refactors based on feedback

demo/mnist_transfer_learning_model.ts

@@ -17,7 +17,7 @@
 
 import * as tf from '@tensorflow/tfjs'
 import {Scalar, Tensor} from '@tensorflow/tfjs';
-import {FederatedModel, ModelDict} from '../src/types';
+import {FederatedModel, ModelDict} from '../src/index';
 
 // https://github.com/tensorflow/tfjs-examples/tree/master/mnist-transfer-cnn
 // tslint:disable-next-line:max-line-length
@@ -35,7 +35,8 @@ export class MnistTransferLearningModel implements FederatedModel {
     const loss =
         (inputs: Tensor, labels: Tensor) => {
           const logits = model.predict(inputs) as Tensor;
-          return tf.losses.softmaxCrossEntropy(logits, labels).mean() as Scalar;
+          const losses = tf.losses.softmaxCrossEntropy(logits, labels);
+          return losses.mean() as Scalar;
         }
 
     return {

src/comm_test.ts

@@ -16,8 +16,6 @@
  * =============================================================================
  */
 
-// import * as tf from '@tensorflow/tfjs';
-// import {test_util} from '@tensorflow/tfjs-core';
 import * as tf from '@tensorflow/tfjs';
 import {test_util, Variable} from '@tensorflow/tfjs';
 import * as fs from 'fs';
@@ -42,6 +40,18 @@ const initWeights =
     [tf.tensor([1, 1, 1, 1], [2, 2]), tf.tensor([1, 2, 3, 4], [1, 4])];
 const updateThreshold = 2;
 
+function waitUntil(done: () => boolean, then: () => void, timeout?: number) {
+  const moveOn = () => {
+    clearInterval(moveOnIfDone);
+    clearTimeout(moveOnAnyway);
+    then();
+  };
+  const moveOnAnyway = setTimeout(moveOn, timeout || 100);
+  const moveOnIfDone = setInterval(() => {
+    if (done()) moveOn();
+  }, 1);
+}
+
 describe('Socket API', () => {
   let dataDir: string;
   let modelDir: string;
@@ -115,20 +125,14 @@ describe('Socket API', () => {
     clientAPI.numExamples = 3;
     await clientAPI.uploadVars();
 
-    const timeout = 100;
-    let elapsed = 0;
-    const interval = setInterval(() => {
-      elapsed += 1;
-      if (elapsed > timeout || clientAPI.modelId != modelId) {
-        clearInterval(interval);
-        test_util.expectArraysClose(
-            clientVars[0], tf.tensor([1.25, 1.25, 1.25, 1.25], [2, 2]))
-        test_util.expectArraysClose(
-            clientVars[1], tf.tensor([3.25, 2.75, 2.25, 1.75], [1, 4]))
-        expect(clientAPI.numExamples).toBe(0);
-        expect(clientAPI.modelId).toBe(modelDB.modelId);
-        done();
-      }
-    }, 1);
+    waitUntil(() => clientAPI.modelId != modelId, () => {
+      test_util.expectArraysClose(
+          clientVars[0], tf.tensor([1.25, 1.25, 1.25, 1.25], [2, 2]))
+      test_util.expectArraysClose(
+          clientVars[1], tf.tensor([3.25, 2.75, 2.25, 1.75], [1, 4]))
+      expect(clientAPI.numExamples).toBe(0);
+      expect(clientAPI.modelId).toBe(modelDB.modelId);
+      done();
+    });
   })
 });

src/index.ts

@@ -0,0 +1,18 @@
+/**
+ * * @license
+ * Copyright 2018 Google LLC. All Rights Reserved.
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ * =============================================================================
+ */
+
+export * from './types';