392 lines
12 KiB
TypeScript
392 lines
12 KiB
TypeScript
// Copyright (c) Microsoft Corporation. All rights reserved.
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// Licensed under the MIT License.
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import { TensorFactory } from './tensor-factory.js';
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import { Tensor as TensorImpl } from './tensor-impl.js';
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import { TypedTensorUtils } from './tensor-utils.js';
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import { TryGetGlobalType } from './type-helper.js';
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/* eslint-disable @typescript-eslint/no-redeclare */
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/**
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* represent a basic tensor with specified dimensions and data type.
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*/
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interface TypedTensorBase<T extends Tensor.Type> {
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/**
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* Get the dimensions of the tensor.
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*/
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readonly dims: readonly number[];
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/**
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* Get the data type of the tensor.
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*/
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readonly type: T;
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/**
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* Get the buffer data of the tensor.
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*
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* If the data is not on CPU (eg. it's in the form of WebGL texture or WebGPU buffer), throw error.
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*/
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readonly data: Tensor.DataTypeMap[T];
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/**
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* Get the location of the data.
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*/
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readonly location: Tensor.DataLocation;
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/**
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* Get the WebGL texture that holds the tensor data.
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*
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* If the data is not on GPU as WebGL texture, throw error.
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*/
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readonly texture: Tensor.TextureType;
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/**
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* Get the WebGPU buffer that holds the tensor data.
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*
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* If the data is not on GPU as WebGPU buffer, throw error.
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*/
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readonly gpuBuffer: Tensor.GpuBufferType;
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/**
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* Get the WebNN MLTensor that holds the tensor data.
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*
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* If the data is not in a WebNN MLTensor, throw error.
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*/
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readonly mlTensor: Tensor.MLTensorType;
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/**
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* Get the buffer data of the tensor.
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*
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* If the data is on CPU, returns the data immediately.
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* If the data is on GPU, downloads the data and returns the promise.
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*
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* @param releaseData - whether release the data on GPU. Ignore if data is already on CPU.
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*/
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getData(releaseData?: boolean): Promise<Tensor.DataTypeMap[T]>;
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/**
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* Dispose the tensor data.
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*
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* If the data is on CPU, remove its internal reference to the underlying data.
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* If the data is on GPU, release the data on GPU.
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*
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* After calling this function, the tensor is considered no longer valid. Its location will be set to 'none'.
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*/
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dispose(): void;
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}
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export declare namespace Tensor {
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interface DataTypeMap {
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float32: Float32Array;
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uint8: Uint8Array;
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int8: Int8Array;
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uint16: Uint16Array;
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int16: Int16Array;
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int32: Int32Array;
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int64: BigInt64Array;
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string: string[];
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bool: Uint8Array;
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float16: Uint16Array; // Keep using Uint16Array until we have a concrete solution for float 16.
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float64: Float64Array;
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uint32: Uint32Array;
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uint64: BigUint64Array;
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// complex64: never;
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// complex128: never;
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// bfloat16: never;
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uint4: Uint8Array;
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int4: Int8Array;
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}
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interface ElementTypeMap {
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float32: number;
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uint8: number;
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int8: number;
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uint16: number;
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int16: number;
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int32: number;
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int64: bigint;
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string: string;
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bool: boolean;
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float16: number; // Keep using Uint16Array until we have a concrete solution for float 16.
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float64: number;
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uint32: number;
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uint64: bigint;
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// complex64: never;
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// complex128: never;
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// bfloat16: never;
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uint4: number;
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int4: number;
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}
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type DataType = DataTypeMap[Type];
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type ElementType = ElementTypeMap[Type];
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/**
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* supported data types for constructing a tensor from a pinned CPU buffer
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*/
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export type CpuPinnedDataTypes = Exclude<Tensor.Type, 'string'>;
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/**
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* type alias for WebGL texture
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*/
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export type TextureType = WebGLTexture;
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/**
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* supported data types for constructing a tensor from a WebGL texture
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*/
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export type TextureDataTypes = 'float32';
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type GpuBufferTypeFallback = { size: number; mapState: 'unmapped' | 'pending' | 'mapped' };
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/**
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* type alias for WebGPU buffer
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*/
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export type GpuBufferType = TryGetGlobalType<'GPUBuffer', GpuBufferTypeFallback>;
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type MLTensorTypeFallback = { destroy(): void };
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/**
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* type alias for WebNN MLTensor
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*
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* The specification for WebNN's MLTensor is currently in flux.
