add mlutils docs dep

docs/Project.toml

@@ -11,6 +11,7 @@ Juniper = "2ddba703-00a4-53a7-87a5-e8b9971dde84"
 Lux = "b2108857-7c20-44ae-9111-449ecde12c47"
 Manifolds = "1cead3c2-87b3-11e9-0ccd-23c62b72b94e"
 Manopt = "0fc0a36d-df90-57f3-8f93-d78a9fc72bb5"
+MLUtils = "f1d291b0-491e-4a28-83b9-f70985020b54"
 ModelingToolkit = "961ee093-0014-501f-94e3-6117800e7a78"
 NLPModels = "a4795742-8479-5a88-8948-cc11e1c8c1a6"
 NLPModelsTest = "7998695d-6960-4d3a-85c4-e1bceb8cd856"
@@ -33,6 +34,8 @@ OptimizationPRIMA = "72f8369c-a2ea-4298-9126-56167ce9cbc2"
 OptimizationPolyalgorithms = "500b13db-7e66-49ce-bda4-eed966be6282"
 OptimizationSpeedMapping = "3d669222-0d7d-4eb9-8a9f-d8528b0d9b91"
 OrdinaryDiffEq = "1dea7af3-3e70-54e6-95c3-0bf5283fa5ed"
+Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
+Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 ReverseDiff = "37e2e3b7-166d-5795-8a7a-e32c996b4267"
 SciMLBase = "0bca4576-84f4-4d90-8ffe-ffa030f20462"
 SciMLSensitivity = "1ed8b502-d754-442c-8d5d-10ac956f44a1"
@@ -53,6 +56,7 @@ Juniper = "0.9"
 Lux = "1"
 Manifolds = "0.9"
 Manopt = "0.4"
+MLUtils = "0.4.4"
 ModelingToolkit = "9"
 NLPModels = "0.21"
 NLPModelsTest = "0.10"
@@ -75,6 +79,8 @@ OptimizationPRIMA = "0.3"
 OptimizationPolyalgorithms = "0.3"
 OptimizationSpeedMapping = "0.3"
 OrdinaryDiffEq = "6"
+Plots = "1"
+Random = "1"
 ReverseDiff = ">= 1.9.0"
 SciMLBase = "2.30.0"
 SciMLSensitivity = "7"

docs/src/tutorials/minibatch.md

@@ -9,7 +9,8 @@ It is possible to solve an optimization problem with batches using a `MLUtils.Da
 
 ```@example minibatch
 
-using Lux, Optimization, OptimizationOptimisers, OrdinaryDiffEq, SciMLSensitivity, MLUtils
+using Lux, Optimization, OptimizationOptimisers, OrdinaryDiffEq, SciMLSensitivity, MLUtils,
+      Random
 
 function newtons_cooling(du, u, p, t)
     temp = u[1]