Python client.V1PersistentVolumeClaimVolumeSource方法代码示例

# 需要导入模块: from kubernetes import client [as 别名]
# 或者: from kubernetes.client import V1PersistentVolumeClaimVolumeSource [as 别名]
def mount_pvc(pvc_name='pipeline-claim', volume_name='pipeline', volume_mount_path='/mnt/pipeline'):
    """
        Modifier function to apply to a Container Op to simplify volume, volume mount addition and
        enable better reuse of volumes, volume claims across container ops.
        Usage:
            train = train_op(...)
            train.apply(mount_pvc('claim-name', 'pipeline', '/mnt/pipeline'))
    """
    def _mount_pvc(task):
        from kubernetes import client as k8s_client
        # there can be other ops in a pipeline (e.g. ResourceOp, VolumeOp)
        # refer to #3906
        if not hasattr(task, "add_volume") or not hasattr(task, "add_volume_mount"):
            return task
        local_pvc = k8s_client.V1PersistentVolumeClaimVolumeSource(claim_name=pvc_name)
        return (
            task
                .add_volume(
                    k8s_client.V1Volume(name=volume_name, persistent_volume_claim=local_pvc)
                )
                .add_volume_mount(
                    k8s_client.V1VolumeMount(mount_path=volume_mount_path, name=volume_name)
                )
        )
    return _mount_pvc 

# 需要导入模块: from kubernetes import client [as 别名]
# 或者: from kubernetes.client import V1PersistentVolumeClaimVolumeSource [as 别名]
def create_job_object(runner_image, region, s3_path, pvc_name):
  target_folder = get_target_folder(s3_path)

  # Configureate Pod template container
  container = k8s_client.V1Container(
      name="copy-dataset-worker",
      image=runner_image,
      command=["aws"],
      args=["s3", "sync", s3_path, "/mnt/" + target_folder],
      volume_mounts=[k8s_client.V1VolumeMount(name="data-storage", mount_path='/mnt')],
      env=[k8s_client.V1EnvVar(name="AWS_REGION", value=region),
        k8s_client.V1EnvVar(name="AWS_ACCESS_KEY_ID", value_from=k8s_client.V1EnvVarSource(secret_key_ref=k8s_client.V1SecretKeySelector(key="AWS_ACCESS_KEY_ID", name="aws-secret"))),
        k8s_client.V1EnvVar(name="AWS_SECRET_ACCESS_KEY", value_from=k8s_client.V1EnvVarSource(secret_key_ref=k8s_client.V1SecretKeySelector(key="AWS_SECRET_ACCESS_KEY", name="aws-secret")))
        ],
    )
  volume = k8s_client.V1Volume(
    name='data-storage',
    persistent_volume_claim=k8s_client.V1PersistentVolumeClaimVolumeSource(claim_name=pvc_name)
  )
  # Create and configurate a spec section
  template = k8s_client.V1PodTemplateSpec(
      # metadata=k8s_client.V1ObjectMeta(labels={"app":"copy-dataset-worker"}),
      spec=k8s_client.V1PodSpec(containers=[container], volumes=[volume], restart_policy="OnFailure"))
  # Create the specification of deployment
  spec = k8s_client.V1JobSpec(
      # selector=k8s_client.V1LabelSelector(match_labels={"app":"copy-dataset-worker"}),
      template=template)
  # Instantiate the deployment object
  deployment = k8s_client.V1Job(
      api_version="batch/v1",
      kind="Job",
      metadata=k8s_client.V1ObjectMeta(name=container.name),
      spec=spec)

  return deployment 

# 需要导入模块: from kubernetes import client [as 别名]
# 或者: from kubernetes.client import V1PersistentVolumeClaimVolumeSource [as 别名]
def onnx_pipeline(
  model,
  output_onnx_path, 
  model_type,
  output_perf_result_path,
  execution_providers="",
  model_inputs_names="", 
  model_outputs_names="",
  model_input_shapes="",
  model_initial_types="",
  caffe_model_prototxt="",
  target_opset=7):

  # Create a component named "Convert To ONNX" and "ONNX Runtime Perf". Edit the V1PersistentVolumeClaimVolumeSource 
  # name to match the persistent volume claim you created if needed. By default the names match ../azure-files-sc.yaml 
  # and ../azure-files-pvc.yaml
  convert_op = onnxConverterOp('Convert To ONNX', 
    '%s' % model, 
    '%s' % output_onnx_path, 
    '%s' % model_type,
    '%s' % model_inputs_names, 
    '%s' % model_outputs_names,
    '%s' % model_input_shapes,
    '%s' % model_initial_types,
    '%s' % caffe_model_prototxt,
    '%s' % target_opset).add_volume(
        k8s_client.V1Volume(name='pipeline-nfs', persistent_volume_claim=k8s_client.V1PersistentVolumeClaimVolumeSource(
            claim_name='azurefile'))).add_volume_mount(k8s_client.V1VolumeMount(mount_path='/mnt', name='pipeline-nfs'))   

  perf_op = perfTestOp('ONNX Runtime Perf', 
    convert_op.output,
    '%s' % output_perf_result_path,
    '%s' % execution_providers,
    ).add_volume(
        k8s_client.V1Volume(name='pipeline-nfs', persistent_volume_claim=k8s_client.V1PersistentVolumeClaimVolumeSource(
            claim_name='azurefile'))).add_volume_mount(
    k8s_client.V1VolumeMount(mount_path='/mnt', name='pipeline-nfs')).set_gpu_limit(1)

  dsl.get_pipeline_conf().set_image_pull_secrets([k8s_client.V1ObjectReference(name="regcred")]) 

# 需要导入模块: from kubernetes import client [as 别名]
# 或者: from kubernetes.client import V1PersistentVolumeClaimVolumeSource [as 别名]
def get_info(self):
        from kubernetes import client as k8sclient

        return k8sclient.V1PersistentVolumeClaimVolumeSource(
                claim_name=self.params.pvc_name
        )