Flux
module
Flux
using
Base
:
tail
using
Preferences
using
LinearAlgebra
,
Statistics
,
Random
# standard lib
using
MacroTools
,
Reexport
,
ProgressLogging
,
SpecialFunctions
using
MacroTools
:
@
forward
@
reexport
using
NNlib
using
MLUtils
import
Optimisers
:
Optimisers
,
trainable
,
destructure
# before v0.13, Flux owned these functions
using
Optimisers
:
freeze!
,
thaw!
,
adjust!
using
Zygote
,
ChainRulesCore
using
Zygote
:
Params
,
@
adjoint
,
gradient
,
pullback
using
Zygote
.
ForwardDiff
:
value
export
gradient
# Pirate error to catch a common mistake. (Internal function `base` because overloading `update!` is more likely to give ambiguities.)
Optimisers
.
base
(
dx
::
Zygote
.
Grads
)
=
error
(
"
Optimisers.jl cannot be used with Zygote.jl's implicit gradients, `Params` & `Grads`
"
)
export
Chain
,
Dense
,
Embedding
,
Maxout
,
SkipConnection
,
Parallel
,
PairwiseFusion
,
RNN
,
LSTM
,
GRU
,
GRUv3
,
SamePad
,
Conv
,
CrossCor
,
ConvTranspose
,
DepthwiseConv
,
AdaptiveMaxPool
,
AdaptiveMeanPool
,
GlobalMaxPool
,
GlobalMeanPool
,
MaxPool
,
MeanPool
,
Dropout
,
AlphaDropout
,
LayerNorm
,
BatchNorm
,
InstanceNorm
,
GroupNorm
,
MultiHeadAttention
,
Upsample
,
PixelShuffle
,
fmap
,
cpu
,
gpu
,
f32
,
f64
,
f16
,
rand32
,
randn32
,
zeros32
,
ones32
,
testmode!
,
trainmode!
include
(
"
optimise/Optimise.jl
"
)
using
.
Optimise
using
.
Optimise
:
@
epochs
using
.
Optimise
:
skip
export
Descent
,
Adam
,
Momentum
,
Nesterov
,
RMSProp
,
AdaGrad
,
AdaMax
,
AdaDelta
,
AMSGrad
,
NAdam
,
OAdam
,
AdamW
,
RAdam
,
AdaBelief
,
InvDecay
,
ExpDecay
,
WeightDecay
,
ClipValue
,
ClipNorm
export
ClipGrad
,
OptimiserChain
# these are const defined in deprecations, for ClipValue, Optimiser
include
(
"
train.jl
"
)
using
.
Train
using
.
Train
:
setup
using
CUDA
import
cuDNN
const
use_cuda
=
Ref
{
Union
{
Nothing
,
Bool
}
}
(
nothing
)
using
Adapt
,
Functors
,
OneHotArrays
include
(
"
utils.jl
"
)
include
(
"
functor.jl
"
)
# Pirate error to catch a common mistake.
Functors
.
functor
(
::
Type
{
<:
MLUtils
.
DataLoader
}
,
x
)
=
error
(
"
`DataLoader` does not support Functors.jl, thus functions like `Flux.gpu` will not act on its contents.
"
)
include
(
"
layers/stateless.jl
"
)
include
(
"
layers/basic.jl
"
)
include
(
"
layers/conv.jl
"
)
include
(
"
layers/recurrent.jl
"
)
include
(
"
layers/normalise.jl
"
)
include
(
"
layers/upsample.jl
"
)
include
(
"
layers/attention.jl
"
)
include
(
"
layers/show.jl
"
)
include
(
"
loading.jl
"
)
include
(
"
outputsize.jl
"
)
export
@
autosize
include
(
"
deprecations.jl
"
)
include
(
"
losses/Losses.jl
"
)
using
.
Losses
include
(
"
cuda/cuda.jl
"
)
endmodule