Move UnicodePlots to extension (#1088)

* Update Flux and GPUArrays compatibility in Project.toml; refactor FluxApproximator and TargetNetwork implementations

* Refactor target network optimization and update test assertions for consistency

* Simplify FluxApproximator's optimise! method by using a single-line function definition

* Bump version to 0.15.4 in Project.toml

* Update NEWS.md for v0.15.4: Upgrade Flux.jl to v0.16 and resolve deprecation warnings

* Add Conda dependency and update test environment setup

* Update test environment setup to use pip for gym installation

* Fix RLEnv tests

* Fix optimizer reference in stock trading environment example

* Fix optimizer reference in stock trading environment example

* Refactor optimizer implementation in DDPGPolicy to use OptimiserChain

* Refactor UnicodePlots integration into extension

* Move UnicodePlots to package extension in release notes

Author: jeremiahpslewis

src/ReinforcementLearningCore/NEWS.md

@@ -1,5 +1,9 @@
 # ReinforcementLearningCore.jl Release Notes
 
+#### v0.15.5
+
+- Move `UnicodePlots` to package extension
+
 #### v0.15.4
 
 - Update `Flux.jl` to `v0.16` and fix deprecation warnings and method errors

src/ReinforcementLearningCore/Project.toml

@@ -4,7 +4,6 @@ version = "0.15.4"
 
 [deps]
 AbstractTrees = "1520ce14-60c1-5f80-bbc7-55ef81b5835c"
-Adapt = "79e6a3ab-5dfb-504d-930d-738a2a938a0e"
 ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
 CircularArrayBuffers = "9de3a189-e0c0-4e15-ba3b-b14b9fb0aec1"
 Crayons = "a8cc5b0e-0ffa-5ad4-8c14-923d3ee1735f"
@@ -21,11 +20,15 @@ ReinforcementLearningTrajectories = "6486599b-a3cd-4e92-a99a-2cea90cc8c3c"
 Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
 TimerOutputs = "a759f4b9-e2f1-59dc-863e-4aeb61b1ea8f"
+
+[weakdeps]
 UnicodePlots = "b8865327-cd53-5732-bb35-84acbb429228"
 
+[extensions]
+UnicodePlotsExt = "UnicodePlots"
+
 [compat]
 AbstractTrees = "0.3, 0.4"
-Adapt = "3, 4"
 ChainRulesCore = "1"
 CircularArrayBuffers = "0.1.12"
 Crayons = "4"
@@ -57,4 +60,4 @@ UUIDs = "cf7118a7-6976-5b1a-9a39-7adc72f591a4"
 cuDNN = "02a925ec-e4fe-4b08-9a7e-0d78e3d38ccd"
 
 [targets]
-test = ["CommonRLInterface", "CUDA", "cuDNN", "DomainSets", "Metal", "Preferences", "ReinforcementLearningEnvironments", "Test", "UUIDs"]
+test = ["CommonRLInterface", "CUDA", "cuDNN", "DomainSets", "Metal", "Preferences", "ReinforcementLearningEnvironments", "Test", "UnicodePlots", "UUIDs"]

src/ReinforcementLearningCore/ext/UnicodePlotsExt.jl

@@ -0,0 +1,18 @@
+module UnicodePlotsExt
+    using ReinforcementLearningCore
+    using UnicodePlots: lineplot, lineplot!
+
+    function Base.show(io::IO, hook::TotalRewardPerEpisode{true, F}) where {F<:Number}
+        if length(hook.rewards) > 0
+            println(io, lineplot(
+                hook.rewards,
+                title="Total reward per episode",
+                xlabel="Episode",
+                ylabel="Score",
+            ))
+        else
+            println(io, typeof(hook))
+        end
+        return
+    end
+end

src/ReinforcementLearningCore/src/core/hooks.jl

@@ -10,7 +10,6 @@ export AbstractHook,
     DoEveryNSteps,
     DoOnExit
 
-using UnicodePlots: lineplot, lineplot!
 using Statistics: mean, std
 using CircularArrayBuffers: CircularVectorBuffer
 import ReinforcementLearningBase: RLBase
@@ -172,20 +171,6 @@ function Base.push!(hook::TotalRewardPerEpisode,
     return
 end
 
-function Base.show(io::IO, hook::TotalRewardPerEpisode{true, F}) where {F<:Number}
-    if length(hook.rewards) > 0
-        println(io, lineplot(
-            hook.rewards,
-            title="Total reward per episode",
-            xlabel="Episode",
-            ylabel="Score",
-        ))
-    else
-        println(io, typeof(hook))
-    end
-    return
-end
-
 function Base.push!(hook::TotalRewardPerEpisode{true, F}, 
     ::PostExperimentStage,
     agent::AbstractPolicy,

src/ReinforcementLearningCore/test/runtests.jl

@@ -1,4 +1,5 @@
 using Test
+using UnicodePlots
 using UUIDs
 using Preferences