Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

feat: bump jll version and add opt pass #400

Merged
merged 3 commits into from
Dec 19, 2024
Merged

feat: bump jll version and add opt pass #400

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
3 commits
Select commit Hold shift + click to select a range
1c9e3e8
feat: bump jll version and add opt pass
avik-pal Dec 19, 2024
edf2d71
fix: return types for Enzyme ForwardDiff
avik-pal Dec 19, 2024
242cfdf
fix: missing promote_to in NNlibExt
avik-pal Dec 19, 2024
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion Project.toml
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -57,7 +57,7 @@ Preferences = "1.4"
Random = "1.10"
Random123 = "1.7"
ReactantCore = "0.1.3"
Reactant_jll = "0.0.26"
Reactant_jll = "0.0.27"
Scratch = "1.2"
Statistics = "1.10"
YaoBlocks = "0.13"
Expand Down
30 changes: 16 additions & 14 deletions ext/ReactantNNlibExt.jl
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -4,7 +4,8 @@ using NNlib
using GPUArraysCore: @allowscalar
using Reactant: Reactant, Ops, TracedRArray, AnyTracedRArray, MLIR, TracedRNumber

using Reactant.TracedUtils: materialize_traced_array, get_mlir_data, set_mlir_data!
using Reactant.TracedUtils:
TracedUtils, materialize_traced_array, get_mlir_data, set_mlir_data!

using ReactantCore: @trace
using LinearAlgebra: LinearAlgebra, triu
Expand All @@ -20,8 +21,8 @@ end
function NNlib.softmax!(out::TracedRArray{T,N}, x::AbstractArray; dims=1) where {T,N}
max_ = NNlib.fast_maximum(x; dims)
# XXX: Once reverse mode of if is properly supported, we can make it @trace
# zero_num = Reactant.promote_to(TracedRNumber{T}, 0)
# one_num = Reactant.promote_to(TracedRNumber{T}, 1)
# zero_num = TracedUtils.promote_to(TracedRNumber{T}, 0)
# one_num = TracedUtils.promote_to(TracedRNumber{T}, 1)
# @trace if all(isfinite, max_)
@. out = exp(x - max_)
# else
Expand All @@ -37,8 +38,8 @@ end
function NNlib.logsoftmax!(out::TracedRArray{T}, x::AbstractArray; dims=1) where {T}
max_ = NNlib.fast_maximum(x; dims)
# XXX: Once reverse mode of if is properly supported, we can make it @trace
# inf_num = Reactant.promote_to(TracedRNumber{T}, Inf)
# zero_num = Reactant.promote_to(TracedRNumber{T}, 0)
# inf_num = TracedUtils.promote_to(TracedRNumber{T}, Inf)
# zero_num = TracedUtils.promote_to(TracedRNumber{T}, 0)
# @trace if all(isfinite, max_)
@. out = x - max_
# else
Expand Down Expand Up @@ -232,9 +233,9 @@ function NNlib.batched_mul!(
if size(x, 3) != size(y, 3)
B = max(size(x, 3), size(y, 3))
if size(x, 3) == 1
x = Reactant.TracedUtils.broadcast_to_size(x, (size(x, 1), size(x, 2), B))
x = TracedUtils.broadcast_to_size(x, (size(x, 1), size(x, 2), B))
elseif size(y, 3) == 1
y = Reactant.TracedUtils.broadcast_to_size(y, (size(y, 1), size(y, 2), B))
y = TracedUtils.broadcast_to_size(y, (size(y, 1), size(y, 2), B))
end
end

Expand All @@ -244,9 +245,9 @@ function NNlib.batched_mul!(
if size(x, 1) != size(y, 1)
B = max(size(x, 1), size(y, 1))
if size(x, 1) == 1
x = Reactant.TracedUtils.broadcast_to_size(x, (B, size(x, 2), size(x, 3)))
x = TracedUtils.broadcast_to_size(x, (B, size(x, 2), size(x, 3)))
elseif size(y, 1) == 1
y = Reactant.TracedUtils.broadcast_to_size(y, (B, size(y, 2), size(y, 3)))
y = TracedUtils.broadcast_to_size(y, (B, size(y, 2), size(y, 3)))
end
end

