pub struct ModelSequenceBatching {
pub max_sequence_idle_microseconds: u64,
pub control_input: Vec<ControlInput>,
pub state: Vec<State>,
pub iterative_sequence: bool,
pub strategy_choice: Option<StrategyChoice>,
}Expand description
@@ @@.. cpp:var:: message ModelSequenceBatching @@ @@ Sequence batching configuration. These settings control how sequence @@ batching operates for the model. @@
Fields§
§max_sequence_idle_microseconds: u64@@ .. cpp:var:: uint64 max_sequence_idle_microseconds @@ @@ The maximum time, in microseconds, that a sequence is allowed to @@ be idle before it is aborted. The inference server considers a @@ sequence idle when it does not have any inference request queued @@ for the sequence. If this limit is exceeded, the inference server @@ will free the sequence slot allocated by the sequence and make it @@ available for another sequence. If not specified (or specified as @@ zero) a default value of 1000000 (1 second) is used. @@
control_input: Vec<ControlInput>@@ .. cpp:var:: ControlInput control_input (repeated) @@ @@ The model input(s) that the server should use to communicate @@ sequence start, stop, ready and similar control values to the @@ model. @@
state: Vec<State>@@ .. cpp:var:: State state (repeated) @@ @@ The optional state that can be stored in Triton for performing @@ inference requests on a sequence. Each sequence holds an implicit @@ state local to itself. The output state tensor provided by the @@ model in ‘output_name’ field of the current inference request will @@ be transferred as an input tensor named ‘input_name’ in the next @@ request of the same sequence. The input state of the first request @@ in the sequence contains garbage data. @@
iterative_sequence: bool@@ .. cpp:var:: bool iterative_sequence @@ @@ Requests for iterative sequences are processed over a number @@ of iterations. An iterative sequence is initiated by a single @@ request and is “rescheduled” by the model until completion. @@ Requests for inflight requests will be batched together @@ and can complete independently. Note this feature @@ requires backend support. Default value is false.
strategy_choice: Option<StrategyChoice>@@ .. cpp:var:: oneof strategy_choice @@ @@ The strategy used by the sequence batcher. Default strategy @@ is ‘direct’. @@
Trait Implementations§
Source§impl Clone for ModelSequenceBatching
impl Clone for ModelSequenceBatching
Source§fn clone(&self) -> ModelSequenceBatching
fn clone(&self) -> ModelSequenceBatching
1.0.0 · Source§fn clone_from(&mut self, source: &Self)
fn clone_from(&mut self, source: &Self)
source. Read moreSource§impl Debug for ModelSequenceBatching
impl Debug for ModelSequenceBatching
Source§impl Default for ModelSequenceBatching
impl Default for ModelSequenceBatching
Source§impl Message for ModelSequenceBatching
impl Message for ModelSequenceBatching
Source§fn encoded_len(&self) -> usize
fn encoded_len(&self) -> usize
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self.Source§impl PartialEq for ModelSequenceBatching
impl PartialEq for ModelSequenceBatching
impl StructuralPartialEq for ModelSequenceBatching
Auto Trait Implementations§
impl Freeze for ModelSequenceBatching
impl RefUnwindSafe for ModelSequenceBatching
impl Send for ModelSequenceBatching
impl Sync for ModelSequenceBatching
impl Unpin for ModelSequenceBatching
impl UnwindSafe for ModelSequenceBatching
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