Add WebNN baseline implementation for first-wave ops

.eslintrc.js

@@ -0,0 +1,23 @@
+module.exports = {
+  root: true,
+  ignorePatterns: ['.eslintrc.js'],
+  env: { 'es6': true, 'browser': true, 'node': true, 'mocha': true },
+  parserOptions: { ecmaVersion: 2020, sourceType: 'module'},
+  globals: {
+    'chai': 'readonly',
+    'BigInt': 'readonly',
+    'BigInt64Array': 'readonly',
+  },
+  rules: {
+    'semi': 'error',
+    'no-multi-spaces': ['error', { 'exceptions': { 'ArrayExpression': true } }],
+    'indent': 2,
+    'require-jsdoc': 'off',
+    'max-len': ['error', {'code': 100}],
+    'prefer-rest-params': 'off'
+  },
+  extends: [
+    'eslint:recommended',
+    'google',
+  ],
+}

.github/dependabot.yml

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+# Set update schedule for GitHub Actions
+
+version: 2
+updates:
+
+  - package-ecosystem: "github-actions"
+    directory: "/"
+    schedule:
+      # Check for updates to GitHub Actions every weekday
+      interval: "daily"

.github/workflows/build_test.yml

@@ -0,0 +1,36 @@
+name: build and test
+
+on: [push, pull_request]
+
+jobs:
+
+  job:
+
+    strategy:
+      matrix:
+        platform: [ubuntu-latest, macos-latest, windows-latest]
+
+    runs-on: ${{ matrix.platform }}
+
+    steps:
+    - name: Git config
+      run: |
+        git config --global core.autocrlf false
+        git config --global core.eol lf
+
+    - name: Checkout repository and submodules
+      uses: actions/[email protected]
+      with:
+        submodules: recursive
+
+    - uses: actions/[email protected]
+      with:
+        node-version: '14.x'
+
+    - run: npm install
+
+    - run: npm run lint
+
+    - run: npm test
+      env:
+        CI: true

.gitignore

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+node_modules/
+.DS_Store
+package-lock.json
+debug.log

LICENSE

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README.md

@@ -1 +1,20 @@
-# webnn-baseline
+# WebNN Baseline
+
+The double-precision baseline implementation of WebNN operations for testing purpose.
+
+### Install
+
+```sh
+> npm install
+```
+
+### Test
+```sh
+> npm test
+```
+
+## Lint
+
+```sh
+> npm run lint
+```

node_setup.js

@@ -0,0 +1,2 @@
+global.chai = require('chai');
+global.fs = require('fs');

package.json

@@ -0,0 +1,27 @@
+{
+  "name": "webnn-baseline",
+  "version": "0.1.0",
+  "description": "WebNN API double-precision baseline implementation for testing",
+  "directories": {
+    "src": "src",
+    "test": "test"
+  },
+  "scripts": {
+    "lint": "eslint . --config .eslintrc.js --ext .js",
+    "test": "cross-env NODE_ENV=test mocha --require ./node_setup.js --exit test/*.js"
+  },
+  "authors": [
+    "Ningxin Hu <[email protected]>"
+  ],
+  "license": "Apache-2.0",
+  "devDependencies": {
+    "chai": "^4.2.0",
+    "cross-env": "^7.0.2",
+    "eslint": "^7.18.0",
+    "eslint-config-google": "^0.14.0",
+    "eslint-plugin-import": "^2.22.0",
+    "eslint-plugin-jsdoc": "^30.3.1",
+    "eslint-plugin-prefer-arrow": "^1.2.2",
+    "mocha": "^9.0.3"
+  }
+}

src/batch_normalization.js

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+'use strict';
+
+import {add, sub, mul, div, pow} from './binary.js';
+import {reshape} from './reshape.js';
+import {Tensor, Scalar} from './lib/tensor.js';
+import {validateBatchNormalizationParams} from './lib/validate-input.js';
+
+/**
+ * Normalize the tensor values of input features across the batch dimension using
+ * [Batch-Normalization](http://arxiv.org/abs/1502.03167).
+ * @param {Tensor} input
+ * @param {Tensor} mean
+ * @param {Tensor} variance
+ * @param {MLBatchNormalizationOptions} [options]
+ * @return {Tensor}
+ */
+export function batchNormalization(input, mean, variance, {axis=1, scale, bias, epsilon=1e-5,
+  activation = (x) => x} = {}) {
+  validateBatchNormalizationParams(...arguments);
+  // The output tensor has the same shape as the input tensor.
+  let output = new Tensor(input.shape);
+  const shape = new Array(input.rank).fill(1);
+  shape[axis] = -1;
+  output = sub(input, reshape(mean, shape));
+  output = div(output,
+      pow(add(reshape(variance, shape), new Scalar(epsilon)), new Scalar(0.5)));
+  if (scale) {
+    output = mul(output, reshape(scale, shape));
+  }
+  if (bias) {
+    output = add(output, reshape(bias, shape));
+  }
+  output = activation(output);
+  return output;
+}