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jeremiahpslewisjeremiahpslewis
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Initial GPUArray transition (#1020)
* Drop LocalPreferences.toml from .gitignore * Transition Project.toml to GPUArrays * Support Metal in RLCore tests * Log GPU_Backend * Make tests work w/o CUDA * Fix CUDA import * Drop CUDA requirement * Make tests GPU aware * Drop CUDA from tests (keep in dependencies for now) * Drop CUDA from test dependencies * Add info statement Flux.GPU * Check if Apple silicon * Apple silicon check * Fix duplicate compat entry * Fix CUDA compat (allow v5) * Fix RLZoo compat * Add missing test import * Use julia-actions cache instead of generic Github one
1 parent 54ace04 commit 96bd7f0

13 files changed

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‎.github/workflows/ci.yml‎

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@@ -38,16 +38,7 @@ jobs:
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with:
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version: ${{ matrix.version }}
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arch: ${{ matrix.arch }}
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- uses: actions/cache@v4
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env:
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cache-name: cache-artifacts
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with:
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path: ~/.julia/artifacts
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key: ${{ runner.os }}-test-${{ env.cache-name }}-${{ hashFiles('**/Project.toml') }}
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restore-keys: |
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${{ runner.os }}-test-${{ env.cache-name }}-
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${{ runner.os }}-test-
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${{ runner.os }}-
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- uses: julia-actions/cache@v1
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- name: Get changed files
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id: RLBase-changed
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uses: tj-actions/changed-files@v42
@@ -86,16 +77,7 @@ jobs:
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with:
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version: ${{ matrix.version }}
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arch: ${{ matrix.arch }}
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- uses: actions/cache@v4
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env:
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cache-name: cache-artifacts
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with:
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path: ~/.julia/artifacts
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key: ${{ runner.os }}-test-${{ env.cache-name }}-${{ hashFiles('**/Project.toml') }}
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restore-keys: |
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${{ runner.os }}-test-${{ env.cache-name }}-
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${{ runner.os }}-test-
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${{ runner.os }}-
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- uses: julia-actions/cache@v1
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- name: Get changed files
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id: RLCore-changed
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uses: tj-actions/changed-files@v42
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with:
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version: ${{ matrix.version }}
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arch: ${{ matrix.arch }}
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- uses: actions/cache@v4
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env:
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cache-name: cache-artifacts
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with:
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path: ~/.julia/artifacts
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key: ${{ runner.os }}-test-${{ env.cache-name }}-${{ hashFiles('**/Project.toml') }}
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restore-keys: |
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${{ runner.os }}-test-${{ env.cache-name }}-
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${{ runner.os }}-test-
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${{ runner.os }}-
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- uses: julia-actions/cache@v1
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- name: Get changed files
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id: RLZoo-changed
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uses: tj-actions/changed-files@v42
@@ -190,16 +163,7 @@ jobs:
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with:
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version: ${{ matrix.version }}
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arch: ${{ matrix.arch }}
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- uses: actions/cache@v4
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env:
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cache-name: cache-artifacts
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with:
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path: ~/.julia/artifacts
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key: ${{ runner.os }}-test-${{ env.cache-name }}-${{ hashFiles('**/Project.toml') }}
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restore-keys: |
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${{ runner.os }}-test-${{ env.cache-name }}-
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${{ runner.os }}-test-
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${{ runner.os }}-
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- uses: julia-actions/cache@v1
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- name: Get changed files
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id: RLEnvironments-changed
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uses: tj-actions/changed-files@v42
@@ -245,17 +209,7 @@ jobs:
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with:
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version: ${{ matrix.version }}
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arch: ${{ matrix.arch }}
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- uses: actions/cache@v4
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env:
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cache-name: cache-artifacts
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with:
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path: ~/.julia/artifacts
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key: ${{ runner.os }}-test-${{ env.cache-name }}-${{ hashFiles('**/Project.toml') }}
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restore-keys: |
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${{ runner.os }}-test-${{ env.cache-name }}-
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${{ runner.os }}-test-
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${{ runner.os }}-
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- uses: julia-actions/cache@v1
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- name: Get changed files
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id: RLExperiments-changed
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uses: tj-actions/changed-files@v42

