TMP eslint 2022

cli/package.json

@@ -7,7 +7,7 @@
     "watch": "nodemon --ext ts --ignore dist --watch ../discojs/discojs-node/dist --watch ../server/dist --watch . --exec npm run",
     "start": "npm run build && node dist/cli.js",
     "build": "tsc",
-    "lint": "npx eslint --ext ts --max-warnings 0 .",
+    "lint": "npx eslint .",
     "test": ": nothing"
   },
   "author": "",

discojs/discojs-core/package.json

@@ -7,7 +7,7 @@
   "scripts": {
     "watch": "nodemon --ext ts --ignore dist --exec npm run",
     "build": "tsc",
-    "lint": "npx eslint --ext ts --max-warnings 0 .",
+    "lint": "npx eslint .",
     "test": "mocha",
     "docs": "typedoc ./src/index.ts --theme oxide"
   },

discojs/discojs-core/src/models/gpt/index.ts

@@ -123,13 +123,13 @@ export class GPT extends Model {
     }
   }
 
-  override async predict (input: Sample): Promise<Prediction> {
+  override predict (input: Sample): Promise<Prediction> {
     const ret = this.model.predict(input)
     if (Array.isArray(ret)) {
       throw new Error('prediction yield many Tensors but should have only returned one')
     }
 
-    return ret
+    return Promise.resolve(ret)
   }
 
   static deserialize (weights: WeightsContainer): Model {

discojs/discojs-core/src/models/gpt/train.ts

@@ -18,7 +18,7 @@ function getCustomAdam (model: tf.LayersModel, c: Required<GPTConfig>): tf.Optim
   const excludeFromWeightDecay: string[] = []
 
   // TODO unsafe cast
-  const namedWeights = (model as unknown as any).getNamedWeights() as Array<{ name: string, tensor: tf.Tensor }>
+  const namedWeights = (model as unknown as Record<'getNamedWeights', () => Array<{ name: string, tensor: tf.Tensor }>>).getNamedWeights()
 
   namedWeights.forEach((v) => {
     if (

discojs/discojs-core/src/models/tfjs.ts

@@ -51,18 +51,18 @@ export class TFJS extends Model {
     }
   }
 
-  override async predict (input: Sample): Promise<Prediction> {
+  override predict (input: Sample): Promise<Prediction> {
     const ret = this.model.predict(input)
     if (Array.isArray(ret)) {
       throw new Error('prediction yield many Tensors but should have only returned one')
     }
 
-    return ret
+    return Promise.resolve(ret)
   }
 
   static async deserialize (raw: tf.io.ModelArtifacts): Promise<Model> {
     return new this(await tf.loadLayersModel({
-      load: async () => raw
+      load: () => Promise.resolve(raw)
     }))
   }
 
@@ -71,14 +71,14 @@ export class TFJS extends Model {
     const ret = new Promise<tf.io.ModelArtifacts>((resolve) => { resolveArtifacts = resolve })
 
     await this.model.save({
-      save: async (artifacts) => {
+      save: (artifacts) => {
         resolveArtifacts(artifacts)
-        return {
+        return Promise.resolve({
           modelArtifactsInfo: {
             dateSaved: new Date(),
             modelTopologyType: 'JSON'
           }
-        }
+        })
       }
     }, {
       includeOptimizer: true // keep model compiled

discojs/discojs-core/src/serialization/model.ts

@@ -4,7 +4,10 @@ import type tf from '@tensorflow/tfjs'
 import type { Model } from '../index.js'
 import { models, serialization } from '../index.js'
 
-const enum Type { TFJS, GPT }
+const Type = {
+  TFJS: 0,
+  GPT: 1
+} as const
 
 export type Encoded = Uint8Array
 
@@ -37,7 +40,7 @@ export async function decode (encoded: unknown): Promise<Model> {
   }
   const [type, rawModel] = raw as [unknown, unknown]
 
-  if (typeof type !== 'number' || (type !== Type.TFJS && type !== Type.GPT)) {
+  if (typeof type !== 'number') {
     throw new Error('invalid encoding')
   }
   switch (type) {
@@ -57,5 +60,7 @@ export async function decode (encoded: unknown): Promise<Model> {
       const serialized = serialization.weights.decode(nums)
       return models.GPT.deserialize(serialized)
     }
+    default:
+      throw new Error('invalid encoding')
   }
 }

discojs/discojs-core/src/serialization/weights.ts

@@ -24,7 +24,6 @@ function isSerialized (raw: unknown): raw is Serialized {
     return false
   }
 
