Files
wifi-densepose/crates/ruvector-nervous-system-wasm/pkg/ruvector_nervous_system_wasm.d.ts
ruv d803bfe2b1 Squashed 'vendor/ruvector/' content from commit b64c2172
git-subtree-dir: vendor/ruvector
git-subtree-split: b64c21726f2bb37286d9ee36a7869fef60cc6900
2026-02-28 14:39:40 -05:00

549 lines
16 KiB
TypeScript

/* tslint:disable */
/* eslint-disable */
export class BTSPAssociativeMemory {
free(): void;
[Symbol.dispose](): void;
/**
* Get memory dimensions
*/
dimensions(): any;
/**
* Store key-value association in one shot
*/
store_one_shot(key: Float32Array, value: Float32Array): void;
/**
* Create new associative memory
*
* # Arguments
* * `input_size` - Dimension of key vectors
* * `output_size` - Dimension of value vectors
*/
constructor(input_size: number, output_size: number);
/**
* Retrieve value from key
*/
retrieve(query: Float32Array): Float32Array;
}
export class BTSPLayer {
free(): void;
[Symbol.dispose](): void;
/**
* Get weights as Float32Array
*/
get_weights(): Float32Array;
/**
* One-shot association: learn pattern -> target in single step
*
* This is the key BTSP capability: immediate learning without iteration.
* Uses gradient normalization for single-step convergence.
*/
one_shot_associate(pattern: Float32Array, target: number): void;
/**
* Create a new BTSP layer
*
* # Arguments
* * `size` - Number of synapses (input dimension)
* * `tau` - Time constant in milliseconds (2000ms default)
*/
constructor(size: number, tau: number);
/**
* Reset layer to initial state
*/
reset(): void;
/**
* Forward pass: compute layer output
*/
forward(input: Float32Array): number;
/**
* Get number of synapses
*/
readonly size: number;
}
export class BTSPSynapse {
free(): void;
[Symbol.dispose](): void;
/**
* Create a new BTSP synapse
*
* # Arguments
* * `initial_weight` - Starting weight (0.0 to 1.0)
* * `tau_btsp` - Time constant in milliseconds (1000-3000ms recommended)
*/
constructor(initial_weight: number, tau_btsp: number);
/**
* Update synapse based on activity and plateau signal
*
* # Arguments
* * `presynaptic_active` - Is presynaptic neuron firing?
* * `plateau_signal` - Dendritic plateau potential detected?
* * `dt` - Time step in milliseconds
*/
update(presynaptic_active: boolean, plateau_signal: boolean, dt: number): void;
/**
* Compute synaptic output
*/
forward(input: number): number;
/**
* Get eligibility trace
*/
readonly eligibility_trace: number;
/**
* Get current weight
*/
readonly weight: number;
}
export class GlobalWorkspace {
free(): void;
[Symbol.dispose](): void;
/**
* Get current load (0.0 to 1.0)
*/
current_load(): number;
/**
* Get most salient item
*/
most_salient(): WorkspaceItem | undefined;
/**
* Retrieve top-k most salient representations
*/
retrieve_top_k(k: number): any;
/**
* Set salience decay rate
*/
set_decay_rate(decay: number): void;
/**
* Create with custom threshold
*/
static with_threshold(capacity: number, threshold: number): GlobalWorkspace;
/**
* Get available slots
*/
available_slots(): number;
/**
* Get average salience
*/
average_salience(): number;
/**
* Create a new global workspace
*
* # Arguments
* * `capacity` - Maximum number of representations (typically 4-7)
*/
constructor(capacity: number);
/**
* Clear all representations
*/
clear(): void;
/**
* Run competitive dynamics (salience decay and pruning)
*/
compete(): void;
/**
* Check if workspace is at capacity
*/
is_full(): boolean;
/**
* Check if workspace is empty
*/
is_empty(): boolean;
/**
* Retrieve all current representations as JSON
*/
retrieve(): any;
/**
* Broadcast a representation to the workspace
*
* Returns true if accepted, false if rejected.
