Skip to content

[js/webgpu] Optimize InstanceNorm in some shapes #22637

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 1 commit into from
Oct 30, 2024
Merged

[js/webgpu] Optimize InstanceNorm in some shapes #22637

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
23 changes: 16 additions & 7 deletions js/web/lib/wasm/jsep/webgpu/ops/instance-norm.ts
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -36,7 +36,10 @@ const computeChannelScaleShift = (
const f32Type = components === 1 ? 'f32' : `vec${components}f`;
const wgType = components === 1 ? 'vec2f' : `mat2x${components}f`;
const unitsOfWork = n * c;

let workgroupSize = 64;
if (unitsOfWork === 1) {
workgroupSize = 256;
}
const inputShape = [n, c, h / components];
const outputShape = [n, c, 2];
const inputDependencies: ProgramInputTensorInfoDependency[] = ['rank', 'type', 'type'];
Expand All @@ -49,7 +52,6 @@ const computeChannelScaleShift = (
const b = inputVariable('bias', bias.dataType, bias.dims);
const output = outputVariable('output', DataType.float, 3, 2);
const variables = [x, s, b, output];
const workgroupSize = 64;
return `
var<workgroup> workgroup_shared : array<${wgType}, ${workgroupSize}>;
const workgroup_size = ${workgroupSize}u;
Expand Down Expand Up @@ -91,7 +93,7 @@ const computeChannelScaleShift = (
{
name: 'InstanceNormComputeChannelScaleShift',
// TODO: use epsilon as uniform. Currently epsilon as uniform fails test_instancenorm_epsilon.
shaderCache: { hint: `${components};${epsilon}`, inputDependencies },
shaderCache: { hint: `${components};${epsilon};${workgroupSize}`, inputDependencies },
getRunData: () => ({
outputs: [{ dims: outputShape, dataType: DataType.float }],
dispatchGroup: { x: unitsOfWork },
Expand Down Expand Up @@ -187,14 +189,21 @@ const createInstanceNormNHWCProgramInfo = (
const inputDependencies: ProgramInputTensorInfoDependency[] = ['type', 'type'];

// 1. transpose x from NHWC to NCHW
let needTranspose = false;
const transposedXPerm = [0, xShape.length - 1];
for (let i = 0; i < xShape.length - 2; i++) {
needTranspose = needTranspose || xShape[i + 1] !== 1;
transposedXPerm.push(i + 1);
}
const transposedX = context.compute(createTransposeProgramInfo(context.inputs[0], transposedXPerm), {
inputs: [context.inputs[0]],
outputs: [-1],
})[0];

needTranspose = needTranspose && xShape[xShape.length - 1] !== 1;

const transposedX = needTranspose
? context.compute(createTransposeProgramInfo(context.inputs[0], transposedXPerm), {
inputs: [context.inputs[0]],
outputs: [-1],
})[0]
: context.inputs[0].reshape(Array.from({ length: xShape.length }, (_, i) => xShape[transposedXPerm[i]]));
// 2. compute channel scale and channel shift.
const channelScaleShift = computeChannelScaleShift(
context,
Expand Down
Loading