fix tests and ci.yml

Author: PasoStudio73

.github/workflows/CI.yml

@@ -1,49 +1,44 @@
 name: CI
 on:
-  pull_request:
-    branches:
-      - master
-      - dev
   push:
     branches:
-      - master
       - dev
-    tags: '*'
+    tags: ['*']
+  pull_request:
+  workflow_dispatch:
+concurrency:
+  # Skip intermediate builds: always.
+  # Cancel intermediate builds: only if it is a pull request build.
+  group: ${{ github.workflow }}-${{ github.ref }}
+  cancel-in-progress: ${{ startsWith(github.ref, 'refs/pull/') }}
 jobs:
   test:
-    name: Julia ${{ matrix.version }} - ${{ matrix.os }} - ${{ matrix.arch }} - ${{ github.event_name }}
+    name: Julia ${{ matrix.version }} - ${{ matrix.os }} - ${{ matrix.arch }}
     runs-on: ${{ matrix.os }}
+    timeout-minutes: 60
+    permissions: # needed to allow julia-actions/cache to proactively delete old caches that it has created
+      actions: write
+      contents: read
     strategy:
       fail-fast: false
       matrix:
         version:
-          - '1.6'
           - '1'
+          - 'lts'
         os:
           - ubuntu-latest
         arch:
           - x64
     steps:
-      - uses: actions/checkout@v2
-      - uses: julia-actions/setup-julia@v1
+      - uses: actions/checkout@v4
+      - uses: julia-actions/setup-julia@v2
         with:
           version: ${{ matrix.version }}
           arch: ${{ matrix.arch }}
-      - uses: actions/cache@v1
-        env:
-          cache-name: cache-artifacts
-        with:
-          path: ~/.julia/artifacts
-          key: ${{ runner.os }}-test-${{ env.cache-name }}-${{ hashFiles('**/Project.toml') }}
-          restore-keys: |
-            ${{ runner.os }}-test-${{ env.cache-name }}-
-            ${{ runner.os }}-test-
-            ${{ runner.os }}-
+      - uses: julia-actions/cache@v2
       - uses: julia-actions/julia-buildpkg@v1
       - uses: julia-actions/julia-runtest@v1
-        env:
-          JULIA_NUM_THREADS: '2'
       - uses: julia-actions/julia-processcoverage@v1
-      - uses: codecov/codecov-action@v1
+      - uses: codecov/codecov-action@v5
         with:
-          file: lcov.info
+          files: lcov.info

Project.toml

@@ -12,5 +12,18 @@ Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 
 [compat]
 Distributions = "0.25"
+LinearAlgebra = "1.11"
+MLJBase = "1.7 - 1.8"
 MLJTuning = "0.8"
+Random = "1"
 julia = "1"
+
+[extras]
+ComputationalResources = "ed09eef8-17a6-5b46-8889-db040fac31e3"
+EvoTrees = "f6006082-12f8-11e9-0c9c-0d5d367ab1e5"
+MLJ = "add582a8-e3ab-11e8-2d5e-e98b27df1bc7"
+StableRNGs = "860ef19b-820b-49d6-a774-d7a799459cd3"
+Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
+
+[targets]
+test = ["ComputationalResources", "EvoTrees", "MLJ", "StableRNGs", "Test"]

test/runtests.jl

@@ -1,3 +1,6 @@
+using Distributed
+addprocs(2)
+
 @everywhere begin
     using MLJParticleSwarmOptimization
     using Random
@@ -6,7 +9,6 @@
     using Distributions
     using EvoTrees
     using MLJ
-    using MLJBase
     using MLJTuning
     using StableRNGs
 end

test/strategies/adaptive.jl

@@ -82,7 +82,7 @@ for acceleration in modes
     @testset "EvoTree Tuning with AdaptiveParticleSwarm and $(typeof(acceleration))" begin
         rng = StableRNG(123)
         features = rand(rng, 10_000) .* 5 .- 2
-        X = MLJBase.table(reshape(features, (size(features)[1], 1)))
+        X = MLJ.table(reshape(features, (size(features)[1], 1)))
         y = sin.(features) .* 0.5 .+ 0.5
         y = EvoTrees.logit(y) + randn(rng, size(y))
         y = EvoTrees.sigmoid(y)
@@ -128,4 +128,4 @@ for acceleration in modes
 end
 
 println("Adaptive PSO losses (see Issue #14):")
-(; modes=modes, losses=losses) |> MLJBase.pretty
+(; modes=modes, losses=losses) |> MLJ.pretty

test/strategies/basic.jl

@@ -18,7 +18,7 @@ for acceleration in (CPU1(), CPUProcesses(), CPUThreads())
     @testset "EvoTree Tuning with ParticleSwarm and $(typeof(acceleration))" begin
         rng = StableRNG(123)
         features = rand(rng, 10_000) .* 5 .- 2
-        X = MLJBase.table(reshape(features, (size(features)[1], 1)))
+        X = MLJ.table(reshape(features, (size(features)[1], 1)))
         y = sin.(features) .* 0.5 .+ 0.5
         y = EvoTrees.logit(y) + randn(rng, size(y))
         y = EvoTrees.sigmoid(y)