Expand All @@ -264,7 +265,7 @@ end
function NNlib.pad_constant(
x::AnyTracedRArray{T,N}, pad::NTuple{N,Tuple{Int,Int}}, value
) where {T,N}
value = Reactant.TracedUtils.promote_to(TracedRNumber{T}, value)
value = TracedUtils.promote_to(TracedRNumber{T}, value)
low = [i[1] for i in pad]
high = [i[2] for i in pad]
interior = [0 for i in pad]
Expand All @@ -287,8 +288,10 @@ function NNlib.gather!(
) where {T1,T2}
dims = NNlib.scatter_dims(src, dst, idxs)
@assert dims == 1 # scatter_dims lets us do some size checks so we call that function
idxs = get_mlir_data(Reactant.promote_to(TracedRArray{Int,1}, idxs) .- 1)
slice_sizes = get_mlir_data(Reactant.promote_to(TracedRArray{Int,1}, [size(src, 1), 1]))
idxs = get_mlir_data(TracedUtils.promote_to(TracedRArray{Int,1}, idxs) .- 1)
slice_sizes = get_mlir_data(
TracedUtils.promote_to(TracedRArray{Int,1}, [size(src, 1), 1])
)

#! format: off
dimension_numbers = MLIR.API.stablehloGatherDimensionNumbersGet(
Expand Down Expand Up @@ -323,8 +326,7 @@ function NNlib.gather!(dst::TracedRArray, src::AnyTracedRArray, idxs::AbstractAr
start_sizes = ntuple(i -> size(src, i), dims)
results = map(CartesianIndices(idxs)) do k
res = @allowscalar src[colons..., Tuple(idxs[k])...]
res isa TracedRNumber &&
(res = Reactant.TracedUtils.broadcast_to_size(res, (1,)))
res isa TracedRNumber && (res = TracedUtils.broadcast_to_size(res, (1,)))
return reshape(res, start_sizes..., :)
end
res = reshape(cat(results...; dims=(dims + 1)), size(dst))
Expand Down
1 change: 1 addition & 0 deletions src/Compiler.jl
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -246,6 +246,7 @@ const opt_passes::String = join(
"if_inline<1>",
"if_to_select<1>",
"dynamic_update_slice_const_prop",
"dynamic_gather_op_is_not_dynamic<16>",
],
';',
) *
Expand Down
2 changes: 1 addition & 1 deletion src/Interpreter.jl
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -283,7 +283,7 @@ function overload_autodiff(
end
end
for (i, act) in enumerate(activity)
if act == enzyme_out || (reverse && (act == enzyme_dup || act == enzyme_dupnoneed))
Copy link
Collaborator Author

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

I am not 100% sure if this is the right fix, but it fixes the tests

Copy link
Member

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

yeah I think it is

if act == enzyme_out || act == enzyme_dup || act == enzyme_dupnoneed
if width == 1
push!(outtys, in_tys[i])
else
Expand Down
9 changes: 2 additions & 7 deletions test/autodiff.jl
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -11,7 +11,7 @@ fwd(Mode, RT, x, y) = Enzyme.autodiff(Mode, square, RT, Duplicated(x, y))

res1 = @jit(
fwd(
set_abi(Forward, Reactant.ReactantABI),
Forward,
Duplicated,
ConcreteRArray(ones(3, 2)),
ConcreteRArray(3.1 * ones(3, 2)),
Expand Down Expand Up @@ -42,12 +42,7 @@ fwd(Mode, RT, x, y) = Enzyme.autodiff(Mode, square, RT, Duplicated(x, y))
@test typeof(ores1) == Tuple{}

res1 = @jit(
fwd(
set_abi(Forward, Reactant.ReactantABI),
Const,
ConcreteRArray(ones(3, 2)),
ConcreteRArray(3.1 * ones(3, 2)),
)
fwd(Forward, Const, ConcreteRArray(ones(3, 2)), ConcreteRArray(3.1 * ones(3, 2)))
)

@test typeof(res1) == Tuple{}
Expand Down
Loading