Modularize: Remove pieces that are going in different repos (tensorfl…

…ow#876)

This change is part of the modularization and moving things to different repos.

Remove deprecated/private API from `src/index.ts`

Also remove:
- `website/` (moving to another repo)
- `docs/` (moving to another repo)
- `starter/` (moving to another repo)
- `src/data/` (deprecated)
- `demos/`
  - `adder/`
  - `imagenet/`
  - `lstm/`
  - `mnist/`
  - `mnist_eager/`
  - `one_plus_one/`
  - `rune_recognition/`

.gitignore

@@ -6,6 +6,7 @@ scripts/**/*.js
 coverage/
 package-lock.json
 npm-debug.log
+yarn-error.log
 .DS_Store
 dist/
 .idea/

.travis.yml

@@ -1,11 +1,5 @@
 language: node_js
 node_js: "8"
-addons:
-  apt:
-    packages:
-      - "python3"
-      - "python3-pip"
 script:
-  - ./scripts/run_python_tests.sh
   - ./scripts/build_and_lint_all
   - if [ "$BROWSERSTACK_KEY" ]; then yarn test-travis; fi

README.md

@@ -79,7 +79,7 @@ the dev environment:
 ```bash
 $ git clone https://github.com/PAIR-code/deeplearnjs.git
 $ cd deeplearnjs
-$ yarn prep # Installs dependencies.
+$ yarn # Installs dependencies.
 ```
 
 #### Yarn vs NPM
@@ -135,21 +135,11 @@ $ yarn test --single-run
 ```
 
 #### Packaging (browser and npm)
-To build a standalone ES5 library that can be imported in the browser with a
-`<script>` tag:
 
 ```bash
-$ ./scripts/build-standalone.sh # Builds standalone library.
->> Stored standalone library at dist/deeplearn(.min).js
-```
-
-To build an npm package:
-
-```bash
-$ ./scripts/build-npm.sh
-...
-Stored standalone library at dist/deeplearn(.min).js
-deeplearn-VERSION.tgz
+$ yarn build-npm
+> Stored standalone library at dist/deeplearn(.min).js
+> deeplearn-VERSION.tgz
 ```
 
 To install it locally, run `npm install ./deeplearn-VERSION.tgz`.

demos/benchmarks/pool_benchmarks.ts

@@ -28,25 +28,24 @@ export interface PoolBenchmarkParams {
   stride: number;
 }
 
-function getPoolingOp(option: string):
-    (x: dl.Tensor3D, filterSize: [number, number]|number,
-     strides: [number, number]|number, pad: 'valid'|'same'|number) =>
-        dl.Tensor3D {
+function getPoolingOp(option: string): (
+    x: dl.Tensor3D, filterSize: [number, number]|number,
+    strides: [number, number]|number) => dl.Tensor3D {
   switch (option) {
     case 'max':
       return (x: dl.Tensor3D, filterSize: [number, number]|number,
-              strides: [number, number]|number, pad: 'valid'|'same'|number) => {
-        return x.maxPool(filterSize, strides, pad);
+              strides: [number, number]|number) => {
+        return x.maxPool(filterSize, strides, 'same');
       };
     case 'min':
       return (x: dl.Tensor3D, filterSize: [number, number]|number,
-              strides: [number, number]|number, pad: 'valid'|'same'|number) => {
-        return x.minPool(filterSize, strides, pad);
+              strides: [number, number]|number) => {
+        return x.minPool(filterSize, strides, 'same');
       };
     case 'avg':
       return (x: dl.Tensor3D, filterSize: [number, number]|number,
-              strides: [number, number]|number, pad: 'valid'|'same'|number) => {
-        return x.avgPool(filterSize, strides, pad);
+              strides: [number, number]|number) => {
+        return x.avgPool(filterSize, strides, 'same');
       };
     default:
       throw new Error(`Not found such ops: ${option}`);
@@ -62,14 +61,13 @@ export class PoolCPUBenchmark implements BenchmarkTest {
     const xShape: [number, number, number] = [size, size, outputDepth];
     const fieldSize = params.fieldSize;
     const stride = params.stride;
-    const zeroPad = dl.conv_util.computeDefaultPad(xShape, fieldSize, stride);
     const op = getPoolingOp(option);
 
     const x: dl.Tensor3D = dl.randomUniform(xShape, -1, 1);
 
     const start = performance.now();
     for (let i = 0; i < CPU_OP_RUNS; i++) {
-      op(x, fieldSize, stride, zeroPad);
+      op(x, fieldSize, stride);
     }
     const avgTime = (performance.now() - start) / CPU_OP_RUNS;
     return new Promise<number>((resolve, reject) => {
@@ -90,7 +88,7 @@ export class PoolGPUBenchmark implements BenchmarkTest {
     const x: dl.Tensor3D = dl.randomUniform(xShape, -1, 1);
     const op = getPoolingOp(option);
 
-    const benchmark = () => op(x, fieldSize, stride, 'same');
+    const benchmark = () => op(x, fieldSize, stride);
     const time = await benchmark_util.warmupAndBenchmarkGPU(benchmark);
 
     x.dispose();

demos/fast-style-transfer/fast-style-transfer.ts

@@ -16,7 +16,6 @@
  */
 
 import * as dl from 'deeplearn';
-
 import {PolymerElement, PolymerHTMLElement} from '../polymer-spec';
 
 import {TransformNet} from './net';

demos/fast-style-transfer/net.ts

@@ -15,6 +15,7 @@
  * =============================================================================
  */
 import * as dl from 'deeplearn';
+import {CheckpointLoader} from 'deeplearn-legacy-loader';
 
 const GOOGLE_CLOUD_STORAGE_DIR =
     'https://storage.googleapis.com/learnjs-data/checkpoint_zoo/transformnet/';
@@ -45,7 +46,7 @@ export class TransformNet {
   async load(): Promise<void> {
     if (this.variableDictionary[this.style] == null) {
       const checkpointLoader =
-          new dl.CheckpointLoader(GOOGLE_CLOUD_STORAGE_DIR + this.style + '/');
+          new CheckpointLoader(GOOGLE_CLOUD_STORAGE_DIR + this.style + '/');
       this.variableDictionary[this.style] =
           await checkpointLoader.getAllVariables();
     }