/**
 * Tensor wrapper for WebGPU buffers
 */
import type { DType } from './types.ts';
/**
 * Compute strides from shape (row-major order)
 */
export declare function computeStrides(shape: number[]): number[];
/**
 * Compute total number of elements from shape
 */
export declare function computeSize(shape: number[]): number;
/**
 * Tensor class wrapping a GPUBuffer with shape and dtype information
 */
export declare class Tensor {
    readonly buffer: GPUBuffer;
    readonly shape: readonly number[];
    readonly dtype: DType;
    readonly strides: readonly number[];
    readonly size: number;
    readonly byteSize: number;
    constructor(buffer: GPUBuffer, shape: number[], dtype: DType, strides?: number[]);
    /**
     * Create a Tensor from an existing GPUBuffer (zero-copy).
     *
     * This is useful for TVM integration where the buffer is already allocated
     * by TVM's WebGPU runtime and we want to wrap it without copying data.
     *
     * @param buffer - The existing GPUBuffer to wrap
     * @param shape - The shape of the tensor
     * @param dtype - The data type of the tensor
     * @param strides - Optional custom strides (default: row-major)
     * @returns A new Tensor wrapping the provided buffer
     */
    static fromBuffer(buffer: GPUBuffer, shape: number[], dtype: DType, strides?: number[]): Tensor;
    /**
     * Get the number of dimensions
     */
    get ndim(): number;
    /**
     * Check if tensor is contiguous (row-major)
     */
    get isContiguous(): boolean;
    /**
     * Get a view of the tensor with new shape (must have same size)
     */
    reshape(newShape: number[]): Tensor;
    /**
     * Destroy the underlying GPU buffer
     */
    dispose(): void;
    /**
     * Get string representation
     */
    toString(): string;
}