[js/webgpu] Float16Array polyfill for uniform

js/common/lib/tensor-impl-type-mapping.ts

@@ -3,9 +3,9 @@
 
 import {Tensor} from './tensor.js';
 
-export type SupportedTypedArrayConstructors = Float32ArrayConstructor|Uint8ArrayConstructor|Int8ArrayConstructor|
-    Uint16ArrayConstructor|Int16ArrayConstructor|Int32ArrayConstructor|BigInt64ArrayConstructor|Uint8ArrayConstructor|
-    Float64ArrayConstructor|Uint32ArrayConstructor|BigUint64ArrayConstructor;
+export type SupportedTypedArrayConstructors = Float32ArrayConstructor|Uint8ArrayConstructor|
+    Int8ArrayConstructor|Uint16ArrayConstructor|Int16ArrayConstructor|Int32ArrayConstructor|BigInt64ArrayConstructor|
+    Uint8ArrayConstructor|Float64ArrayConstructor|Uint32ArrayConstructor|BigUint64ArrayConstructor;
 export type SupportedTypedArray = InstanceType<SupportedTypedArrayConstructors>;
 
 // a runtime map that maps type string to TypedArray constructor. Should match Tensor.DataTypeMap.
@@ -14,7 +14,6 @@ export const NUMERIC_TENSOR_TYPE_TO_TYPEDARRAY_MAP = new Map<string, SupportedTy
   ['uint8', Uint8Array],
   ['int8', Int8Array],
   ['uint16', Uint16Array],
-  ['float16', Uint16Array],
   ['int16', Int16Array],
   ['int32', Int32Array],
   ['bool', Uint8Array],
@@ -34,16 +33,23 @@ export const NUMERIC_TENSOR_TYPEDARRAY_TO_TYPE_MAP = new Map<SupportedTypedArray
   [Uint32Array, 'uint32'],
 ]);
 
-// the following code allows delaying execution of BigInt checking. This allows lazy initialization for
-// NUMERIC_TENSOR_TYPE_TO_TYPEDARRAY_MAP and NUMERIC_TENSOR_TYPEDARRAY_TO_TYPE_MAP, which allows BigInt polyfill
-// if available.
-let isBigIntChecked = false;
-export const checkBigInt = () => {
-  if (!isBigIntChecked) {
-    isBigIntChecked = true;
-    const isBigInt64ArrayAvailable = typeof BigInt64Array !== 'undefined' && typeof BigInt64Array.from === 'function';
-    const isBigUint64ArrayAvailable =
-        typeof BigUint64Array !== 'undefined' && typeof BigUint64Array.from === 'function';
+// a dummy type declaration for Float16Array in case any polyfill is available.
+declare global {
+  // eslint-disable-next-line @typescript-eslint/naming-convention, @typescript-eslint/no-explicit-any
+  const Float16Array: any;
+  const isFloat16Array: any;
+}
+
+// the following code allows delaying execution of BigInt/Float16Array checking. This allows lazy initialization for
+// NUMERIC_TENSOR_TYPE_TO_TYPEDARRAY_MAP and NUMERIC_TENSOR_TYPEDARRAY_TO_TYPE_MAP, which allows BigInt/Float16Array
+// polyfill if available.
+let isTypedArrayChecked = false;
+export const checkTypedArray = () => {
+  if (!isTypedArrayChecked) {
+    isTypedArrayChecked = true;
+    const isBigInt64ArrayAvailable = typeof BigInt64Array !== 'undefined' && BigInt64Array.from;
+    const isBigUint64ArrayAvailable = typeof BigUint64Array !== 'undefined' && BigUint64Array.from;
+    const isFloat16ArrayAvailable = typeof Float16Array !== 'undefined' && Float16Array.from;
 
     if (isBigInt64ArrayAvailable) {
       NUMERIC_TENSOR_TYPE_TO_TYPEDARRAY_MAP.set('int64', BigInt64Array);
@@ -53,5 +59,12 @@ export const checkBigInt = () => {
       NUMERIC_TENSOR_TYPE_TO_TYPEDARRAY_MAP.set('uint64', BigUint64Array);
       NUMERIC_TENSOR_TYPEDARRAY_TO_TYPE_MAP.set(BigUint64Array, 'uint64');
     }
+    if (isFloat16ArrayAvailable) {
+      NUMERIC_TENSOR_TYPE_TO_TYPEDARRAY_MAP.set('float16', Float16Array);
+      NUMERIC_TENSOR_TYPEDARRAY_TO_TYPE_MAP.set(Float16Array, 'float16');
+    } else {
+      // if Float16Array is not available, use 'Uint16Array' to store the data.
+      NUMERIC_TENSOR_TYPE_TO_TYPEDARRAY_MAP.set('float16', Uint16Array);
+    }
   }
 };

