Special case single path HDF5 and JLD2 datasets and add @inferred t…

…ests

src/containers/hdf5dataset.jl

@@ -6,9 +6,9 @@ end
 
 """
     HDF5Dataset(file::Union{AbstractString, AbstractPath}, paths)
-    HDF5Dataset(fid::HDF5.File, paths::Vector{HDF5.Dataset})
-    HDF5Dataset(fid::HDF5.File, paths::Vector{<:AbstractString})
-    HDF5Dataset(fid::HDF5.File, paths::Vector{HDF5.Dataset}, shapes)
+    HDF5Dataset(fid::HDF5.File, paths::Union{HDF5.Dataset, Vector{HDF5.Dataset}})
+    HDF5Dataset(fid::HDF5.File, paths::Union{AbstractString, Vector{<:AbstractString}})
+    HDF5Dataset(fid::HDF5.File, paths::Union{HDF5.Dataset, Vector{HDF5.Dataset}}, shapes)
 
 Wrap several HDF5 datasets (`paths`) as a single dataset container.
 Each dataset `p` in `paths` should be accessible as `fid[p]`.
@@ -19,34 +19,38 @@ See [`close(::HDF5Dataset)`](@ref) for closing the underlying HDF5 file pointer.
 For array datasets, the last dimension is assumed to be the observation dimension.
 For scalar datasets, the stored value is returned by `getobs` for any index.
 """
-struct HDF5Dataset <: AbstractDataContainer
+struct HDF5Dataset{T<:Union{HDF5.Dataset, Vector{HDF5.Dataset}}} <: AbstractDataContainer
     fid::HDF5.File
-    paths::Vector{HDF5.Dataset}
+    paths::T
     shapes::Vector{Tuple}
 
-    function HDF5Dataset(fid::HDF5.File, paths::Vector{HDF5.Dataset}, shapes::Vector)
+    function HDF5Dataset(fid::HDF5.File, paths::T, shapes::Vector) where T<:Union{HDF5.Dataset, Vector{HDF5.Dataset}}
         _check_hdf5_shapes(shapes) ||
             throw(ArgumentError("Cannot create HDF5Dataset for datasets with mismatched number of observations."))
 
-        new(fid, paths, shapes)
+        new{T}(fid, paths, shapes)
     end
 end
 
+HDF5Dataset(fid::HDF5.File, path::HDF5.Dataset) = HDF5Dataset(fid, path, [size(path)])
 HDF5Dataset(fid::HDF5.File, paths::Vector{HDF5.Dataset}) =
     HDF5Dataset(fid, paths, map(size, paths))
+HDF5Dataset(fid::HDF5.File, path::AbstractString) = HDF5Dataset(fid, fid[path])
 HDF5Dataset(fid::HDF5.File, paths::Vector{<:AbstractString}) =
     HDF5Dataset(fid, map(p -> fid[p], paths))
 HDF5Dataset(file::Union{AbstractString, AbstractPath}, paths) =
     HDF5Dataset(h5open(file, "r"), paths)
 
-MLUtils.getobs(dataset::HDF5Dataset, i) = Tuple(map(dataset.paths, dataset.shapes) do path, shape
-    if isempty(shape)
-        return read(path)
-    else
-        I = map(s -> 1:s, shape[1:(end - 1)])
-        return path[I..., i]
-    end
-end)
+_getobs_hdf5(dataset::HDF5.Dataset, ::Tuple{}, i) = read(dataset)
+function _getobs_hdf5(dataset::HDF5.Dataset, shape, i)
+    I = map(s -> 1:s, shape[1:(end - 1)])
+
+    return dataset[I..., i]
+end
+MLUtils.getobs(dataset::HDF5Dataset{HDF5.Dataset}, i) =
+    _getobs_hdf5(dataset.paths, only(dataset.shapes), i)
+MLUtils.getobs(dataset::HDF5Dataset{<:Vector}, i) =
+    Tuple(map((p, s) -> _getobs_hdf5(p, s, i), dataset.paths, dataset.shapes))
 MLUtils.numobs(dataset::HDF5Dataset) = last(first(filter(!isempty, dataset.shapes)))
 
 """

src/containers/jld2dataset.jl

@@ -2,32 +2,35 @@ _check_jld2_nobs(nobs) = all(==(first(nobs)), nobs[2:end])
 
 """
     JLD2Dataset(file::Union{AbstractString, AbstractPath}, paths)
-    JLD2Dataset(fid::JLD2.JLDFile, paths)
+    JLD2Dataset(fid::JLD2.JLDFile, paths::Union{String, Vector{String}})
 
