diff --git a/test/reference32/constructors/format_SparseBand.txt b/test/reference32/constructors/format_SparseBand.txt
index b176a2685..dc6197dff 100644
--- a/test/reference32/constructors/format_SparseBand.txt
+++ b/test/reference32/constructors/format_SparseBand.txt
@@ -1,8 +1,8 @@
 Tensor(SparseBand(Element(0))) constructors:
-initialized tensor: Tensor(SparseBand{Int32}(Element{0.0, Float64, Int32}([2.0, 2.0, 0.0, 3.0]), 6, [1, 2], [5], [1, 5]))
-initialized tensor: Tensor(SparseBand{Int16}(Element{0.0, Float64, Int32}([2.0, 2.0, 0.0, 3.0]), 6, [1, 2], Int16[5], [1, 5]))
-sized tensor: Tensor(SparseBand{Int32}(Element{0.0, Float64, Int32}(Float64[]), 7, [1], Int32[], Int32[]))
-sized tensor: Tensor(SparseBand{Int16}(Element{0.0, Float64, Int32}(Float64[]), 7, [1], Int16[], Int32[]))
-empty tensor: Tensor(SparseBand{Int32}(Element{0.0, Float64, Int32}(Float64[]), 0, [1], Int32[], Int32[]))
-empty tensor: Tensor(SparseBand{Int16}(Element{0.0, Float64, Int32}(Float64[]), 0, [1], Int16[], Int32[]))
+initialized tensor: Tensor(SparseBand{Int32}(Element{0.0, Float64, Int32}([2.0, 2.0, 0.0, 3.0]), 6, [5], [1, 5]))
+initialized tensor: Tensor(SparseBand{Int16}(Element{0.0, Float64, Int32}([2.0, 2.0, 0.0, 3.0]), 6, Int16[5], [1, 5]))
+sized tensor: Tensor(SparseBand{Int32}(Element{0.0, Float64, Int32}(Float64[]), 7, Int32[], Int32[]))
+sized tensor: Tensor(SparseBand{Int16}(Element{0.0, Float64, Int32}(Float64[]), 7, Int16[], Int32[]))
+empty tensor: Tensor(SparseBand{Int32}(Element{0.0, Float64, Int32}(Float64[]), 0, Int32[], Int32[]))
+empty tensor: Tensor(SparseBand{Int16}(Element{0.0, Float64, Int32}(Float64[]), 0, Int16[], Int32[]))
 
diff --git a/test/reference32/constructors/format_SparseInterval.txt b/test/reference32/constructors/format_SparseInterval.txt
index 380540dfa..bffd6264a 100644
--- a/test/reference32/constructors/format_SparseInterval.txt
+++ b/test/reference32/constructors/format_SparseInterval.txt
@@ -1,8 +1,8 @@
 Tensor(SparseInterval(Element(0))) constructors:
-initialized tensor: Tensor(SparseInterval{Int32}(Element{0.0, Float64, Int32}([2.0]), 6, [1, 2], [3], [3]))
-initialized tensor: Tensor(SparseInterval{Int16}(Element{0.0, Float64, Int32}([2.0]), 6, [1, 2], Int16[3], Int16[3]))
-sized tensor: Tensor(SparseInterval{Int32}(Element{0.0, Float64, Int32}(Float64[]), 7, [1], Int32[], Int32[]))
-sized tensor: Tensor(SparseInterval{Int16}(Element{0.0, Float64, Int32}(Float64[]), 7, [1], Int16[], Int16[]))
-empty tensor: Tensor(SparseInterval{Int32}(Element{0.0, Float64, Int32}(Float64[]), 0, [1], Int32[], Int32[]))
-empty tensor: Tensor(SparseInterval{Int16}(Element{0.0, Float64, Int32}(Float64[]), 0, [1], Int16[], Int16[]))
+initialized tensor: Tensor(SparseInterval{Int32}(Element{0.0, Float64, Int32}([2.0]), 6, [3], [3]))
+initialized tensor: Tensor(SparseInterval{Int16}(Element{0.0, Float64, Int32}([2.0]), 6, Int16[3], Int16[3]))
+sized tensor: Tensor(SparseInterval{Int32}(Element{0.0, Float64, Int32}(Float64[]), 7, Int32[], Int32[]))
+sized tensor: Tensor(SparseInterval{Int16}(Element{0.0, Float64, Int32}(Float64[]), 7, Int16[], Int16[]))
+empty tensor: Tensor(SparseInterval{Int32}(Element{0.0, Float64, Int32}(Float64[]), 0, Int32[], Int32[]))
+empty tensor: Tensor(SparseInterval{Int16}(Element{0.0, Float64, Int32}(Float64[]), 0, Int16[], Int16[]))
 
diff --git a/test/reference32/constructors/format_SparsePoint.txt b/test/reference32/constructors/format_SparsePoint.txt
index d7be36827..2b7854852 100644
--- a/test/reference32/constructors/format_SparsePoint.txt
+++ b/test/reference32/constructors/format_SparsePoint.txt
@@ -1,8 +1,8 @@
 Tensor(SparsePoint(Element(0))) constructors:
-initialized tensor: Tensor(SparsePoint{Int32}(Element{0.0, Float64, Int32}([2.0]), 6, [1, 2], [3]))
-initialized tensor: Tensor(SparsePoint{Int16}(Element{0.0, Float64, Int32}([2.0]), 6, [1, 2], Int16[3]))
-sized tensor: Tensor(SparsePoint{Int32}(Element{0.0, Float64, Int32}(Float64[]), 7, [1], Int32[]))
-sized tensor: Tensor(SparsePoint{Int16}(Element{0.0, Float64, Int32}(Float64[]), 7, [1], Int16[]))
-empty tensor: Tensor(SparsePoint{Int32}(Element{0.0, Float64, Int32}(Float64[]), 0, [1], Int32[]))
-empty tensor: Tensor(SparsePoint{Int16}(Element{0.0, Float64, Int32}(Float64[]), 0, [1], Int16[]))
+initialized tensor: Tensor(SparsePoint{Int32}(Element{0.0, Float64, Int32}([2.0]), 6, [3]))
+initialized tensor: Tensor(SparsePoint{Int16}(Element{0.0, Float64, Int32}([2.0]), 6, Int16[3]))
+sized tensor: Tensor(SparsePoint{Int32}(Element{0.0, Float64, Int32}(Float64[]), 7, Int32[]))
+sized tensor: Tensor(SparsePoint{Int16}(Element{0.0, Float64, Int32}(Float64[]), 7, Int16[]))
+empty tensor: Tensor(SparsePoint{Int32}(Element{0.0, Float64, Int32}(Float64[]), 0, Int32[]))
+empty tensor: Tensor(SparsePoint{Int16}(Element{0.0, Float64, Int32}(Float64[]), 0, Int16[]))
 
diff --git a/test/reference32/representation/Dense{SparseBand}_representation.txt b/test/reference32/representation/Dense{SparseBand}_representation.txt
index c3bb36048..f245b32ae 100644
--- a/test/reference32/representation/Dense{SparseBand}_representation.txt
+++ b/test/reference32/representation/Dense{SparseBand}_representation.txt
@@ -1,24 +1,24 @@
 Dense{SparseBand} representation:
 
