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https://github.com/saymrwulf/onnxruntime.git
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### Description This change adds only necessary code to enable ort-web works with any Float16Array polyfill. Unlike #19302, in this PR, ort-web does not include any specific polyfill; instead, it's user's choice for how to use a polyfill. ORT-web uses Float16Array if it's available; otherwise, fallback to use Uint16Array. ```js // case 1: user does not use polyfill: import * as ort from 'onnxruntime-web'; const myF16Data = new Uint16Array(...); // need to use Uint16Array const myF16tensor = new ort.Tensor('float16', myF16Data, dims); ``` ```js // case 2: user use polyfill: import * as ort from 'onnxruntime-web'; import { Float16Array, isFloat16Array, isTypedArray, getFloat16, setFloat16, f16round, } from "@petamoriken/float16"; globalThis.Float16Array = Float16Array; // ort-web will pick the global Float16Array const myF16Data = new Float16Array(...); // Use the polyfilled Float16Array type const myF16tensor = new ort.Tensor('float16', myF16Data, dims); ```
206 lines
5.4 KiB
TypeScript
206 lines
5.4 KiB
TypeScript
// Copyright (c) Microsoft Corporation. All rights reserved.
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// Licensed under the MIT License.
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import {Tensor} from 'onnxruntime-common';
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// a dummy type declaration for Float16Array in case any polyfill is available.
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declare global {
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// eslint-disable-next-line @typescript-eslint/naming-convention, @typescript-eslint/no-explicit-any
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const Float16Array: any;
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}
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// This file includes common definitions. They do NOT have dependency on the WebAssembly instance.
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/**
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* Copied from ONNX definition. Use this to drop dependency 'onnx_proto' to decrease compiled .js file size.
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*/
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export const enum DataType {
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undefined = 0,
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float = 1,
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uint8 = 2,
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int8 = 3,
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uint16 = 4,
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int16 = 5,
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int32 = 6,
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int64 = 7,
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string = 8,
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bool = 9,
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float16 = 10,
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double = 11,
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uint32 = 12,
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uint64 = 13,
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complex64 = 14,
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complex128 = 15,
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bfloat16 = 16
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}
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/**
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* Map string tensor data to enum value
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*/
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export const tensorDataTypeStringToEnum = (type: string): DataType => {
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switch (type) {
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case 'int8':
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return DataType.int8;
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case 'uint8':
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return DataType.uint8;
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case 'bool':
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return DataType.bool;
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case 'int16':
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return DataType.int16;
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case 'uint16':
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return DataType.uint16;
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case 'int32':
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return DataType.int32;
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case 'uint32':
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return DataType.uint32;
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case 'float16':
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return DataType.float16;
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case 'float32':
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return DataType.float;
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case 'float64':
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return DataType.double;
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case 'string':
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return DataType.string;
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case 'int64':
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return DataType.int64;
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case 'uint64':
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return DataType.uint64;
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default:
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throw new Error(`unsupported data type: ${type}`);
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}
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};
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/**
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* Map enum value to string tensor data
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*/
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export const tensorDataTypeEnumToString = (typeProto: DataType): Tensor.Type => {
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switch (typeProto) {
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case DataType.int8:
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return 'int8';
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case DataType.uint8:
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return 'uint8';
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case DataType.bool:
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return 'bool';
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case DataType.int16:
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return 'int16';
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case DataType.uint16:
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return 'uint16';
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case DataType.int32:
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return 'int32';
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case DataType.uint32:
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return 'uint32';
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case DataType.float16:
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return 'float16';
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case DataType.float:
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return 'float32';
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case DataType.double:
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return 'float64';
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case DataType.string:
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return 'string';
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case DataType.int64:
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return 'int64';
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case DataType.uint64:
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return 'uint64';
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default:
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throw new Error(`unsupported data type: ${typeProto}`);
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}
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};
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/**
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* get tensor element size in bytes by the given data type
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* @returns size in integer or undefined if the data type is not supported
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*/
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export const getTensorElementSize = (dateType: number): number|
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undefined => [undefined, 4, 1, 1, 2, 2, 4, 8, undefined, 1, 2, 8, 4, 8, undefined, undefined, undefined][dateType];
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/**
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* get typed array constructor by the given tensor type
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*/
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export const tensorTypeToTypedArrayConstructor = (type: Tensor.Type): Float32ArrayConstructor|Uint8ArrayConstructor|
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Int8ArrayConstructor|Uint16ArrayConstructor|Int16ArrayConstructor|Int32ArrayConstructor|BigInt64ArrayConstructor|
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Uint8ArrayConstructor|Float64ArrayConstructor|Uint32ArrayConstructor|BigUint64ArrayConstructor => {
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switch (type) {
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case 'float16':
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// allow Float16Array polyfill.
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return typeof Float16Array !== 'undefined' && Float16Array.from ? Float16Array : Uint16Array;
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case 'float32':
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return Float32Array;
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case 'uint8':
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return Uint8Array;
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case 'int8':
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return Int8Array;
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case 'uint16':
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return Uint16Array;
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case 'int16':
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return Int16Array;
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case 'int32':
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return Int32Array;
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case 'bool':
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return Uint8Array;
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case 'float64':
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return Float64Array;
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case 'uint32':
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return Uint32Array;
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case 'int64':
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return BigInt64Array;
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case 'uint64':
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return BigUint64Array;
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default:
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throw new Error(`unsupported type: ${type}`);
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}
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};
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/**
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* Map string log level to integer value
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*/
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export const logLevelStringToEnum = (logLevel?: 'verbose'|'info'|'warning'|'error'|'fatal'): number => {
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switch (logLevel) {
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case 'verbose':
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return 0;
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case 'info':
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return 1;
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case 'warning':
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return 2;
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case 'error':
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return 3;
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case 'fatal':
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return 4;
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default:
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throw new Error(`unsupported logging level: ${logLevel}`);
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}
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};
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/**
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* Check whether the given tensor type is supported by GPU buffer
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*/
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export const isGpuBufferSupportedType = (type: Tensor.Type): type is Tensor.GpuBufferDataTypes => type === 'float32' ||
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type === 'float16' || type === 'int32' || type === 'int64' || type === 'uint32' || type === 'uint8' ||
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type === 'bool';
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/**
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* Map string data location to integer value
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*/
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export const dataLocationStringToEnum = (location: Tensor.DataLocation): number => {
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switch (location) {
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case 'none':
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return 0;
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case 'cpu':
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return 1;
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case 'cpu-pinned':
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return 2;
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case 'texture':
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return 3;
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case 'gpu-buffer':
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return 4;
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default:
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throw new Error(`unsupported data location: ${location}`);
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}
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};
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/**
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* Map integer data location to string value
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*/
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export const dataLocationEnumToString = (location: number): Tensor.DataLocation|undefined =>
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(['none', 'cpu', 'cpu-pinned', 'texture', 'gpu-buffer'] as const)[location];
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