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move all layer params into attrs object

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This commit is contained in:
Leon Chen
2016-09-18 23:20:59 -04:00
parent b1af2a7751
commit fd20f1b7b1
47 changed files with 285 additions and 162 deletions
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test/core/Activation.js
+4 -4
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@@ -15,12 +15,12 @@ describe('core layer: Activation', function () {
it('[core.Activation.0] should produce expected values for tanh activation following Dense layer', function () {
const key = 'core.Activation.0'
console.log(`\n%c[${key}] test 1 (tanh)`, styles.h3)
let testLayer1 = new layers.Dense(2)
let testLayer1 = new layers.Dense({ outputDim: 2 })
testLayer1.setWeights(TEST_DATA[key].weights.map(w => new KerasJS.Tensor(w.data, w.shape)))
let t = new KerasJS.Tensor(TEST_DATA[key].input.data, TEST_DATA[key].input.shape)
t = testLayer1.call(t)
console.log('%cin', styles.h4, stringifyCondensed(t.tensor))
let testLayer2 = new layers.Activation('tanh')
let testLayer2 = new layers.Activation({ activation: 'tanh' })
const startTime = performance.now()
t = testLayer2.call(t)
const endTime = performance.now()
@@ -35,12 +35,12 @@ describe('core layer: Activation', function () {
it('[core.Activation.1] should produce expected values for hardSigmoid activation following Dense layer', function () {
const key = 'core.Activation.1'
console.log(`\n%c[${key}] test 2 (hardSigmoid)`, styles.h3)
let testLayer1 = new layers.Dense(2)
let testLayer1 = new layers.Dense({ outputDim: 2 })
testLayer1.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)
t = testLayer1.call(t)
console.log('%cin', styles.h4, stringifyCondensed(t.tensor))
let testLayer2 = new layers.Activation('hardSigmoid')
let testLayer2 = new layers.Activation({ activation: 'hardSigmoid' })
const startTime = performance.now()
t = testLayer2.call(t)
const endTime = performance.now()
test/core/Dense.js
+6 -6
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@@ -24,7 +24,7 @@ describe('core layer: Dense', function () {
it('[core.Dense.0] [CPU] should produce expected values', function () {
const key = 'core.Dense.0'
console.log(`\n%c[${key}] [CPU] test 1`, styles.h3)
let testLayer = new layers.Dense(2)
let testLayer = new layers.Dense({ outputDim: 2 })
testLayer.setWeights(TEST_DATA[key].weights.map(w => new KerasJS.Tensor(w.data, w.shape)))
let t = new KerasJS.Tensor(TEST_DATA[key].input.data, TEST_DATA[key].input.shape)
console.log('%cin', styles.h4, stringifyCondensed(t.tensor))
@@ -42,7 +42,7 @@ describe('core layer: Dense', function () {
it('[core.Dense.1] [CPU] should produce expected values, with sigmoid activation function', function () {
const key = 'core.Dense.1'
console.log(`\n%c[${key}] [CPU] test 2 (with sigmoid activation)`, styles.h3)
let testLayer = new layers.Dense(2, { activation: 'sigmoid' })
let testLayer = new layers.Dense({ outputDim: 2, activation: 'sigmoid' })
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))
@@ -60,7 +60,7 @@ describe('core layer: Dense', function () {
it('[core.Dense.2] [CPU] should produce expected values, with softplus activation function and no bias', function () {
const key = 'core.Dense.2'
console.log(`\n%c[${key}] [CPU] test 3 (with softplus activation and no bias)`, styles.h3)
let testLayer = new layers.Dense(2, { activation: 'softplus', bias: false })
