Fix test commandline options and improve test options

Author: ishii-norimi

.github/workflows/gh-pages.yml

@@ -28,12 +28,12 @@ jobs:
       - name: Prepare ONNX
         run: npm run create-onnx -t
       - name: Test lib
-        run: npm run test:lib --bail
+        run: npm run test:lib -- --bail 1
       - name: Coveralls
         uses: coverallsapp/github-action@master
         with:
           github-token: ${{ secrets.GITHUB_TOKEN }}
-          file: coverage/clover.xml
+          files: coverage/clover.xml
         continue-on-error: true
   test-js:
     runs-on: ubuntu-latest

.github/workflows/npm.yml

@@ -15,7 +15,7 @@ jobs:
       - name: Prepare ONNX
         run: npm run create-onnx -t
       - name: Test
-        run: npm run test:lib --bail
+        run: npm run test:lib -- --bail 1
   publish:
     runs-on: ubuntu-latest
     needs: test

.github/workflows/test.yml

@@ -13,12 +13,12 @@ jobs:
       - name: Prepare ONNX
         run: npm run create-onnx -t
       - name: Test lib
-        run: npm run test:lib --bail
+        run: npm run test:lib -- --bail 1
       - name: Coveralls
         uses: coverallsapp/github-action@master
         with:
           github-token: ${{ secrets.GITHUB_TOKEN }}
-          file: coverage/clover.xml
+          files: coverage/clover.xml
         continue-on-error: true
   test-js:
     runs-on: ubuntu-latest

tests/lib/model/kernelized_perceptron.test.js

@@ -6,7 +6,7 @@ import { accuracy } from '../../../lib/evaluate/classification.js'
 describe('classification', () => {
 	test.each([undefined, 'gaussian', { name: 'gaussian', s: 0.8 }, 'polynomial', { name: 'polynomial', d: 3 }])(
 		'kernel %s',
-		{ retry: 10 },
+		{ retry: 20 },
 		kernel => {
 			const model = new KernelizedPerceptron(1, kernel)
 			const x = Matrix.concat(Matrix.randn(50, 2, 0, 0.2), Matrix.randn(50, 2, 5, 0.2)).toArray()

tests/lib/model/lmclus.test.js

@@ -3,7 +3,7 @@ import LMCLUS from '../../../lib/model/lmclus.js'
 
 import { randIndex } from '../../../lib/evaluate/clustering.js'
 
-test('clustering', { retry: 5 }, () => {
+test('clustering', { retry: 10 }, () => {
 	const model = new LMCLUS(5, 1.5, 0.4)
 	const n = 50
 	const x = Matrix.concat(

tests/lib/model/nns/layer/graph_sage.test.js

@@ -255,7 +255,7 @@ describe('nn', () => {
 		}
 	})
 
-	test('grad decay', () => {
+	test('grad decay', { timeout: 10000 }, () => {
 		const net = NeuralNetwork.fromObject(
 			[{ type: 'input' }, { type: 'graph_sage', out_size: 3, l2_decay: 0.001 }, { type: 'readout' }],
 			'mse',

tests/lib/model/nns/optimizer/rmsprop.test.js

@@ -69,7 +69,7 @@ describe('rmsprop', () => {
 	})
 })
 
-test('nn', { retry: 3 }, () => {
+test('nn', { retry: 5 }, () => {
 	const net = NeuralNetwork.fromObject(
 		[
 			{ type: 'input', name: 'in' },

tests/lib/model/polynomial_histogram.test.js

@@ -33,7 +33,7 @@ describe('density estimation', () => {
 		expect(corr).toBeGreaterThan(0.1)
 	})
 
-	test.each([0, 2, undefined])('%j', p => {
+	test.each([0, 2, undefined])('%j', { retry: 3 }, p => {
 		const model = new PolynomialHistogram(p, 2)
 		const n = 500
 		const x = Matrix.concat(Matrix.randn(n, 2, 0, 0.1), Matrix.randn(n, 2, 5, 0.1)).toArray()