 Wrap several JLD2 datasets (`paths`) as a single dataset container.
 Each dataset `p` in `paths` should be accessible as `fid[p]`.
 Calling `getobs` on a `JLD2Dataset` is equivalent to mapping `getobs` on
 each dataset in `paths`.
 See [`close(::JLD2Dataset)`](@ref) for closing the underlying JLD2 file pointer.
 """
-struct JLD2Dataset{T<:JLD2.JLDFile} <: AbstractDataContainer
+struct JLD2Dataset{T<:JLD2.JLDFile, S<:Tuple} <: AbstractDataContainer
     fid::T
-    paths::Vector{String}
+    paths::S
 
-    function JLD2Dataset(fid::JLD2.JLDFile, paths::Vector{String})
-        nobs = map(p -> numobs(fid[p]), paths)
+    function JLD2Dataset(fid::JLD2.JLDFile, paths)
+        _paths = Tuple(map(p -> fid[p], paths))
+        nobs = map(numobs, _paths)
         _check_jld2_nobs(nobs) ||
-            throw(ArgumentError("Cannot create JLD2Dataset for datasets with mismatched number of observations."))
+            throw(ArgumentError("Cannot create JLD2Dataset for datasets with mismatched number of observations (got $nobs)."))
 
-        new{typeof(fid)}(fid, paths)
+        new{typeof(fid), typeof(_paths)}(fid, _paths)
     end
 end
 
+JLD2Dataset(file::JLD2.JLDFile, path::String) = JLD2Dataset(file, (path,))
 JLD2Dataset(file::Union{AbstractString, AbstractPath}, paths) =
     JLD2Dataset(jldopen(file, "r"), paths)
 
-MLUtils.getobs(dataset::JLD2Dataset, i) = Tuple(map(p -> getobs(dataset.fid[p], i), dataset.paths))
-MLUtils.numobs(dataset::JLD2Dataset) = numobs(dataset.fid[dataset.paths[1]])
+MLUtils.getobs(dataset::JLD2Dataset{<:JLD2.JLDFile, <:NTuple{1}}, i) = getobs(only(dataset.paths), i)
+MLUtils.getobs(dataset::JLD2Dataset, i) = map(Base.Fix2(getobs, i), dataset.paths)
+MLUtils.numobs(dataset::JLD2Dataset) = numobs(dataset.paths[1])
 
 """
     close(dataset::JLD2Dataset)

src/containers/tabledataset.jl

@@ -23,14 +23,18 @@ TableDataset(path::Union{AbstractPath, AbstractString}) =
     TableDataset(DataFrame(CSV.File(path)))
 
 # slow accesses based on Tables.jl
+_getobs_row(x, i) = first(Iterators.peel(Iterators.drop(x, i - 1)))
+function _getobs_column(x, i)
+    colnames = Tuple(Tables.columnnames(x))
+    rowvals = ntuple(j -> Tables.getcolumn(x, j)[i], length(colnames))
+
+    return NamedTuple{colnames}(rowvals)
+end
 function MLUtils.getobs(dataset::TableDataset, i)
     if Tables.rowaccess(dataset.table)
-        row, _ = Iterators.peel(Iterators.drop(Tables.rows(dataset.table), i - 1))
-        return row
+        return _getobs_row(Tables.rows(dataset.table), i)
     elseif Tables.columnaccess(dataset.table)
-        colnames = Tables.columnnames(dataset.table)
-        rowvals = [Tables.getcolumn(dataset.table, j)[i] for j in 1:length(colnames)]
-        return (; zip(colnames, rowvals)...)
+        return _getobs_column(dataset.table, i)
     else
         error("The Tables.jl implementation used should have either rowaccess or columnaccess.")
     end

test/containers/cacheddataset.jl

@@ -13,13 +13,29 @@
 
     @testset "CachedDataset(::HDF5Dataset)" begin
         paths, datas = setup_hdf5dataset_test()
-        hdataset = HDF5Dataset("test.h5", ["d1"])
+        hdataset = HDF5Dataset("test.h5", "d1")
         cdataset = CachedDataset(hdataset, 5)
 
         @test numobs(cdataset) == numobs(hdataset)
+        @test cdataset.cache isa Matrix{Float64}
         @test cdataset.cache == getobs(hdataset, 1:5)
         @test all(getobs(cdataset, i) == getobs(hdataset, i) for i in 1:10)
 