 5x5_falses: Bool[0 0 0 0 0; 0 0 0 0 0; 0 0 0 0 0; 0 0 0 0 0; 0 0 0 0 0]
-tensor: Tensor(Dense{Int32}(SparseBand{Int32}(Element{false, Bool, Int32}(Bool[]), 5, [1, 1, 1, 1, 1, 1], Int32[], [1]), 5))
+tensor: Tensor(Dense{Int32}(SparseBand{Int32}(Element{false, Bool, Int32}(Bool[]), 5, [1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1]), 5))
 countstored: 0
 5x5_trues: Bool[1 1 1 1 1; 1 1 1 1 1; 1 1 1 1 1; 1 1 1 1 1; 1 1 1 1 1]
-tensor: Tensor(Dense{Int32}(SparseBand{Int32}(Element{false, Bool, Int32}(Bool[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]), 5, [1, 2, 3, 4, 5, 6], [5, 5, 5, 5, 5], [1, 6, 11, 16, 21, 26]), 5))
+tensor: Tensor(Dense{Int32}(SparseBand{Int32}(Element{false, Bool, Int32}(Bool[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]), 5, [5, 5, 5, 5, 5], [1, 6, 11, 16, 21, 26]), 5))
 countstored: 25
 4x4_one_bool: Bool[0 0 0 1; 0 0 0 0; 1 0 0 0; 0 1 0 0]
-tensor: Tensor(Dense{Int32}(SparseBand{Int32}(Element{false, Bool, Int32}(Bool[1, 1, 1]), 4, [1, 2, 3, 3, 4], [3, 4, 1], [1, 2, 3, 4]), 4))
+tensor: Tensor(Dense{Int32}(SparseBand{Int32}(Element{false, Bool, Int32}(Bool[1, 1, 1]), 4, [3, 4, 1, 1], [1, 2, 3, 3, 4]), 4))
 countstored: 3
 5x4_bool_mix: Bool[0 1 0 1; 0 0 0 0; 1 1 1 1; 1 1 1 1; 0 1 0 1]
-tensor: Tensor(Dense{Int32}(SparseBand{Int32}(Element{false, Bool, Int32}(Bool[1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1]), 5, [1, 2, 3, 4, 5], [4, 5, 4, 5], [1, 3, 8, 10, 15]), 4))
+tensor: Tensor(Dense{Int32}(SparseBand{Int32}(Element{false, Bool, Int32}(Bool[1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1]), 5, [4, 5, 4, 5], [1, 3, 8, 10, 15]), 4))
 countstored: 14
 5x5_zeros: [0.0 0.0 0.0 0.0 0.0; 0.0 0.0 0.0 0.0 0.0; 0.0 0.0 0.0 0.0 0.0; 0.0 0.0 0.0 0.0 0.0; 0.0 0.0 0.0 0.0 0.0]
-tensor: Tensor(Dense{Int32}(SparseBand{Int32}(Element{0.0, Float64, Int32}(Float64[]), 5, [1, 1, 1, 1, 1, 1], Int32[], [1]), 5))
+tensor: Tensor(Dense{Int32}(SparseBand{Int32}(Element{0.0, Float64, Int32}(Float64[]), 5, [1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1]), 5))
 countstored: 0
 5x5_ones: [1.0 1.0 1.0 1.0 1.0; 1.0 1.0 1.0 1.0 1.0; 1.0 1.0 1.0 1.0 1.0; 1.0 1.0 1.0 1.0 1.0; 1.0 1.0 1.0 1.0 1.0]
-tensor: Tensor(Dense{Int32}(SparseBand{Int32}(Element{0.0, Float64, Int32}([1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]), 5, [1, 2, 3, 4, 5, 6], [5, 5, 5, 5, 5], [1, 6, 11, 16, 21, 26]), 5))
+tensor: Tensor(Dense{Int32}(SparseBand{Int32}(Element{0.0, Float64, Int32}([1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]), 5, [5, 5, 5, 5, 5], [1, 6, 11, 16, 21, 26]), 5))
 countstored: 25
 5x5_float_mix: [0.0 1.0 2.0 2.0 3.0; 0.0 0.0 0.0 0.0 0.0; 1.0 1.0 2.0 0.0 0.0; 0.0 0.0 0.0 3.0 0.0; 0.0 0.0 0.0 0.0 0.0]
-tensor: Tensor(Dense{Int32}(SparseBand{Int32}(Element{0.0, Float64, Int32}([1.0, 1.0, 0.0, 1.0, 2.0, 0.0, 2.0, 2.0, 0.0, 0.0, 3.0, 3.0]), 5, [1, 2, 3, 4, 5, 6], [3, 3, 3, 4, 1], [1, 2, 5, 8, 12, 13]), 5))
+tensor: Tensor(Dense{Int32}(SparseBand{Int32}(Element{0.0, Float64, Int32}([1.0, 1.0, 0.0, 1.0, 2.0, 0.0, 2.0, 2.0, 0.0, 0.0, 3.0, 3.0]), 5, [3, 3, 3, 4, 1], [1, 2, 5, 8, 12, 13]), 5))
 countstored: 12
 
diff --git a/test/reference32/representation/SparseBand_representation.txt b/test/reference32/representation/SparseBand_representation.txt
index 46adcf57e..9eac0f1f1 100644
--- a/test/reference32/representation/SparseBand_representation.txt
+++ b/test/reference32/representation/SparseBand_representation.txt
@@ -1,39 +1,39 @@
 SparseBand representation:
 
 5x_false: Bool[0, 0, 0, 0, 0]
-tensor: Tensor(SparseBand{Int32}(Element{false, Bool, Int32}(Bool[]), 5, [1, 1], Int32[], [1]))
+tensor: Tensor(SparseBand{Int32}(Element{false, Bool, Int32}(Bool[]), 5, [1], [1, 1]))
 countstored: 0
 5x_true: Bool[1, 1, 1, 1, 1]
-tensor: Tensor(SparseBand{Int32}(Element{false, Bool, Int32}(Bool[1, 1, 1, 1, 1]), 5, [1, 2], [5], [1, 6]))
+tensor: Tensor(SparseBand{Int32}(Element{false, Bool, Int32}(Bool[1, 1, 1, 1, 1]), 5, [5], [1, 6]))
 countstored: 5
 6x_bool_mix: Bool[0, 1, 1, 0, 0, 1]
-tensor: Tensor(SparseBand{Int32}(Element{false, Bool, Int32}(Bool[1, 1, 0, 0, 1]), 6, [1, 2], [6], [1, 6]))
+tensor: Tensor(SparseBand{Int32}(Element{false, Bool, Int32}(Bool[1, 1, 0, 0, 1]), 6, [6], [1, 6]))
 countstored: 5
 6x_one_bool: Bool[0, 0, 1, 0, 0, 0]
-tensor: Tensor(SparseBand{Int32}(Element{false, Bool, Int32}(Bool[1]), 6, [1, 2], [3], [1, 2]))
+tensor: Tensor(SparseBand{Int32}(Element{false, Bool, Int32}(Bool[1]), 6, [3], [1, 2]))
 countstored: 1
 1111x_bool_mix: Bool[0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
-tensor: Tensor(SparseBand{Int32}(Element{false, Bool, Int32}(Bool[1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1]), 1111, [1, 2], [1001], [1, 1001]))
+tensor: Tensor(SparseBand{Int32}(Element{false, Bool, Int32}(Bool[1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1]), 1111, [1001], [1, 1001]))
 countstored: 1000
 11x_bool_mix: Bool[0, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1]
-tensor: Tensor(SparseBand{Int32}(Element{false, Bool, Int32}(Bool[1, 1, 0, 1, 1, 1, 1, 1, 0, 1]), 11, [1, 2], [11], [1, 11]))
+tensor: Tensor(SparseBand{Int32}(Element{false, Bool, Int32}(Bool[1, 1, 0, 1, 1, 1, 1, 1, 0, 1]), 11, [11], [1, 11]))
 countstored: 10
 6x_float_mix: [0.0, 2.0, 2.0, 0.0, 3.0, 3.0]
-tensor: Tensor(SparseBand{Int32}(Element{0.0, Float64, Int32}([2.0, 2.0, 0.0, 3.0, 3.0]), 6, [1, 2], [6], [1, 6]))
+tensor: Tensor(SparseBand{Int32}(Element{0.0, Float64, Int32}([2.0, 2.0, 0.0, 3.0, 3.0]), 6, [6], [1, 6]))
 countstored: 5
 4x_zeros: [0.0, 0.0, 0.0, 0.0]
-tensor: Tensor(SparseBand{Int32}(Element{0.0, Float64, Int32}(Float64[]), 4, [1, 1], Int32[], [1]))
+tensor: Tensor(SparseBand{Int32}(Element{0.0, Float64, Int32}(Float64[]), 4, [1], [1, 1]))
 countstored: 0
 5x_zeros: [0.0, 0.0, 0.0, 0.0, 0.0]
-tensor: Tensor(SparseBand{Int32}(Element{0.0, Float64, Int32}(Float64[]), 5, [1, 1], Int32[], [1]))
+tensor: Tensor(SparseBand{Int32}(Element{0.0, Float64, Int32}(Float64[]), 5, [1], [1, 1]))
 countstored: 0
 5x_ones: [1.0, 1.0, 1.0, 1.0, 1.0]
-tensor: Tensor(SparseBand{Int32}(Element{0.0, Float64, Int32}([1.0, 1.0, 1.0, 1.0, 1.0]), 5, [1, 2], [5], [1, 6]))
+tensor: Tensor(SparseBand{Int32}(Element{0.0, Float64, Int32}([1.0, 1.0, 1.0, 1.0, 1.0]), 5, [5], [1, 6]))
 countstored: 5
 9x_float_mix: [0.0, 1.0, 1.0, 2.0, 2.0, 0.0, 0.0, 3.0, 0.0]
-tensor: Tensor(SparseBand{Int32}(Element{0.0, Float64, Int32}([1.0, 1.0, 2.0, 2.0, 0.0, 0.0, 3.0]), 9, [1, 2], [8], [1, 8]))
+tensor: Tensor(SparseBand{Int32}(Element{0.0, Float64, Int32}([1.0, 1.0, 2.0, 2.0, 0.0, 0.0, 3.0]), 9, [8], [1, 8]))
 countstored: 7
 1111x_float_mix: [0.0, 20.0, 30.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 5550.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 6660.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
-tensor: Tensor(SparseBand{Int32}(Element{0.0, Float64, Int32}([20.0, 30.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 5550.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 6660.0]), 1111, [1, 2], [666], [1, 666]))
+tensor: Tensor(SparseBand{Int32}(Element{0.0, Float64, Int32}([20.0, 30.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 5550.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 6660.0]), 1111, [666], [1, 666]))
 countstored: 665
 
