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move all layer params into attrs object

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Leon Chen committed 2016-09-18 23:20:59 -04:00
1 parent b1af2a7751
commit fd20f1b7b1
47 files changed
+285 -162
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test/convolutional/AtrousConvolution2D.js
+2 -2
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@@ -57,7 +57,7 @@ describe('convolutional layer: AtrousConvolution2D', function () {
it(title, function () {
console.log(`\n%c${title}`, styles.h3)
let testLayer = new layers.AtrousConvolution2D(nbFilter, nbRow, nbCol, attrs)
let testLayer = new layers.AtrousConvolution2D(Object.assign({ nbFilter, nbRow, nbCol }, attrs))
testLayer.setWeights(TEST_DATA[key].weights.map(w => new KerasJS.Tensor(w.data, w.shape)))
let t = new KerasJS.Tensor(TEST_DATA[key].input.data, TEST_DATA[key].input.shape)
console.log('%cin', styles.h4, stringifyCondensed(t.tensor))
@@ -91,7 +91,7 @@ describe('convolutional layer: AtrousConvolution2D', function () {
it(title, function () {
console.log(`\n%c${title}`, styles.h3)
let testLayer = new layers.AtrousConvolution2D(nbFilter, nbRow, nbCol, attrs)
let testLayer = new layers.AtrousConvolution2D(Object.assign({ nbFilter, nbRow, nbCol }, attrs))
testLayer.setWeights(TEST_DATA[key].weights.map(w => new KerasJS.Tensor(w.data, w.shape)))
let t = new KerasJS.Tensor(TEST_DATA[key].input.data, TEST_DATA[key].input.shape, { useWeblas: true })
console.log('%cin', styles.h4, stringifyCondensed(t.tensor))
test/convolutional/Convolution1D.js
+2 -2
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@@ -52,7 +52,7 @@ describe('convolutional layer: Convolution1D', function () {
it(title, function () {
console.log(`\n%c${title}`, styles.h3)
let testLayer = new layers.Convolution1D(nbFilter, filterLength, attrs)
let testLayer = new layers.Convolution1D(Object.assign({ nbFilter, filterLength }, attrs))
testLayer.setWeights(TEST_DATA[key].weights.map(w => new KerasJS.Tensor(w.data, w.shape)))
let t = new KerasJS.Tensor(TEST_DATA[key].input.data, TEST_DATA[key].input.shape)
console.log('%cin', styles.h4, stringifyCondensed(t.tensor))
@@ -86,7 +86,7 @@ describe('convolutional layer: Convolution1D', function () {
it(title, function () {
console.log(`\n%c${title}`, styles.h3)
let testLayer = new layers.Convolution1D(nbFilter, filterLength, attrs)
let testLayer = new layers.Convolution1D(Object.assign({ nbFilter, filterLength }, attrs))
testLayer.setWeights(TEST_DATA[key].weights.map(w => new KerasJS.Tensor(w.data, w.shape)))
let t = new KerasJS.Tensor(TEST_DATA[key].input.data, TEST_DATA[key].input.shape, { useWeblas: true })
console.log('%cin', styles.h4, stringifyCondensed(t.tensor))
test/convolutional/Convolution2D.js
+2 -2
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@@ -67,7 +67,7 @@ describe('convolutional layer: Convolution2D', function () {
it(title, function () {
console.log(`\n%c${title}`, styles.h3)
let testLayer = new layers.Convolution2D(nbFilter, nbRow, nbCol, attrs)
let testLayer = new layers.Convolution2D(Object.assign({ nbFilter, nbRow, nbCol }, attrs))
testLayer.setWeights(TEST_DATA[key].weights.map(w => new KerasJS.Tensor(w.data, w.shape)))
let t = new KerasJS.Tensor(TEST_DATA[key].input.data, TEST_DATA[key].input.shape)
console.log('%cin', styles.h4, stringifyCondensed(t.tensor))
@@ -101,7 +101,7 @@ describe('convolutional layer: Convolution2D', function () {