+        close(hdataset)
         cleanup_hdf5dataset_test()
     end
+
+    @testset "CachedDataset(::JLD2Dataset)" begin
+        paths, datas = setup_jld2dataset_test()
+        jdataset = JLD2Dataset("test.jld2", "d1")
+        cdataset = CachedDataset(jdataset, 5)
+
+        @test numobs(cdataset) == numobs(jdataset)
+        @test cdataset.cache isa Matrix{Float64}
+        @test cdataset.cache == getobs(jdataset, 1:5)
+        @test all(@inferred(getobs(cdataset, i)) == getobs(jdataset, i) for i in 1:10)
+
+        close(jdataset)
+        cleanup_jld2dataset_test()
+    end
 end

test/containers/hdf5dataset.jl

@@ -18,12 +18,22 @@ cleanup_hdf5dataset_test() = rm("test.h5")
 
 @testset "HDF5Dataset" begin
     paths, datas = setup_hdf5dataset_test()
-    dataset = HDF5Dataset("test.h5", paths)
-    for i in 1:10
-        data = Tuple(map(x -> (x isa String) ? x : getobs(x, i), datas))
-        @test getobs(dataset, i) == data
+    @testset "Single path" begin
+        dataset = HDF5Dataset("test.h5", "d1")
+        for i in 1:10
+            @test getobs(dataset, i) == getobs(datas[1], i)
+        end
+        @test numobs(dataset) == 10
+        close(dataset)
+    end
+    @testset "Multiple paths" begin
+        dataset = HDF5Dataset("test.h5", paths)
+        for i in 1:10
+            data = Tuple(map(x -> (x isa String) ? x : getobs(x, i), datas))
+            @test @inferred(Tuple, getobs(dataset, i)) == data
+        end
+        @test numobs(dataset) == 10
+        close(dataset)
     end
-    @test numobs(dataset) == 10
-    close(dataset)
     cleanup_hdf5dataset_test()
 end

test/containers/jld2dataset.jl

@@ -18,11 +18,21 @@ cleanup_jld2dataset_test() = rm("test.jld2")
 
 @testset "JLD2Dataset" begin
     paths, datas = setup_jld2dataset_test()
-    dataset = JLD2Dataset("test.jld2", paths)
-    for i in 1:10
-        @test getobs(dataset, i) == getobs(datas, i)
+    @testset "Single path" begin
+        dataset = JLD2Dataset("test.jld2", "d1")
+        for i in 1:10
+            @test @inferred(getobs(dataset, i)) == getobs(datas[1], i)
+        end
+        @test numobs(dataset) == 10
+        close(dataset)
+    end
+    @testset "Multiple paths" begin
+        dataset = JLD2Dataset("test.jld2", paths)
+        for i in 1:10
+            @test @inferred(getobs(dataset, i)) == getobs(datas, i)
+        end
+        @test numobs(dataset) == 10
+        close(dataset)
     end
-    @test numobs(dataset) == 10
-    close(dataset)
     cleanup_jld2dataset_test()
 end

test/containers/tabledataset.jl

@@ -6,7 +6,7 @@
         testtable = Tables.table([1 4.0 "7"; 2 5.0 "8"; 3 6.0 "9"])
         td = TableDataset(testtable)
 
-        @test all(getobs(td, 1) .== [1, 4.0, "7"])
+        @test collect(@inferred(getobs(td, 1))) == [1, 4.0, "7"]
         @test numobs(td) == 3
     end
 
@@ -17,7 +17,7 @@
         testtable = Tables.table([1 4.0 "7"; 2 5.0 "8"; 3 6.0 "9"])
         td = TableDataset(testtable)
 
-        @test [data for data in getobs(td, 2)] == [2, 5.0, "8"]
+        @test collect(@inferred(NamedTuple, getobs(td, 2))) == [2, 5.0, "8"]
         @test numobs(td) == 3
 
         @test getobs(td, 1) isa NamedTuple
@@ -35,7 +35,7 @@
         td = TableDataset(testtable)
         @test td isa TableDataset{<:DataFrame}
 
-        @test [data for data in getobs(td, 1)] == [1, "a", 10, "A", 100.0, "train"]
+        @test collect(@inferred(getobs(td, 1))) == [1, "a", 10, "A", 100.0, "train"]
         @test numobs(td) == 5
     end
 
@@ -46,7 +46,7 @@
         testtable = CSV.File("test.csv")
         td = TableDataset(testtable)
         @test td isa TableDataset{<:CSV.File}
-        @test [data for data in getobs(td, 1)] == [1, "a", 10, "A", 100.0, "train"]
+        @test collect(@inferred(getobs(td, 1))) == [1, "a", 10, "A", 100.0, "train"]
         @test numobs(td) == 1
         rm("test.csv")
     end