tryin again

Project.toml

@@ -13,6 +13,7 @@ Flux = "587475ba-b771-5e3f-ad9e-33799f191a9c"
 MLJFlux = "094fc8d1-fd35-5302-93ea-dabda2abf845"
 MLJModelInterface = "e80e1ace-859a-464e-9ed9-23947d8ae3ea"
 MLUtils = "f1d291b0-491e-4a28-83b9-f70985020b54"
+Optimisers = "3bd65402-5787-11e9-1adc-39752487f4e2"
 ProgressMeter = "92933f4c-e287-5a05-a399-4b506db050ca"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 Reexport = "189a3867-3050-52da-a836-e630ba90ab69"
@@ -32,6 +33,7 @@ Flux = "0.13, 0.14"
 MLJFlux = "0.2, 0.3, 0.4, 0.5"
 MLJModelInterface = "1.8"
 MLUtils = "0.4"
+Optimisers = "0.3"
 ProgressMeter = "1.7"
 Random = "1.10"
 Reexport = "1.2.2"

src/mlj_flux.jl

@@ -2,6 +2,7 @@ using ComputationalResources
 using Flux
 using MLJFlux
 import MLJModelInterface as MMI
+using Optimisers
 using ProgressMeter
 using Random
 using Tables
@@ -31,7 +32,7 @@ function JointEnergyClassifier(
     sampler::AbstractSampler;
     builder::B = default_builder_jem,
     finaliser::F = Flux.softmax,
-    optimiser::O = Flux.Optimise.Adam(),
+    optimiser::O = Optimisers.Adam(),
     loss::L = Flux.crossentropy,
     epochs::Int = 100,
     batch_size::Int = 100,

test/Manifest.toml

@@ -2,7 +2,7 @@
 
 julia_version = "1.10.5"
 manifest_format = "2.0"
-project_hash = "e34d8ebf030e8e97a7b26a2e86c6cd2fc20b9053"
+project_hash = "e5df3295d4fa5526130a8cdbd54efe647549ccfe"
 
 [[deps.AbstractFFTs]]
 deps = ["LinearAlgebra"]