Fix tests

NDTensors/Project.toml

@@ -36,6 +36,7 @@ NDTensorsTBLISExt = "TBLIS"
 
 [compat]
 Adapt = "3.5"
+BlockArrays = "0.16"
 Compat = "4.9"
 Dictionaries = "0.3.5"
 FLoops = "0.2.1"

NDTensors/src/BlockSparseArrays/README.md

@@ -8,7 +8,7 @@ to store non-zero values, specifically a `Dictionary` from `Dictionaries.jl`.
 
 ````julia
 using NDTensors.BlockSparseArrays
-using BlockArrays
+using BlockArrays: BlockArrays, blockedrange
 
 # Block dimensions
 i1 = [2, 3]
@@ -17,11 +17,11 @@ i2 = [2, 3]
 i_axes = (blockedrange(i1), blockedrange(i2))
 
 function block_size(axes, block)
-  return length.(getindex.(axes, Block.(block.n)))
+  return length.(getindex.(axes, BlockArrays.Block.(block.n)))
 end
 
 # Data
-nz_blocks = [Block(1, 1), Block(2, 2)]
+nz_blocks = BlockArrays.Block.([(1, 1), (2, 2)])
 nz_block_sizes = [block_size(i_axes, nz_block) for nz_block in nz_blocks]
 nz_block_lengths = prod.(nz_block_sizes)
 
@@ -35,13 +35,13 @@ d_blocks = randn.(nz_block_sizes)
 B = BlockSparseArray(nz_blocks, d_blocks, i_axes)
 
 # Access a block
-B[Block(1, 1)]
+B[BlockArrays.Block(1, 1)]
 
 # Access a non-zero block, returns a zero matrix
-B[Block(1, 2)]
+B[BlockArrays.Block(1, 2)]
 
 # Set a zero block
-B[Block(1, 2)] = randn(2, 3)
+B[BlockArrays.Block(1, 2)] = randn(2, 3)
 
 # Matrix multiplication (not optimized for sparsity yet)
 B * B

NDTensors/src/BlockSparseArrays/examples/README.jl

@@ -7,7 +7,7 @@
 # `BlockArrays` reinterprets the `SparseArray` as a blocked data structure.
 
 using NDTensors.BlockSparseArrays
-using BlockArrays
+using BlockArrays: BlockArrays, blockedrange
 
 ## Block dimensions
 i1 = [2, 3]
@@ -16,11 +16,11 @@ i2 = [2, 3]
 i_axes = (blockedrange(i1), blockedrange(i2))
 
 function block_size(axes, block)
-  return length.(getindex.(axes, Block.(block.n)))
+  return length.(getindex.(axes, BlockArrays.Block.(block.n)))
 end
 
 ## Data
-nz_blocks = [Block(1, 1), Block(2, 2)]
+nz_blocks = BlockArrays.Block.([(1, 1), (2, 2)])
 nz_block_sizes = [block_size(i_axes, nz_block) for nz_block in nz_blocks]
 nz_block_lengths = prod.(nz_block_sizes)
 
@@ -34,13 +34,13 @@ d_blocks = randn.(nz_block_sizes)
 B = BlockSparseArray(nz_blocks, d_blocks, i_axes)
 
 ## Access a block
-B[Block(1, 1)]
+B[BlockArrays.Block(1, 1)]
 
 ## Access a non-zero block, returns a zero matrix
-B[Block(1, 2)]
+B[BlockArrays.Block(1, 2)]
 
 ## Set a zero block
-B[Block(1, 2)] = randn(2, 3)
+B[BlockArrays.Block(1, 2)] = randn(2, 3)
 
 ## Matrix multiplication (not optimized for sparsity yet)
 B * B

NDTensors/test/BlockSparseArrays.jl

@@ -0,0 +1,4 @@
+using Test
+using NDTensors
+
+include(joinpath(pkgdir(NDTensors), "src", "BlockSparseArrays", "test", "runtests.jl"))

NDTensors/test/Project.toml

@@ -1,4 +1,5 @@
 [deps]
+BlockArrays = "8e7c35d0-a365-5155-bbbb-fb81a777f24e"
 CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba"
 Dictionaries = "85a47980-9c8c-11e8-2b9f-f7ca1fa99fb4"
 ITensors = "9136182c-28ba-11e9-034c-db9fb085ebd5"

NDTensors/test/arraytensor/blocksparsearray.jl

@@ -1,19 +1,21 @@
 using NDTensors
 using NDTensors.BlockSparseArrays
-using BlockArrays
+using BlockArrays: BlockArrays
 using LinearAlgebra
 using Test
 
-using BlockArrays: Block
-
 using NDTensors: storage, storagetype
 
 @testset "Tensor wrapping BlockSparseArray" begin
   is1 = ([1, 1], [1, 2])
-  D1 = BlockSparseArray([Block(1, 1), Block(2, 2)], [randn(1, 1), randn(1, 2)], is1)
+  D1 = BlockSparseArray(
+    [BlockArrays.Block(1, 1), BlockArrays.Block(2, 2)], [randn(1, 1), randn(1, 2)], is1
+  )
 
   is2 = ([1, 2], [2, 2])
-  D2 = BlockSparseArray([Block(1, 1), Block(2, 2)], [randn(1, 2), randn(2, 2)], is2)
+  D2 = BlockSparseArray(
+    [BlockArrays.Block(1, 1), BlockArrays.Block(2, 2)], [randn(1, 2), randn(2, 2)], is2
+  )
 
   T1 = tensor(D1, is1)
   T2 = tensor(D2, is2)

NDTensors/test/runtests.jl

@@ -19,6 +19,7 @@ end
 
 @safetestset "NDTensors" begin
   @testset "$filename" for filename in [
+    "BlockSparseArrays.jl",
     "SetParameters.jl",
     "SmallVectors.jl",
     "linearalgebra.jl",