it(title, function () {
console.log(`\n%c${title}`, styles.h3)
let testLayer = new layers.Convolution2D(nbFilter, nbRow, nbCol, attrs)
let testLayer = new layers.Convolution2D(Object.assign({ nbFilter, nbRow, nbCol }, attrs))
testLayer.setWeights(TEST_DATA[key].weights.map(w => new KerasJS.Tensor(w.data, w.shape)))
let t = new KerasJS.Tensor(TEST_DATA[key].input.data, TEST_DATA[key].input.shape, { useWeblas: true })
console.log('%cin', styles.h4, stringifyCondensed(t.tensor))
test/convolutional/Convolution3D.js
+2 -2
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@@ -57,7 +57,7 @@ describe('convolutional layer: Convolution3D', function () {
it(title, function () {
console.log(`\n%c${title}`, styles.h3)
let testLayer = new layers.Convolution3D(nbFilter, kernelDim1, kernelDim2, kernelDim3, attrs)
let testLayer = new layers.Convolution3D(Object.assign({ nbFilter, kernelDim1, kernelDim2, kernelDim3 }, attrs))
testLayer.setWeights(TEST_DATA[key].weights.map(w => new KerasJS.Tensor(w.data, w.shape)))
let t = new KerasJS.Tensor(TEST_DATA[key].input.data, TEST_DATA[key].input.shape)
console.log('%cin', styles.h4, stringifyCondensed(t.tensor))
@@ -91,7 +91,7 @@ describe('convolutional layer: Convolution3D', function () {
it(title, function () {
console.log(`\n%c${title}`, styles.h3)
let testLayer = new layers.Convolution3D(nbFilter, kernelDim1, kernelDim2, kernelDim3, attrs)
let testLayer = new layers.Convolution3D(Object.assign({ nbFilter, kernelDim1, kernelDim2, kernelDim3 }, attrs))
testLayer.setWeights(TEST_DATA[key].weights.map(w => new KerasJS.Tensor(w.data, w.shape)))
let t = new KerasJS.Tensor(TEST_DATA[key].input.data, TEST_DATA[key].input.shape, { useWeblas: true })
console.log('%cin', styles.h4, stringifyCondensed(t.tensor))
test/convolutional/Deconvolution2D.js
+2 -2
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@@ -69,7 +69,7 @@ describe('convolutional layer: Deconvolution2D', function () {
it(title, function () {
console.log(`\n%c${title}`, styles.h3)
let testLayer = new layers.Deconvolution2D(nbFilter, nbRow, nbCol, outputShape, attrs)
let testLayer = new layers.Deconvolution2D(Object.assign({ nbFilter, nbRow, nbCol, outputShape }, attrs))
testLayer.setWeights(TEST_DATA[key].weights.map(w => new KerasJS.Tensor(w.data, w.shape)))
let t = new KerasJS.Tensor(TEST_DATA[key].input.data, TEST_DATA[key].input.shape)
console.log('%cin', styles.h4, stringifyCondensed(t.tensor))
@@ -104,7 +104,7 @@ describe('convolutional layer: Deconvolution2D', function () {
it(title, function () {
console.log(`\n%c${title}`, styles.h3)
let testLayer = new layers.Deconvolution2D(nbFilter, nbRow, nbCol, outputShape, attrs)
let testLayer = new layers.Deconvolution2D(Object.assign({ nbFilter, nbRow, nbCol, outputShape }, attrs))
testLayer.setWeights(TEST_DATA[key].weights.map(w => new KerasJS.Tensor(w.data, w.shape)))
let t = new KerasJS.Tensor(TEST_DATA[key].input.data, TEST_DATA[key].input.shape, { useWeblas: true })
console.log('%cin', styles.h4, stringifyCondensed(t.tensor))
test/convolutional/SeparableConvolution2D.js
+2 -2
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@@ -67,7 +67,7 @@ describe('convolutional layer: SeparableConvolution2D', function () {
it(title, function () {
console.log(`\n%c${title}`, styles.h3)
let testLayer = new layers.SeparableConvolution2D(nbFilter, nbRow, nbCol, attrs)
let testLayer = new layers.SeparableConvolution2D(Object.assign({ nbFilter, nbRow, nbCol }, attrs))
