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Merge remote-tracking branch 'origin/master' into webgpu
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@reillyeon
reillyeon committed Nov 14, 2023
2 parents 0b5d5d0 + 27039b3 commit bb84cd9
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Showing 11 changed files with 207 additions and 171 deletions.
4 changes: 2 additions & 2 deletions face_recognition/index.html
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Expand Up @@ -227,8 +227,8 @@ <h2 class="text-uppercase text-info">No model selected</h2>
<script src="https://stackpath.bootstrapcdn.com/bootstrap/4.5.2/js/bootstrap.min.js"
integrity="sha384-B4gt1jrGC7Jh4AgTPSdUtOBvfO8shuf57BaghqFfPlYxofvL8/KUEfYiJOMMV+rV"
crossorigin="anonymous"></script>
<script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@3.9.0/dist/tf.min.js"
integrity="sha256-28ZvjeNGrGNEIj9/2D8YAPE6Vm5JSvvDs+LI4ED31x8="
<script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@4.13.0/dist/tf.min.js"
integrity="sha256-thVOvsS0U8X0/2twH3+6dCK3ZPTvgWgFSivgfpj5vQQ="
crossorigin="anonymous"></script>
<script>
// To restore module after loading 3rd-party libraries.
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55 changes: 29 additions & 26 deletions facial_landmark_detection/face_landmark_nchw.js
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Original file line number Diff line number Diff line change
Expand Up @@ -15,6 +15,10 @@ export class FaceLandmarkNchw {
};
}

async buildMaxPool2d(input, options) {
return this.builder_.maxPool2d(await input, options);
}

async buildConv_(input, indice) {
const prefix = `${this.weightsUrl_}/conv2d`;
let weightSuffix = '_kernel.npy';
Expand All @@ -26,33 +30,33 @@ export class FaceLandmarkNchw {
}

const weightsName = prefix + weightSuffix;
const weights = await buildConstantByNpy(this.builder_, weightsName);
const weights = buildConstantByNpy(this.builder_, weightsName);
const biasName = prefix + biasSuffix;
const bias = await buildConstantByNpy(this.builder_, biasName);
const bias = buildConstantByNpy(this.builder_, biasName);
const options = {
bias: bias,
bias: await bias,
activation: this.builder_.relu(),
};
return this.builder_.conv2d(input, weights, options);
return this.builder_.conv2d(await input, await weights, options);
}

async buildGemm_(input, namePrefix, relu = false, reshapeSize) {
const weights = await buildConstantByNpy(this.builder_,
const weights = buildConstantByNpy(this.builder_,
`${this.weightsUrl_}/${namePrefix}_kernel_transpose.npy`);
const bias = await buildConstantByNpy(this.builder_,
const bias = buildConstantByNpy(this.builder_,
`${this.weightsUrl_}/${namePrefix}_MatMul_bias.npy`);
const options = {
aTranspose: false,
bTranspose: true,
c: bias,
c: await bias,
};
let gemm;
if (reshapeSize !== undefined) {
gemm = this.builder_.gemm(this.builder_.reshape(
this.builder_.transpose(input, {permutation: [0, 2, 3, 1]}),
[null, reshapeSize]), weights, options);
this.builder_.transpose(await input, {permutation: [0, 2, 3, 1]}),
[null, reshapeSize]), await weights, options);
} else {
gemm = this.builder_.gemm(input, weights, options);
gemm = this.builder_.gemm(await input, await weights, options);
}
if (relu) {
gemm = this.builder_.relu(gemm);
Expand All @@ -73,27 +77,26 @@ export class FaceLandmarkNchw {
const poolOptions =
{windowDimensions: [2, 2], strides: [2, 2]};

const conv0 = await this.buildConv_(input, 0);
const pool0 = await this.builder_.maxPool2d(conv0, poolOptions);
const conv0 = this.buildConv_(input, 0);
const pool0 = this.buildMaxPool2d(conv0, poolOptions);

