@@ -93,7 +93,7 @@ export class TrainedModelDeploymentStats {
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/** The epoch timestamp when the deployment started. */
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start_time : EpochTime < UnitMillis >
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/** The overall state of the deployment. */
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- state : DeploymentState
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+ state : DeploymentAssignmentState
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/** The number of threads used be each allocation during inference. */
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threads_per_allocation : integer
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/** The sum of `timeout_count` for all nodes in the deployment. */
@@ -270,40 +270,37 @@ export enum TrainedModelType {
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pytorch
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}
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- export enum DeploymentState {
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+ export enum DeploymentAllocationState {
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/**
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- * The deployment is usable; at least one node has the model allocated .
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+ * The trained model is started on at least one node.
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*/
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started ,
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/**
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- * The deployment has recently started but is not yet usable; the model is not allocated on any nodes.
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+ * Trained model deployment is starting but it is not yet deployed on any nodes.
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*/
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starting ,
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/**
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- * The deployment is preparing to stop and deallocate the model from the relevant nodes.
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+ * Trained model deployment has started on all valid nodes.
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*/
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- stopping
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+ fully_allocated
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}
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- export enum DeploymentAllocationState {
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+ export enum DeploymentAssignmentState {
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/**
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- * The trained model is started on at least one node.
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+ * The deployment is usable; at least one node has the model allocated .
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*/
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started ,
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/**
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- * Trained model deployment is starting but it is not yet deployed on any nodes.
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+ * The deployment has recently started but is not yet usable; the model is not allocated on any nodes.
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*/
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starting ,
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/**
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- * Trained model deployment has started on all valid nodes.
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+ * The deployment is preparing to stop and deallocate the model from the relevant nodes.
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*/
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- fully_allocated
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- }
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-
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- export enum DeploymentAssignmentState {
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- starting ,
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- started ,
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stopping ,
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+ /**
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+ * The deployment is on a failed state and must be re-deployed.
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+ */
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failed
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}
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