-  // eslint-disable-next-line
   const _: Serialized = {shape, data}
 
   return true
@@ -48,7 +47,7 @@ export async function encode (weights: WeightsContainer): Promise<Encoded> {
 }
 
 export function decode (encoded: Encoded): WeightsContainer {
-  const raw = msgpack.decode(encoded)
+  const raw: unknown = msgpack.decode(encoded)
 
   if (!(Array.isArray(raw) && raw.every(isSerialized))) {
     throw new Error('expected to decode an array of serialized weights')

discojs/discojs-core/src/task/digest.ts

@@ -8,7 +8,7 @@ export function isDigest (raw: unknown): raw is Digest {
     return false
   }
 
-  const { algorithm, value }: Partial<Record<string, unknown>> = raw
+  const { algorithm, value }: Partial<Record<keyof Digest, unknown>> = raw
 
   if (!(
     typeof algorithm === 'string' &&

discojs/discojs-core/src/task/training_information.ts

@@ -1,5 +1,5 @@
-import { type AggregatorChoice } from '../aggregator/get.js'
-import { type Preprocessing } from '../dataset/data/preprocessing/index.js'
+import type { AggregatorChoice } from '../aggregator/get.js'
+import type { Preprocessing } from '../dataset/data/preprocessing/index.js'
 
 export interface TrainingInformation {
   // modelID: unique ID for the model

discojs/discojs-core/src/training/trainer/distributed_trainer.ts

@@ -31,14 +31,14 @@ export class DistributedTrainer extends Trainer {
     await this.client.onTrainBeginCommunication(this.model.weights, this.trainingInformant)
   }
 
-  async onRoundBegin (accuracy: number): Promise<void> {
+  async onRoundBegin (): Promise<void> {
     await this.client.onRoundBeginCommunication(this.model.weights, this.roundTracker.round, this.trainingInformant)
   }
 
   /**
    * Callback called every time a round is over
    */
-  async onRoundEnd (accuracy: number): Promise<void> {
+  async onRoundEnd (): Promise<void> {
     await this.client.onRoundEndCommunication(this.model.weights, this.roundTracker.round, this.trainingInformant)
     if (this.aggregator.model !== undefined) {
       // The aggregator's own aggregation is async. The trainer updates its model to match the aggregator's

discojs/discojs-core/src/training/trainer/local_trainer.ts

@@ -6,9 +6,11 @@ import { Trainer } from './trainer.js'
  * without any collaborators.
  */
 export class LocalTrainer extends Trainer {
-  async onRoundBegin (accuracy: number): Promise<void> {}
+  async onRoundBegin (): Promise<void> {
+    return await Promise.resolve()
+  }
 
-  async onRoundEnd (accuracy: number): Promise<void> {
+  async onRoundEnd (): Promise<void> {
     console.log('on round end')
     await this.memory.updateWorkingModel(
       { taskID: this.task.id, name: this.task.trainingInformation.modelID },

discojs/discojs-core/src/training/trainer/trainer.ts

@@ -69,7 +69,8 @@ export abstract class Trainer {
     }
   }
 
-  protected onEpochBegin (epoch: number, logs?: tf.Logs): void {}
+  // TODO never used
+  protected onEpochBegin (_epoch: number, _logs?: tf.Logs): void {}
 
   /**
    * We update the training graph, this needs to be done on epoch end as there is no validation accuracy onBatchEnd.
@@ -88,15 +89,17 @@ export abstract class Trainer {
     }
   }
 
-  protected async onTrainBegin (logs?: tf.Logs): Promise<void> {
+  protected async onTrainBegin (_logs?: tf.Logs): Promise<void> {
     this.trainingInformant.addMessage('Training started.')
+    return await Promise.resolve()
   }
 
   /**
    * When the training ends this function will be call
    */
-  protected async onTrainEnd (logs?: tf.Logs): Promise<void> {
+  protected async onTrainEnd (_logs?: tf.Logs): Promise<void> {
     this.trainingInformant.addMessage('Training finished.')
+    return await Promise.resolve()
   }
 