diff --git a/test/reference32/representation/SparseBand{Dense}_representation.txt b/test/reference32/representation/SparseBand{Dense}_representation.txt
index fa0a0a82b..91f33438a 100644
--- a/test/reference32/representation/SparseBand{Dense}_representation.txt
+++ b/test/reference32/representation/SparseBand{Dense}_representation.txt
@@ -1,24 +1,24 @@
 SparseBand{Dense} representation:
 
 5x5_falses: Bool[0 0 0 0 0; 0 0 0 0 0; 0 0 0 0 0; 0 0 0 0 0; 0 0 0 0 0]
-tensor: Tensor(SparseBand{Int32}(Dense{Int32}(Element{false, Bool, Int32}(Bool[]), 5), 5, [1, 1], Int32[], [1]))
+tensor: Tensor(SparseBand{Int32}(Dense{Int32}(Element{false, Bool, Int32}(Bool[]), 5), 5, [1], [1, 1]))
 countstored: 0
 5x5_trues: Bool[1 1 1 1 1; 1 1 1 1 1; 1 1 1 1 1; 1 1 1 1 1; 1 1 1 1 1]
-tensor: Tensor(SparseBand{Int32}(Dense{Int32}(Element{false, Bool, Int32}(Bool[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]), 5), 5, [1, 2], [5], [1, 6]))
+tensor: Tensor(SparseBand{Int32}(Dense{Int32}(Element{false, Bool, Int32}(Bool[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]), 5), 5, [5], [1, 6]))
 countstored: 25
 4x4_one_bool: Bool[0 0 0 1; 0 0 0 0; 1 0 0 0; 0 1 0 0]
-tensor: Tensor(SparseBand{Int32}(Dense{Int32}(Element{false, Bool, Int32}(Bool[0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0]), 4), 4, [1, 2], [4], [1, 5]))
+tensor: Tensor(SparseBand{Int32}(Dense{Int32}(Element{false, Bool, Int32}(Bool[0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0]), 4), 4, [4], [1, 5]))
 countstored: 16
 5x4_bool_mix: Bool[0 1 0 1; 0 0 0 0; 1 1 1 1; 1 1 1 1; 0 1 0 1]
-tensor: Tensor(SparseBand{Int32}(Dense{Int32}(Element{false, Bool, Int32}(Bool[0, 0, 1, 1, 0, 1, 0, 1, 1, 1, 0, 0, 1, 1, 0, 1, 0, 1, 1, 1]), 5), 4, [1, 2], [4], [1, 5]))
+tensor: Tensor(SparseBand{Int32}(Dense{Int32}(Element{false, Bool, Int32}(Bool[0, 0, 1, 1, 0, 1, 0, 1, 1, 1, 0, 0, 1, 1, 0, 1, 0, 1, 1, 1]), 5), 4, [4], [1, 5]))
 countstored: 20
 5x5_zeros: [0.0 0.0 0.0 0.0 0.0; 0.0 0.0 0.0 0.0 0.0; 0.0 0.0 0.0 0.0 0.0; 0.0 0.0 0.0 0.0 0.0; 0.0 0.0 0.0 0.0 0.0]
-tensor: Tensor(SparseBand{Int32}(Dense{Int32}(Element{0.0, Float64, Int32}(Float64[]), 5), 5, [1, 1], Int32[], [1]))
+tensor: Tensor(SparseBand{Int32}(Dense{Int32}(Element{0.0, Float64, Int32}(Float64[]), 5), 5, [1], [1, 1]))
 countstored: 0
 5x5_ones: [1.0 1.0 1.0 1.0 1.0; 1.0 1.0 1.0 1.0 1.0; 1.0 1.0 1.0 1.0 1.0; 1.0 1.0 1.0 1.0 1.0; 1.0 1.0 1.0 1.0 1.0]
-tensor: Tensor(SparseBand{Int32}(Dense{Int32}(Element{0.0, Float64, Int32}([1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]), 5), 5, [1, 2], [5], [1, 6]))
+tensor: Tensor(SparseBand{Int32}(Dense{Int32}(Element{0.0, Float64, Int32}([1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]), 5), 5, [5], [1, 6]))
 countstored: 25
 5x5_float_mix: [0.0 1.0 2.0 2.0 3.0; 0.0 0.0 0.0 0.0 0.0; 1.0 1.0 2.0 0.0 0.0; 0.0 0.0 0.0 3.0 0.0; 0.0 0.0 0.0 0.0 0.0]
-tensor: Tensor(SparseBand{Int32}(Dense{Int32}(Element{0.0, Float64, Int32}([0.0, 0.0, 1.0, 0.0, 0.0, 1.0, 0.0, 1.0, 0.0, 0.0, 2.0, 0.0, 2.0, 0.0, 0.0, 2.0, 0.0, 0.0, 3.0, 0.0, 3.0, 0.0, 0.0, 0.0, 0.0]), 5), 5, [1, 2], [5], [1, 6]))
+tensor: Tensor(SparseBand{Int32}(Dense{Int32}(Element{0.0, Float64, Int32}([0.0, 0.0, 1.0, 0.0, 0.0, 1.0, 0.0, 1.0, 0.0, 0.0, 2.0, 0.0, 2.0, 0.0, 0.0, 2.0, 0.0, 0.0, 3.0, 0.0, 3.0, 0.0, 0.0, 0.0, 0.0]), 5), 5, [5], [1, 6]))
 countstored: 25
 
diff --git a/test/reference32/representation/SparseBand{SparseList}_representation.txt b/test/reference32/representation/SparseBand{SparseList}_representation.txt
index 807c8a91f..48853ab6b 100644
--- a/test/reference32/representation/SparseBand{SparseList}_representation.txt
+++ b/test/reference32/representation/SparseBand{SparseList}_representation.txt
@@ -1,24 +1,24 @@
 SparseBand{SparseList} representation:
 
