diff --git a/.github/workflows/Downstream.yml b/.github/workflows/Downstream.yml index e153cd785..1a76bf1ea 100644 --- a/.github/workflows/Downstream.yml +++ b/.github/workflows/Downstream.yml @@ -50,7 +50,7 @@ jobs: # force it to use this PR's version of the package Pkg.develop(PackageSpec(path=".")) # resolver may fail with main deps Pkg.update() - Pkg.test() # resolver may fail with test time deps + Pkg.test(; coverage=true) # resolver may fail with test time deps catch err err isa Pkg.Resolve.ResolverError || rethrow() # If we can't resolve that means this is incompatible by SemVer and this is fine diff --git a/Manifest.toml b/Manifest.toml new file mode 100644 index 000000000..d404456db --- /dev/null +++ b/Manifest.toml @@ -0,0 +1,630 @@ +# This file is machine-generated - editing it directly is not advised + +julia_version = "1.10.2" +manifest_format = "2.0" +project_hash = "1baceb0c137c49981f015b1d02cf5539271fa2dd" + +[[deps.ADTypes]] +git-tree-sha1 = 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--git a/Project.toml b/Project.toml index f2196629b..ee6f4a81e 100644 --- a/Project.toml +++ b/Project.toml @@ -82,7 +82,7 @@ LuxAMDGPU = "0.2.2" LuxCUDA = "0.3.2" LuxCore = "0.1.12" LuxDeviceUtils = "0.1.19" -LuxLib = "0.3.11" +LuxLib = "0.3.15" LuxTestUtils = "0.1.15" MLUtils = "0.4.3" MPI = "0.20.19" diff --git a/src/layers/basic.jl b/src/layers/basic.jl index dec0504d6..42f23136f 100644 --- a/src/layers/basic.jl +++ b/src/layers/basic.jl @@ -222,7 +222,7 @@ end end @inline function (d::Dense)(x::AbstractArray, ps, st::NamedTuple) - return reshape(first(d(reshape(x, size(x, 1), :), ps, st), :, size(x)[2:end]...)), st + return reshape(first(d(reshape(x, size(x, 1), :), ps, st)), :, size(x)[2:end]...), st end """ diff --git a/src/layers/normalize.jl b/src/layers/normalize.jl index a640329a0..435546009 100644 --- a/src/layers/normalize.jl +++ b/src/layers/normalize.jl @@ -129,15 +129,15 @@ statelength(l::BatchNorm) = (_track_stats(l) ? 2 * l.chs : 0) + 1 function (BN::BatchNorm)(x::AbstractArray, ps, st::NamedTuple) y, stats = batchnorm(x, _getproperty(ps, Val(:scale)), _getproperty(ps, Val(:bias)), - _getproperty(st, Val(:running_mean)), - _getproperty(st, Val(:running_var)); BN.momentum, BN.epsilon, st.training) + _getproperty(st, Val(:running_mean)), _getproperty(st, Val(:running_var)), + BN.activation; BN.momentum, BN.epsilon, st.training) if _track_stats(BN) @set! st.running_mean = stats.running_mean @set! st.running_var = stats.running_var end - return apply_activation(BN.activation, y), st + return y, st end function Base.show(io::IO, l::BatchNorm) @@ -241,9 +241,9 @@ end parameterlength(l::GroupNorm) = _affine(l) ? (l.chs * 2) : 0 function (GN::GroupNorm)(x::AbstractArray, ps, st::NamedTuple) - y = groupnorm(x, _getproperty(ps, Val(:scale)), - _getproperty(ps, Val(:bias)); GN.groups, GN.epsilon) - return apply_activation(GN.activation, y), st + y = groupnorm(x, _getproperty(ps, Val(:scale)), _getproperty(ps, Val(:bias)), + GN.activation; GN.groups, GN.epsilon) + return y, st end function Base.show(io::IO, l::GroupNorm) @@ -355,9 +355,9 @@ initialstates(rng::AbstractRNG, l::InstanceNorm) = (; training=Val(true)) parameterlength(l::InstanceNorm) = _affine(l) ? (l.chs * 2) : 0 function (IN::InstanceNorm)(x::AbstractArray, ps, st::NamedTuple) - y, stats = instancenorm(x, _getproperty(ps, Val(:scale)), - _getproperty(ps, Val(:bias)); IN.epsilon, st.training) - return apply_activation(IN.activation, y), st + y, stats = instancenorm(x, _getproperty(ps, Val(:scale)), _getproperty(ps, Val(:bias)), + IN.activation; IN.epsilon, st.training) + return y, st end function Base.show(io::IO, l::InstanceNorm) @@ -574,9 +574,9 @@ function initialparameters(rng::AbstractRNG, ln::LayerNorm) end function (l::LayerNorm)(x::AbstractArray, ps, st::NamedTuple) - y = layernorm( - x, _getproperty(ps, Val(:scale)), _getproperty(ps, Val(:bias)); l.dims, l.epsilon) - return apply_activation(l.activation, y), st + y = layernorm(x, _getproperty(ps, Val(:scale)), + _getproperty(ps, Val(:bias)), l.activation; l.dims, l.epsilon) + return y, st end function Base.show(io::IO, l::LayerNorm)