Merge pull request #259 from FluxML/dev

For a 0.5.0 release

.github/workflows/ci.yml

@@ -19,6 +19,7 @@ jobs:
       fail-fast: false
       matrix:
         version:
+          - '1.9'
           - '1'
         os:
           - ubuntu-latest

.github/workflows/documenter.yml

@@ -0,0 +1,30 @@
+name: Documentation
+
+on:
+  push:
+    branches:
+      - dev
+      - instate-docs
+    tags: '*'
+  pull_request:
+
+jobs:
+  build:
+    permissions:
+      contents: write
+      pull-requests: read
+      statuses: write
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+      - uses: julia-actions/setup-julia@v2
+        with:
+          version: '1.10'
+      - uses: julia-actions/cache@v1
+      - name: Install dependencies
+        run: julia --project=docs/ -e 'using Pkg; Pkg.develop(PackageSpec(path=pwd())); Pkg.instantiate()'
+      - name: Build and deploy
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} # If authenticating with GitHub Actions token
+          DOCUMENTER_KEY: ${{ secrets.DOCUMENTER_KEY }} # If authenticating with SSH deploy key
+        run: julia --project=docs/ docs/make.jl

.gitignore

@@ -6,4 +6,5 @@
 .DS_Store
 sandbox/
 docs/build
-/examples/mnist/mnist_machine*
+/examples/mnist/mnist_machine*
+Manifest.toml

Project.toml

@@ -1,7 +1,7 @@
 name = "MLJFlux"
 uuid = "094fc8d1-fd35-5302-93ea-dabda2abf845"
 authors = ["Anthony D. Blaom <[email protected]>", "Ayush Shridhar <[email protected]>"]
-version = "0.4.0"
+version = "0.5.0"
 
 [deps]
 CategoricalArrays = "324d7699-5711-5eae-9e2f-1d82baa6b597"
@@ -10,6 +10,7 @@ ComputationalResources = "ed09eef8-17a6-5b46-8889-db040fac31e3"
 Flux = "587475ba-b771-5e3f-ad9e-33799f191a9c"
 MLJModelInterface = "e80e1ace-859a-464e-9ed9-23947d8ae3ea"
 Metalhead = "dbeba491-748d-5e0e-a39e-b530a07fa0cc"
+Optimisers = "3bd65402-5787-11e9-1adc-39752487f4e2"
 ProgressMeter = "92933f4c-e287-5a05-a399-4b506db050ca"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
@@ -21,23 +22,24 @@ ColorTypes = "0.10.3, 0.11"
 ComputationalResources = "0.3.2"
 Flux = "0.14"
 MLJModelInterface = "1.1.1"
-Metalhead = "0.9"
+Metalhead = "0.9.3"
+Optimisers = "0.3.2"
 ProgressMeter = "1.7.1"
 StatisticalMeasures = "0.1"
+Statistics = "<0.0.1, 1"
 Tables = "1.0"
 julia = "1.9"
 
 [extras]
 CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba"
-cuDNN = "02a925ec-e4fe-4b08-9a7e-0d78e3d38ccd"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 MLJBase = "a7f614a8-145f-11e9-1d2a-a57a1082229d"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 StableRNGs = "860ef19b-820b-49d6-a774-d7a799459cd3"
 StatisticalMeasures = "a19d573c-0a75-4610-95b3-7071388c7541"
-Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
+cuDNN = "02a925ec-e4fe-4b08-9a7e-0d78e3d38ccd"
 
 [targets]
-test = ["CUDA", "cuDNN", "LinearAlgebra", "MLJBase", "Random", "StableRNGs", "StatisticalMeasures", "Statistics", "StatsBase", "Test"]
+test = ["CUDA", "cuDNN", "LinearAlgebra", "MLJBase", "Random", "StableRNGs", "StatisticalMeasures", "StatsBase", "Test"]

README.md

@@ -50,10 +50,6 @@ and this will require familiarity with the [Flux
 API](https://fluxml.ai/Flux.jl/stable/) for defining a neural network
 chain.
 
-In the future MLJFlux may provide a larger assortment of canned
-builders. Pull requests introducing new ones are most welcome.
-
-
 ### Installation
 
 ```julia
@@ -197,7 +193,7 @@ with caution.
 
 Instructions for coercing common image formats into some
 `AbstractVector{<:Image}` are
-[here](https://alan-turing-institute.github.io/MLJScientificTypes.jl/dev/#Type-coercion-for-image-data-1).
+[here](https://juliaai.github.io/ScientificTypes.jl/dev/#Type-coercion-for-image-data).
 
 
 ### Warm restart
@@ -250,15 +246,6 @@ to builders for the purposes of weight initialization. This can be
 any `AbstractRNG` or the seed (integer) for a `MersenneTwister` that
 will be reset on every cold restart of model (machine) training.
 
-Until there is a [mechanism for
-doing so](https://github.com/FluxML/Flux.jl/issues/1617) `rng` is *not*
-passed to dropout layers and one must manually seed the `GLOBAL_RNG`
-for reproducibility purposes, when using a builder that includes
-`Dropout` (such as `MLJFlux.Short`). If training models on a
-GPU (i.e., `acceleration isa CUDALibs`) one must additionally call
-`CUDA.seed!(...)`.
-
-
 ### Built-in builders
 
 The following builders are provided out-of-the-box. Query their

docs/.gitignore

@@ -0,0 +1,2 @@
+build/
+site/