let testLayer = new layers.Dense({ outputDim: 2, activation: 'softplus', bias: false })
testLayer.setWeights(TEST_DATA[key].weights.map(w => new KerasJS.Tensor(w.data, w.shape)))
let t = new KerasJS.Tensor(TEST_DATA[key].input.data, TEST_DATA[key].input.shape)
console.log('%cin', styles.h4, stringifyCondensed(t.tensor))
@@ -88,7 +88,7 @@ describe('core layer: Dense', function () {
it('[core.Dense.3] [GPU] should produce expected values', function () {
const key = 'core.Dense.3'
console.log(`\n%c[${key}] [GPU] test 1`, styles.h3)
let testLayer = new layers.Dense(2)
let testLayer = new layers.Dense({ outputDim: 2 })
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))
@@ -106,7 +106,7 @@ describe('core layer: Dense', function () {
it('[core.Dense.4] [GPU] should produce expected values, with sigmoid activation function', function () {
const key = 'core.Dense.4'
console.log(`\n%c[${key}] [GPU] test 2 (with sigmoid activation)`, styles.h3)
let testLayer = new layers.Dense(2, { activation: 'sigmoid' })
let testLayer = new layers.Dense({ outputDim: 2, activation: 'sigmoid' })
testLayer.setWeights(TEST_DATA[key].weights.map(w => new KerasJS.Tensor(w.data, w.shape)))
let t = new KerasJS.Tensor(TEST_DATA[key].input.data, TEST_DATA[key].input.shape, { useWeblas: true })
console.log('%cin', styles.h4, stringifyCondensed(t.tensor))
@@ -124,7 +124,7 @@ describe('core layer: Dense', function () {
it('[core.Dense.5] [GPU] should produce expected values, with softplus activation function and no bias', function () {
const key = 'core.Dense.5'
console.log(`\n%c[${key}] [GPU] test 3 (with softplus activation and no bias)`, styles.h3)
let testLayer = new layers.Dense(2, { activation: 'softplus', bias: false })
let testLayer = new layers.Dense({ outputDim: 2, activation: 'softplus', bias: false })
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/core/Dropout.js
+2 -2
View File
@@ -15,12 +15,12 @@ describe('core layer: Dropout', function () {
it('[core.Dropout.0] should just pass through tensor during test time', function () {
const key = 'core.Dropout.0'
console.log(`\n%c[${key}] should pass through`, styles.h3)
let testLayer1 = new layers.Dense(2)
let testLayer1 = new layers.Dense({ outputDim: 2 })
testLayer1.setWeights(TEST_DATA[key].weights.map(w => new KerasJS.Tensor(w.data, w.shape)))
let t = new KerasJS.Tensor(TEST_DATA[key].input.data, TEST_DATA[key].input.shape)
t = testLayer1.call(t)
console.log('%cin', styles.h4, stringifyCondensed(t.tensor))
let testLayer2 = new layers.Dropout(0.5)
let testLayer2 = new layers.Dropout({ p: 0.5 })
const startTime = performance.now()
t = testLayer2.call(t)
const endTime = performance.now()
test/core/MaxoutDense.js
+2 -2
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@@ -15,7 +15,7 @@ describe('core layer: MaxoutDense', function () {
it('[core.MaxoutDense.0] should produce expected values, nbFeature=4, bias=true', function () {
const key = 'core.MaxoutDense.0'
console.log(`\n%c[${key}] nbFeature=4, bias=true`, styles.h3)
let testLayer = new layers.MaxoutDense(3)
let testLayer = new layers.MaxoutDense({ outputDim: 3 })
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))
@@ -33,7 +33,7 @@ describe('core layer: MaxoutDense', function () {
it('[core.MaxoutDense.1] should produce expected values, nbFeature=7, bias=false', function () {
const key = 'core.MaxoutDense.1'
console.log(`\n%c[${key}] nbFeature=7, bias=false`, styles.h3)
let testLayer = new layers.MaxoutDense(3, { bias: false })