*/
broadcast(item: WorkspaceItem): boolean;
/**
* Get current number of representations
*/
readonly len: number;
/**
* Get workspace capacity
*/
readonly capacity: number;
}
export class HdcMemory {
free(): void;
[Symbol.dispose](): void;
/**
* Get a vector by label
*/
get(label: string): Hypervector | undefined;
/**
* Check if a label exists
*/
has(label: string): boolean;
/**
* Create a new empty HDC memory
*/
constructor();
/**
* Clear all stored vectors
*/
clear(): void;
/**
* Store a hypervector with a label
*/
store(label: string, vector: Hypervector): void;
/**
* Find the k most similar vectors to query
*/
top_k(query: Hypervector, k: number): any;
/**
* Retrieve vectors similar to query above threshold
*
* Returns array of [label, similarity] pairs
*/
retrieve(query: Hypervector, threshold: number): any;
/**
* Get number of stored vectors
*/
readonly size: number;
}
export class Hypervector {
free(): void;
[Symbol.dispose](): void;
/**
* Create from raw bytes
*/
static from_bytes(bytes: Uint8Array): Hypervector;
/**
* Compute similarity between two hypervectors
*
* Returns a value in [-1.0, 1.0] where:
* - 1.0 = identical vectors
* - 0.0 = random/orthogonal vectors
* - -1.0 = completely opposite vectors
*/
similarity(other: Hypervector): number;
/**
* Compute Hamming distance (number of differing bits)
*/
hamming_distance(other: Hypervector): number;
/**
* Create a zero hypervector
*/
constructor();
/**
* Bind two hypervectors using XOR
*
* Binding is associative, commutative, and self-inverse:
* - a.bind(b) == b.bind(a)
* - a.bind(b).bind(b) == a
*/
bind(other: Hypervector): Hypervector;
/**
* Create a random hypervector with ~50% bits set
*/
static random(): Hypervector;
/**
* Bundle multiple vectors by majority voting on each bit
*/
static bundle_3(a: Hypervector, b: Hypervector, c: Hypervector): Hypervector;
/**
* Count the number of set bits (population count)
*/
popcount(): number;
/**
* Get the raw bits as Uint8Array (for serialization)
*/
to_bytes(): Uint8Array;
/**
* Create a hypervector from a seed for reproducibility
*/
static from_seed(seed: bigint): Hypervector;
/**
* Get number of bits
*/
readonly dimension: number;
}
export class KWTALayer {
free(): void;
[Symbol.dispose](): void;
/**
* Set activation threshold
*/
with_threshold(threshold: number): void;
/**
* Select top-k neurons with their activation values
*
* Returns array of [index, value] pairs.
*/
select_with_values(inputs: Float32Array): any;
/**
* Create sparse activation vector (only top-k preserved)
*/
sparse_activations(inputs: Float32Array): Float32Array;
/**
* Create a new K-WTA layer
*
* # Arguments
* * `size` - Total number of neurons
* * `k` - Number of winners to select
*/
constructor(size: number, k: number);
/**
* Select top-k neurons
*
* Returns indices of k neurons with highest activations, sorted descending.
*/
select(inputs: Float32Array): Uint32Array;
/**
* Get number of winners
*/
readonly k: number;
/**
* Get layer size
*/
readonly size: number;
}
export class WTALayer {
free(): void;
[Symbol.dispose](): void;
/**
* Soft competition with normalized activations
*
* Returns activation levels for all neurons after softmax-like normalization.
*/
compete_soft(inputs: Float32Array): Float32Array;
/**
* Get current membrane potentials
*/
get_membranes(): Float32Array;
/**
* Set refractory period
*/
set_refractory_period(period: number): void;
/**
* Create a new WTA layer
*
* # Arguments
* * `size` - Number of competing neurons
* * `threshold` - Activation threshold for firing
* * `inhibition` - Lateral inhibition strength (0.0-1.0)
*/
constructor(size: number, threshold: number, inhibition: number);
/**
* Reset layer state
*/
reset(): void;
/**
* Run winner-take-all competition
*
* Returns the index of the winning neuron, or -1 if no neuron exceeds threshold.
