Flux
Flux
is a module
Name | Kind |
---|---|
DepthwiseConv
|
function |
GRU
|
function |
GRUv3
|
function |
LSTM
|
function |
RNN
|
function |
cpu
|
function |
f16
|
function |
f32
|
function |
f64
|
function |
frequencies
|
function |
gpu
|
function |
ones32
|
function |
rand32
|
function |
randn32
|
function |
rng_from_array
|
function |
testmode!
|
function |
trainmode!
|
function |
zeros32
|
function |
AdaptiveMaxPool
|
struct |
AdaptiveMeanPool
|
struct |
AlphaDropout
|
struct |
BatchNorm
|
struct |
Chain
|
struct |
Conv
|
struct |
ConvTranspose
|
struct |
CrossCor
|
struct |
Dense
|
struct |
Dropout
|
struct |
Embedding
|
struct |
GlobalMaxPool
|
struct |
GlobalMeanPool
|
struct |
GroupNorm
|
struct |
InstanceNorm
|
struct |
LayerNorm
|
struct |
MaxPool
|
struct |
Maxout
|
struct |
MeanPool
|
struct |
MultiHeadAttention
|
struct |
PairwiseFusion
|
struct |
Parallel
|
struct |
PixelShuffle
|
struct |
SamePad
|
struct |
SkipConnection
|
struct |
Upsample
|
struct |
The following pages link back here:
Custom learning tasks, Image segmentation, Keypoint regression, Siamese image similarity, Tabular Classification, TimeSeries Classification, Variational autoencoders, tsregression
FastAI.jl , blocks/continuous.jl , encodings/onehot.jl , learner.jl , training/discriminativelrs.jl , training/lrfind.jl , training/paramgroups.jl , FastTabular.jl , models.jl , FastVision.jl , encodings/keypointpreprocessing.jl , encodings/onehot.jl , models.jl , models/Models.jl , models/blocks.jl , models/layers.jl , models/unet.jl , models/xresnet.jl , Flux.jl , cuda/cuda.jl , cuda/cudnn.jl , deprecations.jl , layers/recurrent.jl , losses/Losses.jl , optimise/optimisers.jl , train.jl , FluxTraining.jl , callbacks/hyperparameters.jl , callbacks/logging/logger.jl , learner.jl , testutils.jl , training.jl