mirror of
https://github.com/saymrwulf/onnxruntime.git
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106 lines
4 KiB
TypeScript
106 lines
4 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, ProgramInfo} from '../types';
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import {inputVariable, outputVariable, ShaderHelper} from './common';
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export interface GatherElementsAttributes extends AttributeWithCacheKey {
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axis: number;
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}
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const validateInputs = (inputs: readonly TensorView[]): void => {
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if (!inputs || inputs.length !== 2) {
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throw new Error('GatherElements requires 2 inputs.');
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}
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if (inputs[0].dims.length < 1) {
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throw new Error('GatherElements requires that the data input be rank >= 1.');
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}
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if (inputs[0].dims.length !== inputs[1].dims.length) {
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throw new Error(`GatherElements requires that the data input and
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indices input tensors be of same rank.`);
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}
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};
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const createGatherElementsProgramInfo =
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(inputs: readonly TensorView[], attributes: GatherElementsAttributes): ProgramInfo => {
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const inputShape = inputs[0].dims;
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const inputOutputDataType = inputs[0].dataType;
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const inputRank = inputShape.length;
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const inputStrides = ShapeUtil.computeStrides(inputShape);
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const inputSize = ShapeUtil.size(inputShape);
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const indicesShape = inputs[1].dims;
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const indicesDataType = inputs[1].dataType;
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const indicesSize = ShapeUtil.size(indicesShape);
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const axis = ShapeUtil.normalizeAxis(attributes.axis, inputRank);
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const axisDimLimit = inputShape[axis];
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const outputShape = indicesShape.slice(0);
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const outputSize = ShapeUtil.size(outputShape);
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const input = inputVariable('input', inputOutputDataType, inputShape);
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const indices = inputVariable('indices', indicesDataType, [indicesSize]);
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const output = outputVariable('output', inputOutputDataType, outputShape);
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// int64 indices would be treated as little endian i32 with assumption they fall in i32 limits
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// That assumption is safe as it's not possible to allocate >2gb buffer for input tensor
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// Input data will be treated as u32 or two u32 for 8-byte tensors
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const getShaderSource = (shaderHelper: ShaderHelper) => `
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const inputStrides = array<u32, ${inputStrides.length}>(${inputStrides.map(i => `${i}u`).join(',')});
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${shaderHelper.declareVariables(input, indices, output)}
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${shaderHelper.mainStart()}
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${shaderHelper.guardAgainstOutOfBoundsWorkgroupSizes(outputSize)}
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let outputIndices = ${output.offsetToIndices('global_idx')};
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var idx = ${indices.getByOffset('global_idx')};
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if (idx < 0) {
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idx = idx + ${axisDimLimit};
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}
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var srcOffset = u32(0);
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for (var i = 0; i < ${inputShape.length}; i++) {
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if (i == ${axis}) {
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srcOffset += u32(idx) * inputStrides[i];
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} else {
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srcOffset += ${output.indicesGet('outputIndices', 'i')} * inputStrides[i];
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}
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}
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// Should never hit this with valid values in indices
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// This is a guard against malicious data in the indices input
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if (srcOffset < 0 || srcOffset >= ${inputSize}) {
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return;
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}
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output[global_idx] = input[srcOffset];
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}`;
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return {
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name: 'GatherElements',
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shaderCache: {hint: attributes.cacheKey},
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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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}),
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getShaderSource,
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};
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};
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export const parseGatherElementsAttributes = (attributes: Record<string, unknown>): GatherElementsAttributes =>
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createAttributeWithCacheKey({axis: attributes.axis as number});
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export const gatherElements = (context: ComputeContext, attributes: GatherElementsAttributes): void => {
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const inputs = context.inputs;
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validateInputs(inputs);
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context.compute(createGatherElementsProgramInfo(context.inputs, attributes));
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};
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