testLayer.setWeights(TEST_DATA[key].weights.map(w => new KerasJS.Tensor(w.data, w.shape)))
let t = new KerasJS.Tensor(TEST_DATA[key].input.data, TEST_DATA[key].input.shape)
console.log('%cin', styles.h4, stringifyCondensed(t.tensor))
@@ -101,7 +101,7 @@ describe('convolutional layer: SeparableConvolution2D', function () {
it(title, function () {
console.log(`\n%c${title}`, styles.h3)
let testLayer = new layers.SeparableConvolution2D(nbFilter, nbRow, nbCol, attrs)
let testLayer = new layers.SeparableConvolution2D(Object.assign({ nbFilter, nbRow, nbCol }, attrs))
testLayer.setWeights(TEST_DATA[key].weights.map(w => new KerasJS.Tensor(w.data, w.shape)))
let t = new KerasJS.Tensor(TEST_DATA[key].input.data, TEST_DATA[key].input.shape, { useWeblas: true })
console.log('%cin', styles.h4, stringifyCondensed(t.tensor))
test/convolutional/UpSampling1D.js
+2 -2
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@@ -15,7 +15,7 @@ describe('convolutional layer: UpSampling1D', function () {
it(`[convolutional.UpSampling1D.0] length 2 upsampling on 3x5 input`, function () {
const key = `convolutional.UpSampling1D.0`
console.log(`\n%c[${key}] length 2 upsampling on 3x5 input`, styles.h3)
let testLayer = new layers.UpSampling1D(2)
let testLayer = new layers.UpSampling1D({ length: 2 })
let t = new KerasJS.Tensor(TEST_DATA[key].input.data, TEST_DATA[key].input.shape)
console.log('%cin', styles.h4, stringifyCondensed(t.tensor))
const startTime = performance.now()
@@ -32,7 +32,7 @@ describe('convolutional layer: UpSampling1D', function () {
it(`[convolutional.UpSampling1D.1] length 3 upsampling on 4x4 input`, function () {
const key = `convolutional.UpSampling1D.1`
console.log(`\n%c[${key}] length 3 upsampling on 4x4 input`, styles.h3)
let testLayer = new layers.UpSampling1D(3)
let testLayer = new layers.UpSampling1D({ length: 3 })
let t = new KerasJS.Tensor(TEST_DATA[key].input.data, TEST_DATA[key].input.shape)
console.log('%cin', styles.h4, stringifyCondensed(t.tensor))
const startTime = performance.now()
test/convolutional/UpSampling2D.js
+4 -4
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@@ -15,7 +15,7 @@ describe('convolutional layer: UpSampling2D', function () {
it(`[convolutional.UpSampling2D.0] size 2x2 upsampling on 3x3x3 input, dimOrdering=tf`, function () {
const key = `convolutional.UpSampling2D.0`
console.log(`\n%c[${key}] size 2x2 upsampling on 3x3x3 input, dimOrdering=tf`, styles.h3)
let testLayer = new layers.UpSampling2D([2, 2], { dimOrdering: 'tf' })
let testLayer = new layers.UpSampling2D({ size: [2, 2], dimOrdering: 'tf' })
let t = new KerasJS.Tensor(TEST_DATA[key].input.data, TEST_DATA[key].input.shape)
console.log('%cin', styles.h4, stringifyCondensed(t.tensor))
const startTime = performance.now()
@@ -32,7 +32,7 @@ describe('convolutional layer: UpSampling2D', function () {
it(`[convolutional.UpSampling2D.1] size 2x2 upsampling on 3x3x3 input, dimOrdering=th`, function () {
const key = `convolutional.UpSampling2D.1`
console.log(`\n%c[${key}] size 2x2 upsampling on 3x3x3 input, dimOrdering=th`, styles.h3)
let testLayer = new layers.UpSampling2D([2, 2], { dimOrdering: 'th' })
let testLayer = new layers.UpSampling2D({ size: [2, 2], dimOrdering: 'th' })
let t = new KerasJS.Tensor(TEST_DATA[key].input.data, TEST_DATA[key].input.shape)
console.log('%cin', styles.h4, stringifyCondensed(t.tensor))
const startTime = performance.now()
@@ -49,7 +49,7 @@ describe('convolutional layer: UpSampling2D', function () {
