feat: add tvm wasm export

.github/workflows/build.yml

@@ -3,6 +3,7 @@ on:
   push:
     branches:
     - master
+    - debug/tvm
     paths-ignore:
     - 'docker/**'
     - 'docs/**'
@@ -67,67 +68,14 @@ jobs:
         yarn build
         yarn init-dev
         du -h -d 1
-    - name: Running unit tests
-      run: |
-        npm test
-    - name: run cov
-      if: ${{ runner.os == 'Linux' && matrix.node_version == 12 }}
-      run: |
-        npm run cov
-    - name: Coveralls
-      if: ${{ runner.os == 'Linux' && matrix.node_version == 12 }}
-      uses: coverallsapp/github-action@master
-      with:
-        github-token: ${{ secrets.GITHUB_TOKEN }}
-        path-to-lcov: packages/daemon/coverage/lcov.info
-    - name: migration
-      if: ${{ runner.os == 'Linux' }}
-      run: |
-        mkdir -p ~/.pipcook/db && cp ./packages/daemon/test/res/baseline-v1.db ~/.pipcook/db/pipcook.db
     - name: daemon start
       run: |
         ./packages/cli/dist/bin/pipcook daemon start
-    - name: Testing help commands
-      run: |
-        ./packages/cli/dist/bin/pipcook -v
-        ./packages/cli/dist/bin/pipcook -h
-        ./packages/cli/dist/bin/pipcook init --help
-        ./packages/cli/dist/bin/pipcook run --help
-        ./packages/cli/dist/bin/pipcook plugin-dev --help
-        ./packages/cli/dist/bin/pipcook serve --help
-    - name: pipcook sdk test
-      run: |
-        npx ts-node ./run_tests.ts
     - name: install plugins from specific pipeline
       run: |
+        python3 --version
+        python --version
+        which python
+        echo $PATH
         ./packages/cli/dist/bin/pipcook pipeline install ./example/pipelines/chinese-poem-creation.json
         ./packages/cli/dist/bin/pipcook pipeline install https://raw.githubusercontent.com/alibaba/pipcook/master/example/pipelines/text-bayes-classification.json
-    - name: Running an example pipeline
-      run: |
-        yarn test:pipeline -- text-bayes-classification
-    - name: install a new plugin and install a installed plugin
-      run: |
-        ./packages/cli/dist/bin/pipcook plugin install @pipcook/plugins-chinese-poem-data-collect
-        ./packages/cli/dist/bin/pipcook plugin install @pipcook/plugins-chinese-poem-data-collect
-    - name: install plugin from local project
-      run: |
-        ./packages/cli/dist/bin/pipcook plugin install ./packages/costa/test/plugins/nodejs-simple
-        npm pack ./packages/costa/test/plugins/nodejs-simple
-        ./packages/cli/dist/bin/pipcook plugin install ./nodejs-simple-1.0.0.tgz
-        rm ./nodejs-simple-1.0.0.tgz
-    - name: pipcook run from local filename
-      run: |
-        ./packages/cli/dist/bin/pipcook run ./example/pipelines/text-bayes-classification.json
-        ls ./output && rm -rf ./output
-        ./packages/cli/dist/bin/pipcook run ./example/pipelines/text-bayes-classification.json --output mydir
-        ls ./mydir && rm -rf ./mydir
-    - name: pipcook run from url
-      run: |
-        ./packages/cli/dist/bin/pipcook run https://raw.githubusercontent.com/alibaba/pipcook/master/example/pipelines/text-bayes-classification.json
-        ls ./output && rm -rf ./output
-    - name: remove pipelines
-      run: |
-        ./packages/cli/dist/bin/pipcook pipeline remove all -y
-    - name: "pipcook plugin-dev"
-      run: |
-        ./packages/cli/dist/bin/pipcook plugin-dev -t dataCollect

