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### Description support using uniform buffer. This PR allows to use uniform buffer in shader program, so that some runtime information (eg. input/output shape) is no longer need to be hardcoded into shader code. There are 2 commits in this PR: - [667f31c](667f31c83d): framework changes to support uniform buffer, as well as updates in program manager, gpu data manager and indices helper. - [09e1d2a](09e1d2ad1d): an example change for operator `Transpose` to use input's rank-only instead of dims as shader key. With this change, model mobilenetv2-12 shader compile times dropped from 71 to 52.
85 lines
3.5 KiB
TypeScript
85 lines
3.5 KiB
TypeScript
// Copyright (c) Microsoft Corporation. All rights reserved.
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// Licensed under the MIT License.
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import {TensorView} from '../../tensor-view';
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import {ShapeUtil} from '../../util';
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import {AttributeWithCacheKey, createAttributeWithCacheKey} from '../attribute-with-cache-key';
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import {ComputeContext, GpuDataType, ProgramInfo} from '../types';
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import {createTensorShapeVariables, IndicesHelper, inputVariable, outputVariable, ShaderHelper} from './common';
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export interface TransposeAttributes extends AttributeWithCacheKey {
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readonly perm: number[];
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}
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const validateInputs = (inputs: readonly TensorView[]): void => {
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if (!inputs || inputs.length !== 1) {
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throw new Error('Transpose requires 1 input.');
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}
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};
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const getAdjustedPerm = (inputRank: number, perm: number[]): number[] =>
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(perm && perm.length !== inputRank) ? [...(new Array(inputRank).keys())].reverse() : perm;
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const getOutputShape = (inputShape: readonly number[], perm: number[]): readonly number[] =>
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ShapeUtil.sortBasedOnPerm(inputShape, getAdjustedPerm(inputShape.length, perm));
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const permFunctionBody = (perm: number[], rank: number, input: IndicesHelper, output: IndicesHelper): string => {
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const reverseFunc = [];
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reverseFunc.push(`fn perm(i: ${output.type.indices}) -> ${input.type.indices} {
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var a: ${input.type.indices};`);
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for (let i = 0; i < rank; ++i) {
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reverseFunc.push(input.indicesSet('a', perm[i], `i[${i}]`));
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}
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reverseFunc.push('return a;}');
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return reverseFunc.join('\n');
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};
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export const createTransposeProgramInfo =
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(inputDataType: number, inputRank: number, permAttr: number[]): ProgramInfo => {
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const perm = getAdjustedPerm(inputRank, permAttr);
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const output = outputVariable('output', inputDataType, (permAttr && permAttr.length) || inputRank);
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const input = inputVariable('a', inputDataType, inputRank);
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const getShaderSource = (shaderHelper: ShaderHelper) => `
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${shaderHelper.registerUniform('output_size', 'u32').declareVariables(input, output)}
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${permFunctionBody(perm, inputRank, input, output)}
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${shaderHelper.mainStart()}
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${shaderHelper.guardAgainstOutOfBoundsWorkgroupSizes('uniforms.output_size')}
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let indices = ${output.offsetToIndices('global_idx')};
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let aIndices = perm(indices);
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${output.setByOffset('global_idx', input.getByIndices('aIndices'))}
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}`;
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return {
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name: 'Transpose',
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inputTypes: [GpuDataType.default],
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shaderCache: {hint: `${permAttr}`, inputDependencies: ['rank']},
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getRunData: (inputs) => {
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const outputShape = getOutputShape(inputs[0].dims, perm);
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const outputSize = ShapeUtil.size(outputShape);
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return {
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outputs: [{dims: outputShape, dataType: inputs[0].dataType, gpuDataType: GpuDataType.default}],
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dispatchGroup: {x: Math.ceil(outputSize / 64 /* workgroup size */)},
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variables: [
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{type: 'uint32', data: outputSize},
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...createTensorShapeVariables(inputs[0].dims),
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...createTensorShapeVariables(outputShape),
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],
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};
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},
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getShaderSource,
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};
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};
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export const transpose = (context: ComputeContext, attributes: TransposeAttributes): void => {
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validateInputs(context.inputs);
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context.compute(
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createTransposeProgramInfo(context.inputs[0].dataType, context.inputs[0].dims.length, attributes.perm));
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};
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export const parseTransposeAttributes = (attributes: Record<string, unknown>): TransposeAttributes =>
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createAttributeWithCacheKey({perm: attributes.perm as number[]});
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