it(`[convolutional.UpSampling2D.2] size 3x2 upsampling on 4x2x2 input, dimOrdering=tf`, function () {
const key = `convolutional.UpSampling2D.2`
console.log(`\n%c[${key}] size 3x2 upsampling on 4x2x2 input, dimOrdering=tf`, styles.h3)
let testLayer = new layers.UpSampling2D([3, 2], { dimOrdering: 'tf' })
let testLayer = new layers.UpSampling2D({ size: [3, 2], dimOrdering: 'tf' })
let t = new KerasJS.Tensor(TEST_DATA[key].input.data, TEST_DATA[key].input.shape)
console.log('%cin', styles.h4, stringifyCondensed(t.tensor))
const startTime = performance.now()
@@ -66,7 +66,7 @@ describe('convolutional layer: UpSampling2D', function () {
it(`[convolutional.UpSampling2D.3] size 1x3 upsampling on 4x3x2 input, dimOrdering=th`, function () {
const key = `convolutional.UpSampling2D.3`
console.log(`\n%c[${key}] size 1x3 upsampling on 4x3x2 input, dimOrdering=th`, styles.h3)
let testLayer = new layers.UpSampling2D([1, 3], { dimOrdering: 'th' })
let testLayer = new layers.UpSampling2D({ size: [1, 3], dimOrdering: 'th' })
let t = new KerasJS.Tensor(TEST_DATA[key].input.data, TEST_DATA[key].input.shape)
console.log('%cin', styles.h4, stringifyCondensed(t.tensor))
const startTime = performance.now()
test/convolutional/UpSampling3D.js
+4 -4
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@@ -15,7 +15,7 @@ describe('convolutional layer: UpSampling3D', function () {
it(`[convolutional.UpSampling3D.0] size 2x2x2 upsampling on 2x2x2x3 input, dimOrdering=tf`, function () {
const key = `convolutional.UpSampling3D.0`
console.log(`\n%c[${key}] size 2x2x2 upsampling on 2x2x2x3 input, dimOrdering=tf`, styles.h3)
let testLayer = new layers.UpSampling3D([2, 2, 2], { dimOrdering: 'tf' })
let testLayer = new layers.UpSampling3D({ size: [2, 2, 2], dimOrdering: 'tf' })
let t = new KerasJS.Tensor(TEST_DATA[key].input.data, TEST_DATA[key].input.shape)
console.log('%cin', styles.h4, stringifyCondensed(t.tensor))
const startTime = performance.now()
@@ -32,7 +32,7 @@ describe('convolutional layer: UpSampling3D', function () {
it(`[convolutional.UpSampling3D.1] size 2x2x2 upsampling on 2x2x2x3 input, dimOrdering=th`, function () {
const key = `convolutional.UpSampling3D.1`
console.log(`\n%c[${key}] size 2x2x2 upsampling on 2x2x2x3 input, dimOrdering=th`, styles.h3)
let testLayer = new layers.UpSampling3D([2, 2, 2], { dimOrdering: 'th' })
let testLayer = new layers.UpSampling3D({ size: [2, 2, 2], dimOrdering: 'th' })
let t = new KerasJS.Tensor(TEST_DATA[key].input.data, TEST_DATA[key].input.shape)
console.log('%cin', styles.h4, stringifyCondensed(t.tensor))
const startTime = performance.now()
@@ -49,7 +49,7 @@ describe('convolutional layer: UpSampling3D', function () {
it(`[convolutional.UpSampling3D.2] size 1x3x2 upsampling on 2x1x3x2 input, dimOrdering=tf`, function () {
const key = `convolutional.UpSampling3D.2`
console.log(`\n%c[${key}] size 1x3x2 upsampling on 2x1x3x2 input, dimOrdering=tf`, styles.h3)
let testLayer = new layers.UpSampling3D([1, 3, 2], { dimOrdering: 'tf' })
let testLayer = new layers.UpSampling3D({ size: [1, 3, 2], dimOrdering: 'tf' })
let t = new KerasJS.Tensor(TEST_DATA[key].input.data, TEST_DATA[key].input.shape)
console.log('%cin', styles.h4, stringifyCondensed(t.tensor))
const startTime = performance.now()
@@ -66,7 +66,7 @@ describe('convolutional layer: UpSampling3D', function () {
it(`[convolutional.UpSampling3D.3] 2x1x2 upsampling on 2x1x3x3 input, dimOrdering=th`, function () {
