chore: fix lint errors in discojs

Author: hleepfl

discojs/src/client/decentralized/peer.ts

@@ -137,7 +137,7 @@ export class Peer {
         : FIRST_HEADER_SIZE + b.length,
     );
     firstChunk.writeUint16BE(messageID);
-    firstChunk.writeUint8(0 as ChunkID, 2);
+    firstChunk.writeUint8(0, 2);
     firstChunk.writeUint8(totalChunkCount, 3);
     b.copy(
       firstChunk,
@@ -147,7 +147,7 @@ export class Peer {
     );
 
     return Seq.Indexed([firstChunk]).concat(
-      Range(1 as ChunkID, Number.POSITIVE_INFINITY)
+      Range(1, Number.POSITIVE_INFINITY)
         .zip(tail)
         .map(([id, raw]) => {
           const chunk = Buffer.alloc(HEADER_SIZE + raw.length);

discojs/src/privacy.spec.ts

@@ -7,7 +7,6 @@ import {
   addOptimalNoise,
   getClippingRadius,
 } from "./privacy.js";
-import { WeightNormHistory } from "./training/trainer.js";
 import * as tf from "@tensorflow/tfjs";
 import { List } from "immutable";
 
@@ -79,17 +78,13 @@ describe("getClippingRadius", () => {
       List([10]),
     ]);
 
-    expect(
-      getClippingRadius(weightNormHistory as WeightNormHistory, 5),
-    ).toEqual([4, 5]);
+    expect(getClippingRadius(weightNormHistory, 5)).toEqual([4, 5]);
   });
 
   it("uses smaller window size automatically if needed", () => {
     const weightNormHistory = List([List([2, 4])]);
 
     // Automatically use window size of 2 instead of 10
-    expect(
-      getClippingRadius(weightNormHistory as WeightNormHistory, 10),
-    ).toEqual([3]);
+    expect(getClippingRadius(weightNormHistory, 10)).toEqual([3]);
   });
 });

discojs/src/processing/index.ts

@@ -109,7 +109,7 @@ export function postprocess<D extends DataType>(
   switch (task.dataType) {
     case "image": {
       // cast as typescript doesn't reduce generic type
-      const index = encoded as DataFormat.ModelEncoded["image"][1];
+      const index = encoded;
       const labels = List(task.trainingInformation.LABEL_LIST);
 
       const v = labels.get(index);
@@ -118,13 +118,13 @@ export function postprocess<D extends DataType>(
     }
     case "tabular": {
       // cast as typescript doesn't reduce generic type
-      const v = encoded as DataFormat.ModelEncoded["tabular"][1];
+      const v = encoded;
 
       return v as DataFormat.Inferred[D];
     }
     case "text": {
       // cast as typescript doesn't reduce generic type
-      const token = encoded as DataFormat.ModelEncoded["text"][1];
+      const token = encoded;
 
       return task.trainingInformation.tokenizer.decode([
         token,

discojs/src/serialization/weights.ts

@@ -29,7 +29,7 @@ function isSerialized(raw: unknown): raw is Serialized {
 export async function encode(weights: WeightsContainer): Promise<Encoded> {
   const serialized: Serialized[] = await Promise.all(
     weights.weights.map(async (t) => ({
-      shape: t.shape as number[],
+      shape: t.shape,
       data: await t.data<"float32">(),
     })),
   );

discojs/src/training/disco.ts

@@ -224,7 +224,8 @@ export class Disco<D extends DataType, N extends Network> extends EventEmitter<{
       await this.#preprocessSplitAndBatch(dataset);
 
     // the client fetches the latest weights upon connection
-    // TODO unsafe cast
+    // TODO unsafe cast, and eslint rule is buggy
+    // eslint-disable-next-line @typescript-eslint/no-unnecessary-type-assertion
     this.trainer.model = (await this.#client.connect()) as Model<D>;
 
     for await (const [roundNum, round] of enumerate(