let testLayer = new layers.MaxoutDense({ outputDim: 3, bias: false })
testLayer.setWeights(TEST_DATA[key].weights.map(w => new KerasJS.Tensor(w.data, w.shape)))
let t = new KerasJS.Tensor(TEST_DATA[key].input.data, TEST_DATA[key].input.shape)
console.log('%cin', styles.h4, stringifyCondensed(t.tensor))
test/core/Merge.js
+42 -42
View File
@@ -24,8 +24,8 @@ describe('core layer: Merge', function () {
it('[core.Merge.0] should produce expected values in sum mode', function () {
const key = 'core.Merge.0'
console.log(`\n%c[${key}] mode: sum`, styles.h3)
let testLayer1a = new layers.Dense(2)
let testLayer1b = new layers.Dense(2)
let testLayer1a = new layers.Dense({ outputDim: 2 })
let testLayer1b = new layers.Dense({ outputDim: 2 })
let testLayer2 = new layers.Merge({ mode: 'sum' })
testLayer1a.setWeights(TEST_DATA[key].weights.slice(0, 2).map(w => new KerasJS.Tensor(w.data, w.shape)))
testLayer1b.setWeights(TEST_DATA[key].weights.slice(2, 4).map(w => new KerasJS.Tensor(w.data, w.shape)))
@@ -59,8 +59,8 @@ describe('core layer: Merge', function () {
it('[core.Merge.1] should produce expected values in mul mode', function () {
const key = 'core.Merge.1'
console.log(`\n%c[${key}] mode: mul`, styles.h3)
let testLayer1a = new layers.Dense(2)
let testLayer1b = new layers.Dense(2)
let testLayer1a = new layers.Dense({ outputDim: 2 })
let testLayer1b = new layers.Dense({ outputDim: 2 })
let testLayer2 = new layers.Merge({ mode: 'mul' })
testLayer1a.setWeights(TEST_DATA[key].weights.slice(0, 2).map(w => new KerasJS.Tensor(w.data, w.shape)))
testLayer1b.setWeights(TEST_DATA[key].weights.slice(2, 4).map(w => new KerasJS.Tensor(w.data, w.shape)))
@@ -94,8 +94,8 @@ describe('core layer: Merge', function () {
it('[core.Merge.2] should produce expected values in ave mode', function () {
const key = 'core.Merge.2'
console.log(`\n%c[${key}] mode: ave`, styles.h3)
let testLayer1a = new layers.Dense(2)
let testLayer1b = new layers.Dense(2)
let testLayer1a = new layers.Dense({ outputDim: 2 })
let testLayer1b = new layers.Dense({ outputDim: 2 })
let testLayer2 = new layers.Merge({ mode: 'ave' })
testLayer1a.setWeights(TEST_DATA[key].weights.slice(0, 2).map(w => new KerasJS.Tensor(w.data, w.shape)))
testLayer1b.setWeights(TEST_DATA[key].weights.slice(2, 4).map(w => new KerasJS.Tensor(w.data, w.shape)))
@@ -129,8 +129,8 @@ describe('core layer: Merge', function () {
it('[core.Merge.3] should produce expected values in max mode', function () {
const key = 'core.Merge.3'
console.log(`\n%c[${key}] mode: max`, styles.h3)
let testLayer1a = new layers.Dense(2)
let testLayer1b = new layers.Dense(2)
let testLayer1a = new layers.Dense({ outputDim: 2 })
let testLayer1b = new layers.Dense({ outputDim: 2 })
let testLayer2 = new layers.Merge({ mode: 'max' })
testLayer1a.setWeights(TEST_DATA[key].weights.slice(0, 2).map(w => new KerasJS.Tensor(w.data, w.shape)))
testLayer1b.setWeights(TEST_DATA[key].weights.slice(2, 4).map(w => new KerasJS.Tensor(w.data, w.shape)))
@@ -164,8 +164,8 @@ describe('core layer: Merge', function () {
it('[core.Merge.4] should produce expected values in concat mode (1D)', function () {
const key = 'core.Merge.4'
console.log(`\n%c[${key}] mode: concat (1D)`, styles.h3)
let testLayer1a = new layers.Dense(2)
let testLayer1b = new layers.Dense(2)
let testLayer1a = new layers.Dense({ outputDim: 2 })
let testLayer1b = new layers.Dense({ outputDim: 2 })
let testLayer2 = new layers.Merge({ mode: 'concat', concatAxis: -1 })