const conv1 = await this.buildConv_(pool0, 1);
const conv2 = await this.buildConv_(conv1, 2);
const pool1 = await this.builder_.maxPool2d(conv2, poolOptions);
const conv1 = this.buildConv_(pool0, 1);
const conv2 = this.buildConv_(conv1, 2);
const pool1 = this.buildMaxPool2d(conv2, poolOptions);

const conv3 = await this.buildConv_(pool1, 3);
const conv4 = await this.buildConv_(conv3, 4);
const pool2 = await this.builder_.maxPool2d(conv4, poolOptions);
const conv3 = this.buildConv_(pool1, 3);
const conv4 = this.buildConv_(conv3, 4);
const pool2 = this.buildMaxPool2d(conv4, poolOptions);

const conv5 = await this.buildConv_(pool2, 5);
const conv6 = await this.buildConv_(conv5, 6);
const pool3 = await this.builder_.maxPool2d(
conv6, {windowDimensions: [2, 2]});
const conv5 = this.buildConv_(pool2, 5);
const conv6 = this.buildConv_(conv5, 6);
const pool3 = this.buildMaxPool2d(conv6, {windowDimensions: [2, 2]});

const conv7 = await this.buildConv_(pool3, 7);
const gemm0 = await this.buildGemm_(conv7, 'dense', true, 6400);
const gemm1 = await this.buildGemm_(gemm0, 'logits');
const conv7 = this.buildConv_(pool3, 7);
const gemm0 = this.buildGemm_(conv7, 'dense', true, 6400);
const gemm1 = this.buildGemm_(gemm0, 'logits');

return gemm1;
return await gemm1;
}

async build(outputOperand) {
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52 changes: 28 additions & 24 deletions facial_landmark_detection/face_landmark_nhwc.js
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Original file line number Diff line number Diff line change
Expand Up @@ -15,6 +15,10 @@ export class FaceLandmarkNhwc {
};
}

async buildMaxPool2d(input, options) {
return this.builder_.maxPool2d(await input, options);
}

async buildConv_(input, indice) {
const prefix = `${this.weightsUrl_}/conv2d`;
let weightSuffix = '_kernel.npy';
Expand All @@ -26,34 +30,34 @@ export class FaceLandmarkNhwc {
}

const weightsName = prefix + weightSuffix;
const weights = await buildConstantByNpy(this.builder_, weightsName);
const weights = buildConstantByNpy(this.builder_, weightsName);
const biasName = prefix + biasSuffix;
const bias = await buildConstantByNpy(this.builder_, biasName);
const bias = buildConstantByNpy(this.builder_, biasName);
const options = {
inputLayout: 'nhwc',
filterLayout: 'ohwi',
bias: bias,
bias: await bias,
activation: this.builder_.relu(),
};
return this.builder_.conv2d(input, weights, options);
return this.builder_.conv2d(await input, await weights, options);
}

async buildFullyConnected_(input, namePrefix, relu = false, reshapeSize) {
const weights = await buildConstantByNpy(this.builder_,
const weights = buildConstantByNpy(this.builder_,
`${this.weightsUrl_}/${namePrefix}_kernel_transpose.npy`);
const bias = await buildConstantByNpy(this.builder_,
const bias = buildConstantByNpy(this.builder_,
`${this.weightsUrl_}/${namePrefix}_MatMul_bias.npy`);
const options = {
aTranspose: false,
bTranspose: true,
c: bias,
c: await bias,
};
let fc;
if (reshapeSize !== undefined) {
fc = this.builder_.gemm(this.builder_.reshape(
input, [null, reshapeSize]), weights, options);
await input, [null, reshapeSize]), await weights, options);
} else {
fc = this.builder_.gemm(input, weights, options);
fc = this.builder_.gemm(await input, await weights, options);
}
if (relu) {
fc = this.builder_.relu(fc);
Expand All @@ -74,28 +78,28 @@ export class FaceLandmarkNhwc {
const poolOptions =
{windowDimensions: [2, 2], strides: [2, 2], layout: 'nhwc'};

