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Add PrecompileTools #18

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Add PrecompileTools #18

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3da141f
Add PrecompileTools
vchuravy Jun 28, 2024
b6897d3
Minor changes to support Julia 1.11
pxl-th Jul 2, 2024
87144c1
Compile workload
pxl-th Jul 3, 2024
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5 changes: 3 additions & 2 deletions Project.toml
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Original file line number Diff line number Diff line change
Expand Up @@ -4,13 +4,13 @@ authors = ["Anton Smirnov <tonysmn97@gmail.com>"]
version = "0.1.4"

[deps]
AMDGPU = "21141c5a-9bdb-4563-92ae-f87d6854732e"
Adapt = "79e6a3ab-5dfb-504d-930d-738a2a938a0e"
BSON = "fbb218c0-5317-5bc6-957e-2ee96dd4b1f0"
BenchmarkTools = "6e4b80f9-dd63-53aa-95a3-0cdb28fa8baf"
CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba"
ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
FileIO = "5789e2e9-d7fb-5bc7-8068-2c6fae9b9549"
GPUCompiler = "61eb1bfa-7361-4325-ad38-22787b887f55"
ImageCore = "a09fc81d-aa75-5fe9-8630-4744c3626534"
ImageMagick = "6218d12a-5da1-5696-b52f-db25d2ecc6d1"
ImageTransformations = "02fcd773-0e25-5acc-982a-7f6622650795"
Expand All @@ -19,6 +19,7 @@ JpegTurbo = "b835a17e-a41a-41e7-81f0-2f016b05efe0"
KernelAbstractions = "63c18a36-062a-441e-b654-da1e3ab1ce7c"
LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
NerfUtils = "99c1d5ce-7c61-4a25-a107-a5ade2e2a8e4"
PrecompileTools = "aea7be01-6a6a-4083-8856-8a6e6704d82a"
Preferences = "21216c6a-2e73-6563-6e65-726566657250"
Quaternions = "94ee1d12-ae83-5a48-8b1c-48b8ff168ae0"
Rotations = "6038ab10-8711-5258-84ad-4b1120ba62dc"
Expand All @@ -27,7 +28,6 @@ Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
Zygote = "e88e6eb3-aa80-5325-afca-941959d7151f"

[compat]
AMDGPU = "0.8"
Adapt = "4"
BSON = "0.3"
BenchmarkTools = "1.3.2"
Expand All @@ -41,6 +41,7 @@ JSON = "0.21"
JpegTurbo = "0.1"
KernelAbstractions = "0.9"
NerfUtils = "0.1.5"
PrecompileTools = "1.2.1"
Preferences = "1.4"
Quaternions = "0.7"
Rotations = "1.6"
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2 changes: 0 additions & 2 deletions benchmark/pipeline.jl
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Expand Up @@ -7,14 +7,12 @@ const Backend = Nerf.Backend

function trainer_benchmark(trainer::Nerf.Trainer, n::Int)
for i in 1:n
Core.println(i)
Nerf.step!(trainer)
end
end

function render_benchmark(renderer::Nerf.Renderer, trainer::Nerf.Trainer, n::Int)
for i in 1:n
Core.println(i)
Nerf.render!(trainer.model, renderer, trainer.occupancy, trainer.bbox)
end
end
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24 changes: 24 additions & 0 deletions src/Nerf.jl
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Expand Up @@ -115,4 +115,28 @@ function main()
return
end

using PrecompileTools

@setup_workload let
config_file = joinpath(pkgdir(Nerf), "data", "raccoon_sofa2", "transforms.json")
dataset = Dataset(Backend; config_file)
model = BasicModel(BasicField(Backend))

trainer = Trainer(model, dataset; n_rays=128)
camera = Camera(MMatrix{3, 4, Float32}(I), dataset.intrinsics)
renderer = Renderer(Backend, camera, trainer.bbox, trainer.cone)

pose_idx = clamp(round(Int, rand() * length(dataset)), 1, length(dataset))
NU.set_projection!(camera, get_pose(dataset, pose_idx)...)

@compile_workload begin
for _ in 1:20
step!(trainer)
end
render!(renderer, trainer.occupancy, trainer.bbox) do points, directions
model(points, directions)
end
end
end

end
2 changes: 1 addition & 1 deletion src/kautils.jl
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Expand Up @@ -6,7 +6,7 @@ function is_valid_backend(name::String)
""")
end

backend_name() = is_valid_backend(@load_preference("backend", "AMDGPU"))
backend_name() = is_valid_backend(@load_preference("backend", "CUDA"))

function set_backend!(name::String)::Bool
backend_name() == name && return false
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