import { TensorFactory } from './tensor-factory.js';
import { TypedTensorUtils } from './tensor-utils.js';
import { TryGetGlobalType } from './type-helper.js';
/**
 * represent a basic tensor with specified dimensions and data type.
 */
interface TypedTensorBase<T extends Tensor.Type> {
    /**
     * Get the dimensions of the tensor.
     */
    readonly dims: readonly number[];
    /**
     * Get the data type of the tensor.
     */
    readonly type: T;
    /**
     * Get the buffer data of the tensor.
     *
     * If the data is not on CPU (eg. it's in the form of WebGL texture or WebGPU buffer), throw error.
     */
    readonly data: Tensor.DataTypeMap[T];
    /**
     * Get the location of the data.
     */
    readonly location: Tensor.DataLocation;
    /**
     * Get the WebGL texture that holds the tensor data.
     *
     * If the data is not on GPU as WebGL texture, throw error.
     */
    readonly texture: Tensor.TextureType;
    /**
     * Get the WebGPU buffer that holds the tensor data.
     *
     * If the data is not on GPU as WebGPU buffer, throw error.
     */
    readonly gpuBuffer: Tensor.GpuBufferType;
    /**
     * Get the WebNN MLTensor that holds the tensor data.
     *
     * If the data is not in a WebNN MLTensor, throw error.
     */
    readonly mlTensor: Tensor.MLTensorType;
    /**
     * Get the buffer data of the tensor.
     *
     * If the data is on CPU, returns the data immediately.
     * If the data is on GPU, downloads the data and returns the promise.
     *
     * @param releaseData - whether release the data on GPU. Ignore if data is already on CPU.
     */
    getData(releaseData?: boolean): Promise<Tensor.DataTypeMap[T]>;
    /**
     * Dispose the tensor data.
     *
     * If the data is on CPU, remove its internal reference to the underlying data.
     * If the data is on GPU, release the data on GPU.
     *
     * After calling this function, the tensor is considered no longer valid. Its location will be set to 'none'.
     */
    dispose(): void;
}
export declare namespace Tensor {
    interface DataTypeMap {
        float32: Float32Array;
        uint8: Uint8Array;
        int8: Int8Array;
        uint16: Uint16Array;
        int16: Int16Array;
        int32: Int32Array;
        int64: BigInt64Array;
        string: string[];
        bool: Uint8Array;
        float16: Uint16Array;
        float64: Float64Array;
        uint32: Uint32Array;
        uint64: BigUint64Array;
        uint4: Uint8Array;
        int4: Int8Array;
    }
    interface ElementTypeMap {
        float32: number;
        uint8: number;
        int8: number;
        uint16: number;
        int16: number;
        int32: number;
        int64: bigint;
        string: string;
        bool: boolean;
        float16: number;
        float64: number;
        uint32: number;
        uint64: bigint;
        uint4: number;
        int4: number;
    }
    type DataType = DataTypeMap[Type];
    type ElementType = ElementTypeMap[Type];
    /**
     * supported data types for constructing a tensor from a pinned CPU buffer
     */
    type CpuPinnedDataTypes = Exclude<Tensor.Type, 'string'>;
    /**
     * type alias for WebGL texture
     */
    type TextureType = WebGLTexture;
    /**
     * supported data types for constructing a tensor from a WebGL texture
     */
    type TextureDataTypes = 'float32';
    type GpuBufferTypeFallback = {
        size: number;
        mapState: 'unmapped' | 'pending' | 'mapped';
    };
    /**
     * type alias for WebGPU buffer
     */
    type GpuBufferType = TryGetGlobalType<'GPUBuffer', GpuBufferTypeFallback>;
    type MLTensorTypeFallback = {
        destroy(): void;
    };
    /**
     * type alias for WebNN MLTensor
     *
     * The specification for WebNN's MLTensor is currently in flux.
     */
    type MLTensorType = TryGetGlobalType<'MLTensor', MLTensorTypeFallback>;
    /**
     * supported data types for constructing a tensor from a WebGPU buffer
     */
    type GpuBufferDataTypes = 'float32' | 'float16' | 'int32' | 'int64' | 'uint32' | 'uint8' | 'bool';
    /**
     * supported data types for constructing a tensor from a WebNN MLTensor
     */
    type MLTensorDataTypes = 'float32' | 'float16' | 'int8' | 'uint8' | 'int32' | 'uint32' | 'int64' | 'uint64' | 'bool' | 'uint4' | 'int4';
    /**
     * represent where the tensor data is stored
     */
    type DataLocation = 'none' | 'cpu' | 'cpu-pinned' | 'texture' | 'gpu-buffer' | 'ml-tensor';
    /**
     * represent the data type of a tensor
     */
    type Type = keyof DataTypeMap;
}
/**
 * Represent multi-dimensional arrays to feed to or fetch from model inferencing.
 */
export interface TypedTensor<T extends Tensor.Type> extends TypedTensorBase<T>, TypedTensorUtils<T> {
}
/**
 * Represent multi-dimensional arrays to feed to or fetch from model inferencing.
 */
export interface Tensor extends TypedTensorBase<Tensor.Type>, TypedTensorUtils<Tensor.Type> {
}
/**
 * type TensorConstructor defines the constructors of 'Tensor' to create CPU tensor instances.
 */
export interface TensorConstructor extends TensorFactory {
    /**
     * Construct a new string tensor object from the given type, data and dims.
     *
     * @param type - Specify the element type.