const conv0 = await this.buildConv_(input, 0);
const pool0 = await this.builder_.maxPool2d(conv0, poolOptions);
const conv0 = this.buildConv_(input, 0);
const pool0 = this.buildMaxPool2d(conv0, poolOptions);

const conv1 = await this.buildConv_(pool0, 1);
const conv2 = await this.buildConv_(conv1, 2);
const pool1 = await this.builder_.maxPool2d(conv2, poolOptions);
const conv1 = this.buildConv_(pool0, 1);
const conv2 = this.buildConv_(conv1, 2);
const pool1 = this.buildMaxPool2d(conv2, poolOptions);

const conv3 = await this.buildConv_(pool1, 3);
const conv4 = await this.buildConv_(conv3, 4);
const pool2 = await this.builder_.maxPool2d(conv4, poolOptions);
const conv3 = this.buildConv_(pool1, 3);
const conv4 = this.buildConv_(conv3, 4);
const pool2 = this.buildMaxPool2d(conv4, poolOptions);

const conv5 = await this.buildConv_(pool2, 5);
const conv6 = await this.buildConv_(conv5, 6);
const pool3 = await this.builder_.maxPool2d(
const conv5 = this.buildConv_(pool2, 5);
const conv6 = this.buildConv_(conv5, 6);
const pool3 = this.buildMaxPool2d(
conv6, {windowDimensions: [2, 2], layout: 'nhwc'});

const conv7 = await this.buildConv_(pool3, 7);
const fc0 = await this.buildFullyConnected_(
const conv7 = this.buildConv_(pool3, 7);
const fc0 = this.buildFullyConnected_(
conv7, 'dense', true, 6400);
const fc1 = await this.buildFullyConnected_(fc0, 'logits');
const fc1 = this.buildFullyConnected_(fc0, 'logits');

return fc1;
return await fc1;
}

async build(outputOperand) {
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4 changes: 2 additions & 2 deletions facial_landmark_detection/index.html
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Original file line number Diff line number Diff line change
Expand Up @@ -200,8 +200,8 @@ <h2 class="text-uppercase text-info">No model selected</h2>
<script src="https://stackpath.bootstrapcdn.com/bootstrap/4.5.2/js/bootstrap.min.js"
integrity="sha384-B4gt1jrGC7Jh4AgTPSdUtOBvfO8shuf57BaghqFfPlYxofvL8/KUEfYiJOMMV+rV"
crossorigin="anonymous"></script>
<script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@3.9.0/dist/tf.min.js"
integrity="sha256-28ZvjeNGrGNEIj9/2D8YAPE6Vm5JSvvDs+LI4ED31x8="
<script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@4.13.0/dist/tf.min.js"
integrity="sha256-thVOvsS0U8X0/2twH3+6dCK3ZPTvgWgFSivgfpj5vQQ="
crossorigin="anonymous"></script>
<script>
// To restore module after loading 3rd-party libraries.
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12 changes: 8 additions & 4 deletions facial_landmark_detection/main.js
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Original file line number Diff line number Diff line change
Expand Up @@ -258,16 +258,20 @@ async function main() {
contextOptions['numThreads'] = numThreads;
}
start = performance.now();
const fdOutputOperand = await fdInstance.load(contextOptions);
const fldOutputOperand = await fldInstance.load(contextOptions);
const [fdOutputOperand, fldOutputOperand] = await Promise.all([
fdInstance.load(contextOptions),
fldInstance.load(contextOptions),
]);
loadTime = (performance.now() - start).toFixed(2);
console.log(` done in ${loadTime} ms.`);
// UI shows model building progress
await ui.showProgressComponent('done', 'current', 'pending');
console.log('- Building... ');
start = performance.now();
await fdInstance.build(fdOutputOperand);
await fldInstance.build(fldOutputOperand);
await Promise.all([
fdInstance.build(fdOutputOperand),
fldInstance.build(fldOutputOperand),
]);
buildTime = (performance.now() - start).toFixed(2);
console.log(` done in ${buildTime} ms.`);
}
Expand Down
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