seldon-od-model¶

Chart to deploy an outlier detector as a single Seldon model.

Usage¶

使用本chart，首先要添加 seldonio Helm 仓库：

helm repo add seldonio https://storage.googleapis.com/seldon-charts
helm repo update

一旦完成，你可以按照如下使用预估图模板：

helm template $MY_MODEL_NAME seldonio/seldon-od-model --namespace $MODELS_NAMESPACE

注意你也可以直接部署预估图到集群中：使用：

helm install $MY_MODEL_NAME seldonio/seldon-od-model --namespace $MODELS_NAMESPACE

主页: https://github.com/SeldonIO/seldon-core

源码¶

设置值¶

键	类型	默认值	描述
engine.env.SELDON_LOG_MESSAGES_EXTERNALLY	bool	`false`
engine.env.SELDON_LOG_MESSAGE_TYPE	string	`"seldon.message.pair"`
engine.env.SELDON_LOG_REQUESTS	bool	`false`
engine.env.SELDON_LOG_RESPONSES	bool	`false`
engine.resources.requests.cpu	string	`"0.1"`
model.isolationforest.image.name	string	`"seldonio/outlier-if-model:0.1"`
model.isolationforest.load_path	string	`"./models/"`
model.isolationforest.model_name	string	`"if"`
model.isolationforest.threshold	int	`0`
model.mahalanobis.image.name	string	`"seldonio/outlier-mahalanobis-model:0.1"`
model.mahalanobis.max_n	int	`-1`
model.mahalanobis.n_components	int	`3`
model.mahalanobis.n_stdev	int	`3`
model.mahalanobis.start_clip	int	`50`
model.mahalanobis.threshold	int	`25`
model.name	string	`"outlier-detector"`
model.parameterTypes.load_path	string	`"STRING"`
model.parameterTypes.max_n	string	`"INT"`
model.parameterTypes.model_name	string	`"STRING"`
model.parameterTypes.n_components	string	`"INT"`
model.parameterTypes.n_stdev	string	`"FLOAT"`
model.parameterTypes.reservoir_size	string	`"INT"`
model.parameterTypes.start_clip	string	`"INT"`
model.parameterTypes.threshold	string	`"FLOAT"`
model.seq2seq.image.name	string	`"seldonio/outlier-s2s-lstm-model:0.1"`
model.seq2seq.load_path	string	`"./models/"`
model.seq2seq.model_name	string	`"seq2seq"`
model.seq2seq.reservoir_size	int	`50000`
model.seq2seq.threshold	float	`0.003`
model.type	string	`"vae"`	Type of outlier detector. Valid values are: `vae`, `mahalanobis`, `seq2seq` and `isolationforest`.
model.vae.image.name	string	`"seldonio/outlier-vae-model:0.1"`
model.vae.load_path	string	`"./models/"`
model.vae.model_name	string	`"vae"`
model.vae.reservoir_size	int	`50000`
model.vae.threshold	int	`10`
name	string	`"seldon-od-model"`
predictorLabels.fluentd	string	`"true"`
predictorLabels.version	string	`"v1"`
replicas	int	`1`
sdepLabels.app	string	`"seldon"`