js/common/lib/tensor-impl.ts

@@ -5,7 +5,7 @@ import {tensorToDataURL, tensorToImageData} from './tensor-conversion-impl.js';
 import {TensorToDataUrlOptions, TensorToImageDataOptions} from './tensor-conversion.js';
 import {tensorFromGpuBuffer, tensorFromImage, tensorFromPinnedBuffer, tensorFromTexture} from './tensor-factory-impl.js';
 import {CpuPinnedConstructorParameters, GpuBufferConstructorParameters, TensorFromGpuBufferOptions, TensorFromImageBitmapOptions, TensorFromImageDataOptions, TensorFromImageElementOptions, TensorFromTextureOptions, TensorFromUrlOptions, TextureConstructorParameters} from './tensor-factory.js';
-import {checkBigInt, NUMERIC_TENSOR_TYPE_TO_TYPEDARRAY_MAP, NUMERIC_TENSOR_TYPEDARRAY_TO_TYPE_MAP, SupportedTypedArray, SupportedTypedArrayConstructors} from './tensor-impl-type-mapping.js';
+import {checkTypedArray, NUMERIC_TENSOR_TYPE_TO_TYPEDARRAY_MAP, NUMERIC_TENSOR_TYPEDARRAY_TO_TYPE_MAP, SupportedTypedArray, SupportedTypedArrayConstructors} from './tensor-impl-type-mapping.js';
 import {calculateSize, tensorReshape} from './tensor-utils-impl.js';
 import {Tensor as TensorInterface} from './tensor.js';
 
@@ -67,8 +67,8 @@ export class Tensor implements TensorInterface {
       arg0: TensorType|TensorDataType|readonly string[]|readonly boolean[]|CpuPinnedConstructorParameters|
       TextureConstructorParameters|GpuBufferConstructorParameters,
       arg1?: TensorDataType|readonly number[]|readonly string[]|readonly boolean[], arg2?: readonly number[]) {
-    // perform one-time check for BigInt support
-    checkBigInt();
+    // perform one-time check for BigInt/Float16Array support
+    checkTypedArray();
 
     let type: TensorType;
     let dims: readonly number[];
@@ -146,8 +146,8 @@ export class Tensor implements TensorInterface {
               // Throw error here because when user try to use number array as data,
               // e.g. new Tensor('float16', [1, 2, 3, 4], dims)), it will actually call
               // Uint16Array.from(arg1) which generates wrong data.
-              throw new TypeError(
-                  'Creating a float16 tensor from number array is not supported. Please use Uint16Array as data.');
+              // eslint-disable-next-line  @typescript-eslint/no-explicit-any
+              data = (typedArrayConstructor as any).from(arg1);
             } else if (arg0 === 'uint64' || arg0 === 'int64') {
               // use 'as any' here because:
               // 1. TypeScript's check on type of 'Array.isArray()' does not work with readonly arrays.
@@ -168,6 +168,8 @@ export class Tensor implements TensorInterface {
             }
           } else if (arg1 instanceof typedArrayConstructor) {
             data = arg1;
+          } else if (isFloat16Array !== undefined && isFloat16Array(arg1)) {
+            data = arg1 as InstanceType<typeof Float16Array>;
           } else {
             throw new TypeError(`A ${type} tensor's data must be type of ${typedArrayConstructor}`);
           }

js/common/lib/tensor.ts

@@ -63,6 +63,7 @@ interface TypedTensorBase<T extends Tensor.Type> {
   dispose(): void;
 }
 
+// type Float16ArrayType = InstanceType<typeof Float16Array>;
 export declare namespace Tensor {
   interface DataTypeMap {
     float32: Float32Array;

js/common/package.json

@@ -30,5 +30,8 @@
     "ONNXRuntime",
     "ONNX Runtime"
   ],
-  "description": "ONNXRuntime JavaScript API library"
+  "description": "ONNXRuntime JavaScript API library",
+  "dependencies": {
+    "@petamoriken/float16": "^3.8.4"
+  }
 }

js/common/test/unit-tests/common.ts

@@ -1,6 +1,7 @@
 // Copyright (c) Microsoft Corporation. All rights reserved.
 // Licensed under the MIT License.
 
