/**
 * WebGPU Tensor Implementation
 * GPU-backed tensor class for efficient numerical computations
 */
export type TensorDType = 'f32' | 'f16' | 'i32' | 'u32';
export interface TensorOptions {
    dtype?: TensorDType;
    label?: string;
    pooled?: boolean;
}
/**
 * Compute the total number of elements from shape
 */
export declare function shapeToSize(shape: number[]): number;
/**
 * Compute strides for a contiguous tensor
 */
export declare function shapeToStrides(shape: number[]): number[];
/**
 * GPU Tensor class
 */
export declare class Tensor {
    readonly shape: number[];
    readonly strides: number[];
    readonly size: number;
    readonly dtype: TensorDType;
    readonly label: string;
    private buffer;
    private readonly pooled;
    private destroyed;
    /**
     * Create a tensor with the given shape and buffer
     */
    constructor(shape: number[], buffer: GPUBuffer, options?: TensorOptions);
    /**
     * Get the number of dimensions
     */
    get ndim(): number;
    /**
     * Get the total byte size
     */
    get byteSize(): number;
    /**
     * Get the underlying GPU buffer
     */
    getBuffer(): GPUBuffer;
    /**
     * Read tensor data to CPU
     */
    toArray(): Promise<Float32Array>;
    /**
     * Read tensor data as a nested array (for easier debugging)
     */
    toNestedArray(): Promise<number[] | number[][]>;
    /**
     * Write data to tensor from CPU
     */
    fromArray(data: Float32Array | number[]): Promise<void>;
    /**
     * Create a view with a different shape (same underlying buffer)
     */
    reshape(newShape: number[]): Tensor;
    /**
     * Release GPU memory
     */
    destroy(): void;
    /**
     * Check if tensor is destroyed
     */
    isDestroyed(): boolean;
    /**
     * Create an empty tensor with given shape
     */
    static empty(shape: number[], options?: TensorOptions): Tensor;
    /**
     * Create a tensor from data
     */
    static fromData(data: Float32Array | number[], shape: number[], options?: TensorOptions): Tensor;
    /**
     * Create a tensor filled with zeros
     */
    static zeros(shape: number[], options?: TensorOptions): Tensor;
    /**
     * Create a tensor filled with ones
     */
    static ones(shape: number[], options?: TensorOptions): Tensor;
    /**
     * Create a tensor with random values in [0, 1)
     */
    static random(shape: number[], options?: TensorOptions): Tensor;
    /**
     * Create a tensor with values from a range
     */
    static arange(start: number, end: number, step?: number, options?: TensorOptions): Tensor;
    /**
     * Create an identity matrix
     */
    static eye(n: number, options?: TensorOptions): Tensor;
}
/**
 * Utility to run multiple operations and clean up intermediate tensors
 */
export declare function withTensors<T>(tensors: Tensor[], fn: () => T): T;
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