 5x5_falses: Bool[0 0 0 0 0; 0 0 0 0 0; 0 0 0 0 0; 0 0 0 0 0; 0 0 0 0 0]
-tensor: Tensor(SparseBand{Int32}(SparseList{Int32}(Element{false, Bool, Int32}(Bool[]), 5, [1], Int32[]), 5, [1, 1], Int32[], [1]))
+tensor: Tensor(SparseBand{Int32}(SparseList{Int32}(Element{false, Bool, Int32}(Bool[]), 5, [1], Int32[]), 5, [1], [1, 1]))
 countstored: 0
 5x5_trues: Bool[1 1 1 1 1; 1 1 1 1 1; 1 1 1 1 1; 1 1 1 1 1; 1 1 1 1 1]
-tensor: Tensor(SparseBand{Int32}(SparseList{Int32}(Element{false, Bool, Int32}(Bool[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]), 5, [1, 6, 11, 16, 21, 26], [1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 1, 2, 3, 4, 5]), 5, [1, 2], [5], [1, 6]))
+tensor: Tensor(SparseBand{Int32}(SparseList{Int32}(Element{false, Bool, Int32}(Bool[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]), 5, [1, 6, 11, 16, 21, 26], [1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 1, 2, 3, 4, 5]), 5, [5], [1, 6]))
 countstored: 25
 4x4_one_bool: Bool[0 0 0 1; 0 0 0 0; 1 0 0 0; 0 1 0 0]
-tensor: Tensor(SparseBand{Int32}(SparseList{Int32}(Element{false, Bool, Int32}(Bool[1, 1, 1]), 4, [1, 2, 3, 3, 4], [3, 4, 1]), 4, [1, 2], [4], [1, 5]))
+tensor: Tensor(SparseBand{Int32}(SparseList{Int32}(Element{false, Bool, Int32}(Bool[1, 1, 1]), 4, [1, 2, 3, 3, 4], [3, 4, 1]), 4, [4], [1, 5]))
 countstored: 3
 5x4_bool_mix: Bool[0 1 0 1; 0 0 0 0; 1 1 1 1; 1 1 1 1; 0 1 0 1]
-tensor: Tensor(SparseBand{Int32}(SparseList{Int32}(Element{false, Bool, Int32}(Bool[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]), 5, [1, 3, 7, 9, 13], [3, 4, 1, 3, 4, 5, 3, 4, 1, 3, 4, 5]), 4, [1, 2], [4], [1, 5]))
+tensor: Tensor(SparseBand{Int32}(SparseList{Int32}(Element{false, Bool, Int32}(Bool[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]), 5, [1, 3, 7, 9, 13], [3, 4, 1, 3, 4, 5, 3, 4, 1, 3, 4, 5]), 4, [4], [1, 5]))
 countstored: 12
 5x5_zeros: [0.0 0.0 0.0 0.0 0.0; 0.0 0.0 0.0 0.0 0.0; 0.0 0.0 0.0 0.0 0.0; 0.0 0.0 0.0 0.0 0.0; 0.0 0.0 0.0 0.0 0.0]
-tensor: Tensor(SparseBand{Int32}(SparseList{Int32}(Element{0.0, Float64, Int32}(Float64[]), 5, [1], Int32[]), 5, [1, 1], Int32[], [1]))
+tensor: Tensor(SparseBand{Int32}(SparseList{Int32}(Element{0.0, Float64, Int32}(Float64[]), 5, [1], Int32[]), 5, [1], [1, 1]))
 countstored: 0
 5x5_ones: [1.0 1.0 1.0 1.0 1.0; 1.0 1.0 1.0 1.0 1.0; 1.0 1.0 1.0 1.0 1.0; 1.0 1.0 1.0 1.0 1.0; 1.0 1.0 1.0 1.0 1.0]
-tensor: Tensor(SparseBand{Int32}(SparseList{Int32}(Element{0.0, Float64, Int32}([1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]), 5, [1, 6, 11, 16, 21, 26], [1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 1, 2, 3, 4, 5]), 5, [1, 2], [5], [1, 6]))
+tensor: Tensor(SparseBand{Int32}(SparseList{Int32}(Element{0.0, Float64, Int32}([1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]), 5, [1, 6, 11, 16, 21, 26], [1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 1, 2, 3, 4, 5]), 5, [5], [1, 6]))
 countstored: 25
 5x5_float_mix: [0.0 1.0 2.0 2.0 3.0; 0.0 0.0 0.0 0.0 0.0; 1.0 1.0 2.0 0.0 0.0; 0.0 0.0 0.0 3.0 0.0; 0.0 0.0 0.0 0.0 0.0]
-tensor: Tensor(SparseBand{Int32}(SparseList{Int32}(Element{0.0, Float64, Int32}([1.0, 1.0, 1.0, 2.0, 2.0, 2.0, 3.0, 3.0]), 5, [1, 2, 4, 6, 8, 9], [3, 1, 3, 1, 3, 1, 4, 1]), 5, [1, 2], [5], [1, 6]))
+tensor: Tensor(SparseBand{Int32}(SparseList{Int32}(Element{0.0, Float64, Int32}([1.0, 1.0, 1.0, 2.0, 2.0, 2.0, 3.0, 3.0]), 5, [1, 2, 4, 6, 8, 9], [3, 1, 3, 1, 3, 1, 4, 1]), 5, [5], [1, 6]))
 countstored: 8
 
diff --git a/test/reference32/representation/SparseInterval_representation.txt b/test/reference32/representation/SparseInterval_representation.txt
index f17c5e63c..16a0f6fde 100644
--- a/test/reference32/representation/SparseInterval_representation.txt
+++ b/test/reference32/representation/SparseInterval_representation.txt
@@ -1,6 +1,6 @@
 SparseInterval representation:
 
 6x_one_bool: Bool[0, 0, 1, 0, 0, 0]
-tensor: Tensor(SparseInterval{Int32}(Element{false, Bool, Int32}(Bool[1]), 6, [1, 2], [3], [3]))
+tensor: Tensor(SparseInterval{Int32}(Element{false, Bool, Int32}(Bool[1]), 6, [3], [3]))
 countstored: 1
 
diff --git a/test/reference32/representation/SparseList{SparseBand}_representation.txt b/test/reference32/representation/SparseList{SparseBand}_representation.txt
index ce8c6b160..2d6066e3d 100644
--- a/test/reference32/representation/SparseList{SparseBand}_representation.txt
+++ b/test/reference32/representation/SparseList{SparseBand}_representation.txt
@@ -1,24 +1,24 @@
 SparseList{SparseBand} representation:
 
 5x5_falses: Bool[0 0 0 0 0; 0 0 0 0 0; 0 0 0 0 0; 0 0 0 0 0; 0 0 0 0 0]
-tensor: Tensor(SparseList{Int32}(SparseBand{Int32}(Element{false, Bool, Int32}(Bool[]), 5, [1], Int32[], [1]), 5, [1, 1], Int32[]))
+tensor: Tensor(SparseList{Int32}(SparseBand{Int32}(Element{false, Bool, Int32}(Bool[]), 5, Int32[], [1]), 5, [1, 1], Int32[]))
 countstored: 0
 5x5_trues: Bool[1 1 1 1 1; 1 1 1 1 1; 1 1 1 1 1; 1 1 1 1 1; 1 1 1 1 1]
-tensor: Tensor(SparseList{Int32}(SparseBand{Int32}(Element{false, Bool, Int32}(Bool[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]), 5, [1, 2, 3, 4, 5, 6], [5, 5, 5, 5, 5], [1, 6, 11, 16, 21, 26]), 5, [1, 6], [1, 2, 3, 4, 5]))
+tensor: Tensor(SparseList{Int32}(SparseBand{Int32}(Element{false, Bool, Int32}(Bool[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]), 5, [5, 5, 5, 5, 5], [1, 6, 11, 16, 21, 26]), 5, [1, 6], [1, 2, 3, 4, 5]))
 countstored: 25
 4x4_one_bool: Bool[0 0 0 1; 0 0 0 0; 1 0 0 0; 0 1 0 0]
-tensor: Tensor(SparseList{Int32}(SparseBand{Int32}(Element{false, Bool, Int32}(Bool[1, 1, 1]), 4, [1, 2, 3, 4], [3, 4, 1], [1, 2, 3, 4]), 4, [1, 4], [1, 2, 4]))
+tensor: Tensor(SparseList{Int32}(SparseBand{Int32}(Element{false, Bool, Int32}(Bool[1, 1, 1]), 4, [3, 4, 1], [1, 2, 3, 4]), 4, [1, 4], [1, 2, 4]))
 countstored: 3
 5x4_bool_mix: Bool[0 1 0 1; 0 0 0 0; 1 1 1 1; 1 1 1 1; 0 1 0 1]
-tensor: Tensor(SparseList{Int32}(SparseBand{Int32}(Element{false, Bool, Int32}(Bool[1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1]), 5, [1, 2, 3, 4, 5], [4, 5, 4, 5], [1, 3, 8, 10, 15]), 4, [1, 5], [1, 2, 3, 4]))
+tensor: Tensor(SparseList{Int32}(SparseBand{Int32}(Element{false, Bool, Int32}(Bool[1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1]), 5, [4, 5, 4, 5], [1, 3, 8, 10, 15]), 4, [1, 5], [1, 2, 3, 4]))
 countstored: 14
 5x5_zeros: [0.0 0.0 0.0 0.0 0.0; 0.0 0.0 0.0 0.0 0.0; 0.0 0.0 0.0 0.0 0.0; 0.0 0.0 0.0 0.0 0.0; 0.0 0.0 0.0 0.0 0.0]
-tensor: Tensor(SparseList{Int32}(SparseBand{Int32}(Element{0.0, Float64, Int32}(Float64[]), 5, [1], Int32[], [1]), 5, [1, 1], Int32[]))
+tensor: Tensor(SparseList{Int32}(SparseBand{Int32}(Element{0.0, Float64, Int32}(Float64[]), 5, Int32[], [1]), 5, [1, 1], Int32[]))
 countstored: 0
 5x5_ones: [1.0 1.0 1.0 1.0 1.0; 1.0 1.0 1.0 1.0 1.0; 1.0 1.0 1.0 1.0 1.0; 1.0 1.0 1.0 1.0 1.0; 1.0 1.0 1.0 1.0 1.0]
-tensor: Tensor(SparseList{Int32}(SparseBand{Int32}(Element{0.0, Float64, Int32}([1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]), 5, [1, 2, 3, 4, 5, 6], [5, 5, 5, 5, 5], [1, 6, 11, 16, 21, 26]), 5, [1, 6], [1, 2, 3, 4, 5]))
+tensor: Tensor(SparseList{Int32}(SparseBand{Int32}(Element{0.0, Float64, Int32}([1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]), 5, [5, 5, 5, 5, 5], [1, 6, 11, 16, 21, 26]), 5, [1, 6], [1, 2, 3, 4, 5]))
 countstored: 25
 5x5_float_mix: [0.0 1.0 2.0 2.0 3.0; 0.0 0.0 0.0 0.0 0.0; 1.0 1.0 2.0 0.0 0.0; 0.0 0.0 0.0 3.0 0.0; 0.0 0.0 0.0 0.0 0.0]
-tensor: Tensor(SparseList{Int32}(SparseBand{Int32}(Element{0.0, Float64, Int32}([1.0, 1.0, 0.0, 1.0, 2.0, 0.0, 2.0, 2.0, 0.0, 0.0, 3.0, 3.0]), 5, [1, 2, 3, 4, 5, 6], [3, 3, 3, 4, 1], [1, 2, 5, 8, 12, 13]), 5, [1, 6], [1, 2, 3, 4, 5]))
+tensor: Tensor(SparseList{Int32}(SparseBand{Int32}(Element{0.0, Float64, Int32}([1.0, 1.0, 0.0, 1.0, 2.0, 0.0, 2.0, 2.0, 0.0, 0.0, 3.0, 3.0]), 5, [3, 3, 3, 4, 1], [1, 2, 5, 8, 12, 13]), 5, [1, 6], [1, 2, 3, 4, 5]))
 countstored: 12
 