+import {Float16Array} from '@petamoriken/float16';
 import assert from 'assert/strict';
 import {Tensor} from 'onnxruntime-common';
 
@@ -34,7 +35,7 @@ export const BIGINT_TYPES = [
 /**
  * float16 type, data represented by Uint16Array
  */
-export const FLOAT16_TYPE = ['float16', Uint16Array, false] as const;
+export const FLOAT16_TYPE = ['float16', Float16Array, false] as const;
 
 /**
  * A list of all numerical types.

js/web/lib/onnxjs/backends/webgl/ops/pad.ts

@@ -88,7 +88,7 @@ const validateInputsV2 = (inputs: Tensor[]): void => {
   if (!inputs || inputs.length !== 1) {
     throw new Error('Pad requires 1 input');
   }
-  if (inputs[0].type !== 'float32' && inputs[0].type !== 'float64') {
+  if (inputs[0].type !== 'float16' && inputs[0].type !== 'float32' && inputs[0].type !== 'float64') {
     throw new Error('Invalid input type.');
   }
 };

js/web/lib/onnxjs/backends/webgl/ops/resize-packed.ts

@@ -241,8 +241,8 @@ const prepareInputs = (inputs: Tensor[], attributes: UpsampleAttributes): [reado
 
 const parseScalesData = (scale: Tensor, mode: string, isResize: boolean): number[] => {
   const scales = Array.from(scale.floatData);
-  scalesValidation(scales, mode, isResize);
-  return scales;
+  scalesValidation(scales as number[], mode, isResize);
+  return scales as number[];
 };
 
 const parseScalesDataFromOutputSize =

js/web/lib/onnxjs/tensor.ts

@@ -10,9 +10,11 @@ import {decodeUtf8String, ProtoUtil, ShapeUtil} from './util';
 
 import ortFbs = onnxruntime.experimental.fbs;
 
+type Float16ArrayType = InstanceType<typeof Float16Array>;
 export declare namespace Tensor {
   export interface DataTypeMap {
     bool: Uint8Array;
+    float16: Float16ArrayType;
     float32: Float32Array;
     float64: Float64Array;
     string: string[];
@@ -31,7 +33,7 @@ export declare namespace Tensor {
   export type BooleanType = Tensor.DataTypeMap['bool'];
   export type IntegerType = Tensor.DataTypeMap['int8']|Tensor.DataTypeMap['uint8']|Tensor.DataTypeMap['int16']|
                             Tensor.DataTypeMap['uint16']|Tensor.DataTypeMap['int32']|Tensor.DataTypeMap['uint32'];
-  export type FloatType = Tensor.DataTypeMap['float32']|Tensor.DataTypeMap['float64'];
+  export type FloatType = Tensor.DataTypeMap['float16']|Tensor.DataTypeMap['float32']|Tensor.DataTypeMap['float64'];
   export type NumberType = BooleanType|IntegerType|FloatType;
 
   export type Id = Guid;
@@ -93,6 +95,7 @@ export class Tensor {
    */
   get floatData() {
     switch (this.type) {
+      case 'float16':
       case 'float32':
       case 'float64':
         return this.data as Tensor.FloatType;
@@ -188,7 +191,7 @@ export class Tensor {
     } else {
       if (cache !== undefined) {
         const constructor = dataviewConstructor(type);
-        if (!(cache instanceof constructor)) {
+        if (!(cache instanceof constructor) && !isFloat16Array(cache)) {
           throw new TypeError(`cache should be type ${constructor.name}`);
         }
       }
@@ -357,6 +360,7 @@ function sizeof(type: Tensor.DataType): number {
       return 1;
     case 'int16':
     case 'uint16':
+    case 'float16':
       return 2;
     case 'int32':
     case 'uint32':
@@ -412,6 +416,8 @@ function dataviewConstructor(type: Tensor.DataType) {
       return Uint32Array;
     case 'int64':
       return BigInt64Array;
+    case 'float16':
+      return Float16Array; //typeof Float16Array !== 'undefined' && Float16Array.from ? Float16Array : Uint16Array;;
     case 'float32':
       return Float32Array;
     case 'float64':

js/web/lib/wasm/wasm-common.ts

@@ -3,6 +3,12 @@
 
 import {Tensor} from 'onnxruntime-common';
 
+// a dummy type declaration for Float16Array in case any polyfill is available.
+declare global {
+  var Float16Array: any;
+  var isFloat16Array: any;
+}
+
 // This file includes common definitions. They do NOT have dependency on the WebAssembly instance.
 
