fix: incorrect rebase

Author: avik-pal

src/stdlibs/LinearAlgebra.jl

@@ -317,64 +317,4 @@ function diagonal_indices_zero_indexed(m::Integer, n::Integer, k::Integer=0)
     return indices
 end
 
-## This is quite handy to have but is not generalized enough to be put into Ops? Or maybe
-## we can document it and place it there under a different name. It takes a list of values
-## and a list of indices and constructs a matrix with the values at the indices.
-function simple_scatter_op(
-    shape, scatter_indices::TracedRArray{Int64,2}, updates::TracedRArray{T,1}
-) where {T}
-    @assert length(updates) == size(scatter_indices, 1)
-    @assert size(scatter_indices, 2) == 2
-
-    update_computation = MLIR.IR.Region()
-    block = MLIR.IR.Block(
-        [mlir_type(TracedRNumber{T}), mlir_type(TracedRNumber{T})],
-        [MLIR.IR.Location(), MLIR.IR.Location()],
-    )
-    return_op = MLIR.Dialects.stablehlo.return_([MLIR.IR.argument(block, 2)])
-    MLIR.IR.rmfromparent!(return_op)
-    push!(block, return_op)
-    pushfirst!(update_computation, block)
-
-    init_array = Ops.constant(fill(zero(T), shape)).mlir_data
-
-    #! format: off
-    scatter_dimension_numbers = MLIR.API.stablehloScatterDimensionNumbersGet(
-        MLIR.IR.context(),
-        0, Int64[],
-        2, Int64[0, 1],
-        0, Int64[],
-        0, Int64[],
-        2, Int64[0, 1],
-        1
-    )
-    #! format: on
-
-    res = MLIR.IR.result(
-        MLIR.Dialects.stablehlo.scatter(
-            [init_array],
-            scatter_indices.mlir_data,
-            [updates.mlir_data];
-            result_0=[mlir_type(TracedRArray{T,2}, shape)],
-            update_computation,
-            scatter_dimension_numbers,
-        ),
-        1,
-    )
-
-    return TracedRArray{T,2}((), res, shape)
-end
-
-## The cartesian version doesn't exist in julia 1.10
-function diagonal_indices_zero_indexed(m::Integer, n::Integer, k::Integer=0)
-    idx1, idx2 = 1 + max(0, -k), 1 + max(0, k)
-    L = max(0, k ≤ 0 ? min(m + k, n) : min(m, n - k))
-    indices = Matrix{Int}(undef, (L, 2))
-    for i in axes(indices, 1)
-        indices[i, 1] = idx1 + i - 2
-        indices[i, 2] = idx2 + i - 2
-    end
-    return indices
-end
-
 end