diff --git a/test/reference32/representation/SparsePoint_representation.txt b/test/reference32/representation/SparsePoint_representation.txt
index d17e96caf..49eb14481 100644
--- a/test/reference32/representation/SparsePoint_representation.txt
+++ b/test/reference32/representation/SparsePoint_representation.txt
@@ -1,6 +1,6 @@
 SparsePoint representation:
 
 6x_one_bool: Bool[0, 0, 1, 0, 0, 0]
-tensor: Tensor(SparsePoint{Int32}(Element{false, Bool, Int32}(Bool[1]), 6, [1, 2], [3]))
+tensor: Tensor(SparsePoint{Int32}(Element{false, Bool, Int32}(Bool[1]), 6, [3]))
 countstored: 1
 
diff --git a/test/reference32/representation/convert_from_SparseBand{Element{0.0}}.jl b/test/reference32/representation/convert_from_SparseBand{Element{0.0}}.jl
index e942e37b3..de55cc94a 100644
--- a/test/reference32/representation/convert_from_SparseBand{Element{0.0}}.jl
+++ b/test/reference32/representation/convert_from_SparseBand{Element{0.0}}.jl
@@ -5,7 +5,6 @@ quote
     res_lvl_2 = res_lvl.lvl
     res_lvl_val = res_lvl.lvl.val
     tmp_lvl = ((ex.bodies[1]).bodies[2]).body.rhs.tns.bind.lvl
-    tmp_lvl_ptr = tmp_lvl.ptr
     tmp_lvl_idx = tmp_lvl.idx
     tmp_lvl_ofs = tmp_lvl.ofs
     tmp_lvl_val = tmp_lvl.lvl.val
@@ -14,17 +13,10 @@ quote
     Finch.fill_range!(res_lvl_ptr, 0, 1 + 1, 1 + 1)
     res_lvl_qos = 0 + 1
     0 < 1 || throw(FinchProtocolError("SparseListLevels cannot be updated multiple times"))
-    tmp_lvl_r = tmp_lvl_ptr[1]
-    tmp_lvl_r_stop = tmp_lvl_ptr[1 + 1] - 1
-    if tmp_lvl_r <= tmp_lvl_r_stop
-        tmp_lvl_i1 = tmp_lvl_idx[tmp_lvl_r]
-        tmp_lvl_q_stop = tmp_lvl_ofs[tmp_lvl_r + 1]
-        tmp_lvl_i_2 = tmp_lvl_i1 - ((tmp_lvl_q_stop - tmp_lvl_ofs[tmp_lvl_r]) - 1)
-        tmp_lvl_q_ofs = (tmp_lvl_q_stop - tmp_lvl_i1) - 1
-    else
-        tmp_lvl_i_2 = 1
-        tmp_lvl_i1 = 0
-    end
+    tmp_lvl_i1 = tmp_lvl_idx[1]
+    tmp_lvl_q_stop = tmp_lvl_ofs[1 + 1]
+    tmp_lvl_i_2 = tmp_lvl_i1 - ((tmp_lvl_q_stop - tmp_lvl_ofs[1]) - 1)
+    tmp_lvl_q_ofs = (tmp_lvl_q_stop - tmp_lvl_i1) - 1
     phase_start_2 = max(1, tmp_lvl_i_2)
     phase_stop_2 = min(tmp_lvl.shape, tmp_lvl_i1)
     if phase_stop_2 >= phase_start_2
diff --git a/test/reference32/representation/convert_from_SparseBand{Element{false}}.jl b/test/reference32/representation/convert_from_SparseBand{Element{false}}.jl
index 073819839..8be7d517d 100644
--- a/test/reference32/representation/convert_from_SparseBand{Element{false}}.jl
+++ b/test/reference32/representation/convert_from_SparseBand{Element{false}}.jl
@@ -5,7 +5,6 @@ quote
     res_lvl_2 = res_lvl.lvl
     res_lvl_val = res_lvl.lvl.val
     tmp_lvl = ((ex.bodies[1]).bodies[2]).body.rhs.tns.bind.lvl
-    tmp_lvl_ptr = tmp_lvl.ptr
     tmp_lvl_idx = tmp_lvl.idx
     tmp_lvl_ofs = tmp_lvl.ofs
     tmp_lvl_val = tmp_lvl.lvl.val
@@ -14,17 +13,10 @@ quote
     Finch.fill_range!(res_lvl_ptr, 0, 1 + 1, 1 + 1)
     res_lvl_qos = 0 + 1
     0 < 1 || throw(FinchProtocolError("SparseListLevels cannot be updated multiple times"))
-    tmp_lvl_r = tmp_lvl_ptr[1]
-    tmp_lvl_r_stop = tmp_lvl_ptr[1 + 1] - 1
-    if tmp_lvl_r <= tmp_lvl_r_stop
-        tmp_lvl_i1 = tmp_lvl_idx[tmp_lvl_r]
-        tmp_lvl_q_stop = tmp_lvl_ofs[tmp_lvl_r + 1]
-        tmp_lvl_i_2 = tmp_lvl_i1 - ((tmp_lvl_q_stop - tmp_lvl_ofs[tmp_lvl_r]) - 1)
-        tmp_lvl_q_ofs = (tmp_lvl_q_stop - tmp_lvl_i1) - 1
-    else
-        tmp_lvl_i_2 = 1
-        tmp_lvl_i1 = 0
-    end
+    tmp_lvl_i1 = tmp_lvl_idx[1]
+    tmp_lvl_q_stop = tmp_lvl_ofs[1 + 1]
+    tmp_lvl_i_2 = tmp_lvl_i1 - ((tmp_lvl_q_stop - tmp_lvl_ofs[1]) - 1)
+    tmp_lvl_q_ofs = (tmp_lvl_q_stop - tmp_lvl_i1) - 1
     phase_start_2 = max(1, tmp_lvl_i_2)
     phase_stop_2 = min(tmp_lvl.shape, tmp_lvl_i1)
     if phase_stop_2 >= phase_start_2
diff --git a/test/reference32/representation/convert_from_SparseInterval{Element{false}}.jl b/test/reference32/representation/convert_from_SparseInterval{Element{false}}.jl
index 7ddae043b..a43d2394b 100644
--- a/test/reference32/representation/convert_from_SparseInterval{Element{false}}.jl
+++ b/test/reference32/representation/convert_from_SparseInterval{Element{false}}.jl
@@ -5,7 +5,6 @@ quote
     res_lvl_2 = res_lvl.lvl
     res_lvl_val = res_lvl.lvl.val
     tmp_lvl = ((ex.bodies[1]).bodies[2]).body.rhs.tns.bind.lvl
-    tmp_lvl_ptr = tmp_lvl.ptr
     tmp_lvl_left = tmp_lvl.left
     tmp_lvl_right = tmp_lvl.right
     tmp_lvl_val = tmp_lvl.lvl.val
@@ -14,19 +13,12 @@ quote
     Finch.fill_range!(res_lvl_ptr, 0, 1 + 1, 1 + 1)
     res_lvl_qos = 0 + 1
     0 < 1 || throw(FinchProtocolError("SparseListLevels cannot be updated multiple times"))
-    tmp_lvl_q = tmp_lvl_ptr[1]
-    tmp_lvl_q_stop = tmp_lvl_ptr[1 + 1]
-    if tmp_lvl_q < tmp_lvl_q_stop
-        tmp_lvl_i_start = tmp_lvl_left[tmp_lvl_q]
-        tmp_lvl_i_stop = tmp_lvl_right[tmp_lvl_q]
-    else
-        tmp_lvl_i_start = 1
-        tmp_lvl_i_stop = 0
-    end
+    tmp_lvl_i_start = tmp_lvl_left[1]
+    tmp_lvl_i_stop = tmp_lvl_right[1]
     phase_start_2 = max(1, tmp_lvl_i_start)
     phase_stop_2 = min(tmp_lvl.shape, tmp_lvl_i_stop)
     if phase_stop_2 >= phase_start_2
-        tmp_lvl_2_val = tmp_lvl_val[tmp_lvl_q]
+        tmp_lvl_2_val = tmp_lvl_val[1]
         for i_6 = phase_start_2:phase_stop_2
             if res_lvl_qos > res_lvl_qos_stop
                 res_lvl_qos_stop = max(res_lvl_qos_stop << 1, 1)
