Fix linter errors on Secure-history and Byzantine aggregator

Author: mina5rovic

discojs/src/aggregator/byzantine.spec.ts

@@ -1,6 +1,5 @@
-import { expect } from "chai";
 import { Set } from "immutable";
-import * as tf from "@tensorflow/tfjs";
+import { describe, expect, it } from "vitest";
 
 import { WeightsContainer } from "../index.js";
 import { ByzantineRobustAggregator } from "./byzantine.js";
@@ -88,7 +87,6 @@ describe("ByzantineRobustAggregator", () => {
     const id = "c1";
     agg.setNodes(Set.of(id));
 
-    // Round 0
     const p0 = agg.getPromiseForAggregation();
     agg.add(id, WeightsContainer.of([10]), 0);
     const out0 = await p0;

discojs/src/aggregator/byzantine.ts

@@ -4,7 +4,6 @@ import { AggregationStep } from "./aggregator.js";
 import { MultiRoundAggregator, ThresholdType } from "./multiround.js";
 import { WeightsContainer, client } from "../index.js";
 import { aggregation } from "../index.js";
-import { Repeat } from "immutable";
 
 /**
  * Byzantine-robust aggregator using Centered Clipping (CC), based on the
@@ -84,8 +83,8 @@ export class ByzantineRobustAggregator extends MultiRoundAggregator {
       v = this.prevAggregate;
     } else {
       // Use shape of the first contribution to create zero vector
-      const sample = currentContributions.values().next().value;
-      v = sample.map((t: any) => tf.zerosLike(t));
+      const sample = currentContributions.values().next().value as WeightsContainer;
+      v = sample.map((t: tf.Tensor) => tf.zerosLike(t));
     }
     // Step 2: Iterative Centered ClippingF
     for (let l = 0; l < this.maxIterations; l++) {
@@ -119,8 +118,8 @@ export class ByzantineRobustAggregator extends MultiRoundAggregator {
 function euclideanNorm(w: WeightsContainer): tf.Scalar {
   // Computes the Euclidean (L2) norm of all tensors in a WeightsContainer by summing the squares of their elements and taking the square root.
   return tf.tidy(() => {
-    const norms = w.weights.map(t => tf.sum(tf.square(t)) as tf.Scalar);
-    const total = norms.reduce((a, b) => tf.add(a, b)) as tf.Scalar;
+    const norms: tf.Scalar[] = w.weights.map(t => tf.sum(tf.square(t)));
+    const total = norms.reduce((a, b) => tf.add(a, b));
     return tf.sqrt(total);
   });
 }

discojs/src/aggregator/mean.ts

@@ -3,10 +3,6 @@ import { AggregationStep } from "./aggregator.js";
 import { MultiRoundAggregator, ThresholdType } from "./multiround.js";
 import type { WeightsContainer, client } from "../index.js";
 import { aggregation } from "../index.js";
-import createDebug from "debug"
-
-const debug = createDebug("discojs:aggregator:mean");
-
 
 /** 
  * Mean aggregator whose aggregation step consists in computing the mean of the received weights. 

discojs/src/aggregator/multiround.ts

@@ -1,4 +1,4 @@
-import { Aggregator, AggregationStep } from "./aggregator.js";
+import { Aggregator } from "./aggregator.js";
 import createDebug from "debug";
 
 export type ThresholdType = 'relative' | 'absolute';

discojs/src/aggregator/secure_history.spec.ts

@@ -1,9 +1,9 @@
 import { List, Set, Range, Map } from "immutable";
-import { assert, expect } from "chai";
+import { describe, expect, it, assert } from "vitest";
+
 import * as tf from "@tensorflow/tfjs";
 
 import {
-    aggregator as aggregators,
     aggregation,
     WeightsContainer,
 } from "../index.js";
@@ -16,7 +16,6 @@ import { wsIntoArrays, communicate, setupNetwork } from "../aggregator.spec.js";
 describe("Secure history aggregator", function () {
     const epsilon = 1e-4;
 
-    const expected = WeightsContainer.of([2, 2, 5, 1], [-10, 10]);
     const secrets = List.of(
         WeightsContainer.of([1, 2, 3, -1], [-5, 6]),
         WeightsContainer.of([2, 3, 7, 1], [-10, 5]),
@@ -32,15 +31,6 @@ describe("Secure history aggregator", function () {
         });
     }
 
-    function buildPartialSums(
-        allShares: List<List<WeightsContainer>>,
-    ): List<WeightsContainer> {
-        return Range(0, secrets.size)
-            .map((idx) => allShares.map((shares) => shares.get(idx)))
-            .map((shares) => aggregation.sum(shares as List<WeightsContainer>))
-            .toList();
-    }
-
     it("recovers secrets from shares", () => {
         const recovered = buildShares().map((shares) => aggregation.sum(shares));
         assert.isTrue(
@@ -60,9 +50,9 @@ describe("Secure history aggregator", function () {
 
         const sharesRound0 = buildShares();
 
-        let partialSums = Range(0, nodes.size).map((receiverIdx) => {
+        const partialSums = Range(0, nodes.size).map((receiverIdx) => {
             const receivedShares = sharesRound0.map(shares => shares.get(receiverIdx)!);
-            return aggregation.sum(receivedShares as List<WeightsContainer>);
+            return aggregation.sum(receivedShares);
         }).toList();
 
         // Add one total contribution per node

discojs/src/aggregator/secure_history.ts

@@ -1,6 +1,5 @@
-import type { WeightsContainer, client } from "../index.js";
+import type { WeightsContainer } from "../index.js";
 import { SecureAggregator } from "./secure.js"; 
-import * as tf from "@tensorflow/tfjs";
 import { aggregation } from "../index.js";
 
 /**