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*/
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export type MLTensorType = TryGetGlobalType<'MLTensor', MLTensorTypeFallback>;
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/**
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* supported data types for constructing a tensor from a WebGPU buffer
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*/
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export type GpuBufferDataTypes = 'float32' | 'float16' | 'int32' | 'int64' | 'uint32' | 'uint8' | 'bool';
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/**
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* supported data types for constructing a tensor from a WebNN MLTensor
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*/
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export type MLTensorDataTypes =
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| 'float32'
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| 'float16'
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| 'int8'
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| 'uint8'
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| 'int32'
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| 'uint32'
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| 'int64'
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| 'uint64'
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| 'bool'
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| 'uint4'
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| 'int4';
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/**
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* represent where the tensor data is stored
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*/
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export type DataLocation = 'none' | 'cpu' | 'cpu-pinned' | 'texture' | 'gpu-buffer' | 'ml-tensor';
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/**
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* represent the data type of a tensor
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*/
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export type Type = keyof DataTypeMap;
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}
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/**
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* Represent multi-dimensional arrays to feed to or fetch from model inferencing.
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*/
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export interface TypedTensor<T extends Tensor.Type> extends TypedTensorBase<T>, TypedTensorUtils<T> {}
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/**
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* Represent multi-dimensional arrays to feed to or fetch from model inferencing.
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*/
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export interface Tensor extends TypedTensorBase<Tensor.Type>, TypedTensorUtils<Tensor.Type> {}
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/**
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* type TensorConstructor defines the constructors of 'Tensor' to create CPU tensor instances.
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*/
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export interface TensorConstructor extends TensorFactory {
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// #region CPU tensor - specify element type
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/**
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* Construct a new string tensor object from the given type, data and dims.
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*
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* @param type - Specify the element type.
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* @param data - Specify the CPU tensor data.
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* @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
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*/
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new (
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type: 'string',
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data: Tensor.DataTypeMap['string'] | readonly string[],
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dims?: readonly number[],
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): TypedTensor<'string'>;
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/**
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* Construct a new bool tensor object from the given type, data and dims.
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*
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* @param type - Specify the element type.
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* @param data - Specify the CPU tensor data.
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* @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
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*/
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new (
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type: 'bool',
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data: Tensor.DataTypeMap['bool'] | readonly boolean[],
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dims?: readonly number[],
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): TypedTensor<'bool'>;
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/**
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* Construct a new uint8 tensor object from a Uint8ClampedArray, data and dims.
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*
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* @param type - Specify the element type.
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* @param data - Specify the CPU tensor data.
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* @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
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*/
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new (type: 'uint8', data: Uint8ClampedArray, dims?: readonly number[]): TypedTensor<'uint8'>;
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/**
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* Construct a new 64-bit integer typed tensor object from the given type, data and dims.
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*
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* @param type - Specify the element type.
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* @param data - Specify the CPU tensor data.
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* @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
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*/
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new <T extends 'uint64' | 'int64'>(
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type: T,
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data: Tensor.DataTypeMap[T] | readonly bigint[] | readonly number[],
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dims?: readonly number[],
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): TypedTensor<T>;
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/**
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* Construct a new numeric tensor object from the given type, data and dims.
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*
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* @param type - Specify the element type.
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* @param data - Specify the CPU tensor data.
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* @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
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*/
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new <T extends Exclude<Tensor.Type, 'string' | 'bool' | 'uint64' | 'int64'>>(
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type: T,
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data: Tensor.DataTypeMap[T] | readonly number[],
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dims?: readonly number[],
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): TypedTensor<T>;
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// #endregion
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// #region CPU tensor - infer element types
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/**
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* Construct a new float32 tensor object from the given data and dims.