testLayer1a.setWeights(TEST_DATA[key].weights.slice(0, 2).map(w => new KerasJS.Tensor(w.data, w.shape)))
testLayer1b.setWeights(TEST_DATA[key].weights.slice(2, 4).map(w => new KerasJS.Tensor(w.data, w.shape)))
@@ -189,10 +189,10 @@ describe('core layer: Merge', function () {
it('[core.Merge.5] should produce expected values in concat mode (2D, concatAxis=-1)', function () {
const key = 'core.Merge.5'
console.log(`\n%c[${key}] mode: concat (2D, concatAxis=-1)`, styles.h3)
let testLayer1a = new layers.Dense(2)
let testLayer2a = new layers.RepeatVector(3)
let testLayer1b = new layers.Dense(2)
let testLayer2b = new layers.RepeatVector(3)
let testLayer1a = new layers.Dense({ outputDim: 2 })
let testLayer2a = new layers.RepeatVector({ n: 3 })
let testLayer1b = new layers.Dense({ outputDim: 2 })
let testLayer2b = new layers.RepeatVector({ n: 3 })
let testLayer3 = new layers.Merge({ mode: 'concat', concatAxis: -1 })
testLayer1a.setWeights(TEST_DATA[key].weights.slice(0, 2).map(w => new KerasJS.Tensor(w.data, w.shape)))
testLayer1b.setWeights(TEST_DATA[key].weights.slice(2, 4).map(w => new KerasJS.Tensor(w.data, w.shape)))
@@ -218,10 +218,10 @@ describe('core layer: Merge', function () {
it('[core.Merge.6] should produce expected values in concat mode (2D, concatAxis=-2)', function () {
const key = 'core.Merge.6'
console.log(`\n%c[${key}] mode: concat (2D, concatAxis=-2)`, styles.h3)
let testLayer1a = new layers.Dense(2)
let testLayer2a = new layers.RepeatVector(3)
let testLayer1b = new layers.Dense(2)
let testLayer2b = new layers.RepeatVector(3)
let testLayer1a = new layers.Dense({ outputDim: 2 })
let testLayer2a = new layers.RepeatVector({ n: 3 })
let testLayer1b = new layers.Dense({ outputDim: 2 })
let testLayer2b = new layers.RepeatVector({ n: 3 })
let testLayer3 = new layers.Merge({ mode: 'concat', concatAxis: -2 })
testLayer1a.setWeights(TEST_DATA[key].weights.slice(0, 2).map(w => new KerasJS.Tensor(w.data, w.shape)))
testLayer1b.setWeights(TEST_DATA[key].weights.slice(2, 4).map(w => new KerasJS.Tensor(w.data, w.shape)))
@@ -247,10 +247,10 @@ describe('core layer: Merge', function () {
it('[core.Merge.7] should produce expected values in concat mode (2D, concatAxis=1)', function () {
const key = 'core.Merge.7'
console.log(`\n%c[${key}] mode: concat (2D, concatAxis=1)`, styles.h3)
let testLayer1a = new layers.Dense(2)
let testLayer2a = new layers.RepeatVector(3)
let testLayer1b = new layers.Dense(2)
let testLayer2b = new layers.RepeatVector(3)
let testLayer1a = new layers.Dense({ outputDim: 2 })
let testLayer2a = new layers.RepeatVector({ n: 3 })
let testLayer1b = new layers.Dense({ outputDim: 2 })
let testLayer2b = new layers.RepeatVector({ n: 3 })
let testLayer3 = new layers.Merge({ mode: 'concat', concatAxis: 1 })
testLayer1a.setWeights(TEST_DATA[key].weights.slice(0, 2).map(w => new KerasJS.Tensor(w.data, w.shape)))
testLayer1b.setWeights(TEST_DATA[key].weights.slice(2, 4).map(w => new KerasJS.Tensor(w.data, w.shape)))
@@ -276,10 +276,10 @@ describe('core layer: Merge', function () {
it('[core.Merge.8] should produce expected values in concat mode (2D, concatAxis=2)', function () {
const key = 'core.Merge.8'
console.log(`\n%c[${key}] mode: concat (2D, concatAxis=2)`, styles.h3)
let testLayer1a = new layers.Dense(2)
let testLayer2a = new layers.RepeatVector(3)
let testLayer1b = new layers.Dense(2)
let testLayer2b = new layers.RepeatVector(3)
let testLayer1a = new layers.Dense({ outputDim: 2 })
