Merge pull request #127 from FluxML/dev

For a 0.1.10 release

.github/workflows/CompatHelper.yml

@@ -1,7 +1,7 @@
 name: CompatHelper
 on:
   schedule:
-    - cron: '00 00 * * *'
+    - cron: 0 0 * * *
   workflow_dispatch:
 jobs:
   CompatHelper:
@@ -12,5 +12,5 @@ jobs:
       - name: CompatHelper.main()
         env:
           GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
-          COMPATHELPER_PRIV: ${{ secrets.COMPATHELPER_PRIV }}  # optional
-        run: julia -e 'using CompatHelper; CompatHelper.main()'
+          COMPATHELPER_PRIV: ${{ secrets.COMPATHELPER_PRIV }}
+        run: julia -e 'using CompatHelper; CompatHelper.main()'

.github/workflows/ci.yml

@@ -18,7 +18,9 @@ jobs:
       matrix:
         version:
           - '1.3'
+          - '1.4'
           - '1'
+          - 'nightly'
         os:
           - ubuntu-latest
         arch:

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 = "0.1.9"
+version = "0.1.10"
 
 [deps]
 CategoricalArrays = "324d7699-5711-5eae-9e2f-1d82baa6b597"
@@ -18,9 +18,9 @@ Tables = "bd369af6-aec1-5ad0-b16a-f7cc5008161c"
 CategoricalArrays = "^0.8.1,^0.9"
 ColorTypes = "^0.10.3"
 ComputationalResources = "^0.3.2"
-Flux = "^0.10.4, ^0.11"
+Flux = "^0.10.4, ^0.11, 0.12"
 LossFunctions = "^0.5, ^0.6"
-MLJModelInterface = "^0.4.1"
+MLJModelInterface = "^0.4.1, 1"
 ProgressMeter = "^1.1"
 Tables = "^1.0"
 julia = "^1.3"

README.md

@@ -65,11 +65,13 @@ Pkg.add("RDatasets")  # for the demo below
 Following is an introductory example using a default builder and no
 standardization of input features ([notebook/script](/examples/iris)).
 
-For a more advanced illustration, see the [MNIST dataset
+For an example implementing early stopping and snapshots, using MLJ's
+[`IteratedModel`
+wrapper](https://alan-turing-institute.github.io/MLJ.jl/dev/controlling_iterative_models/),
+see the [MNIST dataset
 example](https://github.com/FluxML/MLJFlux.jl/blob/dev/examples/mnist).
 
 
-
 #### Loading some data and instantiating a model
 
 ```julia
@@ -365,8 +367,8 @@ you *should* use MLJ loss functions in MLJ meta-algorithms.
 
 ### An image classification example
 
-An expanded version of this example, with early stopping, is available
-[here](/examples/mnist).
+An expanded version of this example, with early stopping and
+snapshots, is available [here](/examples/mnist).
 
 We define a builder that builds a chain with six alternating
 convolution and max-pool layers, and a final dense layer, which we