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[js/webgpu] Reland the optimization of ConvTranspose #23858

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Merged
guschmue merged 4 commits into from
Mar 4, 2025
Merged

[js/webgpu] Reland the optimization of ConvTranspose #23858

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98c8e89
Reland: Optimize ConvTranspose (Continue)
qjia7 Feb 26, 2025
18d60ea
fix the incorrect result
qjia7 Mar 1, 2025
22355ac
add tests
qjia7 Mar 1, 2025
854b073
Set packInputAs4 to false if inputChannelsPerGroup is less than 4
qjia7 Mar 1, 2025
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96 changes: 77 additions & 19 deletions js/web/lib/wasm/jsep/webgpu/ops/3rd-party/conv_backprop_webgpu.ts
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Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -46,6 +46,11 @@ export const createConvTranspose2DProgramInfo = (
const inputChannelsPerGroup = wShape[2] / group;
const outputChannelsPerGroup = wShape[3];
const aComponents = isChannelsLast ? getMaxComponents(inputChannelsPerGroup) : 1;
const packInputAs4 = isChannelsLast && outputChannelsPerGroup === 1 && inputChannelsPerGroup >= 4;
const inputChannelsPerGroupInt = packInputAs4
? Math.floor(inputChannelsPerGroup / 4) * 4
: Math.floor(inputChannelsPerGroup / aComponents) * aComponents;
const inputChannelsRemainder = inputChannelsPerGroup - inputChannelsPerGroupInt;
const components = isChannelsLast ? getMaxComponents(outputChannelsPerGroup) : 1;
const bComponents = isChannelsLast ? (outputChannelsPerGroup === 1 ? aComponents : components) : 1;
const outputSize = ShapeUtil.size(outputShape) / components;
Expand Down Expand Up @@ -78,6 +83,7 @@ export const createConvTranspose2DProgramInfo = (
{ type: DataType.uint32, data: dilations },
{ type: DataType.uint32, data: effectiveFilterDims },
{ type: DataType.int32, data: pads },
{ type: DataType.uint32, data: inputChannelsPerGroupInt },
{ type: DataType.uint32, data: inputChannelsPerGroup },
{ type: DataType.uint32, data: outputChannelsPerGroup },
...createTensorShapeVariables(inputs[0].dims, inputs[1].dims),
Expand All @@ -96,6 +102,7 @@ export const createConvTranspose2DProgramInfo = (
{ name: 'dilations', type: 'u32', length: filterDims.length },
{ name: 'effective_filter_dims', type: 'u32', length: effectiveFilterDims.length },
{ name: 'pads', type: 'i32', length: pads.length },
{ name: 'input_channels_per_group_int', type: 'u32' },
{ name: 'input_channels_per_group', type: 'u32' },
{ name: 'output_channels_per_group', type: 'u32' },
];
Expand All @@ -114,16 +121,40 @@ export const createConvTranspose2DProgramInfo = (

