forked from microsoft/onnxruntime
-
Notifications
You must be signed in to change notification settings - Fork 0
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
Supported type: float. int32_t, uint32_t, bool. Case where_broadcast.jsonc is not enabled due to microsoft#17405.
- Loading branch information
Showing
11 changed files
with
568 additions
and
140 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,120 @@ | ||
| // Copyright (c) Microsoft Corporation. All rights reserved. | ||
| // Licensed under the MIT License. | ||
|
|
||
| import {DataType} from '../../../wasm-common'; | ||
| import {TensorView} from '../../tensor'; | ||
| import {BroadcastUtil, ShapeUtil} from '../../util'; | ||
| import {GpuDataType, ProgramInfo, ProgramInfoLoader, ProgramMetadata} from '../types'; | ||
|
|
||
| import {ShaderHelper} from './common'; | ||
|
|
||
| type BuiltinFunctionName = string; | ||
| export type BinaryCustomExpression = (expressionA: string, expressionB: string, expressionC?: string) => string; | ||
| export type BinaryFunctionCall = BuiltinFunctionName|BinaryCustomExpression|{ | ||
| scalar: BinaryCustomExpression; | ||
| vector: BinaryCustomExpression; | ||
| }; | ||
|
|
||
| type CreateOpProgramShader = | ||
| (shaderHelper: ShaderHelper, inputs: readonly TensorView[], dimsOutput: readonly number[], vectorize: boolean, | ||
| doBroadcast: boolean, funcCall: BinaryFunctionCall, typeOutput: number, additionalImplementation?: string) => | ||
| string; | ||
|
|
||
| /* eslint-disable no-param-reassign */ | ||
| const createOpProgramInfo = | ||
| (metadata: ProgramMetadata, inputs: readonly TensorView[], funcCall: BinaryFunctionCall, | ||
| createOpProgramShader: CreateOpProgramShader, additionalImplementation?: string, | ||
| outputDataType?: number): ProgramInfo => { | ||
| const a = inputs.length === 3 ? inputs[1] : inputs[0]; | ||
| const b = inputs.length === 3 ? inputs[2] : inputs[1]; | ||
| if (outputDataType == null) { | ||
| outputDataType = inputs.length === 3 ? inputs[1].dataType : inputs[0].dataType; | ||
| } | ||
|
|
||
| const isBroadcast = !ShapeUtil.areEqual(a.dims, b.dims); | ||
| let outputShape = a.dims; | ||
| let outputSize = ShapeUtil.size(a.dims); | ||
|
|
||
| let vectorize = false; | ||
|
|
||
| // TODO: deal with zero-sized tensors (eg. dims=[1,0]) | ||
| if (isBroadcast) { | ||
| const calculatedShape = BroadcastUtil.calcShape(a.dims, b.dims, false); | ||
| if (!calculatedShape) { | ||
| throw new Error('Can\'t perform binary op on the given tensors'); | ||
| } | ||
| outputShape = calculatedShape; | ||
| outputSize = ShapeUtil.size(outputShape); | ||
|
|
||
| // check whether vectorize can be enabled | ||
| let sharedDimension = 1; | ||
| for (let i = 1; i < outputShape.length; i++) { | ||
| const dimA = a.dims[a.dims.length - i] ?? 1; | ||
| const dimB = b.dims[b.dims.length - i] ?? 1; | ||
| if (dimA === dimB) { | ||
| sharedDimension *= dimA; | ||
| } else { | ||
| break; | ||
| } | ||
| } | ||
| if (sharedDimension % 4 === 0) { | ||
| vectorize = true; | ||
| } | ||
| } else { | ||
| // element-wise | ||
| vectorize = true; | ||
| } | ||
|
|
||
| return { | ||
| ...metadata, | ||
| getShaderSource: (shaderHelper) => createOpProgramShader( | ||
| shaderHelper, inputs, outputShape, vectorize, isBroadcast, funcCall, outputDataType as number, | ||
| additionalImplementation), | ||
| outputs: [{dims: outputShape, dataType: outputDataType, gpuDataType: GpuDataType.default}], | ||
| dispatchGroup: () => | ||
| ({x: Math.ceil(outputSize / 64 /* workgroup size */ / (vectorize ? 4 : 1) /* vec size */)}) | ||
| }; | ||
| }; | ||
|
|
||
| // This is used for ops like binary, where. | ||
| export const createOpProgramInfoLoader = | ||
| (inputs: readonly TensorView[], name: string, funcCall: BinaryFunctionCall, | ||
| createOpProgramShader: CreateOpProgramShader, additionalImplementation?: string, cacheKey?: string, | ||
| outputDataType?: number): ProgramInfoLoader => { | ||
| const inputTypes = inputs.length === 3 ? [GpuDataType.default, GpuDataType.default, GpuDataType.default] : | ||
| [GpuDataType.default, GpuDataType.default]; | ||
| const metadata: ProgramMetadata = {name, inputTypes, cacheHint: cacheKey}; | ||
| return { | ||
| ...metadata, | ||
| get: () => createOpProgramInfo( | ||
| metadata, inputs, funcCall, createOpProgramShader, additionalImplementation, outputDataType) | ||
| }; | ||
| }; | ||
|
|
||
| export const getBroadcastIndexComponent = (name: string, x: number) => (` | ||
| let offset${name}${x} = broadcastIndicesToOffset${name}(outputIndices${x}); | ||
| let index${name}${x} = offset${name}${x} / 4u; | ||
| let component${name}${x} = offset${name}${x} % 4u; | ||
| `); | ||
|
|
||
| type SingleAssignmentFuncCall = (resStr: string, x: number, typeCast?: string) => string; | ||
| export const fourAssignment = (singleAssignment: SingleAssignmentFuncCall, typeOutput: number) => { | ||
| let assignment = ''; | ||
| if (typeOutput === DataType.bool) { | ||
| assignment = ` | ||
| var data = vec4<u32>(0); | ||
| ${singleAssignment('data', 0, 'u32')} | ||
| ${singleAssignment('data', 1, 'u32')} | ||
| ${singleAssignment('data', 2, 'u32')} | ||
| ${singleAssignment('data', 3, 'u32')} | ||
| outputData[global_idx] = dot(vec4<u32>(0x1, 0x100, 0x10000, 0x1000000), vec4<u32>(data));`; | ||
| } else { | ||
| assignment = ` | ||
| ${singleAssignment('outputData[global_idx]', 0)} | ||
| ${singleAssignment('outputData[global_idx]', 1)} | ||
| ${singleAssignment('outputData[global_idx]', 2)} | ||
| ${singleAssignment('outputData[global_idx]', 3)} | ||
| `; | ||
| } | ||
| return assignment; | ||
| }; |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Oops, something went wrong.