‎.gitignore‎

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@@ -33,6 +33,7 @@ docs/experiments
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# environment.
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Manifest.toml
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**/Manifest.toml
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LocalPreferences.toml
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.vscode/*
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tags
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# Persistent undo
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[._]*.un~
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‎src/ReinforcementLearningCore/Project.toml‎

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@@ -39,6 +39,7 @@ FillArrays = "0.8, 0.9, 0.10, 0.11, 0.12, 0.13, 1"
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Flux = "0.13, 0.14"
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Functors = "0.1, 0.2, 0.3, 0.4"
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GPUArrays = "8, 9, 10"
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Metal = "1.0"
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Parsers = "2"
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ProgressMeter = "1"
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Reexport = "1"
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[extras]
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CommonRLInterface = "d842c3ba-07a1-494f-bbec-f5741b0a3e98"
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DomainSets = "5b8099bc-c8ec-5219-889f-1d9e522a28bf"
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Metal = "dde4c033-4e86-420c-a63e-0dd931031962"
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Preferences = "21216c6a-2e73-6563-6e65-726566657250"
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Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
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Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
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UUIDs = "cf7118a7-6976-5b1a-9a39-7adc72f591a4"
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[targets]
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test = ["CommonRLInterface", "DomainSets", "Test", "Random"]
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test = ["CommonRLInterface", "DomainSets", "Metal", "Preferences", "Test", "UUIDs"]

‎src/ReinforcementLearningCore/test/runtests.jl‎

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@@ -1,12 +1,25 @@
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using Test
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using UUIDs
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using Preferences
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if Sys.isapple() && Sys.ARCH === :aarch64
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flux_uuid = UUID("587475ba-b771-5e3f-ad9e-33799f191a9c")
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set_preferences!(flux_uuid, "gpu_backend" => "Metal")
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using Metal
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else
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using CUDA, cuDNN
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end
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using ReinforcementLearningBase
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using ReinforcementLearningCore
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using ReinforcementLearningTrajectories
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using Test
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using CUDA
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using CircularArrayBuffers
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using Flux
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@info "Flux.GPU_BACKEND = $(Flux.GPU_BACKEND)"
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include("environments/randomwalk1D.jl")
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include("environments/tictactoe.jl")
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include("environments/rockpaperscissors.jl")

‎src/ReinforcementLearningCore/test/utils/device.jl‎

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@@ -5,7 +5,7 @@
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@test device(Conv((2, 2), 1 => 16, relu)) == Val(:cpu)
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@test device(Chain(x -> x .^ 2, Dense(2, 3))) == Val(:cpu)
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if CUDA.functional()
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if (@isdefined CUDA) && CUDA.functional()
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@test device(rand(2) |> gpu) isa CuDevice
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@test device(Dense(2, 3) |> gpu) isa CuDevice
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@test device(Conv((2, 2), 1 => 16, relu) |> gpu) isa CuDevice

‎src/ReinforcementLearningCore/test/utils/distributions.jl‎

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@@ -1,4 +1,4 @@
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using Test, LinearAlgebra, Distributions, CUDA, Flux
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using Test, LinearAlgebra, Distributions, Flux
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@testset "utils/distributions" begin
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@testset "logdetLorU" begin
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logdetM = logdet(M)
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@test logdetM == ReinforcementLearningCore.logdetLorU(L)
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@test logdetM == ReinforcementLearningCore.logdetLorU(U)
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if CUDA.functional()
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if (@isdefined CUDA) && CUDA.functional()
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L_d = cu(L)
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U_d = cu(U)
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@test logdetM == ReinforcementLearningCore.logdetLorU(L_d)
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end
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end
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@testset "CUDA" begin
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if CUDA.functional()
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if (@isdefined CUDA) && CUDA.functional()
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CUDA.allowscalar(false)
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#These only test GPU compatibility, exactness of results is tested above on the CPU
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@testset "Diagonal Gaussian" begin