const calculateResult = (): string => {
let calcStr = '';
if (aComponents === 1) {
calcStr += `
let w_offset = ${w.indicesToOffset(`${w.type.indices}(u32(wRPerm), u32(wCPerm), inputChannel, wOutChannel)`)};
let wValue = ${w.getByOffset(`w_offset / ${bComponents}`)};
dotProd = dotProd + xValue * wValue;`;
if (packInputAs4) {
if (aComponents === 4) {
calcStr += `
let xValue = ${dy.getByOffset('x_offset')};
let wValue = ${w.getByOffset('w_offset')};
dotProd = dotProd + dot(xValue, wValue);
x_offset += 1u;
w_offset += 1u;`;
} else if (aComponents === 2) {
calcStr += `
dotProd = dotProd + dot(vec4<${dataType}>(${dy.getByOffset('x_offset')}, ${dy.getByOffset('x_offset + 1u')}), vec4<${dataType}>(${w.getByOffset('w_offset')}, ${w.getByOffset('w_offset + 1u')}));
x_offset += 2u;
w_offset += 2u;`;
} else if (aComponents === 1) {
calcStr += `
dotProd = dotProd + dot(vec4<${dataType}>(${dy.getByOffset('x_offset')}, ${dy.getByOffset('x_offset + 1u')}, ${dy.getByOffset('x_offset + 2u')}, ${dy.getByOffset('x_offset + 3u')}), vec4<${dataType}>(${w.getByOffset('w_offset')}, ${w.getByOffset('w_offset + 1u')}, ${w.getByOffset('w_offset + 2u')}, ${w.getByOffset('w_offset + 3u')}));
x_offset += 4u;
w_offset += 4u;`;
}
} else {
if (outputChannelsPerGroup === 1) {
calcStr += `
let xValue = ${
isChannelsLast
? dy.getByOffset(
`${dy.indicesToOffset(`${dy.type.indices}(batch, idyR, idyC, inputChannel)`)} / ${aComponents}`,
)
: dy.get('batch', 'inputChannel', 'idyR', 'idyC')
};
`;
if (aComponents === 1) {
calcStr += `
let wValue = ${w.getByOffset(`${w.indicesToOffset(`${w.type.indices}(u32(wRPerm), u32(wCPerm), inputChannel, wOutChannel)`)} / ${bComponents}`)};
dotProd = dotProd + dot(xValue, wValue);`;
let w_offset = ${w.indicesToOffset(`${w.type.indices}(u32(wRPerm), u32(wCPerm), inputChannel, wOutChannel)`)};
let wValue = ${w.getByOffset(`w_offset / ${bComponents}`)};
dotProd = dotProd + xValue * wValue;`;
} else {
for (let c = 0; c < aComponents; c++) {
calcStr += `
Expand All @@ -134,6 +165,32 @@ export const createConvTranspose2DProgramInfo = (
}
return calcStr;
};
const calculateRemainder = (): string => {
if (inputChannelsRemainder === 0) {
return '';
}
if (!packInputAs4) {
throw new Error(`packInputAs4 ${packInputAs4} is not true.`);
}
let calcStr = '';
if (aComponents === 1) {
calcStr += 'dotProd = dotProd';
for (let i = 0; i < inputChannelsRemainder; i++) {
calcStr += `
+ ${dy.getByOffset(`x_offset + ${i}`)} * ${w.getByOffset(`w_offset + ${i}`)}`;
}
calcStr += ';';
} else if (aComponents === 2) {
if (inputChannelsRemainder !== 2) {
throw new Error(`Invalid inputChannelsRemainder ${inputChannelsRemainder}.`);
}
calcStr += `
let xValue = ${dy.getByOffset('x_offset')};
let wValue = ${w.getByOffset('w_offset')};
dotProd = dotProd + dot(xValue, wValue);`;
}
return calcStr;
};
const codeSnippet = `
let outputIndices = ${output.offsetToIndices(`global_idx * ${components}`)};
let batch = ${output.indicesGet('outputIndices', 0)};
Expand Down Expand Up @@ -169,7 +226,6 @@ export const createConvTranspose2DProgramInfo = (
// Minimum wC >= 0 that satisfies (dyCCorner + wC) % (uniforms.strides.y) == 0
wC = u32(((dyCCorner + i32(uniforms.strides.y) - 1) / i32(uniforms.strides.y)) * i32(uniforms.strides.y) - dyCCorner);
}