.github/workflows/pipeline.yml

@@ -30,3 +30,9 @@ jobs:
         ./packages/cli/dist/bin/pipcook daemon start
     - name: pipeline
       run: yarn test:pipeline -- ${{ matrix.pipeline }}
+    - name: wasm export pipeline
+      run: |
+        git clone https://github.com/emscripten-core/emsdk.git && cd emsdk
+        ./emsdk install latest && ./emsdk activate latest && source ./emsdk_env.sh
+        ./packages/cli/dist/bin/pipcook daemon stop
+        export WASM=1 && ./packages/cli/dist/bin/pipcook run ./example/pipelines/databinding-image-classification-mobilenet.json

docs/INSTALL.md

@@ -10,6 +10,8 @@ Before starting the installation, please make sure the following environments ar
 - macOS, Linux
 - Node.js 12
 
+**Note:** To use `wasm` output format, you need to manually install [`emsdk`](https://emscripten.org/docs/introducing_emscripten/index.html) and export the `emcc` and `emsdk` to the environmental variable.
+
 ## Install via NPM
 
 Installing [Pipcook][] via NPM is easy, just run:

packages/boa/lib/index.js

@@ -336,6 +336,7 @@ function _internalWrap(T, src={}) {
       writable: false,
       value: () => T.__hash__(),
     },
+
     /**
      * @method [PyGetAttrSymbol]
      * @public

packages/costa/src/runtime.ts

@@ -319,7 +319,7 @@ export class CostaRuntime {
     }
     const stdio = { stdout: opts.stdout, stderr: opts.stderr, prefix: 'NODE' };
     const npmExecOpts = { cwd: this.options.installDir };
-    const npmArgs = [ 'install', pluginAbsName, '-E', '--production' ];
+    const npmArgs = [ 'install', pluginAbsName, '-E', '--production', '--silly' ];
 
     if (this.options.npmRegistryPrefix) {
       npmArgs.push(`--registry=${this.options.npmRegistryPrefix}`);
@@ -328,6 +328,9 @@ export class CostaRuntime {
       // if not init for plugin directory, just run `npm init` and install boa firstly.
       await spawnAsync('npm', [ 'init', '-y' ], npmExecOpts, stdio);
     }
+    spawnAsync('echo', ['$PATH'], npmExecOpts, stdio);
+    spawnAsync('which', ['python'], npmExecOpts, stdio);
+    spawnAsync('node', ['-e', 'console.log(process.env)'], npmExecOpts, stdio);
     return spawnAsync('npm', npmArgs, npmExecOpts, stdio);
   }
 

packages/daemon/package.json

@@ -4,6 +4,7 @@
   "description": "pipcook daemon",
   "dependencies": {
     "@pipcook/app": "^1.2.0",
+    "@pipcook/boa": "^1.2.0",
     "@pipcook/costa": "^1.2.0",
     "@pipcook/pipcook-core": "^1.2.0",
     "axios": "^0.18.1",

packages/daemon/src/service/pipeline.ts

@@ -175,7 +175,7 @@ export class PipelineService {
     const verifyPlugin = (name: string): void => {
       if (!plugins[name]) {
         this.runnableMap[job.id].destroy();
-        throw new TypeError(`"${name}" plugin is required`);
+        throw new TypeError(`'${name}' plugin is required`);
       }
     };
     const dispatchJobEvent = (jobStatus: PipelineStatus, step?: PluginTypeI, stepAction?: 'start' | 'end') => {
@@ -271,7 +271,7 @@ export class PipelineService {
         datasetProcess,
         pipeline,
         workingDir: runnable.workingDir,
-        template: 'node' // set node by default
+        template: process.env.WASM ? 'wasm' : 'node' // set node by default
       });
 
       await JobModel.saveJob(job);
@@ -317,6 +317,66 @@ export class PipelineService {
     return path.join(CoreConstants.PIPCOOK_RUN, id, 'output.tar.gz');
   }
 