     * @param data - Specify the CPU tensor data.
     * @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
     */
    new (type: 'string', data: Tensor.DataTypeMap['string'] | readonly string[], dims?: readonly number[]): TypedTensor<'string'>;
    /**
     * Construct a new bool tensor object from the given type, data and dims.
     *
     * @param type - Specify the element type.
     * @param data - Specify the CPU tensor data.
     * @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
     */
    new (type: 'bool', data: Tensor.DataTypeMap['bool'] | readonly boolean[], dims?: readonly number[]): TypedTensor<'bool'>;
    /**
     * Construct a new uint8 tensor object from a Uint8ClampedArray, data and dims.
     *
     * @param type - Specify the element type.
     * @param data - Specify the CPU tensor data.
     * @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
     */
    new (type: 'uint8', data: Uint8ClampedArray, dims?: readonly number[]): TypedTensor<'uint8'>;
    /**
     * Construct a new 64-bit integer typed tensor object from the given type, data and dims.
     *
     * @param type - Specify the element type.
     * @param data - Specify the CPU tensor data.
     * @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
     */
    new <T extends 'uint64' | 'int64'>(type: T, data: Tensor.DataTypeMap[T] | readonly bigint[] | readonly number[], dims?: readonly number[]): TypedTensor<T>;
    /**
     * Construct a new numeric tensor object from the given type, data and dims.
     *
     * @param type - Specify the element type.
     * @param data - Specify the CPU tensor data.
     * @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
     */
    new <T extends Exclude<Tensor.Type, 'string' | 'bool' | 'uint64' | 'int64'>>(type: T, data: Tensor.DataTypeMap[T] | readonly number[], dims?: readonly number[]): TypedTensor<T>;
    /**
     * Construct a new float32 tensor object from the given data and dims.
     *
     * @param data - Specify the CPU tensor data.
     * @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
     */
    new (data: Float32Array, dims?: readonly number[]): TypedTensor<'float32'>;
    /**
     * Construct a new int8 tensor object from the given data and dims.
     *
     * @param data - Specify the CPU tensor data.
     * @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
     */
    new (data: Int8Array, dims?: readonly number[]): TypedTensor<'int8'>;
    /**
     * Construct a new uint8 tensor object from the given data and dims.
     *
     * @param data - Specify the CPU tensor data.
     * @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
     */
    new (data: Uint8Array, dims?: readonly number[]): TypedTensor<'uint8'>;
    /**
     * Construct a new uint8 tensor object from the given data and dims.
     *
     * @param data - Specify the CPU tensor data.
     * @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
     */
    new (data: Uint8ClampedArray, dims?: readonly number[]): TypedTensor<'uint8'>;
    /**
     * Construct a new uint16 tensor object from the given data and dims.
     *
     * @param data - Specify the CPU tensor data.
     * @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
     */
    new (data: Uint16Array, dims?: readonly number[]): TypedTensor<'uint16'>;
    /**
     * Construct a new int16 tensor object from the given data and dims.
     *
     * @param data - Specify the CPU tensor data.
     * @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
     */
    new (data: Int16Array, dims?: readonly number[]): TypedTensor<'int16'>;
    /**
     * Construct a new int32 tensor object from the given data and dims.
     *
     * @param data - Specify the CPU tensor data.
     * @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
     */
    new (data: Int32Array, dims?: readonly number[]): TypedTensor<'int32'>;
    /**
     * Construct a new int64 tensor object from the given data and dims.
     *
     * @param data - Specify the CPU tensor data.
     * @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
     */
    new (data: BigInt64Array, dims?: readonly number[]): TypedTensor<'int64'>;
    /**
     * Construct a new string tensor object from the given data and dims.
     *
     * @param data - Specify the CPU tensor data.
     * @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
     */
    new (data: readonly string[], dims?: readonly number[]): TypedTensor<'string'>;
    /**
     * Construct a new bool tensor object from the given data and dims.
     *
     * @param data - Specify the CPU tensor data.
     * @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
     */
    new (data: readonly boolean[], dims?: readonly number[]): TypedTensor<'bool'>;
    /**
     * Construct a new float64 tensor object from the given data and dims.
     *
     * @param data - Specify the CPU tensor data.
     * @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
     */
    new (data: Float64Array, dims?: readonly number[]): TypedTensor<'float64'>;
    /**
     * Construct a new uint32 tensor object from the given data and dims.
     *
     * @param data - Specify the CPU tensor data.
     * @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
     */
    new (data: Uint32Array, dims?: readonly number[]): TypedTensor<'uint32'>;
    /**
     * Construct a new uint64 tensor object from the given data and dims.
     *
     * @param data - Specify the CPU tensor data.
     * @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
     */
    new (data: BigUint64Array, dims?: readonly number[]): TypedTensor<'uint64'>;
    /**
     * Construct a new tensor object from the given type, data and dims.
     *
     * @param type - Specify the element type.
     * @param data - Specify the CPU tensor data.
     * @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
     */
    new (type: Tensor.Type, data: Tensor.DataType | readonly number[] | readonly string[] | readonly bigint[] | readonly boolean[], dims?: readonly number[]): Tensor;
    /**
     * Construct a new tensor object from the given data and dims.
     *
     * @param data - Specify the CPU tensor data.
     * @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
     */
    new (data: Tensor.DataType, dims?: readonly number[]): Tensor;
}
export declare const Tensor: TensorConstructor;
export {};
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