 /**
@@ -112,12 +118,14 @@ export const getTensorElementSize = (dateType: number): number|
 /**
  * get typed array constructor by the given tensor type
  */
-export const tensorTypeToTypedArrayConstructor = (type: Tensor.Type): Float32ArrayConstructor|Uint8ArrayConstructor|
-    Int8ArrayConstructor|Uint16ArrayConstructor|Int16ArrayConstructor|Int32ArrayConstructor|BigInt64ArrayConstructor|
-    Uint8ArrayConstructor|Float64ArrayConstructor|Uint32ArrayConstructor|BigUint64ArrayConstructor => {
+export const tensorTypeToTypedArrayConstructor =
+    (type: Tensor.Type): Float32ArrayConstructor|Uint8ArrayConstructor|Int8ArrayConstructor|
+    Uint16ArrayConstructor|Int16ArrayConstructor|Int32ArrayConstructor|BigInt64ArrayConstructor|Uint8ArrayConstructor|
+    Float64ArrayConstructor|Uint32ArrayConstructor|BigUint64ArrayConstructor => {
       switch (type) {
         case 'float16':
-          return Uint16Array;
+          // allow Float16Array polyfill.
+          return typeof Float16Array !== 'undefined' && Float16Array.from ? Float16Array : Uint16Array;;
         case 'float32':
           return Float32Array;
         case 'uint8':

js/web/package.json

@@ -11,6 +11,7 @@
   "version": "1.18.0",
   "jsdelivr": "dist/ort.min.js",
   "dependencies": {
+    "@petamoriken/float16": "^3.8.4",
     "flatbuffers": "^1.12.0",
     "guid-typescript": "^1.0.9",
     "long": "^5.2.3",

js/web/test/data/ops/padf16.jsonc

@@ -0,0 +1,35 @@
+[
+  {
+    "name": "constant 2D",
+    "operator": "Pad",
+    "opset": { "domain": "", "version": 10 },
+    "attributes": [
+      { "name": "mode", "data": "constant", "type": "string" },
+      { "name": "value", "data": 1.2, "type": "float" },
+      { "name": "pads", "data": [3, 2, 2, 3], "type": "ints" }
+    ],
+    "cases": [
+      {
+        "name": "[2,2]->[7,7]",
+        "inputs": [
+          {
+            "data": [1.0, 2.0, 3.0, 4.0],
+            "dims": [2, 2],
+            "type": "float16"
+          }
+        ],
+        "outputs": [
+          {
+            "data": [
+              1.2, 1.2, 1.2, 1.2, 1.2, 1.2, 1.2, 1.2, 1.2, 1.2, 1.2, 1.2, 1.2, 1.2, 1.2, 1.2, 1.2, 1.2, 1.2, 1.2, 1.2,
+              1.2, 1.2, 1.0, 2.0, 1.2, 1.2, 1.2, 1.2, 1.2, 3.0, 4.0, 1.2, 1.2, 1.2, 1.2, 1.2, 1.2, 1.2, 1.2, 1.2, 1.2,
+              1.2, 1.2, 1.2, 1.2, 1.2, 1.2, 1.2
+            ],
+            "dims": [7, 7],
+            "type": "float16"
+          }
+        ]
+      }
+    ]
+  }
+]

js/web/test/test-main.ts

@@ -13,6 +13,11 @@ import {Logger} from '../lib/onnxjs/instrument';
 
 import {Test} from './test-types';
 
+import {Float16Array, isFloat16Array} from '@petamoriken/float16';
+
+globalThis.Float16Array = Float16Array;
+globalThis.isFloat16Array = isFloat16Array;
+
 if (ORT_WEB_TEST_CONFIG.model.some(testGroup => testGroup.tests.some(test => test.backend === 'cpu'))) {
   // require onnxruntime-node
   require('../../node');

js/web/test/test-runner.ts

@@ -1,6 +1,7 @@
 // Copyright (c) Microsoft Corporation. All rights reserved.
 // Licensed under the MIT License.
 
+import {Float16Array} from '@petamoriken/float16';
 import {expect} from 'chai';
 import * as ort from 'onnxruntime-common';
 import {extname} from 'path';
@@ -393,11 +394,12 @@ export class TensorResultValidator {
       case 'string':
         return this.strictEqual(actual.stringData, expected.stringData);
 
+      case 'float16':
       case 'float32':
       case 'float64':
         return this.floatEqual(
-            actual.numberData as number[] | Float32Array | Float64Array,
-            expected.numberData as number[] | Float32Array | Float64Array);
+            actual.numberData as number[] | Float16Array | Float32Array | Float64Array,
+            expected.numberData as number[] | Float16Array | Float32Array | Float64Array);
 
       case 'uint8':
       case 'int8':
@@ -425,7 +427,10 @@ export class TensorResultValidator {
       return false;
     }
   }
-  floatEqual(actual: number[]|Float32Array|Float64Array, expected: number[]|Float32Array|Float64Array): boolean {
+
+  floatEqual(
+      actual: number[]|Float16Array|Float32Array|Float64Array,
+      expected: number[]|Float16Array|Float32Array|Float64Array): boolean {
     if (actual.length !== expected.length) {
       return false;
     }