for (; wC < uniforms.effective_filter_dims.y; wC = wC + 1) {
if (wC % uniforms.dilations.y != 0) {
continue;
Expand All @@ -182,17 +238,19 @@ export const createConvTranspose2DProgramInfo = (
}
let idyC: u32 = u32(dyC);
var inputChannel = groupId * uniforms.input_channels_per_group;
for (var d2: u32 = 0; d2 < uniforms.input_channels_per_group; d2 = d2 + ${aComponents}) {
let xValue = ${
isChannelsLast
? dy.getByOffset(
`${dy.indicesToOffset(`${dy.type.indices}(batch, idyR, idyC, inputChannel)`)} / ${aComponents}`,
)
: dy.get('batch', 'inputChannel', 'idyR', 'idyC')
};
${
packInputAs4
? `
var x_offset = ${dy.indicesToOffset(`${dy.type.indices}(batch, idyR, idyC, inputChannel)`)} / ${aComponents};
var w_offset = ${w.indicesToOffset(`${w.type.indices}(wRPerm, wCPerm, inputChannel, wOutChannel)`)} / ${bComponents};
`
: ''
}
for (var d2: u32 = 0; d2 < uniforms.input_channels_per_group_int; d2 = d2 + ${packInputAs4 ? 4 : aComponents}) {
${calculateResult()}
inputChannel = inputChannel + ${aComponents};
inputChannel = inputChannel + ${packInputAs4 ? 4 : aComponents};
}
${calculateRemainder()}
wC = wC + uniforms.strides.y - 1;
}
wR = wR + uniforms.strides[0] - 1;
Expand All @@ -211,7 +269,7 @@ export const createConvTranspose2DProgramInfo = (
return {
name: 'ConvTranspose2D',
shaderCache: {
hint: `${attributes.cacheKey};${aComponents}${bComponents}${components}${outputChannelsPerGroup === 1}`,
hint: `${attributes.cacheKey};${aComponents}${bComponents}${components}${packInputAs4}${inputChannelsRemainder}`,
inputDependencies,
},
getRunData: () => ({
Expand Down
122 changes: 122 additions & 0 deletions js/web/test/data/ops/conv-transpose.jsonc
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -348,6 +348,128 @@
}
]
},
{
"name": "ConvTranspose NHWC- group - A",
"operator": "ConvTranspose",
"inputShapeDefinitions": "rankOnly",
"opset": { "domain": "", "version": 17 },
"attributes": [
{ "name": "kernel_shape", "data": [1, 1], "type": "ints" },
{ "name": "group", "data": 2, "type": "int" }
],
"cases": [
{
"name": "T[0]",
"inputs": [
{
"data": [0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 18.0, 20.0, 22.0, 24.0, 26.0, 28.0, 30.0, 32.0, 34.0],
"dims": [1, 2, 3, 3],
"type": "float32"
},
{
"data": [1.0, 2.0],
"dims": [2, 1, 1, 1],
"type": "float32"
}
],
"outputs": [
{
"data": [0, 1, 2, 3, 4, 5, 6, 7, 8, 36, 40, 44, 48, 52, 56, 60, 64, 68],
"dims": [1, 2, 3, 3],
"type": "float32"
}
]
}
]
},
{
"name": "ConvTranspose NHWC- group - B",
"operator": "ConvTranspose",
"inputShapeDefinitions": "rankOnly",
"opset": { "domain": "", "version": 17 },
"attributes": [
{ "name": "kernel_shape", "data": [2, 2], "type": "ints" },
{ "name": "group", "data": 3, "type": "int" }
],
"cases": [
{
"name": "T[0]",
"inputs": [
{
"data": [
0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0,
19.0, 20.0, 21.0, 22.0, 23.0, 0, 0, 0
],
"dims": [1, 3, 3, 3],
"type": "float32"
},
{
"data": [1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0],
"dims": [3, 1, 2, 2],
"type": "float32"
},
{
"data": [0.125, 0.25, 0.375],
"dims": [3],
"type": "float32"
}
],
"outputs": [
{
"data": [
0.125, 1.125, 4.125, 4.125, 3.125, 13.125, 23.125, 18.125, 15.125, 43.125, 53.125, 36.125, 18.125, 45.125,
52.125, 32.125, 45.25, 104.25, 115.25, 66.25, 123.25, 279.25, 305.25, 172.25, 159.25, 357.25, 383.25,
214.25, 105.25, 232.25, 247.25, 136.25, 162.375, 351.375, 370.375, 200.375, 387.375, 833.375, 875.375,
470.375, 231.375, 494.375, 517.375, 276.375, 0.375, 0.375, 0.375, 0.375
],
"dims": [1, 3, 4, 4],
"type": "float32"
}
]
}
]
},
{
"name": "ConvTranspose NHWC- group - C",
"operator": "ConvTranspose",
"inputShapeDefinitions": "rankOnly",
"opset": { "domain": "", "version": 17 },
"attributes": [
{ "name": "kernel_shape", "data": [2, 2], "type": "ints" },
{ "name": "group", "data": 3, "type": "int" }
],
"cases": [
{
"name": "T[0]",
"inputs": [
{
"data": [
0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0,
19.0, 20.0, 21.0, 22.0, 23.0, 24.0, 25.0, 26.0, 27.0, 28.0, 29.0, 30.0, 31.0, 32.0, 33.0, 34.0, 35.0
],
"dims": [1, 3, 3, 4],
"type": "float32"
},
{
"data": [1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0],
"dims": [3, 1, 2, 2],
"type": "float32"
}
],
"outputs": [
{
"data": [
0, 1, 4, 7, 6, 4, 16, 26, 36, 26, 20, 56, 66, 76, 50, 24, 59, 66, 73, 44, 60, 137, 148, 159, 90, 164, 368,
394, 420, 234, 212, 472, 498, 524, 290, 140, 307, 322, 337, 184, 216, 465, 484, 503, 270, 516, 1104, 1146,
1188, 634, 596, 1272, 1314, 1356, 722, 352, 747, 770, 793, 420
],
"dims": [1, 3, 4, 5],
"type": "float32"
}
]
}
]
},
{
"name": "ConvTranspose with bias addition C",
"operator": "ConvTranspose",
Expand Down
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