let testLayer2a = new layers.RepeatVector({ n: 3 })
let testLayer1b = new layers.Dense({ outputDim: 2 })
let testLayer2b = new layers.RepeatVector({ n: 3 })
let testLayer3 = new layers.Merge({ mode: 'concat', concatAxis: 2 })
testLayer1a.setWeights(TEST_DATA[key].weights.slice(0, 2).map(w => new KerasJS.Tensor(w.data, w.shape)))
testLayer1b.setWeights(TEST_DATA[key].weights.slice(2, 4).map(w => new KerasJS.Tensor(w.data, w.shape)))
@@ -315,10 +315,10 @@ describe('core layer: Merge', function () {
it('[core.Merge.9] should produce expected values in dot mode (2D x 2D, dotAxes=1)', function () {
const key = 'core.Merge.9'
console.log(`\n%c[${key}] mode: dot (2D x 2D, dotAxes=1)`, styles.h3)
let testLayer1a = new layers.Dense(2)
let testLayer2a = new layers.RepeatVector(3)
let testLayer1b = new layers.Dense(2)
let testLayer2b = new layers.RepeatVector(3)
let testLayer1a = new layers.Dense({ outputDim: 2 })
let testLayer2a = new layers.RepeatVector({ n: 3 })
let testLayer1b = new layers.Dense({ outputDim: 2 })
let testLayer2b = new layers.RepeatVector({ n: 3 })
let testLayer3 = new layers.Merge({ mode: 'dot', dotAxes: 1 })
testLayer1a.setWeights(TEST_DATA[key].weights.slice(0, 2).map(w => new KerasJS.Tensor(w.data, w.shape)))
testLayer1b.setWeights(TEST_DATA[key].weights.slice(2, 4).map(w => new KerasJS.Tensor(w.data, w.shape)))
@@ -344,10 +344,10 @@ describe('core layer: Merge', function () {
it('[core.Merge.10] should produce expected values in dot mode (2D x 2D, dotAxes=2)', function () {
const key = 'core.Merge.10'
console.log(`\n%c[${key}] mode: dot (2D x 2D, dotAxes=2)`, styles.h3)
let testLayer1a = new layers.Dense(2)
let testLayer2a = new layers.RepeatVector(3)
let testLayer1b = new layers.Dense(2)
let testLayer2b = new layers.RepeatVector(3)
let testLayer1a = new layers.Dense({ outputDim: 2 })
let testLayer2a = new layers.RepeatVector({ n: 3 })
let testLayer1b = new layers.Dense({ outputDim: 2 })
let testLayer2b = new layers.RepeatVector({ n: 3 })
let testLayer3 = new layers.Merge({ mode: 'dot', dotAxes: 2 })
testLayer1a.setWeights(TEST_DATA[key].weights.slice(0, 2).map(w => new KerasJS.Tensor(w.data, w.shape)))
testLayer1b.setWeights(TEST_DATA[key].weights.slice(2, 4).map(w => new KerasJS.Tensor(w.data, w.shape)))
@@ -383,10 +383,10 @@ describe('core layer: Merge', function () {
it('[core.Merge.11] should produce expected values in cos mode (2D x 2D, dotAxes=1)', function () {
const key = 'core.Merge.11'
console.log(`\n%c[${key}] mode: cos (2D x 2D, dotAxes=1)`, styles.h3)
let testLayer1a = new layers.Dense(2)
let testLayer2a = new layers.RepeatVector(3)
let testLayer1b = new layers.Dense(2)
let testLayer2b = new layers.RepeatVector(3)
let testLayer1a = new layers.Dense({ outputDim: 2 })
let testLayer2a = new layers.RepeatVector({ n: 3 })
let testLayer1b = new layers.Dense({ outputDim: 2 })
let testLayer2b = new layers.RepeatVector({ n: 3 })
let testLayer3 = new layers.Merge({ mode: 'cos', dotAxes: 1 })
testLayer1a.setWeights(TEST_DATA[key].weights.slice(0, 2).map(w => new KerasJS.Tensor(w.data, w.shape)))
testLayer1b.setWeights(TEST_DATA[key].weights.slice(2, 4).map(w => new KerasJS.Tensor(w.data, w.shape)))
@@ -412,10 +412,10 @@ describe('core layer: Merge', function () {
it('[core.Merge.12] should produce expected values in cos mode (2D x 2D, dotAxes=2)', function () {
const key = 'core.Merge.12'
console.log(`\n%c[${key}] mode: cos (2D x 2D, dotAxes=2)`, styles.h3)
let testLayer1a = new layers.Dense(2)