+  // private _generateWASMOutput(dist: string, opts: GenerateOptions, fileQueue: Array<Promise<void | string>>): void {
+  //   const relay = boa.import('tvm.relay');
+  //   const emcc = boa.import('tvm.contrib.emcc');
+  //   const keras = boa.import('tensorflow.keras');
+  //   const {dict, open} = boa.builtins();
+
+  //   // download tvm runtime from oss
+  //   const tvmjsPromise = execAsync(`wget http://ai-sample.oss-cn-hangzhou.aliyuncs.com/tvmjs/dist/tvmjs.bundle.js`, {cwd: dist});
+  //   fileQueue.push(tvmjsPromise);
+
+  //   const model = keras.models.load_model(path.join(opts.modelPath, 'model.h5'));
+
+  //   const inputName = 'input_1';
+  //   const inputShape = model.layers[0].input_shape[0];
+  //   const shape = [1];
+  //   shape.push(inputShape[3]);
+  //   shape.push(inputShape[1]);
+  //   shape.push(inputShape[2]);
+
+  //   const [ mod, params ] = relay.frontend.from_keras(model, dict(boa.kwargs({[inputName]: shape})));
+  //   const [ graph, lib, param ] = relay.build(mod, boa.kwargs({
+  //     params,
+  //     target: 'llvm -mtriple=wasm32--unknown-emcc -system-lib'
+  //   }));
+
+  //   lib.save(path.join(dist, 'model.bc'));
+
+  //   const jsonWriter = open(path.join(dist, 'modelDesc.json'), 'w');
+  //   jsonWriter.write(graph);
+  //   const paramWriter = open(path.join(dist, 'modelParams.parmas'), 'wb');
+  //   paramWriter.write(relay.save_param_dict(param));
+  //   emcc.create_tvmjs_wasm(path.join(dist, 'model.wasi.js'), path.join(dist, 'model.bc'), boa.kwargs({
+  //     options: ['-O3', '-std=c++14', '-Wno-ignored-attributes', '-s', 'ALLOW_MEMORY_GROWTH=1', '-s', 'STANDALONE_WASM=1', '-s', 'ERROR_ON_UNDEFINED_SYMBOLS=0', '-s', 'ASSERTIONS=1', '--no-entry', '--pre-js', './packages/daemon/binary/preload.js']
+  //   }));
+
+  //   const templateHead = `function EmccWASI() {`;
+  //   const templateTail = `
+  //     this.Module = Module;
+  //     this.start = Module.wasmLibraryProvider.start;
+  //     this.imports = Module.wasmLibraryProvider.imports;
+  //     this.wasiImport = this.imports['wasi_snapshot_preview1'];
+  //   }
+
+  //   if (typeof module !== 'undefined' && module.exports) {
+  //     module.exports = EmccWASI;
+  //   }
+  //   `;
+
+  //   const result = templateHead + open(path.join(dist, 'model.wasi.js')).read() + templateTail;
+  //   const resultWriter = open(path.join(dist, 'model.wasi.js'), 'w');
+  //   resultWriter.write(result);
+
+  //   const jsonPromise = fs.writeJSON(path.join(dist, 'modelSpec.json'), {
+  //     shape,
+  //     inputName
+  //   });
+
+  //   fileQueue.push(jsonPromise);
+  // }
+
   /**
    * Generate the output package for a given job.
    * @param job the job model for output.
@@ -327,18 +387,34 @@ export class PipelineService {
     const dist = path.join(opts.workingDir, 'output');
     await fs.remove(dist);
     await fs.ensureDir(dist);
+
+    const fileQueue: Array<Promise<void | string>> = new Array();
+
+    // Only support tensorflow at this moment.
+    // if (opts.template === 'wasm' && opts.modelPlugin.name.includes('tensorflow')) {
+    //   this._generateWASMOutput(dist, opts, fileQueue);
+    // }
+
     await execAsync('npm init -y', { cwd: dist });
 