‎src/ReinforcementLearningCore/test/utils/networks.jl‎

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using Test, Flux, CUDA, ChainRulesCore, LinearAlgebra, Distributions
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using Flux: params, gradient, unsqueeze
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using Test, Flux, ChainRulesCore, LinearAlgebra, Distributions, ReinforcementLearningCore
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using Flux: params, gradient, unsqueeze, InvDecay, gpu, cpu
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import ReinforcementLearningBase: RLBase
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@testset "Approximators" begin
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#= These may need to be updated due to recent changes
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@testset "TabularApproximator" begin
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end
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end
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@testset "CUDA" begin
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if CUDA.functional()
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if (@isdefined CUDA) && CUDA.functional()
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CUDA.allowscalar(false)
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gn = GaussianNetwork(Dense(20,15), Dense(15,10), Dense(15,10, softplus)) |> gpu
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state = rand(20,3) |> gpu #batch of 3 states
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end
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end
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@testset "CUDA" begin
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if CUDA.functional()
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if (@isdefined CUDA) && CUDA.functional()
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CUDA.allowscalar(false)
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rng = CUDA.CURAND.RNG()
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pre = Dense(20,15) |> gpu

‎src/ReinforcementLearningExperiments/Project.toml‎

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@@ -19,10 +19,11 @@ Weave = "44d3d7a6-8a23-5bf8-98c5-b353f8df5ec9"
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cuDNN = "02a925ec-e4fe-4b08-9a7e-0d78e3d38ccd"
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[compat]
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CUDA = "5"
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CUDA = "4, 5"
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Distributions = "0.25"
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Flux = "0.13, 0.14"
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IntervalSets = "0.7"
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Metal = "1.0"
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Reexport = "1"
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ReinforcementLearningBase = "0.12"
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ReinforcementLearningCore = "0.13.1"
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[extras]
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CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba"
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cuDNN = "02a925ec-e4fe-4b08-9a7e-0d78e3d38ccd"
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Metal = "dde4c033-4e86-420c-a63e-0dd931031962"
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Preferences = "21216c6a-2e73-6563-6e65-726566657250"
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Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
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UUIDs = "cf7118a7-6976-5b1a-9a39-7adc72f591a4"
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[targets]
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test = ["CUDA", "Test"]
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test = ["Metal", "Preferences", "Test", "UUIDs"]

‎src/ReinforcementLearningExperiments/deps/experiments/experiments/CFR/JuliaRL_DeepCFR_OpenSpiel.jl‎

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n_training_steps_Π = 2000,
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batchsize_V = 2048,
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batchsize_Π = 2048,
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initializer = glorot_normal(CUDA.CURAND.default_rng()),
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initializer = glorot_normal((@isdefined CUDA) && CUDA.functional() ? CUDA.CURAND.RNG() : rng),
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)
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Experiment(p, env, StopAfterStep(500, is_show_progress=!haskey(ENV, "CI")), EmptyHook(), "# run DeepcCFR on leduc_poker")
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end

‎src/ReinforcementLearningExperiments/deps/experiments/experiments/DQN/Dopamine_IQN_Atari.jl‎

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)
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rng = Random.default_rng()
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Random.seed!(rng, seed)
185-
device_rng = CUDA.functional() ? CUDA.CURAND.RNG() : rng
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device_rng = ((@isdefined CUDA) && CUDA.functional()) ? CUDA.CURAND.RNG() : rng
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Random.seed!(device_rng, isnothing(seed) ? nothing : hash(seed + 1))
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if isnothing(save_dir)

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