diff --git a/test/reference32/representation/convert_from_SparsePoint{Element{false}}.jl b/test/reference32/representation/convert_from_SparsePoint{Element{false}}.jl
index 9c28282cf..671dca2c7 100644
--- a/test/reference32/representation/convert_from_SparsePoint{Element{false}}.jl
+++ b/test/reference32/representation/convert_from_SparsePoint{Element{false}}.jl
@@ -5,25 +5,18 @@ quote
     res_lvl_2 = res_lvl.lvl
     res_lvl_val = res_lvl.lvl.val
     tmp_lvl = ((ex.bodies[1]).bodies[2]).body.rhs.tns.bind.lvl
-    tmp_lvl_ptr = tmp_lvl.ptr
     tmp_lvl_idx = tmp_lvl.idx
     tmp_lvl_val = tmp_lvl.lvl.val
     Finch.resize_if_smaller!(res_lvl_ptr, 1 + 1)
     Finch.fill_range!(res_lvl_ptr, 0, 1 + 1, 1 + 1)
     res_lvl_qos = 0 + 1
     0 < 1 || throw(FinchProtocolError("SparseListLevels cannot be updated multiple times"))
-    tmp_lvl_q = tmp_lvl_ptr[1]
-    tmp_lvl_q_stop = tmp_lvl_ptr[1 + 1]
-    if tmp_lvl_q < tmp_lvl_q_stop
-        tmp_lvl_i = tmp_lvl_idx[tmp_lvl_q]
-    else
-        tmp_lvl_i = 0
-    end
+    tmp_lvl_i = max(tmp_lvl_idx[1], 1)
     phase_stop = min(tmp_lvl_i, tmp_lvl.shape)
     if phase_stop >= 1
         if phase_stop < tmp_lvl_i
         else
-            tmp_lvl_2_val = tmp_lvl_val[tmp_lvl_q]
+            tmp_lvl_2_val = tmp_lvl_val[1]
             if res_lvl_qos > 0
                 res_lvl_qos_stop = max(0 << 1, 1)
                 Finch.resize_if_smaller!(res_lvl_idx, res_lvl_qos_stop)
diff --git a/test/reference32/representation/convert_to_SparseBand{Element{0.0}}.jl b/test/reference32/representation/convert_to_SparseBand{Element{0.0}}.jl
index e4f345ba8..03c6759ae 100644
--- a/test/reference32/representation/convert_to_SparseBand{Element{0.0}}.jl
+++ b/test/reference32/representation/convert_to_SparseBand{Element{0.0}}.jl
@@ -1,6 +1,5 @@
 quote
     tmp_lvl = ((ex.bodies[1]).bodies[1]).tns.bind.lvl
-    tmp_lvl_ptr = tmp_lvl.ptr
     tmp_lvl_idx = tmp_lvl.idx
     tmp_lvl_ofs = tmp_lvl.ofs
     tmp_lvl_2 = tmp_lvl.lvl
@@ -12,11 +11,11 @@ quote
     tmp_lvl_qos_stop = 0
     Finch.resize_if_smaller!(tmp_lvl_ofs, 1)
     tmp_lvl_ofs[1] = 1
-    Finch.resize_if_smaller!(tmp_lvl_ptr, 1 + 1)
-    Finch.fill_range!(tmp_lvl_ptr, 0, 1 + 1, 1 + 1)
-    tmp_lvl_ros = 0
+    Finch.resize_if_smaller!(tmp_lvl_idx, 1)
+    Finch.fill_range!(tmp_lvl_idx, 1, 1, 1)
+    Finch.resize_if_smaller!(tmp_lvl_ofs, 1 + 1)
+    Finch.fill_range!(tmp_lvl_ofs, 0, 1 + 1, 1 + 1)
     tmp_lvl_qos = 0 + 1
-    tmp_lvl_qos_set = 0
     tmp_lvl_i_prev = -1
     tmp_lvl_i_set = -1
     0 < 1 || throw(FinchProtocolError("SparseBandLevels cannot be updated multiple times"))
@@ -55,7 +54,6 @@ quote
                     tmp_lvl_i_prev = ref_lvl_i
                 end
                 tmp_lvl_i_set = ref_lvl_i
-                tmp_lvl_qos_set = tmp_lvl_qos
                 ref_lvl_q += 1
             else
                 phase_stop_3 = min(phase_stop, ref_lvl_i)
@@ -80,7 +78,6 @@ quote
                         tmp_lvl_i_prev = phase_stop_3
                     end
                     tmp_lvl_i_set = phase_stop_3
-                    tmp_lvl_qos_set = tmp_lvl_qos
                     ref_lvl_q += 1
                 end
                 break
@@ -88,24 +85,15 @@ quote
         end
     end
     if tmp_lvl_i_prev > 0
-        tmp_lvl_ros = 0 + 1
-        if tmp_lvl_ros > 0
-            tmp_lvl_ros_stop = max(0 << 1, 1)
-            Finch.resize_if_smaller!(tmp_lvl_idx, tmp_lvl_ros_stop)
-            Finch.resize_if_smaller!(tmp_lvl_ofs, tmp_lvl_ros_stop + 1)
-        end
-        tmp_lvl_idx[tmp_lvl_ros] = tmp_lvl_i_set
-        tmp_lvl_ofs[tmp_lvl_ros + 1] = tmp_lvl_qos_set + 1
+        tmp_lvl_idx[1] = tmp_lvl_i_set
+        tmp_lvl_ofs[1 + 1] = (tmp_lvl_i_set - tmp_lvl_i_prev) + 1
     end
-    tmp_lvl_ptr[1 + 1] += tmp_lvl_ros - 0
-    resize!(tmp_lvl_ptr, 1 + 1)
+    resize!(tmp_lvl_idx, 1)
+    resize!(tmp_lvl_ofs, 1 + 1)
     for p = 2:1 + 1
-        tmp_lvl_ptr[p] += tmp_lvl_ptr[p - 1]
+        tmp_lvl_ofs[p] += tmp_lvl_ofs[p - 1]
     end
-    ros_stop = tmp_lvl_ptr[1 + 1] - 1
-    resize!(tmp_lvl_idx, ros_stop)
-    resize!(tmp_lvl_ofs, ros_stop + 1)
-    qos_stop = tmp_lvl_ofs[ros_stop + 1] - 1
+    qos_stop = tmp_lvl_ofs[1 + 1] - 1
     resize!(tmp_lvl_val, qos_stop)
-    (tmp = Tensor((SparseBandLevel){Int32}(tmp_lvl_2, ref_lvl.shape, tmp_lvl_ptr, tmp_lvl_idx, tmp_lvl_ofs)),)
+    (tmp = Tensor((SparseBandLevel){Int32}(tmp_lvl_2, ref_lvl.shape, tmp_lvl_idx, tmp_lvl_ofs)),)
 end
diff --git a/test/reference32/representation/convert_to_SparseBand{Element{false}}.jl b/test/reference32/representation/convert_to_SparseBand{Element{false}}.jl
index d5e6404bf..3b2788185 100644
--- a/test/reference32/representation/convert_to_SparseBand{Element{false}}.jl
+++ b/test/reference32/representation/convert_to_SparseBand{Element{false}}.jl
@@ -1,6 +1,5 @@
 quote
     tmp_lvl = ((ex.bodies[1]).bodies[1]).tns.bind.lvl
-    tmp_lvl_ptr = tmp_lvl.ptr
     tmp_lvl_idx = tmp_lvl.idx
     tmp_lvl_ofs = tmp_lvl.ofs
     tmp_lvl_2 = tmp_lvl.lvl
@@ -12,11 +11,11 @@ quote
     tmp_lvl_qos_stop = 0
     Finch.resize_if_smaller!(tmp_lvl_ofs, 1)
     tmp_lvl_ofs[1] = 1
-    Finch.resize_if_smaller!(tmp_lvl_ptr, 1 + 1)
-    Finch.fill_range!(tmp_lvl_ptr, 0, 1 + 1, 1 + 1)
-    tmp_lvl_ros = 0
+    Finch.resize_if_smaller!(tmp_lvl_idx, 1)
+    Finch.fill_range!(tmp_lvl_idx, 1, 1, 1)
+    Finch.resize_if_smaller!(tmp_lvl_ofs, 1 + 1)
