TastyPancakes
/
Flux.jl
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Apply suggestions from code review 

accept suggested changes

Co-authored-by: Carlo Lucibello <carlo.lucibello@gmail.com>
This commit is contained in:
cossio 2020-06-12 11:45:42 +02:00 committed by cossio
parent 909a55ac10
commit 75692161a7
2 changed files with 5 additions and 5 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

8
src/data/dataloader.jl
View File

@ -16,7 +16,7 @@ end
An object that iterates over mini-batches of `data`, each mini-batch containing `batchsize` observations
(except possibly the last one).
Takes as input a data tensors or a tuple (or `NamedTuple`) of one or more such tensors.
Takes as input a single data tensor, or a tuple (or a named tuple) of tensors.
The last dimension in each tensor is considered to be the observation dimension.
If `shuffle=true`, shuffles the observations each time iterations are re-started.
@ -59,7 +59,7 @@ Usage example:
Flux.train!(loss, ps, ncycle(train_loader, 10), opt)
# can use NamedTuple to name tensors
train_loader = DataLoader((images = Xtrain, labels = Ytrain), batchsize=2, shuffle=true)
train_loader = DataLoader((images=Xtrain, labels=Ytrain), batchsize=2, shuffle=true)
for datum in train_loader
@assert size(datum.images) == (10, 2)
@assert size(datum.labels) == (2,)
@ -95,7 +95,7 @@ end
_nobs(data::AbstractArray) = size(data)[end]
function _nobs(data::Union{Tuple,NamedTuple})
function _nobs(data::Union{Tuple, NamedTuple})
length(data) > 0 || throw(ArgumentError("Need at least one data input"))
n = _nobs(data[1])
if !all(x -> _nobs(x) == n, Base.tail(data))
@ -108,6 +108,6 @@ function _getobs(data::AbstractArray{T,N}, i) where {T,N}
getindex(data, ntuple(i->Colon(), Val(N-1))..., i)
end
_getobs(data::Union{Tuple,NamedTuple}, i) = map(x -> _getobs(x, i), data)
_getobs(data::Union{Tuple, NamedTuple}, i) = map(x -> _getobs(x, i), data)
Base.eltype(d::DataLoader{D}) where D = D

2
test/data.jl
View File

@ -39,7 +39,7 @@
@test batches[3][2] == Y[5:5]
# test with NamedTuple
d = DataLoader((x = X, y = Y), batchsize=2)
d = DataLoader((x=X, y=Y), batchsize=2)
batches = collect(d)
@test eltype(batches) == eltype(d) == NamedTuple{(:x, :y), Tuple{typeof(X), typeof(Y)}}
@test length(batches) == 3