Skip to content

Commit

Permalink
fix: use Enzyme's native Jacobian in forward mode with constant conte…
Browse files Browse the repository at this point in the history 
…xts (#710)

* fix: use Enzyme's native Jacobian in forward mode with constant contexts

* Add tests
  • Loading branch information
@gdalle
gdalle authored Jan 30, 2025
1 parent bf47700 commit 0ea7f1d
Show file tree
Hide file tree
Showing 5 changed files with 70 additions and 27 deletions.
2 changes: 1 addition & 1 deletion DifferentiationInterface/Project.toml
View file
Original file line number Diff line number Diff line change
@@ -1,7 +1,7 @@
name = "DifferentiationInterface"
uuid = "a0c0ee7d-e4b9-4e03-894e-1c5f64a51d63"
authors = ["Guillaume Dalle", "Adrian Hill"]
version = "0.6.36"
version = "0.6.37"

[deps]
ADTypes = "47edcb42-4c32-4615-8424-f2b9edc5f35b"
Expand Down
2 changes: 1 addition & 1 deletion DifferentiationInterface/docs/src/explanation/backends.md
View file
Original file line number Diff line number Diff line change
Expand Up @@ -61,7 +61,7 @@ Moreover, each context type is supported by a specific subset of backends:
| `AutoChainRules` | ✅ | ❌ |
| `AutoDiffractor` | ❌ | ❌ |
| `AutoEnzyme` (forward) | ✅ | ✅ |
| `AutoEnzyme` (reverse) | ✅ | ✅ |
| `AutoEnzyme` (reverse) | ✅ | ❌ (soon) |
| `AutoFastDifferentiation` | ✅ | ✅ |
| `AutoFiniteDiff` | ✅ | ✅ |
| `AutoFiniteDifferences` | ✅ | ✅ |
Expand Down
76 changes: 51 additions & 25 deletions DifferentiationInterface/ext/DifferentiationInterfaceEnzymeExt/forward_onearg.jl
View file
Original file line number Diff line number Diff line change
Expand Up @@ -119,8 +119,11 @@ function EnzymeForwardGradientPrep(::Val{B}, shadows::O) where {B,O}
end

function DI.prepare_gradient(
f::F, backend::AutoEnzyme{<:ForwardMode,<:Union{Nothing,Const}}, x
) where {F}
f::F,
backend::AutoEnzyme{<:ForwardMode,<:Union{Nothing,Const}},
x,
contexts::Vararg{DI.Constant,C},
) where {F,C}
valB = to_val(DI.pick_batchsize(backend, x))
shadows = create_shadows(valB, x)
return EnzymeForwardGradientPrep(valB, shadows)
Expand All @@ -131,23 +134,31 @@ function DI.gradient(
prep::EnzymeForwardGradientPrep{B},
backend::AutoEnzyme{<:ForwardMode,<:Union{Nothing,Const}},
x,
) where {F,B}
contexts::Vararg{DI.Constant,C},
) where {F,B,C}
mode = forward_noprimal(backend)
f_and_df = get_f_and_df(f, backend, mode)
derivs = gradient(mode, f_and_df, x; chunk=Val(B), shadows=prep.shadows)
return only(derivs)
annotated_contexts = translate(backend, mode, Val(B), contexts...)
derivs = gradient(
mode, f_and_df, x, annotated_contexts...; chunk=Val(B), shadows=prep.shadows
)
return first(derivs)
end

function DI.value_and_gradient(
f::F,
prep::EnzymeForwardGradientPrep{B},
backend::AutoEnzyme{<:ForwardMode,<:Union{Nothing,Const}},
x,
) where {F,B}
contexts::Vararg{DI.Constant,C},
) where {F,B,C}
mode = forward_withprimal(backend)
f_and_df = get_f_and_df(f, backend, mode)
(; derivs, val) = gradient(mode, f_and_df, x; chunk=Val(B), shadows=prep.shadows)
return val, only(derivs)
annotated_contexts = translate(backend, mode, Val(B), contexts...)
(; derivs, val) = gradient(
mode, f_and_df, x, annotated_contexts...; chunk=Val(B), shadows=prep.shadows
)
return val, first(derivs)
end

function DI.gradient!(
Expand All @@ -156,8 +167,9 @@ function DI.gradient!(
prep::EnzymeForwardGradientPrep{B},
backend::AutoEnzyme{<:ForwardMode,<:Union{Nothing,Const}},
x,
) where {F,B}
return copyto!(grad, DI.gradient(f, prep, backend, x))
contexts::Vararg{DI.Constant,C},
) where {F,B,C}
return copyto!(grad, DI.gradient(f, prep, backend, x, contexts...))
end

function DI.value_and_gradient!(
Expand All @@ -166,8 +178,9 @@ function DI.value_and_gradient!(
prep::EnzymeForwardGradientPrep{B},
backend::AutoEnzyme{<:ForwardMode,<:Union{Nothing,Const}},
x,
) where {F,B}
y, new_grad = DI.value_and_gradient(f, prep, backend, x)
contexts::Vararg{DI.Constant,C},
) where {F,B,C}
y, new_grad = DI.value_and_gradient(f, prep, backend, x, contexts...)
return y, copyto!(grad, new_grad)
end