   /**

discojs/discojs-core/src/validation/validator.ts

@@ -81,8 +81,8 @@ export class Validator {
           [],
           0
         ).arraySync()
-      } catch (e: any) {
-        console.error(e instanceof Error ? e.message : e.toString())
+      } catch (e) {
+        console.error(e instanceof Error ? e.message : e)
         throw new Error('Failed to compute the confusion matrix')
       }
     }

discojs/discojs-core/src/weights/aggregation.spec.ts

@@ -3,7 +3,7 @@ import { assert } from 'chai'
 import { WeightsContainer, aggregation } from './index.js'
 
 describe('weights aggregation', () => {
-  it('avg of weights with two operands', async () => {
+  it('avg of weights with two operands', () => {
     const actual = aggregation.avg([
       WeightsContainer.of([1, 2, 3, -1], [-5, 6]),
       WeightsContainer.of([2, 3, 7, 1], [-10, 5]),
@@ -14,7 +14,7 @@ describe('weights aggregation', () => {
     assert.isTrue(actual.equals(expected))
   })
 
-  it('sum of weights with two operands', async () => {
+  it('sum of weights with two operands', () => {
     const actual = aggregation.sum([
       [[3, -4], [9]],
       [[2, 13], [0]]
@@ -24,7 +24,7 @@ describe('weights aggregation', () => {
     assert.isTrue(actual.equals(expected))
   })
 
-  it('diff of weights with two operands', async () => {
+  it('diff of weights with two operands', () => {
     const actual = aggregation.diff([
       [[3, -4, 5], [9, 1]],
       [[2, 13, 4], [0, 1]]

discojs/discojs-node/package.json

@@ -7,7 +7,7 @@
   "scripts": {
     "watch": "nodemon --ext ts --ignore dist --watch ../discojs-core/dist --watch . --exec npm run",
     "build": "tsc",
-    "lint": "npx eslint --ext ts --max-warnings 0 .",
+    "lint": "npx eslint .",
     "test": "mocha",
     "docs": "typedoc ./src/imports.ts --theme oxide"
   },

discojs/discojs-web/package.json

@@ -7,7 +7,7 @@
   "scripts": {
     "watch": "nodemon --ext ts --ignore dist --watch ../discojs-core/dist --watch . --exec npm run",
     "build": "tsc",
-    "lint": "npx eslint --ext ts --max-warnings 0 .",
+    "lint": "npx eslint .",
     "test": ": nothing",
     "docs": "typedoc ./src/index.ts --theme oxide"
   },

docs/examples/custom_task.ts

@@ -32,7 +32,7 @@ const customTask: TaskProvider = {
     }
   },
 
-  async getModel () {
+  getModel () {
     const model = tf.sequential()
 
     model.add(
@@ -52,7 +52,7 @@ const customTask: TaskProvider = {
       metrics: ['accuracy']
     })
 
-    return new models.TFJS(model)
+    return Promise.resolve(new models.TFJS(model))
   }
 }
 

eslint.config.js → docs/examples/eslint.config.js

@@ -7,12 +7,13 @@ export default tseslint.config(
   eslint.configs.recommended,
   ...tseslint.configs.recommendedTypeChecked,
   {
+    files: ['*.ts'],
     languageOptions: {
       parserOptions: {
-        project: './tsconfig.eslint.json',
+        project: true,
         tsconfigRootDir: import.meta.dirname
       }
     }
   },
-  { ignores: ['**/dist/*'] }
+  { ignores: ['eslint.config.js', 'dist/*'] }
 )

docs/examples/package.json

@@ -7,7 +7,7 @@
     "train": "npm run build && node dist/training.js",
     "custom_task": "npm run build && node dist/custom_task.js",
     "build": "tsc",
-    "lint": "npx eslint --ext ts --max-warnings 0 .",
+    "lint": "npx eslint .",
     "test": "npm run train"
   },
   "license": "ISC",
@@ -17,12 +17,8 @@
     "@epfml/discojs-node": "*"
   },
   "devDependencies": {
-    "@typescript-eslint/eslint-plugin": "6",
     "eslint": "8",
-    "eslint-config-standard-with-typescript": "43",
-    "eslint-plugin-import": "2",
-    "eslint-plugin-n": "15",
-    "eslint-plugin-promise": "6",
-    "typescript": "4"
+    "typescript": "4",
+    "typescript-eslint": "7"
   }
 }

docs/examples/training.ts

@@ -78,7 +78,7 @@ async function loadSimpleFaceData (task: Task): Promise<data.DataSplit> {
 
   const filesPerFolder = [youngFiles, oldFiles]
 
-  const labels = filesPerFolder.flatMap((files, index) => Array(files.length).fill(index))
+  const labels = filesPerFolder.flatMap((files, index) => Array<string>(files.length).fill(`${index}`))
   const files = filesPerFolder.flat()
 
   return await new NodeImageLoader(task).loadAll(files, { labels })