def deployment_yaml_to_pb(deployment_yaml):
deployment_pb = Deployment()
if deployment_yaml.get('name') is not None:
deployment_pb.name = deployment_yaml.get('name')
if deployment_yaml.get('namespace') is not None:
deployment_pb.namespace = deployment_yaml.get('namespace')
if deployment_yaml.get('labels') is not None:
deployment_pb.labels.update(dict(deployment_yaml.get('labels')))
if deployment_yaml.get('annotations') is not None:
deployment_pb.annotations.update(
dict(deployment_yaml.get('annotations')))
spec_yaml = deployment_yaml.get('spec')
platform = spec_yaml.get('operator')
if platform is not None:
deployment_pb.spec.operator = DeploymentSpec.DeploymentOperator.Value(
platform.replace('-', '_').upper())
if spec_yaml.get('bento_name'):
deployment_pb.spec.bento_name = spec_yaml.get('bento_name')
if spec_yaml.get('bento_version'):
deployment_pb.spec.bento_version = spec_yaml.get('bento_version')
if platform == 'aws_sagemaker':
sagemaker_config = spec_yaml.get('sagemaker_operator_config')
sagemaker_operator_config_pb = deployment_pb.spec.sagemaker_operator_config
if sagemaker_config.get('api_name'):
sagemaker_operator_config_pb.api_name = sagemaker_config.get(
'api_name')
if sagemaker_config.get('region'):
sagemaker_operator_config_pb.region = sagemaker_config.get(
'region')
if sagemaker_config.get('instance_count'):
sagemaker_operator_config_pb.instance_count = sagemaker_config.get(
'instance_count')
if sagemaker_config.get('instance_type'):
sagemaker_operator_config_pb.instance_type = sagemaker_config.get(
'instance_type')
elif platform == 'aws_lambda':
lambda_config = spec_yaml.get('aws_lambda_operator_config')
if lambda_config.get('region'):
deployment_pb.spec.aws_lambda_config.region = lambda_config.get(
'region')
elif platform == 'gcp_function':
gcp_config = spec_yaml.get('gcp_function_operator_config')
if gcp_config.get('region'):
deployment_pb.spec.gcp_function_operator_config.region = gcp_config.get(
'region')
elif platform == 'kubernetes':
k8s_config = spec_yaml.get('kubernetes_operator_config')
k8s_operator_config_pb = deployment_pb.spec.kubernetes_operator_config
if k8s_config.get('kube_namespace'):
k8s_operator_config_pb.kube_namespace = k8s_config.get(
'kube_namespace')
if k8s_config.get('replicas'):
k8s_operator_config_pb.replicas = k8s_config.get('replicas')
if k8s_config.get('service_name'):
k8s_operator_config_pb.service_name = k8s_config.get(
'service_name')
if k8s_config.get('service_type'):
k8s_operator_config_pb.service_type = k8s_config.get(
'service_type')
else:
raise BentoMLException(
'Custom deployment is not supported in the current version of BentoML'
)
return deployment_pb
def deployment_dict_to_pb(deployment_dict):
deployment_pb = Deployment()
if deployment_dict.get('name') is not None:
deployment_pb.name = deployment_dict.get('name')
if deployment_dict.get('namespace') is not None:
deployment_pb.namespace = deployment_dict.get('namespace')
if deployment_dict.get('labels') is not None:
deployment_pb.labels.update(deployment_dict.get('labels'))
if deployment_dict.get('annotations') is not None:
deployment_pb.annotations.update(deployment_dict.get('annotations'))
if deployment_dict.get('spec'):
spec_dict = deployment_dict.get('spec')
else:
raise BentoMLDeploymentException(
'"spec" is required field for deployment')
platform = spec_dict.get('operator')
if platform is not None:
# converting platform parameter to DeploymentOperator name in proto
# e.g. 'aws-lambda' to 'AWS_LAMBDA'
deployment_pb.spec.operator = DeploymentSpec.DeploymentOperator.Value(
platform.replace('-', '_').upper())
if spec_dict.get('bento_name'):
deployment_pb.spec.bento_name = spec_dict.get('bento_name')
if spec_dict.get('bento_version'):
deployment_pb.spec.bento_version = spec_dict.get('bento_version')
if deployment_pb.spec.operator == DeploymentSpec.AWS_SAGEMAKER:
sagemaker_config = spec_dict.get('sagemaker_operator_config', {})
sagemaker_operator_config_pb = deployment_pb.spec.sagemaker_operator_config
if sagemaker_config.get('api_name'):
sagemaker_operator_config_pb.api_name = sagemaker_config.get(
'api_name')
if sagemaker_config.get('region'):
sagemaker_operator_config_pb.region = sagemaker_config.get(
'region')
if sagemaker_config.get('instance_count'):
sagemaker_operator_config_pb.instance_count = int(
sagemaker_config.get('instance_count'))
if sagemaker_config.get('instance_type'):
sagemaker_operator_config_pb.instance_type = sagemaker_config.get(
'instance_type')
elif deployment_pb.spec.operator == DeploymentSpec.AWS_LAMBDA:
lambda_config = spec_dict.get('aws_lambda_operator_config', {})
if lambda_config.get('region'):
deployment_pb.spec.aws_lambda_operator_config.region = lambda_config.get(
'region')
if lambda_config.get('api_name'):
deployment_pb.spec.aws_lambda_operator_config.api_name = lambda_config.get(
'api_name')
elif deployment_pb.spec.operator == DeploymentSpec.GCP_FUNCTION:
gcp_config = spec_dict.get('gcp_function_operator_config', {})
if gcp_config.get('region'):
deployment_pb.spec.gcp_function_operator_config.region = gcp_config.get(
'region')
if gcp_config.get('api_name'):
deployment_pb.spec.aws_lambda_operator_config.api_name = gcp_config.get(
'api_name')
elif deployment_pb.spec.operator == DeploymentSpec.KUBERNETES:
k8s_config = spec_dict.get('kubernetes_operator_config', {})
k8s_operator_config_pb = deployment_pb.spec.kubernetes_operator_config
if k8s_config.get('kube_namespace'):
k8s_operator_config_pb.kube_namespace = k8s_config.get(
'kube_namespace')
if k8s_config.get('replicas'):
k8s_operator_config_pb.replicas = k8s_config.get('replicas')
if k8s_config.get('service_name'):
k8s_operator_config_pb.service_name = k8s_config.get(
'service_name')
if k8s_config.get('service_type'):
k8s_operator_config_pb.service_type = k8s_config.get(
'service_type')
else:
raise BentoMLException(
'Platform "{}" is not supported in the current version of '
'BentoML'.format(platform))
return deployment_pb