const key = `convolutional.UpSampling3D.3`
console.log(`\n%c[${key}] 2x1x2 upsampling on 2x1x3x3 input, dimOrdering=th`, styles.h3)
let testLayer = new layers.UpSampling3D([2, 1, 2], { dimOrdering: 'th' })
let testLayer = new layers.UpSampling3D({ size: [2, 1, 2], dimOrdering: 'th' })
let t = new KerasJS.Tensor(TEST_DATA[key].input.data, TEST_DATA[key].input.shape)
console.log('%cin', styles.h4, stringifyCondensed(t.tensor))
const startTime = performance.now()
test/convolutional/ZeroPadding1D.js
+2 -2
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@@ -15,7 +15,7 @@ describe('convolutional layer: ZeroPadding1D', function () {
it(`[convolutional.ZeroPadding1D.0] padding 1 on 3x5 input`, function () {
const key = `convolutional.ZeroPadding1D.0`
console.log(`\n%c[${key}] padding 1 on 3x5 input`, styles.h3)
let testLayer = new layers.ZeroPadding1D(1)
let testLayer = new layers.ZeroPadding1D({ padding: 1 })
let t = new KerasJS.Tensor(TEST_DATA[key].input.data, TEST_DATA[key].input.shape)
console.log('%cin', styles.h4, stringifyCondensed(t.tensor))
const startTime = performance.now()
@@ -32,7 +32,7 @@ describe('convolutional layer: ZeroPadding1D', function () {
it(`[convolutional.ZeroPadding1D.1] padding 3 on 4x4 input`, function () {
const key = `convolutional.ZeroPadding1D.1`
console.log(`\n%c[${key}] padding 3 on 4x4 input`, styles.h3)
let testLayer = new layers.ZeroPadding1D(3)
let testLayer = new layers.ZeroPadding1D({ padding: 3 })
let t = new KerasJS.Tensor(TEST_DATA[key].input.data, TEST_DATA[key].input.shape)
console.log('%cin', styles.h4, stringifyCondensed(t.tensor))
const startTime = performance.now()
test/convolutional/ZeroPadding2D.js
+4 -4
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@@ -15,7 +15,7 @@ describe('convolutional layer: ZeroPadding2D', function () {
it(`[convolutional.ZeroPadding2D.0] padding 1,1 on 3x5x2 input, dimOrdering=tf`, function () {
const key = `convolutional.ZeroPadding2D.0`
console.log(`\n%c[${key}] padding 1,1 on 3x5x2 input, dimOrdering=tf`, styles.h3)
let testLayer = new layers.ZeroPadding2D([1, 1], { dimOrdering: 'tf' })
let testLayer = new layers.ZeroPadding2D({ padding: [1, 1], dimOrdering: 'tf' })
let t = new KerasJS.Tensor(TEST_DATA[key].input.data, TEST_DATA[key].input.shape)
console.log('%cin', styles.h4, stringifyCondensed(t.tensor))
const startTime = performance.now()
@@ -32,7 +32,7 @@ describe('convolutional layer: ZeroPadding2D', function () {
it(`[convolutional.ZeroPadding2D.1] padding 1,1 on 3x5x2 input, dimOrdering=th`, function () {
const key = `convolutional.ZeroPadding2D.1`
console.log(`\n%c[${key}] padding 1,1 on 3x5x2 input, dimOrdering=th`, styles.h3)
let testLayer = new layers.ZeroPadding2D([1, 1], { dimOrdering: 'th' })
let testLayer = new layers.ZeroPadding2D({ padding: [1, 1], dimOrdering: 'th' })
let t = new KerasJS.Tensor(TEST_DATA[key].input.data, TEST_DATA[key].input.shape)
console.log('%cin', styles.h4, stringifyCondensed(t.tensor))
const startTime = performance.now()
@@ -49,7 +49,7 @@ describe('convolutional layer: ZeroPadding2D', function () {
it(`[convolutional.ZeroPadding2D.2] padding 3,2 on 2x6x4 input, dimOrdering=tf`, function () {
const key = `convolutional.ZeroPadding2D.2`
console.log(`\n%c[${key}] padding 3,2 on 2x6x4 input, dimOrdering=tf`, styles.h3)
let testLayer = new layers.ZeroPadding2D([3, 2], { dimOrdering: 'tf' })
let testLayer = new layers.ZeroPadding2D({ padding: [3, 2], dimOrdering: 'tf' })