*/
compete(inputs: Float32Array): number;
/**
* Get layer size
*/
readonly size: number;
}
export class WorkspaceItem {
free(): void;
[Symbol.dispose](): void;
/**
* Check if expired
*/
is_expired(current_time: bigint): boolean;
/**
* Create with custom decay and lifetime
*/
static with_decay(content: Float32Array, salience: number, source_module: number, timestamp: bigint, decay_rate: number, lifetime: bigint): WorkspaceItem;
/**
* Apply temporal decay
*/
apply_decay(dt: number): void;
/**
* Get content as Float32Array
*/
get_content(): Float32Array;
/**
* Update salience
*/
update_salience(new_salience: number): void;
/**
* Create a new workspace item
*/
constructor(content: Float32Array, salience: number, source_module: number, timestamp: bigint);
/**
* Compute content magnitude (L2 norm)
*/
magnitude(): number;
/**
* Get source module
*/
readonly source_module: number;
/**
* Get ID
*/
readonly id: bigint;
/**
* Get salience
*/
readonly salience: number;
/**
* Get timestamp
*/
readonly timestamp: bigint;
}
/**
* Get information about available bio-inspired mechanisms
*/
export function available_mechanisms(): any;
/**
* Get biological references for the mechanisms
*/
export function biological_references(): any;
/**
* Initialize the WASM module with panic hook
*/
export function init(): void;
/**
* Get performance targets for each mechanism
*/
export function performance_targets(): any;
/**
* Get the version of the crate
*/
export function version(): string;
export type InitInput = RequestInfo | URL | Response | BufferSource | WebAssembly.Module;
export interface InitOutput {
readonly memory: WebAssembly.Memory;
readonly __wbg_btspassociativememory_free: (a: number, b: number) => void;
readonly __wbg_btsplayer_free: (a: number, b: number) => void;
readonly __wbg_btspsynapse_free: (a: number, b: number) => void;
readonly __wbg_globalworkspace_free: (a: number, b: number) => void;
readonly __wbg_hdcmemory_free: (a: number, b: number) => void;
readonly __wbg_hypervector_free: (a: number, b: number) => void;
readonly __wbg_kwtalayer_free: (a: number, b: number) => void;
readonly __wbg_workspaceitem_free: (a: number, b: number) => void;
readonly __wbg_wtalayer_free: (a: number, b: number) => void;
readonly available_mechanisms: () => number;
readonly biological_references: () => number;
readonly btspassociativememory_dimensions: (a: number) => number;
readonly btspassociativememory_new: (a: number, b: number) => number;
readonly btspassociativememory_retrieve: (a: number, b: number, c: number, d: number) => void;
readonly btspassociativememory_store_one_shot: (a: number, b: number, c: number, d: number, e: number, f: number) => void;
readonly btsplayer_forward: (a: number, b: number, c: number, d: number) => void;
readonly btsplayer_get_weights: (a: number) => number;
readonly btsplayer_new: (a: number, b: number) => number;
readonly btsplayer_one_shot_associate: (a: number, b: number, c: number, d: number, e: number) => void;
readonly btsplayer_reset: (a: number) => void;
readonly btsplayer_size: (a: number) => number;
readonly btspsynapse_eligibility_trace: (a: number) => number;
readonly btspsynapse_forward: (a: number, b: number) => number;
readonly btspsynapse_new: (a: number, b: number, c: number) => void;
readonly btspsynapse_update: (a: number, b: number, c: number, d: number) => void;
readonly btspsynapse_weight: (a: number) => number;
readonly globalworkspace_available_slots: (a: number) => number;
readonly globalworkspace_average_salience: (a: number) => number;
readonly globalworkspace_broadcast: (a: number, b: number) => number;
readonly globalworkspace_capacity: (a: number) => number;
readonly globalworkspace_clear: (a: number) => void;
readonly globalworkspace_compete: (a: number) => void;
readonly globalworkspace_current_load: (a: number) => number;
readonly globalworkspace_is_empty: (a: number) => number;
readonly globalworkspace_is_full: (a: number) => number;
readonly globalworkspace_len: (a: number) => number;
readonly globalworkspace_most_salient: (a: number) => number;
readonly globalworkspace_new: (a: number) => number;
readonly globalworkspace_retrieve: (a: number) => number;
readonly globalworkspace_retrieve_top_k: (a: number, b: number) => number;
readonly globalworkspace_set_decay_rate: (a: number, b: number) => void;
