Machine Learning Inferencing Software. 
    curl -X 'POST' \
  '<YOUR_EXT_CLUSTER_IP>/api/v1/login' \
  -H 'accept: application/json' \
  -H 'Content-Type: application/json' \
  -d '{
  "username": "<YOUR_USERNAME>",
  "password": "<YOUR_PASSWORD>"
}'
  2. Obtain the Bearer token from the response.
  3. Use the following cURL command to add a new packaged model. For information on setting environment variables and arguments, see the Advanced Configuration reference article. 
    curl -X 'POST' \
  '<YOUR_EXT_CLUSTER_IP>/api/v1/models' \
  -H 'accept: application/json' \
  -H 'Authorization: Bearer <YOUR_ACCESS_TOKEN>' \
  -H 'Content-Type: application/json' \
  -d '{
  "arguments": ["--model_dir <PATH_WHERE_MODEL_IS_STORED>"],
  "description": "<DESCRIPTION>",
  "environment": {
      "key": "value",
      "key2": "value2"
  },
  "image": "<USER_NAME>/<MODEL_NAME>:<TAG>",
  "modelFormat": "<MODEL_FORMAT>",
  "name": "<MODEL_NAME>",
  "resources": {
      "gpuType": "<GPU_TYPE>",
      "limits": {
          "cpu": "<CPU_LIMIT>",
          "gpu": "<GPU_LIMIT>",
          "memory": "<MEMORY_LIMIT>"
      },
      "requests": {
          "cpu": "<CPU_REQUEST>",
          "gpu": "<GPU_REQUEST>",
          "memory": "<MEMORY_REQUEST>"
      }
  },
  "url": "pvc://<PVC_NAME>/<OPTIONAL_PATH>?containerPath=<DIR_IN_CONTAINER>"
}'