+    Finch.fill_range!(tmp_lvl_ofs, 0, 1 + 1, 1 + 1)
     tmp_lvl_qos = 0 + 1
-    tmp_lvl_qos_set = 0
     tmp_lvl_i_prev = -1
     tmp_lvl_i_set = -1
     0 < 1 || throw(FinchProtocolError("SparseBandLevels cannot be updated multiple times"))
@@ -55,7 +54,6 @@ quote
                     tmp_lvl_i_prev = ref_lvl_i
                 end
                 tmp_lvl_i_set = ref_lvl_i
-                tmp_lvl_qos_set = tmp_lvl_qos
                 ref_lvl_q += 1
             else
                 phase_stop_3 = min(phase_stop, ref_lvl_i)
@@ -80,7 +78,6 @@ quote
                         tmp_lvl_i_prev = phase_stop_3
                     end
                     tmp_lvl_i_set = phase_stop_3
-                    tmp_lvl_qos_set = tmp_lvl_qos
                     ref_lvl_q += 1
                 end
                 break
@@ -88,24 +85,15 @@ quote
         end
     end
     if tmp_lvl_i_prev > 0
-        tmp_lvl_ros = 0 + 1
-        if tmp_lvl_ros > 0
-            tmp_lvl_ros_stop = max(0 << 1, 1)
-            Finch.resize_if_smaller!(tmp_lvl_idx, tmp_lvl_ros_stop)
-            Finch.resize_if_smaller!(tmp_lvl_ofs, tmp_lvl_ros_stop + 1)
-        end
-        tmp_lvl_idx[tmp_lvl_ros] = tmp_lvl_i_set
-        tmp_lvl_ofs[tmp_lvl_ros + 1] = tmp_lvl_qos_set + 1
+        tmp_lvl_idx[1] = tmp_lvl_i_set
+        tmp_lvl_ofs[1 + 1] = (tmp_lvl_i_set - tmp_lvl_i_prev) + 1
     end
-    tmp_lvl_ptr[1 + 1] += tmp_lvl_ros - 0
-    resize!(tmp_lvl_ptr, 1 + 1)
+    resize!(tmp_lvl_idx, 1)
+    resize!(tmp_lvl_ofs, 1 + 1)
     for p = 2:1 + 1
-        tmp_lvl_ptr[p] += tmp_lvl_ptr[p - 1]
+        tmp_lvl_ofs[p] += tmp_lvl_ofs[p - 1]
     end
-    ros_stop = tmp_lvl_ptr[1 + 1] - 1
-    resize!(tmp_lvl_idx, ros_stop)
-    resize!(tmp_lvl_ofs, ros_stop + 1)
-    qos_stop = tmp_lvl_ofs[ros_stop + 1] - 1
+    qos_stop = tmp_lvl_ofs[1 + 1] - 1
     resize!(tmp_lvl_val, qos_stop)
-    (tmp = Tensor((SparseBandLevel){Int32}(tmp_lvl_2, ref_lvl.shape, tmp_lvl_ptr, tmp_lvl_idx, tmp_lvl_ofs)),)
+    (tmp = Tensor((SparseBandLevel){Int32}(tmp_lvl_2, ref_lvl.shape, tmp_lvl_idx, tmp_lvl_ofs)),)
 end
diff --git a/test/reference32/representation/convert_to_SparseInterval{Element{false}}.jl b/test/reference32/representation/convert_to_SparseInterval{Element{false}}.jl
index 8034c67af..9c6ccedeb 100644
--- a/test/reference32/representation/convert_to_SparseInterval{Element{false}}.jl
+++ b/test/reference32/representation/convert_to_SparseInterval{Element{false}}.jl
@@ -1,6 +1,5 @@
 quote
     tmp_lvl = ((ex.bodies[1]).bodies[1]).tns.bind.lvl
-    tmp_lvl_ptr = tmp_lvl.ptr
     tmp_lvl_left = tmp_lvl.left
     tmp_lvl_right = tmp_lvl.right
     tmp_lvl_2 = tmp_lvl.lvl
@@ -9,11 +8,12 @@ quote
     ref_lvl_ptr = ref_lvl.ptr
     ref_lvl_idx = ref_lvl.idx
     ref_lvl_val = ref_lvl.lvl.val
-    tmp_lvl_qos_stop = 0
-    Finch.resize_if_smaller!(tmp_lvl_ptr, 1 + 1)
-    Finch.fill_range!(tmp_lvl_ptr, 0, 1 + 1, 1 + 1)
-    tmp_lvl_qos = 0 + 1
-    tmp_lvl_ptr[1 + 1] == 0 || throw(FinchProtocolError("SparseIntervalLevels can only be updated once"))
+    Finch.resize_if_smaller!(tmp_lvl_left, 1)
+    Finch.resize_if_smaller!(tmp_lvl_right, 1)
+    Finch.fill_range!(tmp_lvl_left, 1, 1, 1)
+    Finch.fill_range!(tmp_lvl_right, 0, 1, 1)
+    Finch.resize_if_smaller!(tmp_lvl_val, 1)
+    Finch.fill_range!(tmp_lvl_val, false, 1, 1)
     ref_lvl_q = ref_lvl_ptr[1]
     ref_lvl_q_stop = ref_lvl_ptr[1 + 1]
     if ref_lvl_q < ref_lvl_q_stop
@@ -30,49 +30,27 @@ quote
             ref_lvl_i = ref_lvl_idx[ref_lvl_q]
             if ref_lvl_i < phase_stop
                 ref_lvl_2_val = ref_lvl_val[ref_lvl_q]
-                if tmp_lvl_qos > tmp_lvl_qos_stop
-                    tmp_lvl_qos_stop = max(tmp_lvl_qos_stop << 1, 1)
-                    Finch.resize_if_smaller!(tmp_lvl_left, tmp_lvl_qos_stop)
-                    Finch.resize_if_smaller!(tmp_lvl_right, tmp_lvl_qos_stop)
-                    Finch.resize_if_smaller!(tmp_lvl_val, tmp_lvl_qos_stop)
-                    Finch.fill_range!(tmp_lvl_val, false, tmp_lvl_qos, tmp_lvl_qos_stop)
-                end
-                tmp_lvl_val[tmp_lvl_qos] = ref_lvl_2_val
-                tmp_lvl_qos == 0 + 1 || throw(FinchProtocolError("SparseIntervalLevels can only be updated once"))
-                tmp_lvl_left[tmp_lvl_qos] = ref_lvl_i
-                tmp_lvl_right[tmp_lvl_qos] = ref_lvl_i
-                tmp_lvl_qos += 1
+                tmp_lvl_val[1] = ref_lvl_2_val
+                tmp_lvl_left[1] < tmp_lvl_right[1] && throw(FinchProtocolError("SparseIntervalLevels can only be updated once"))
+                tmp_lvl_left[1] = ref_lvl_i
+                tmp_lvl_right[1] = ref_lvl_i
                 ref_lvl_q += 1
             else
                 phase_stop_3 = min(phase_stop, ref_lvl_i)
                 if ref_lvl_i == phase_stop_3
                     ref_lvl_2_val = ref_lvl_val[ref_lvl_q]
-                    if tmp_lvl_qos > tmp_lvl_qos_stop
-                        tmp_lvl_qos_stop = max(tmp_lvl_qos_stop << 1, 1)
-                        Finch.resize_if_smaller!(tmp_lvl_left, tmp_lvl_qos_stop)
-                        Finch.resize_if_smaller!(tmp_lvl_right, tmp_lvl_qos_stop)
-                        Finch.resize_if_smaller!(tmp_lvl_val, tmp_lvl_qos_stop)
-                        Finch.fill_range!(tmp_lvl_val, false, tmp_lvl_qos, tmp_lvl_qos_stop)
-                    end
