Struct InferenceSession 

pub struct InferenceSession { /* private fields */ }

Implementations

impl InferenceSession

pub fn new(model_type: String) -> Result<InferenceSession, JsValue>

pub async fn initialize_with_auto_device(&mut self) -> Result<(), JsValue>

Initialize with automatic device selection

pub async fn load_model(&mut self, model_data: &[u8]) -> Result<(), JsValue>

pub fn predict(&mut self, input: &WasmTensor) -> Result<WasmTensor, JsValue>

pub fn enable_debug_logging(&mut self, config: DebugConfig)

Initialize debug logging

pub fn disable_debug_logging(&mut self)

Disable debug logging

pub fn start_timer(&mut self, operation: &str)

Start a performance timer

pub fn end_timer(&mut self, operation: &str) -> Option<f64>

End a performance timer

pub fn get_performance_summary(&self) -> Option<String>

Get debug performance summary

pub fn export_debug_logs(&self) -> Option<String>

Export debug logs

pub fn clear_debug_logs(&mut self)

Clear debug logs

pub fn log_memory_usage(&mut self, context: &str)

Log memory usage with context

pub fn enable_quantization(&mut self, config: QuantizationConfig)

Initialize quantization with configuration

pub fn disable_quantization(&mut self)

Disable quantization

pub async fn load_model_with_quantization( &mut self, model_data: &[u8], ) -> Result<(), JsValue>

Load model with automatic quantization

pub fn get_quantization_recommendations( &self, model_size_bytes: usize, ) -> Option<QuantizationConfig>

Get quantization recommendations for current model

pub fn should_quantize_model(&self, model_size_bytes: usize) -> bool

Check if quantization would be beneficial for a given model size

pub fn enable_batch_processing(&mut self, config: BatchConfig)

Initialize batch processing with configuration

pub fn disable_batch_processing(&mut self)

Disable batch processing

pub fn add_batch_request( &mut self, input: &WasmTensor, priority: Priority, timeout_ms: Option<u32>, ) -> Option<String>

Add a request to the batch queue

pub async fn process_batch(&mut self) -> Result<Vec<BatchResponse>, JsValue>

Process pending batch requests

pub fn is_batch_ready(&self) -> bool

Check if a batch is ready for processing

pub fn get_batch_queue_length(&self) -> usize

Get current batch queue length

pub fn get_batch_stats(&self) -> Option<String>

Get batch processing statistics

pub fn clear_batch_queue(&mut self)

Clear the batch queue

pub fn enable_events(&mut self)

Enable event system

pub fn disable_events(&mut self)

Disable event system

pub fn get_event_history(&self) -> Option<String>

Get event history as JSON

pub fn clear_event_history(&mut self)

Clear event history

pub fn emit_custom_event( &mut self, event_type: u32, source: &str, data: Option<String>, )

Emit a custom event

pub async fn predict_with_batching( &mut self, input: &WasmTensor, priority: Priority, ) -> Result<WasmTensor, JsValue>

Single inference with automatic batching support

pub async fn flush_batches(&mut self) -> Result<Vec<BatchResponse>, JsValue>

Process all pending batches

Trait Implementations

impl From<InferenceSession> for JsValue

fn from(value: InferenceSession) -> Self

Converts to this type from the input type.

impl FromWasmAbi for InferenceSession

type Abi = u32

The Wasm ABI type that this converts from when coming back out from the ABI boundary.

unsafe fn from_abi(js: u32) -> Self

Recover a Self from Self::Abi.

impl IntoWasmAbi for InferenceSession

type Abi = u32

The Wasm ABI type that this converts into when crossing the ABI boundary.

fn into_abi(self) -> u32

Convert self into Self::Abi so that it can be sent across the wasm ABI boundary.

impl LongRefFromWasmAbi for InferenceSession

type Abi = u32

Same as RefFromWasmAbi::Abi

type Anchor = RcRef<InferenceSession>

Same as RefFromWasmAbi::Anchor

unsafe fn long_ref_from_abi(js: Self::Abi) -> Self::Anchor

Same as RefFromWasmAbi::ref_from_abi

impl OptionFromWasmAbi for InferenceSession

fn is_none(abi: &Self::Abi) -> bool

Tests whether the argument is a “none” instance. If so it will be deserialized as None, and otherwise it will be passed to FromWasmAbi.

impl OptionIntoWasmAbi for InferenceSession

fn none() -> Self::Abi

Returns an ABI instance indicating “none”, which JS will interpret as the None branch of this option.

impl RefFromWasmAbi for InferenceSession

type Abi = u32

The Wasm ABI type references to Self are recovered from.

type Anchor = RcRef<InferenceSession>

The type that holds the reference to Self for the duration of the invocation of the function that has an &Self parameter. This is required to ensure that the lifetimes don’t persist beyond one function call, and so that they remain anonymous.

unsafe fn ref_from_abi(js: Self::Abi) -> Self::Anchor

Recover a Self::Anchor from Self::Abi.

impl RefMutFromWasmAbi for InferenceSession

type Abi = u32

Same as RefFromWasmAbi::Abi

type Anchor = RcRefMut<InferenceSession>

Same as RefFromWasmAbi::Anchor

unsafe fn ref_mut_from_abi(js: Self::Abi) -> Self::Anchor

Same as RefFromWasmAbi::ref_from_abi

impl TryFromJsValue for InferenceSession

fn try_from_js_value(value: JsValue) -> Result<Self, JsValue>

Performs the conversion.

fn try_from_js_value_ref(value: &JsValue) -> Option<Self>

Performs the conversion.

impl VectorFromWasmAbi for InferenceSession

type Abi = <Box<[JsValue]> as FromWasmAbi>::Abi

unsafe fn vector_from_abi(js: Self::Abi) -> Box<[InferenceSession]>

impl VectorIntoWasmAbi for InferenceSession

type Abi = <Box<[JsValue]> as IntoWasmAbi>::Abi

fn vector_into_abi(vector: Box<[InferenceSession]>) -> Self::Abi

impl WasmDescribe for InferenceSession

fn describe()

impl WasmDescribeVector for InferenceSession

fn describe_vector()

impl SupportsConstructor for InferenceSession

impl SupportsInstanceProperty for InferenceSession

impl SupportsStaticProperty for InferenceSession