mirror of
https://github.com/saymrwulf/onnxruntime.git
synced 2026-06-22 02:30:26 +00:00
### Description
See
454996d496
for manual changes (excluded auto-generated formatting changes)
### Why
Because the toolsets for old clang-format is out-of-date. This reduces
the development efficiency.
- The NPM package `clang-format` is already in maintenance mode. not
updated since 2 years ago.
- The VSCode extension for clang-format is not maintained for a while,
and a recent Node.js security update made it not working at all in
Windows.
No one in community seems interested in fixing those.
Choose Prettier as it is the most popular TS/JS formatter.
### How to merge
It's easy to break the build:
- Be careful of any new commits on main not included in this PR.
- Be careful that after this PR is merged, other PRs that already passed
CI can merge.
So, make sure there is no new commits before merging this one, and
invalidate js PRs that already passed CI, force them to merge to latest.
162 lines
5.4 KiB
TypeScript
162 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 { DataType } from '../../../wasm-common';
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import { TensorView } from '../../tensor-view';
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import { GemmUtil, ShapeUtil } from '../../util';
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import { AttributeWithCacheKey } from '../attribute-with-cache-key';
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import { ComputeContext, ProgramInfo, ProgramInputTensorInfoDependency, ProgramUniform } from '../types';
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import {
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createTensorShapeVariables,
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IndicesHelper,
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inputVariable,
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outputVariable,
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ShaderHelper,
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UniformsArrayType,
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} from './common';
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const validateInputs = (inputs: readonly TensorView[]): void => {
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if (!inputs) {
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throw new Error('Input is missing');
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}
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if (inputs.length < 2 || inputs.length > 3) {
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throw new Error('Invaid input number.');
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}
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// 'C' can be of dimensionality 0, 1 or 2 only
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if (inputs.length === 3 && inputs[2].dims.length > 2) {
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throw new Error('Invalid input shape of C');
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}
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if (inputs[0].dataType !== inputs[1].dataType || (inputs.length === 3 && inputs[0].dataType !== inputs[2].dataType)) {
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throw new Error('Input types are mismatched');
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}
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};
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export interface GemmAttributes extends AttributeWithCacheKey {
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transA: boolean;
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transB: boolean;
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alpha: number;
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beta: number;
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}
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const createGemmProgramInfo = (inputs: readonly TensorView[], attributes: GemmAttributes): ProgramInfo => {
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const aShape = inputs[0].dims.slice();
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const bShape = inputs[1].dims.slice();
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const [M, N, K] = GemmUtil.getShapeOfGemmResult(
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aShape,
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attributes.transA,
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bShape,
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attributes.transB,
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inputs.length === 3 ? inputs[2].dims : undefined,
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);
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const outputShape = [M, N];
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if (!outputShape) {
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throw new Error("Can't use gemm on the given tensors");
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}
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const outputSize = ShapeUtil.size(outputShape);
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const programUniforms: ProgramUniform[] = [
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{ type: DataType.uint32, data: outputSize },
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{ type: DataType.uint32, data: M },
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{ type: DataType.uint32, data: N },
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{ type: DataType.uint32, data: K },
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{ type: DataType.float, data: attributes.alpha },
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{ type: DataType.float, data: attributes.beta },
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];
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const inputDependencies: ProgramInputTensorInfoDependency[] = ['type', 'type'];
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if (inputs.length === 3) {
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programUniforms.push(...createTensorShapeVariables(inputs[2].dims));
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inputDependencies.push('rank');
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}
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programUniforms.push(...createTensorShapeVariables(outputShape));
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const getShaderSource = (shaderHelper: ShaderHelper) => {
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let line = '';
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if (attributes.transA && attributes.transB) {
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line = 'value += a[k * uniforms.M + m] * b[n * uniforms.K + k];';
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} else if (attributes.transA && !attributes.transB) {
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line = 'value += a[k * uniforms.M + m] * b[k * uniforms.N + n];';
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} else if (!attributes.transA && attributes.transB) {
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line = 'value += a[m * uniforms.K + k] * b[n * uniforms.K + k];';
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} else if (!attributes.transA && !attributes.transB) {
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line = 'value += a[m * uniforms.K + k] * b[k * uniforms.N + n];';
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}
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const calculateAlpha = attributes.alpha === 1 ? '' : 'value *= uniforms.alpha;';
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const a = inputVariable('a', inputs[0].dataType, inputs[0].dims);
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const b = inputVariable('b', inputs[1].dataType, inputs[1].dims);
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const dataType = a.type.value;
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let c: IndicesHelper | null = null;
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const variables = [a, b];
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if (inputs.length === 3) {
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c = inputVariable('c', inputs[2].dataType, inputs[2].dims.length);
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variables.push(c);
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}
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const output = outputVariable('output', inputs[0].dataType, outputShape.length);
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variables.push(output);
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const uniforms: UniformsArrayType = [
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{ name: 'output_size', type: 'u32' },
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{ name: 'M', type: 'u32' },
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{ name: 'N', type: 'u32' },
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{ name: 'K', type: 'u32' },
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{ name: 'alpha', type: 'f32' },
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{ name: 'beta', type: 'f32' },
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];
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return `
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${shaderHelper.registerUniforms(uniforms).declareVariables(...variables)}
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${shaderHelper.mainStart()}
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${shaderHelper.guardAgainstOutOfBoundsWorkgroupSizes('uniforms.output_size')}
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let m = global_idx / uniforms.N;
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let n = global_idx % uniforms.N;
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var value = ${dataType}(0);
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for (var k: u32 = 0u; k < uniforms.K; k++) {
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${line}
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}
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${calculateAlpha}
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${(() => {
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if (c != null) {
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return `let cOffset = ${c.broadcastedIndicesToOffset('vec2(m, n)', output)}; value += ${
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dataType
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}(uniforms.beta) * ${c.getByOffset('cOffset')};`;
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}
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return '';
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})()}
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output[global_idx] = value;
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}`;
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};
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return {
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name: 'Gemm',
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shaderCache: { hint: `${attributes.cacheKey}`, inputDependencies },
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getRunData: () => ({
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outputs: [{ dims: outputShape, dataType: inputs[0].dataType }],
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dispatchGroup: { x: Math.ceil(outputSize / 64 /* workgroup size */) },
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programUniforms,
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}),
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getShaderSource,
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};
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};
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export const parseGemmAttributes = (attributes: Record<string, unknown>): GemmAttributes => {
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const transA = attributes.transA as boolean;
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const transB = attributes.transB as boolean;
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const alpha = attributes.alpha as number;
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const beta = attributes.beta as number;
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return {
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transA,
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transB,
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alpha,
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beta,
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cacheKey: `${attributes.transA};${attributes.transB};${attributes.alpha === 1}`,
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};
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};
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export const gemm = (context: ComputeContext, attributes: GemmAttributes): void => {
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validateInputs(context.inputs);
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context.compute(createGemmProgramInfo(context.inputs, attributes));
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};
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