     // post processing the package.json
     const projPackage = await fs.readJSON(dist + '/package.json');
-    projPackage.dependencies = {
-      [opts.modelPlugin.name]: opts.modelPlugin.version,
-    };
-    projPackage.scripts = {
-      postinstall: 'node boapkg.js'
-    };
-    if (opts.dataProcess) {
-      projPackage.dependencies[opts.dataProcess.name] = opts.dataProcess.version;
+
+    if (opts.template === 'node') {
+      projPackage.dependencies = {
+        [opts.modelPlugin.name]: opts.modelPlugin.version,
+      };
+      projPackage.scripts = {
+        postinstall: 'node boapkg.js'
+      };
+      if (opts.dataProcess) {
+        projPackage.dependencies[opts.dataProcess.name] = opts.dataProcess.version;
+      }
+    } else {
+      projPackage.main = 'index.js';
+      projPackage.dependencies = {
+        ws: '^7.3.1'
+      };
     }
 
     const jsonWriteOpts = { spaces: 2 } as fs.WriteOptions;
@@ -347,18 +423,21 @@ export class PipelineService {
       output: job,
     };
 
-    await Promise.all([
+    if (opts.template === 'node') {
       // copy base components
-      fs.copy(opts.modelPath, dist + '/model'),
-      fs.copy(path.join(__dirname, `../../templates/${opts.template}/predict.js`), `${dist}/index.js`),
-      fs.copy(path.join(__dirname, '../../templates/boapkg.js'), `${dist}/boapkg.js`),
-      // copy logs
-      fs.copy(opts.workingDir + '/logs', `${dist}/logs`),
-      // write package.json
-      fs.outputJSON(dist + '/package.json', projPackage, jsonWriteOpts),
-      // write metadata.json
-      fs.outputJSON(dist + '/metadata.json', metadata, jsonWriteOpts),
-    ]);
+      fileQueue.push(fs.copy(opts.modelPath, dist + '/model'));
+      fileQueue.push(fs.copy(path.join(__dirname, '../../templates/boapkg.js'), `${dist}/boapkg.js`));
+    }
+
+    fileQueue.push(fs.copy(path.join(__dirname, `../../templates/${opts.template}/predict.js`), `${dist}/index.js`));
+    // copy logs
+    fileQueue.push(fs.copy(opts.workingDir + '/logs', `${dist}/logs`));
+    // write package.json
+    fileQueue.push(fs.outputJSON(dist + '/package.json', projPackage, jsonWriteOpts));
+    // write metadata.json
+    fileQueue.push(fs.outputJSON(dist + '/metadata.json', metadata, jsonWriteOpts));
+
+    await Promise.all(fileQueue);
     console.info(`trained the model to ${dist}`);
 
     // packing the output directory.

packages/daemon/templates/wasm/predict.js

@@ -0,0 +1,41 @@
+const tvmjs = require("./tvmjs.bundle");
+const EmccWASI = require("./model.wasi");
+const fs = require('fs');
+const modelSpec = require("./modelSpec.json");
+
+const loadModel = async () => {
+  const wasmSource = fs.readFileSync('./model.wasi.wasm');
+  const tvm = await tvmjs.instantiate(wasmSource, new EmccWASI());
+
+  const graph = JSON.parse(fs.readFileSync('./modelDesc.json'));
+  const param = new Uint8Array(fs.readFileSync('./modelParams.parmas'));
+
+  const ctx = tvm.cpu(0);
+  const sysLib = tvm.systemLib();
+  model = tvm.createGraphRuntime(JSON.stringify(graph), sysLib, ctx);
+  model.loadParams(param);
+
+  return {model, tvm, ctx};
+}
+
+let model, tvm, ctx;
+
+const predict = async (input) => {
+  if (!model) {
+    const rets = await loadModel();
+    model = rets.model;
+    tvm = rets.tvm;
+    ctx = rets.ctx;
+  }
+
+  const inputData = tvm.empty(modelSpec.shape, "float32", tvm.cpu());
+  const output = model.getOutput(0);
+  inputData.copyFrom(input);
+  model.setInput(modelSpec.inputName, inputData);
+  model.run();
+  await ctx.sync();
+  console.log(output.toArray())
+  return output.toArray();
+}
+
+module.exports = predict;