readonly globalworkspace_with_threshold: (a: number, b: number) => number;
readonly hdcmemory_clear: (a: number) => void;
readonly hdcmemory_get: (a: number, b: number, c: number) => number;
readonly hdcmemory_has: (a: number, b: number, c: number) => number;
readonly hdcmemory_new: () => number;
readonly hdcmemory_retrieve: (a: number, b: number, c: number) => number;
readonly hdcmemory_size: (a: number) => number;
readonly hdcmemory_store: (a: number, b: number, c: number, d: number) => void;
readonly hdcmemory_top_k: (a: number, b: number, c: number) => number;
readonly hypervector_bind: (a: number, b: number) => number;
readonly hypervector_bundle_3: (a: number, b: number, c: number) => number;
readonly hypervector_dimension: (a: number) => number;
readonly hypervector_from_bytes: (a: number, b: number, c: number) => void;
readonly hypervector_from_seed: (a: bigint) => number;
readonly hypervector_hamming_distance: (a: number, b: number) => number;
readonly hypervector_new: () => number;
readonly hypervector_popcount: (a: number) => number;
readonly hypervector_random: () => number;
readonly hypervector_similarity: (a: number, b: number) => number;
readonly hypervector_to_bytes: (a: number) => number;
readonly kwtalayer_k: (a: number) => number;
readonly kwtalayer_new: (a: number, b: number, c: number) => void;
readonly kwtalayer_select: (a: number, b: number, c: number, d: number) => void;
readonly kwtalayer_select_with_values: (a: number, b: number, c: number, d: number) => void;
readonly kwtalayer_size: (a: number) => number;
readonly kwtalayer_sparse_activations: (a: number, b: number, c: number, d: number) => void;
readonly kwtalayer_with_threshold: (a: number, b: number) => void;
readonly performance_targets: () => number;
readonly version: (a: number) => void;
readonly workspaceitem_apply_decay: (a: number, b: number) => void;
readonly workspaceitem_get_content: (a: number) => number;
readonly workspaceitem_id: (a: number) => bigint;
readonly workspaceitem_is_expired: (a: number, b: bigint) => number;
readonly workspaceitem_magnitude: (a: number) => number;
readonly workspaceitem_new: (a: number, b: number, c: number, d: number, e: bigint) => number;
readonly workspaceitem_salience: (a: number) => number;
readonly workspaceitem_source_module: (a: number) => number;
readonly workspaceitem_timestamp: (a: number) => bigint;
readonly workspaceitem_update_salience: (a: number, b: number) => void;
readonly workspaceitem_with_decay: (a: number, b: number, c: number, d: number, e: bigint, f: number, g: bigint) => number;
readonly wtalayer_compete: (a: number, b: number, c: number, d: number) => void;
readonly wtalayer_compete_soft: (a: number, b: number, c: number, d: number) => void;
readonly wtalayer_get_membranes: (a: number) => number;
readonly wtalayer_new: (a: number, b: number, c: number, d: number) => void;
readonly wtalayer_reset: (a: number) => void;
readonly wtalayer_set_refractory_period: (a: number, b: number) => void;
readonly init: () => void;
readonly wtalayer_size: (a: number) => number;
readonly __wbindgen_export: (a: number, b: number) => number;
readonly __wbindgen_export2: (a: number, b: number, c: number, d: number) => number;
readonly __wbindgen_export3: (a: number) => void;
readonly __wbindgen_export4: (a: number, b: number, c: number) => void;
readonly __wbindgen_add_to_stack_pointer: (a: number) => number;
readonly __wbindgen_start: () => void;
}
export type SyncInitInput = BufferSource | WebAssembly.Module;
/**
* Instantiates the given `module`, which can either be bytes or
* a precompiled `WebAssembly.Module`.
*
* @param {{ module: SyncInitInput }} module - Passing `SyncInitInput` directly is deprecated.
*
* @returns {InitOutput}
*/
export function initSync(module: { module: SyncInitInput } | SyncInitInput): InitOutput;
/**
* If `module_or_path` is {RequestInfo} or {URL}, makes a request and
* for everything else, calls `WebAssembly.instantiate` directly.
*
* @param {{ module_or_path: InitInput | Promise<InitInput> }} module_or_path - Passing `InitInput` directly is deprecated.
*
* @returns {Promise<InitOutput>}
*/
export default function __wbg_init (module_or_path?: { module_or_path: InitInput | Promise<InitInput> } | InitInput | Promise<InitInput>): Promise<InitOutput>;