onnxruntime/js/web/lib/wasm/jsep/webgpu/ops/gather.ts
Yulong Wang 9aafbe3feb
[js/web] revise TensorView (#17473)
### Description

This change:
- removes the unused `Tensor` types declared in
/js/web/lib/wasm/jsep/tensor.ts
- removes duplicated util functions in  /js/web/lib/wasm/jsep/tensor.ts
- renames /js/web/lib/wasm/jsep/**tensor.ts** to
/js/web/lib/wasm/jsep/**tensor-view.ts** and update corresponding
references. It was kind of confusing that we have multiple `Tensor`
types defined in different places also we have multiple `tensor.ts`
source files.

This is one of the prerequisites for supporting IO binding for WebGPU
buffer in onnxruntime-web.

list of prerequisites PRs:
https://github.com/microsoft/onnxruntime/pull/17465
https://github.com/microsoft/onnxruntime/pull/17469
https://github.com/microsoft/onnxruntime/pull/17470
https://github.com/microsoft/onnxruntime/pull/17472
https://github.com/microsoft/onnxruntime/pull/17473 (this one)
2023-09-14 21:14:44 -07:00

107 lines
4.1 KiB
TypeScript

// Copyright (c) Microsoft Corporation. All rights reserved.
// Licensed under the MIT License.
import {DataType} from '../../../wasm-common';
import {TensorView} from '../../tensor-view';
import {ShapeUtil} from '../../util';
import {AttributeWithCacheKey, createAttributeWithCacheKey} from '../attribute-with-cache-key';
import {ComputeContext, GpuDataType, ProgramInfo, ProgramMetadata} from '../types';
import {ShaderHelper} from './common';
export interface GatherAttributes extends AttributeWithCacheKey {
axis: number;
}
const validateInputs = (inputs: readonly TensorView[]): void => {
if (!inputs || inputs.length !== 2) {
throw new Error('Gather requires 2 inputs.');
}
};
const createGatherProgramInfo =
(metadata: ProgramMetadata, inputs: readonly TensorView[], attributes: GatherAttributes): ProgramInfo => {
const inputShape = inputs[0].dims;
const indicesShape = inputs[1].dims;
const inputRank = inputShape.length;
const axis = ShapeUtil.normalizeAxis(attributes.axis, inputRank);
const outputShape = inputShape.slice(0);
outputShape.splice(axis, 1, ...indicesShape);
const inputDataType = inputs[0].dataType;
const block = ShapeUtil.sizeFromDimension(inputShape, axis + 1);
const elementSize = [DataType.int64, DataType.uint64, DataType.double].includes(inputDataType) ? 2 : 1;
const indicesElementSize = inputs[1].dataType === DataType.int64 ? 2 : 1;
const blockSize = elementSize * block;
const M = ShapeUtil.sizeToDimension(inputShape, axis);
const N = ShapeUtil.size(indicesShape);
const dataBatchElements = ShapeUtil.sizeFromDimension(inputShape, axis) * elementSize;
const gatheredBatchElements = N * block * elementSize;
const axisDimLimit = inputShape[axis];
const inputSize = ShapeUtil.size(inputShape) * elementSize;
const outputSize = ShapeUtil.size(outputShape) * elementSize;
const totalGathers = M * N;
// 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 N: u32 = ${N};
const elementSize: u32 = ${elementSize};
const indicesElementSize: u32 = ${indicesElementSize};
@group(0) @binding(0) var<storage, read> input : array<u32>;
@group(0) @binding(1) var<storage, read> inputIndices : array<i32>;
@group(0) @binding(2) var<storage, read_write> output: array<u32>;
${shaderHelper.mainStart()}
let batch: u32 = global_idx / N;
let i: u32 = global_idx % N;
let srcOffsetBatch: u32 = batch * ${dataBatchElements};
let dstOffsetBatch: u32 = batch * ${gatheredBatchElements};
var idx = inputIndices[i * indicesElementSize];
if (idx < 0) {
idx = idx + ${axisDimLimit};
}
let srcOffset = srcOffsetBatch + u32(idx) * ${blockSize};
let dstOffset = dstOffsetBatch + i * ${blockSize};
if (srcOffset >= ${inputSize}) {
return;
}
if (dstOffset >= ${outputSize}) {
return;
}
for (var j: u32 = 0; j < ${blockSize}; j++) {
output[dstOffset + j] = input[srcOffset + j];
}
}`;
return {
...metadata,
outputs: [
{dims: outputShape, dataType: inputs[0].dataType, gpuDataType: GpuDataType.default},
],
getShaderSource,
dispatchGroup: () => ({x: Math.ceil(totalGathers / 64 /* workgroup size */)})
};
};
export const parseGatherAttributes = (attributes: Record<string, unknown>): GatherAttributes =>
createAttributeWithCacheKey({axis: attributes.axis as number});
export const gather = (context: ComputeContext, attributes: GatherAttributes): void => {
const inputs = context.inputs;
validateInputs(inputs);
const metadata = {
name: 'Gather',
inputTypes: [GpuDataType.default, GpuDataType.default],
cacheHint: attributes.cacheKey,
};
context.compute(createGatherProgramInfo(metadata, context.inputs, attributes));
};