Expand All @@ -185,9 +198,12 @@ function EnzymeForwardOneArgJacobianPrep(
end

function DI.prepare_jacobian(
f::F, backend::AutoEnzyme{<:Union{ForwardMode,Nothing},<:Union{Nothing,Const}}, x
) where {F}
y = f(x)
f::F,
backend::AutoEnzyme{<:Union{ForwardMode,Nothing},<:Union{Nothing,Const}},
x,
contexts::Vararg{DI.Constant,C},
) where {F,C}
y = f(x, map(DI.unwrap, contexts)...)
valB = to_val(DI.pick_batchsize(backend, x))
shadows = create_shadows(valB, x)
return EnzymeForwardOneArgJacobianPrep(valB, shadows, length(y))
Expand All @@ -198,11 +214,15 @@ function DI.jacobian(
prep::EnzymeForwardOneArgJacobianPrep{B},
backend::AutoEnzyme{<:Union{ForwardMode,Nothing},<:Union{Nothing,Const}},
x,
) where {F,B}
contexts::Vararg{DI.Constant,C},
) where {F,B,C}
mode = forward_noprimal(backend)
f_and_df = get_f_and_df(f, backend, mode)
derivs = jacobian(mode, f_and_df, x; chunk=Val(B), shadows=prep.shadows)
jac_tensor = only(derivs)
annotated_contexts = translate(backend, mode, Val(B), contexts...)
derivs = jacobian(
mode, f_and_df, x, annotated_contexts...; chunk=Val(B), shadows=prep.shadows
)
jac_tensor = first(derivs)
return maybe_reshape(jac_tensor, prep.output_length, length(x))
end

Expand All @@ -211,11 +231,15 @@ function DI.value_and_jacobian(
prep::EnzymeForwardOneArgJacobianPrep{B},
backend::AutoEnzyme{<:Union{ForwardMode,Nothing},<:Union{Nothing,Const}},
x,
) where {F,B}
contexts::Vararg{DI.Constant,C},
) where {F,B,C}
mode = forward_withprimal(backend)
f_and_df = get_f_and_df(f, backend, mode)
(; derivs, val) = jacobian(mode, f_and_df, x; chunk=Val(B), shadows=prep.shadows)
jac_tensor = only(derivs)
annotated_contexts = translate(backend, mode, Val(B), contexts...)
(; derivs, val) = jacobian(
mode, f_and_df, x, annotated_contexts...; chunk=Val(B), shadows=prep.shadows
)
jac_tensor = first(derivs)
return val, maybe_reshape(jac_tensor, prep.output_length, length(x))
end

Expand All @@ -225,8 +249,9 @@ function DI.jacobian!(
prep::EnzymeForwardOneArgJacobianPrep,
backend::AutoEnzyme{<:Union{ForwardMode,Nothing},<:Union{Nothing,Const}},
x,
) where {F}
return copyto!(jac, DI.jacobian(f, prep, backend, x))
contexts::Vararg{DI.Constant,C},
) where {F,C}
return copyto!(jac, DI.jacobian(f, prep, backend, x, contexts...))
end

function DI.value_and_jacobian!(
Expand All @@ -235,7 +260,8 @@ function DI.value_and_jacobian!(
prep::EnzymeForwardOneArgJacobianPrep,
backend::AutoEnzyme{<:Union{ForwardMode,Nothing},<:Union{Nothing,Const}},
x,
) where {F}
y, new_jac = DI.value_and_jacobian(f, prep, backend, x)
contexts::Vararg{DI.Constant,C},
) where {F,C}
y, new_jac = DI.value_and_jacobian(f, prep, backend, x, contexts...)
return y, copyto!(jac, new_jac)
end
10 changes: 10 additions & 0 deletions DifferentiationInterface/ext/DifferentiationInterfaceEnzymeExt/utils.jl
View file
Original file line number Diff line number Diff line change
Expand Up @@ -53,6 +53,16 @@ force_annotation(f::F) where {F} = Const(f)
return Const(DI.unwrap(c))
end

@inline function _translate(
backend::AutoEnzyme, mode::Mode, ::Val{B}, c::DI.Cache
) where {B}
if B == 1
return Duplicated(DI.unwrap(c), make_zero(DI.unwrap(c)))
else
return BatchDuplicated(DI.unwrap(c), ntuple(_ -> make_zero(DI.unwrap(c)), Val(B)))
end
end

@inline function _translate(
backend::AutoEnzyme, mode::Mode, ::Val{B}, c::DI.FunctionContext
) where {B}
Expand Down
7 changes: 7 additions & 0 deletions DifferentiationInterface/test/Back/Enzyme/test.jl
View file
Original file line number Diff line number Diff line change
Expand Up @@ -53,6 +53,13 @@ end;
logging=LOGGING,
)

test_differentiation(
backends[2],
default_scenarios(; include_normal=false, include_cachified=true);
excluded=SECOND_ORDER,
logging=LOGGING,
)

test_differentiation(
duplicated_backends,
default_scenarios(; include_normal=false, include_closurified=true);
Expand Down

2 comments on commit 0ea7f1d

@gdalle
Copy link
Member Author

@gdalle gdalle commented on 0ea7f1d Jan 30, 2025

Choose a reason for hiding this comment

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

@JuliaRegistrator register subdir=DifferentiationInterface

@JuliaRegistrator
Copy link

Choose a reason for hiding this comment

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

Registration pull request created: JuliaRegistries/General/124040

Tip: Release Notes

Did you know you can add release notes too? Just add markdown formatted text underneath the comment after the text
"Release notes:" and it will be added to the registry PR, and if TagBot is installed it will also be added to the
release that TagBot creates. i.e.

@JuliaRegistrator register

Release notes:

## Breaking changes

- blah

To add them here just re-invoke and the PR will be updated.

Tagging

After the above pull request is merged, it is recommended that a tag is created on this repository for the registered package version.

This will be done automatically if the Julia TagBot GitHub Action is installed, or can be done manually through the github interface, or via:

git tag -a DifferentiationInterface-v0.6.37 -m "<description of version>" 0ea7f1de01c59e9589e635f04cc7c6939070c768
git push origin DifferentiationInterface-v0.6.37

Please sign in to comment.