-                    tmp_lvl_val[tmp_lvl_qos] = ref_lvl_2_val
-                    tmp_lvl_qos == 0 + 1 || throw(FinchProtocolError("SparseIntervalLevels can only be updated once"))
-                    tmp_lvl_left[tmp_lvl_qos] = phase_stop_3
-                    tmp_lvl_right[tmp_lvl_qos] = phase_stop_3
-                    tmp_lvl_qos += 1
+                    tmp_lvl_val[1] = ref_lvl_2_val
+                    tmp_lvl_left[1] < tmp_lvl_right[1] && throw(FinchProtocolError("SparseIntervalLevels can only be updated once"))
+                    tmp_lvl_left[1] = phase_stop_3
+                    tmp_lvl_right[1] = phase_stop_3
                     ref_lvl_q += 1
                 end
                 break
             end
         end
     end
-    tmp_lvl_ptr[1 + 1] = (tmp_lvl_qos - 0) - 1
-    resize!(tmp_lvl_ptr, 1 + 1)
-    for p = 1:1
-        tmp_lvl_ptr[p + 1] += tmp_lvl_ptr[p]
-    end
-    qos_stop = tmp_lvl_ptr[1 + 1] - 1
-    resize!(tmp_lvl_left, qos_stop)
-    resize!(tmp_lvl_right, qos_stop)
-    resize!(tmp_lvl_val, qos_stop)
-    (tmp = Tensor((SparseIntervalLevel){Int32}(tmp_lvl_2, ref_lvl.shape, tmp_lvl.ptr, tmp_lvl.left, tmp_lvl.right)),)
+    resize!(tmp_lvl_left, 1)
+    resize!(tmp_lvl_right, 1)
+    resize!(tmp_lvl_val, 1)
+    (tmp = Tensor((SparseIntervalLevel){Int32}(tmp_lvl_2, ref_lvl.shape, tmp_lvl.left, tmp_lvl.right)),)
 end
diff --git a/test/reference32/representation/convert_to_SparsePoint{Element{false}}.jl b/test/reference32/representation/convert_to_SparsePoint{Element{false}}.jl
index 3282015c6..b51d6030e 100644
--- a/test/reference32/representation/convert_to_SparsePoint{Element{false}}.jl
+++ b/test/reference32/representation/convert_to_SparsePoint{Element{false}}.jl
@@ -1,6 +1,5 @@
 quote
     tmp_lvl = ((ex.bodies[1]).bodies[1]).tns.bind.lvl
-    tmp_lvl_ptr = tmp_lvl.ptr
     tmp_lvl_idx = tmp_lvl.idx
     tmp_lvl_2 = tmp_lvl.lvl
     tmp_lvl_val = tmp_lvl.lvl.val
@@ -8,12 +7,10 @@ quote
     ref_lvl_ptr = ref_lvl.ptr
     ref_lvl_idx = ref_lvl.idx
     ref_lvl_val = ref_lvl.lvl.val
-    tmp_lvl_qos_stop = 0
-    Finch.resize_if_smaller!(tmp_lvl_ptr, 1 + 1)
-    Finch.fill_range!(tmp_lvl_ptr, 0, 1 + 1, 1 + 1)
-    tmp_lvl_qos = 0 + 1
-    tmp_lvl_ptr[1 + 1] == 0 || throw(FinchProtocolError("SparsePointLevels can only be updated once"))
-    0 < 1 || throw(FinchProtocolError("SparsePointLevels cannot be updated multiple times"))
+    Finch.resize_if_smaller!(tmp_lvl_idx, 1)
+    Finch.fill_range!(tmp_lvl_idx, 0, 1, 1)
+    Finch.resize_if_smaller!(tmp_lvl_val, 1)
+    Finch.fill_range!(tmp_lvl_val, false, 1, 1)
     ref_lvl_q = ref_lvl_ptr[1]
     ref_lvl_q_stop = ref_lvl_ptr[1 + 1]
     if ref_lvl_q < ref_lvl_q_stop
@@ -30,44 +27,24 @@ quote
             ref_lvl_i = ref_lvl_idx[ref_lvl_q]
             if ref_lvl_i < phase_stop
                 ref_lvl_2_val = ref_lvl_val[ref_lvl_q]
-                if tmp_lvl_qos > tmp_lvl_qos_stop
-                    tmp_lvl_qos_stop = max(tmp_lvl_qos_stop << 1, 1)
-                    Finch.resize_if_smaller!(tmp_lvl_idx, tmp_lvl_qos_stop)
-                    Finch.resize_if_smaller!(tmp_lvl_val, tmp_lvl_qos_stop)
-                    Finch.fill_range!(tmp_lvl_val, false, tmp_lvl_qos, tmp_lvl_qos_stop)
-                end
-                tmp_lvl_val[tmp_lvl_qos] = ref_lvl_2_val
-                tmp_lvl_qos == 0 + 1 || throw(FinchProtocolError("SparsePointLevels can only be updated once"))
-                tmp_lvl_idx[tmp_lvl_qos] = ref_lvl_i
-                tmp_lvl_qos += 1
+                tmp_lvl_val[1] = ref_lvl_2_val
+                @assert tmp_lvl_idx[1] == 0 || tmp_lvl_idx[1] == ref_lvl_i
+                tmp_lvl_idx[1] = ref_lvl_i
                 ref_lvl_q += 1
             else
                 phase_stop_3 = min(phase_stop, ref_lvl_i)
                 if ref_lvl_i == phase_stop_3
                     ref_lvl_2_val = ref_lvl_val[ref_lvl_q]
-                    if tmp_lvl_qos > tmp_lvl_qos_stop
-                        tmp_lvl_qos_stop = max(tmp_lvl_qos_stop << 1, 1)
-                        Finch.resize_if_smaller!(tmp_lvl_idx, tmp_lvl_qos_stop)
-                        Finch.resize_if_smaller!(tmp_lvl_val, tmp_lvl_qos_stop)
-                        Finch.fill_range!(tmp_lvl_val, false, tmp_lvl_qos, tmp_lvl_qos_stop)
-                    end
-                    tmp_lvl_val[tmp_lvl_qos] = ref_lvl_2_val
-                    tmp_lvl_qos == 0 + 1 || throw(FinchProtocolError("SparsePointLevels can only be updated once"))
-                    tmp_lvl_idx[tmp_lvl_qos] = phase_stop_3
-                    tmp_lvl_qos += 1
+                    tmp_lvl_val[1] = ref_lvl_2_val
+                    @assert tmp_lvl_idx[1] == 0 || tmp_lvl_idx[1] == phase_stop_3
+                    tmp_lvl_idx[1] = phase_stop_3
                     ref_lvl_q += 1
                 end
                 break
             end
         end
     end
-    tmp_lvl_ptr[1 + 1] += (tmp_lvl_qos - 0) - 1
-    resize!(tmp_lvl_ptr, 1 + 1)
-    for p = 1:1
-        tmp_lvl_ptr[p + 1] += tmp_lvl_ptr[p]
-    end
-    qos_stop = tmp_lvl_ptr[1 + 1] - 1
-    resize!(tmp_lvl_idx, qos_stop)
-    resize!(tmp_lvl_val, qos_stop)
-    (tmp = Tensor((SparsePointLevel){Int32}(tmp_lvl_2, ref_lvl.shape, tmp_lvl_ptr, tmp_lvl_idx)),)
+    resize!(tmp_lvl_idx, 1)
+    resize!(tmp_lvl_val, 1)
+    (tmp = Tensor((SparsePointLevel){Int32}(tmp_lvl_2, ref_lvl.shape, tmp_lvl_idx)),)
 end