fix tests

JuliaReinforcementLearning · Oct 11, 2023 · cf89b5c · cf89b5c
1 parent 365201c
commit cf89b5c
Show file tree

Hide file tree

Showing 9 changed files with 9 additions and 11 deletions.
diff --git a/src/ReinforcementLearningCore/src/policies/random_policy.jl b/src/ReinforcementLearningCore/src/policies/random_policy.jl
@@ -24,7 +24,7 @@ RandomPolicy(s = nothing; rng = Random.default_rng()) = RandomPolicy(s, rng)
 
 RLBase.optimise!(::RandomPolicy, x::NamedTuple) = nothing
 
-RLBase.plan!(p::RandomPolicy{S,RNG}, env::AbstractEnv) where {S,RNG<:AbstractRNG} = rand.(p.rng, p.action_space)
+RLBase.plan!(p::RandomPolicy{S,RNG}, env::AbstractEnv) where {S,RNG<:AbstractRNG} = rand(p.rng, p.action_space)
 
 function RLBase.plan!(p::RandomPolicy{Nothing,RNG}, env::AbstractEnv) where {RNG<:AbstractRNG}
     legal_action_space_ = RLBase.legal_action_space(env)
@@ -33,7 +33,7 @@ end
 
 function RLBase.plan!(p::RandomPolicy{Nothing,RNG}, env::E, player::Symbol) where {E<:AbstractEnv, RNG<:AbstractRNG}
     legal_action_space_ = RLBase.legal_action_space(env, player)
-    return rand.(p.rng, legal_action_space_)
+    return rand(p.rng, legal_action_space_)
 end
 
 #####

diff --git a/src/ReinforcementLearningCore/test/core/base.jl b/src/ReinforcementLearningCore/test/core/base.jl
@@ -1,4 +1,4 @@
-using ReinforcementLearningCore
+#using ReinforcementLearningCore
 using ReinforcementLearningBase
 using TimerOutputs
 

diff --git a/src/ReinforcementLearningCore/test/core/stop_conditions.jl b/src/ReinforcementLearningCore/test/core/stop_conditions.jl
@@ -1,4 +1,4 @@
-using ReinforcementLearningCore: check_stop
+import ReinforcementLearningCore.check_stop
 
 @testset "StopAfterStep" begin
     stop_condition = StopAfterStep(10)

diff --git a/src/ReinforcementLearningCore/test/policies/agent.jl b/src/ReinforcementLearningCore/test/policies/agent.jl
@@ -1,6 +1,5 @@
 using ReinforcementLearningBase, ReinforcementLearningEnvironments
-using ReinforcementLearningCore: SRT
-using ReinforcementLearningCore
+import ReinforcementLearningCore.SRT
 
 @testset "agent.jl" begin
     @testset "Agent Tests" begin

diff --git a/src/ReinforcementLearningCore/test/policies/multi_agent.jl b/src/ReinforcementLearningCore/test/policies/multi_agent.jl
@@ -1,7 +1,6 @@
 using Test
 using ReinforcementLearningEnvironments
 using ReinforcementLearningTrajectories
-using ReinforcementLearningCore
 using ReinforcementLearningBase
 using DomainSets
 

diff --git a/src/ReinforcementLearningCore/test/runtests.jl b/src/ReinforcementLearningCore/test/runtests.jl
@@ -1,5 +1,5 @@
 using ReinforcementLearningBase
-using ReinforcementLearningCore
+#using ReinforcementLearningCore
 using ReinforcementLearningEnvironments
 using ReinforcementLearningTrajectories
 

diff --git a/src/ReinforcementLearningCore/test/utils/distributions.jl b/src/ReinforcementLearningCore/test/utils/distributions.jl
@@ -1,4 +1,4 @@
-using Test, LinearAlgebra, Distributions, ReinforcementLearningCore, CUDA, Flux
+using Test, LinearAlgebra, Distributions, CUDA, Flux
 
 @testset "utils/distributions" begin
     @testset "logdetLorU" begin

diff --git a/src/ReinforcementLearningCore/test/utils/networks.jl b/src/ReinforcementLearningCore/test/utils/networks.jl
@@ -1,4 +1,4 @@
-using Test, Flux, CUDA, ChainRulesCore, LinearAlgebra, Distributions, ReinforcementLearningCore
+using Test, Flux, CUDA, ChainRulesCore, LinearAlgebra, Distributions
 using Flux: params, gradient, unsqueeze
 @testset "Approximators" begin
     #= These may need to be updated due to recent changes

diff --git a/...tLearningExperiments/deps/experiments/experiments/Policy Gradient/JuliaRL_SAC_Pendulum.jl b/...tLearningExperiments/deps/experiments/experiments/Policy Gradient/JuliaRL_SAC_Pendulum.jl
@@ -67,7 +67,7 @@ function RLCore.Experiment(
             γ=0.99f0,
             α=0.2f0,
             start_steps=1000,
-            start_policy=RandomPolicy([-1.0 .. 1.0 for _ in 1:na]; rng=rng),
+            start_policy=RandomPolicy(-1.0 .. 1.0; rng=rng),
             automatic_entropy_tuning=true,
             lr_alpha=0.003f0,
             action_dims=action_dims,