let t = new KerasJS.Tensor(TEST_DATA[key].input.data, TEST_DATA[key].input.shape)
console.log('%cin', styles.h4, stringifyCondensed(t.tensor))
const startTime = performance.now()
@@ -66,7 +66,7 @@ describe('convolutional layer: ZeroPadding2D', function () {
it(`[convolutional.ZeroPadding2D.3] padding 3,2 on 2x6x4 input, dimOrdering=th`, function () {
const key = `convolutional.ZeroPadding2D.3`
console.log(`\n%c[${key}] padding 3,2 on 2x6x4 input, dimOrdering=th`, styles.h3)
let testLayer = new layers.ZeroPadding2D([3, 2], { dimOrdering: 'th' })
let testLayer = new layers.ZeroPadding2D({ padding: [3, 2], dimOrdering: 'th' })
let t = new KerasJS.Tensor(TEST_DATA[key].input.data, TEST_DATA[key].input.shape)
console.log('%cin', styles.h4, stringifyCondensed(t.tensor))
const startTime = performance.now()
test/convolutional/ZeroPadding3D.js
+4 -4
View File
@@ -15,7 +15,7 @@ describe('convolutional layer: ZeroPadding3D', function () {
it(`[convolutional.ZeroPadding3D.0] padding 1,1,1 on 3x5x2x2 input, dimOrdering=tf`, function () {
const key = `convolutional.ZeroPadding3D.0`
console.log(`\n%c[${key}] padding 1,1,1 on 3x5x2x2 input, dimOrdering=tf`, styles.h3)
let testLayer = new layers.ZeroPadding3D([1, 1, 1], { dimOrdering: 'tf' })
let testLayer = new layers.ZeroPadding3D({ padding: [1, 1, 1], dimOrdering: 'tf' })
let t = new KerasJS.Tensor(TEST_DATA[key].input.data, TEST_DATA[key].input.shape)
console.log('%cin', styles.h4, stringifyCondensed(t.tensor))
const startTime = performance.now()
@@ -32,7 +32,7 @@ describe('convolutional layer: ZeroPadding3D', function () {
it(`[convolutional.ZeroPadding3D.1] padding 1,1,1 on 3x5x2x2 input, dimOrdering=th`, function () {
const key = `convolutional.ZeroPadding3D.1`
console.log(`\n%c[${key}] padding 1,1,1 on 3x5x2x2 input, dimOrdering=th`, styles.h3)
let testLayer = new layers.ZeroPadding3D([1, 1, 1], { dimOrdering: 'th' })
let testLayer = new layers.ZeroPadding3D({ padding: [1, 1, 1], dimOrdering: 'th' })
let t = new KerasJS.Tensor(TEST_DATA[key].input.data, TEST_DATA[key].input.shape)
console.log('%cin', styles.h4, stringifyCondensed(t.tensor))
const startTime = performance.now()
@@ -49,7 +49,7 @@ describe('convolutional layer: ZeroPadding3D', function () {
it(`[convolutional.ZeroPadding3D.2] padding 3,2,2 on 3x2x1x4 input, dimOrdering=tf`, function () {
const key = `convolutional.ZeroPadding3D.2`
console.log(`\n%c[${key}] padding 3,2,2 on 3x2x1x4 input, dimOrdering=tf`, styles.h3)
let testLayer = new layers.ZeroPadding3D([3, 2, 2], { dimOrdering: 'tf' })
let testLayer = new layers.ZeroPadding3D({ padding: [3, 2, 2], dimOrdering: 'tf' })
let t = new KerasJS.Tensor(TEST_DATA[key].input.data, TEST_DATA[key].input.shape)
console.log('%cin', styles.h4, stringifyCondensed(t.tensor))
const startTime = performance.now()
@@ -66,7 +66,7 @@ describe('convolutional layer: ZeroPadding3D', function () {
it(`[convolutional.ZeroPadding3D.3] padding 3,2,2 on 3x2x1x4 input, dimOrdering=th`, function () {
const key = `convolutional.ZeroPadding3D.3`
console.log(`\n%c[${key}] padding 3,2,2 on 3x2x1x4 input, dimOrdering=th`, styles.h3)
let testLayer = new layers.ZeroPadding3D([3, 2, 2], { dimOrdering: 'th' })
let testLayer = new layers.ZeroPadding3D({ padding: [3, 2, 2], dimOrdering: 'th' })
let t = new KerasJS.Tensor(TEST_DATA[key].input.data, TEST_DATA[key].input.shape)
console.log('%cin', styles.h4, stringifyCondensed(t.tensor))
const startTime = performance.now()