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*
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* @param data - Specify the CPU tensor data.
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* @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
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*/
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new (data: Float32Array, dims?: readonly number[]): TypedTensor<'float32'>;
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/**
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* Construct a new int8 tensor object from the given data and dims.
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*
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* @param data - Specify the CPU tensor data.
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* @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
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*/
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new (data: Int8Array, dims?: readonly number[]): TypedTensor<'int8'>;
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/**
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* Construct a new uint8 tensor object from the given data and dims.
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*
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* @param data - Specify the CPU tensor data.
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* @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
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*/
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new (data: Uint8Array, dims?: readonly number[]): TypedTensor<'uint8'>;
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/**
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* Construct a new uint8 tensor object from the given data and dims.
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*
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* @param data - Specify the CPU tensor data.
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* @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
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*/
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new (data: Uint8ClampedArray, dims?: readonly number[]): TypedTensor<'uint8'>;
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/**
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* Construct a new uint16 tensor object from the given data and dims.
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*
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* @param data - Specify the CPU tensor data.
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* @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
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*/
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new (data: Uint16Array, dims?: readonly number[]): TypedTensor<'uint16'>;
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/**
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* Construct a new int16 tensor object from the given data and dims.
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*
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* @param data - Specify the CPU tensor data.
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* @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
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*/
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new (data: Int16Array, dims?: readonly number[]): TypedTensor<'int16'>;
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/**
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* Construct a new int32 tensor object from the given data and dims.
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*
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* @param data - Specify the CPU tensor data.
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* @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
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*/
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new (data: Int32Array, dims?: readonly number[]): TypedTensor<'int32'>;
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/**
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* Construct a new int64 tensor object from the given data and dims.
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*
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* @param data - Specify the CPU tensor data.
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* @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
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*/
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new (data: BigInt64Array, dims?: readonly number[]): TypedTensor<'int64'>;
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/**
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* Construct a new string tensor object from the given data and dims.
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*
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* @param data - Specify the CPU tensor data.
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* @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
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*/
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new (data: readonly string[], dims?: readonly number[]): TypedTensor<'string'>;
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/**
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* Construct a new bool tensor object from the given data and dims.
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*
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* @param data - Specify the CPU tensor data.
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* @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
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*/
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new (data: readonly boolean[], dims?: readonly number[]): TypedTensor<'bool'>;
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/**
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* Construct a new float64 tensor object from the given data and dims.
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*
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* @param data - Specify the CPU tensor data.
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* @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
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*/
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new (data: Float64Array, dims?: readonly number[]): TypedTensor<'float64'>;
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/**
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* Construct a new uint32 tensor object from the given data and dims.
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*
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* @param data - Specify the CPU tensor data.
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* @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
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*/
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new (data: Uint32Array, dims?: readonly number[]): TypedTensor<'uint32'>;
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/**
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* Construct a new uint64 tensor object from the given data and dims.
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*
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* @param data - Specify the CPU tensor data.
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* @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
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*/
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new (data: BigUint64Array, dims?: readonly number[]): TypedTensor<'uint64'>;
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// #endregion
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// #region CPU tensor - fall back to non-generic tensor type declaration
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/**
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* Construct a new tensor object from the given type, data and dims.
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*
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* @param type - Specify the element type.
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* @param data - Specify the CPU tensor data.
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* @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
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*/
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new (
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type: Tensor.Type,
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data: Tensor.DataType | readonly number[] | readonly string[] | readonly bigint[] | readonly boolean[],
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dims?: readonly number[],
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): Tensor;
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/**
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* Construct a new tensor object from the given data and dims.
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*
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* @param data - Specify the CPU tensor data.
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* @param dims - Specify the dimension of the tensor. If omitted, a 1-D tensor is assumed.
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*/
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new (data: Tensor.DataType, dims?: readonly number[]): Tensor;
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// #endregion
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}
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// eslint-disable-next-line @typescript-eslint/naming-convention
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export const Tensor = TensorImpl as TensorConstructor;
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