onnxruntime/js/web/lib/wasm/jsep/webgpu/ops/gather-elements.ts
Yulong Wang d532645bed
[js/webgpu] revise uniform support (#17871)
### Description
<!-- Describe your changes. -->

work for items (2) and (3) in #17860
2023-10-11 16:41:46 -07:00

106 lines
4 KiB
TypeScript

// Copyright (c) Microsoft Corporation. All rights reserved.
// Licensed under the MIT License.
import {TensorView} from '../../tensor-view';
import {ShapeUtil} from '../../util';
import {AttributeWithCacheKey, createAttributeWithCacheKey} from '../attribute-with-cache-key';
import {ComputeContext, ProgramInfo} from '../types';
import {inputVariable, outputVariable, ShaderHelper} from './common';
export interface GatherElementsAttributes extends AttributeWithCacheKey {
axis: number;
}
const validateInputs = (inputs: readonly TensorView[]): void => {
if (!inputs || inputs.length !== 2) {
throw new Error('GatherElements requires 2 inputs.');
}
if (inputs[0].dims.length < 1) {
throw new Error('GatherElements requires that the data input be rank >= 1.');
}
if (inputs[0].dims.length !== inputs[1].dims.length) {
throw new Error(`GatherElements requires that the data input and
indices input tensors be of same rank.`);
}
};
const createGatherElementsProgramInfo =
(inputs: readonly TensorView[], attributes: GatherElementsAttributes): ProgramInfo => {
const inputShape = inputs[0].dims;
const inputOutputDataType = inputs[0].dataType;
const inputRank = inputShape.length;
const inputStrides = ShapeUtil.computeStrides(inputShape);
const inputSize = ShapeUtil.size(inputShape);
const indicesShape = inputs[1].dims;
const indicesDataType = inputs[1].dataType;
const indicesSize = ShapeUtil.size(indicesShape);
const axis = ShapeUtil.normalizeAxis(attributes.axis, inputRank);
const axisDimLimit = inputShape[axis];
const outputShape = indicesShape.slice(0);
const outputSize = ShapeUtil.size(outputShape);
const input = inputVariable('input', inputOutputDataType, inputShape);
const indices = inputVariable('indices', indicesDataType, [indicesSize]);
const output = outputVariable('output', inputOutputDataType, outputShape);
// int64 indices would be treated as little endian i32 with assumption they fall in i32 limits
// That assumption is safe as it's not possible to allocate >2gb buffer for input tensor
// Input data will be treated as u32 or two u32 for 8-byte tensors
const getShaderSource = (shaderHelper: ShaderHelper) => `
const inputStrides = array<u32, ${inputStrides.length}>(${inputStrides.map(i => `${i}u`).join(',')});
${shaderHelper.declareVariables(input, indices, output)}
${shaderHelper.mainStart()}
${shaderHelper.guardAgainstOutOfBoundsWorkgroupSizes(outputSize)}
let outputIndices = ${output.offsetToIndices('global_idx')};
var idx = ${indices.getByOffset('global_idx')};
if (idx < 0) {
idx = idx + ${axisDimLimit};
}
var srcOffset = u32(0);
for (var i = 0; i < ${inputShape.length}; i++) {
if (i == ${axis}) {
srcOffset += u32(idx) * inputStrides[i];
} else {
srcOffset += ${output.indicesGet('outputIndices', 'i')} * inputStrides[i];
}
}
// Should never hit this with valid values in indices
// This is a guard against malicious data in the indices input
if (srcOffset < 0 || srcOffset >= ${inputSize}) {
return;
}
output[global_idx] = input[srcOffset];
}`;
return {
name: 'GatherElements',
shaderCache: {hint: attributes.cacheKey},
getRunData: () => ({
outputs: [{dims: outputShape, dataType: inputs[0].dataType}],
dispatchGroup: {x: Math.ceil(outputSize / 64 /* workgroup size */)}
}),
getShaderSource,
};
};
export const parseGatherElementsAttributes = (attributes: Record<string, unknown>): GatherElementsAttributes =>
createAttributeWithCacheKey({axis: attributes.axis as number});
export const gatherElements = (context: ComputeContext, attributes: GatherElementsAttributes): void => {
const inputs = context.inputs;
validateInputs(inputs);
context.compute(createGatherElementsProgramInfo(context.inputs, attributes));
};