Format .jl files (#83)

Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>

src/implementations/environments.jl

@@ -159,7 +159,8 @@ mutable struct MaxTimeoutEnv{E<:AbstractEnv} <: AbstractEnv
     current_t::Int
 end
 
-MaxTimeoutEnv(env::E, max_t::Int; current_t::Int = 1) where E<:AbstractEnv = MaxTimeoutEnv(E, max_t, current_t)
+MaxTimeoutEnv(env::E, max_t::Int; current_t::Int = 1) where {E<:AbstractEnv} =
+    MaxTimeoutEnv(E, max_t, current_t)
 
 function (env::MaxTimeoutEnv)(args...; kwargs...)
     env.env(args...; kwargs...)
@@ -195,19 +196,25 @@ end
 `processors` will be applied to the `action` before sending it to the inner environment.
 The same effect like `env(action |> processors)`.
 """
-ActionTransformedEnv(processors...;mapping=identity) = env -> ActionTransformedEnv(processors, mapping, env)
+ActionTransformedEnv(processors...; mapping = identity) =
+    env -> ActionTransformedEnv(processors, mapping, env)
 
 for f in vcat(ENV_API, MULTI_AGENT_ENV_API)
     if f ∉ (:get_actions, :get_legal_actions)
-        @eval $f(x::ActionTransformedEnv, args...; kwargs...) = $f(x.env, args...; kwargs...)
+        @eval $f(x::ActionTransformedEnv, args...; kwargs...) =
+            $f(x.env, args...; kwargs...)
     end
 end
 
-get_actions(env::ActionTransformedEnv{<:Any, typeof(identity)}, args...) = get_actions(env.env, args...)
-get_legal_actions(env::ActionTransformedEnv{<:Any, typeof(identity)}, args...) = get_legal_actions(env.env, args...)
+get_actions(env::ActionTransformedEnv{<:Any,typeof(identity)}, args...) =
+    get_actions(env.env, args...)
+get_legal_actions(env::ActionTransformedEnv{<:Any,typeof(identity)}, args...) =
+    get_legal_actions(env.env, args...)
 
-get_actions(env::ActionTransformedEnv, args...) = map(env.mapping, get_actions(env.env, args...))
-get_legal_actions(env::ActionTransformedEnv, args...) = map(env.mapping, get_legal_actions(env.env, args...))
+get_actions(env::ActionTransformedEnv, args...) =
+    map(env.mapping, get_actions(env.env, args...))
+get_legal_actions(env::ActionTransformedEnv, args...) =
+    map(env.mapping, get_legal_actions(env.env, args...))
 
 (env::ActionTransformedEnv)(action, args...; kwargs...) =
     env.env(foldl(|>, env.processors; init = action), args...; kwargs...)

src/implementations/policies.jl

@@ -40,7 +40,8 @@ RandomPolicy(::FullActionSet, env::AbstractEnv, rng) = RandomPolicy(nothing, rng
 # Ideally we should return a Categorical distribution.
 # But this means we need to introduce an extra dependency of Distributions
 # watch https://github.com/JuliaStats/Distributions.jl/issues/1139
-get_prob(p::RandomPolicy{<:VectSpace}, env::MultiThreadEnv) = [fill(1/length(s), length(s)) for s in p.action_space]
+get_prob(p::RandomPolicy{<:VectSpace}, env::MultiThreadEnv) =
+    [fill(1 / length(s), length(s)) for s in p.action_space]
 get_prob(p::RandomPolicy, env::MultiThreadEnv) = [get_prob(p, x) for x in env]
 get_prob(p::RandomPolicy, env) = fill(1 / length(p.action_space), length(p.action_space))
 get_prob(p::RandomPolicy{Nothing}, env) = get_prob(p, env, ChanceStyle(env))

src/interface.jl

@@ -46,7 +46,8 @@ Get the probability distribution of actions based on policy `π` given an `env`.
 
 Only valid for environments with discrete action space.
 """
-@api get_prob(π::AbstractPolicy, env, action) = get_prob(π, env)[findfirst(==(action), get_actions(env))]
+@api get_prob(π::AbstractPolicy, env, action) =
+    get_prob(π, env)[findfirst(==(action), get_actions(env))]
 
 """
     get_priority(π::AbstractPolicy, experience)

test/base.jl

@@ -7,9 +7,10 @@
     run(policy, env)
     @test get_terminal(env)
 
-    discrete_env =  env |> ActionTransformedEnv(
-        a -> get_actions(env)[a];  # action index to action
-        mapping = x -> Dict(x => i for (i, a) in enumerate(get_actions(env)))[x] # arbitrary vector to DiscreteSpace
+    discrete_env =
+        env |> ActionTransformedEnv(
+            a -> get_actions(env)[a];  # action index to action
+            mapping = x -> Dict(x => i for (i, a) in enumerate(get_actions(env)))[x], # arbitrary vector to DiscreteSpace
         )
     policy = RandomPolicy(discrete_env)
     reset!(discrete_env)