let testLayer2a = new layers.RepeatVector(3)
let testLayer1b = new layers.Dense(2)
let testLayer2b = new layers.RepeatVector(3)
let testLayer1a = new layers.Dense({ outputDim: 2 })
let testLayer2a = new layers.RepeatVector({ n: 3 })
let testLayer1b = new layers.Dense({ outputDim: 2 })
let testLayer2b = new layers.RepeatVector({ n: 3 })
let testLayer3 = new layers.Merge({ mode: 'cos', dotAxes: 2 })
testLayer1a.setWeights(TEST_DATA[key].weights.slice(0, 2).map(w => new KerasJS.Tensor(w.data, w.shape)))
testLayer1b.setWeights(TEST_DATA[key].weights.slice(2, 4).map(w => new KerasJS.Tensor(w.data, w.shape)))
test/core/Permute.js
+2 -2
View File
@@ -15,7 +15,7 @@ describe('core layer: Permute', function () {
it('[core.Permute.0] should be able to go from shape [3, 2] -> [2, 3]', function () {
const key = 'core.Permute.0'
console.log(`\n%c[${key}] shape [3, 2] -> [2, 3]`, styles.h3)
let testLayer = new layers.Permute([2, 1])
let testLayer = new layers.Permute({ dims: [2, 1] })
let t = new KerasJS.Tensor(TEST_DATA[key].input.data, TEST_DATA[key].input.shape)
console.log('%cin', styles.h4, stringifyCondensed(t.tensor))
const startTime = performance.now()
@@ -32,7 +32,7 @@ describe('core layer: Permute', function () {
it('[core.Permute.1] should be able to go from shape [2, 3, 4] -> [4, 3, 2]', function () {
const key = 'core.Permute.1'
console.log(`\n%c[${key}] shape [2, 3, 4] -> [4, 3, 2]`, styles.h3)
let testLayer = new layers.Permute([3, 2, 1])
let testLayer = new layers.Permute({ dims: [3, 2, 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()
test/core/RepeatVector.js
+1 -1
View File
@@ -15,7 +15,7 @@ describe('core layer: RepeatVector', function () {
it('[core.RepeatVector.0] should be able to go from shape [6] -> [7, 6]', function () {
const key = 'core.RepeatVector.0'
console.log(`\n%c[${key}] repeat vector, shape [6] -> [7, 6]`, styles.h3)
let testLayer = new layers.RepeatVector(7)
let testLayer = new layers.RepeatVector({ n: 7 })
let t = new KerasJS.Tensor(TEST_DATA[key].input.data, TEST_DATA[key].input.shape)
console.log('%cin', styles.h4, stringifyCondensed(t.tensor))
const startTime = performance.now()
test/core/Reshape.js
+3 -3
View File
@@ -15,7 +15,7 @@ describe('core layer: Reshape', function () {
it('[core.Reshape.0] should be able to go from shape [6] -> [2, 3]', function () {
const key = 'core.Reshape.0'
console.log(`\n%c[${key}] shape [6] -> [2, 3]`, styles.h3)
let testLayer = new layers.Reshape([2, 3])
let testLayer = new layers.Reshape({ shape: [2, 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()
@@ -32,7 +32,7 @@ describe('core layer: Reshape', function () {
it('[core.Reshape.1] should be able to go from shape [3, 2] -> [6]', function () {
const key = 'core.Reshape.1'
console.log(`\n%c[${key}] shape [3, 2] -> [6]`, styles.h3)
let testLayer = new layers.Reshape([6])
let testLayer = new layers.Reshape({ shape: [6] })
let t = new KerasJS.Tensor(TEST_DATA[key].input.data, TEST_DATA[key].input.shape)
console.log('%cin', styles.h4, stringifyCondensed(t.tensor))
const startTime = performance.now()
@@ -49,7 +49,7 @@ describe('core layer: Reshape', function () {
it('[core.Reshape.2] should be able to go from shape [3, 2, 2] -> [4, 3]', function () {
const key = 'core.Reshape.2'
console.log(`\n%c[${key}] shape [3, 2, 2] -> [4, 3]`, styles.h3)
let testLayer = new layers.Reshape([4, 3])
let testLayer = new layers.Reshape({ shape: [4, 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()