Scatter optimization

```mlir
p.forwardFFT = ReactantAbstractFFTsExt.ReactantFFTInPlacePlan{ComplexF64, UnitRange{Int64}}(1:2)
p.tmpVec.mlir_data = %89 = "stablehlo.transpose"(%87) <{permutation = array}> : (tensor<12x12xcomplex>) -> tensor<12x12xcomplex>
module @reactant_nfft attributes {mhlo.num_partitions = 1 : i64, mhlo.num_replicas = 1 : i64} {
func.func @main(%arg0: tensor<6x6xcomplex> {enzymexla.memory_effects = []}) -> tensor<6xcomplex> attributes {enzymexla.memory_effects = []} {
%cst = stablehlo.constant 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: tensor<6x144xcomplex>
%c = stablehlo.constant dense<[[9, 9], [10, 9], [11, 9], [0, 9], [1, 9], [2, 9], [9, 10], [10, 10], [11, 10], [0, 10], [1, 10], [2, 10], [9, 11], [10, 11], [11, 11], [0, 11], [1, 11], [2, 11], [9, 0], [10, 0], [11, 0], [0, 0], [1, 0], [2, 0], [9, 1], [10, 1], [11, 1], [0, 1], [1, 1], [2, 1], [9, 2], [10, 2], [11, 2], [0, 2], [1, 2], [2, 2]]> : tensor<36x2xi64>
%cst_0 = stablehlo.constant dense<[(6.9922380976076615E-18,0.000000e+00), (3.3313971283295199E-18,0.000000e+00), (2.1593533194956E-18,0.000000e+00), (1.872085750299054E-18,0.000000e+00), (2.1593533194956039E-18,0.000000e+00), (3.3313971283295152E-18,0.000000e+00), (3.3313971283295199E-18,0.000000e+00), (1.5872180940805397E-18,0.000000e+00), (1.0288069924389033E-18,0.000000e+00), (8.919406069233695E-19,0.000000e+00), (1.0288069924389053E-18,0.000000e+00), (1.5872180940805374E-18,0.000000e+00), (2.1593533194956E-18,0.000000e+00), (1.0288069924389033E-18,0.000000e+00), (6.6685468848836949E-19,0.000000e+00), (5.7814029254406829E-19,0.000000e+00), (6.6685468848837065E-19,0.000000e+00), (1.028806992438902E-18,0.000000e+00), (1.872085750299054E-18,0.000000e+00), (8.919406069233695E-19,0.000000e+00), (5.7814029254406829E-19,0.000000e+00), (5.0122793411052162E-19,0.000000e+00), (5.7814029254406935E-19,0.000000e+00), (8.9194060692336816E-19,0.000000e+00), (2.1593533194956039E-18,0.000000e+00), (1.0288069924389053E-18,0.000000e+00), (6.6685468848837065E-19,0.000000e+00), (5.7814029254406935E-19,0.000000e+00), (6.668546884883718E-19,0.000000e+00), (1.0288069924389037E-18,0.000000e+00), (3.3313971283295152E-18,0.000000e+00), (1.5872180940805374E-18,0.000000e+00), (1.028806992438902E-18,0.000000e+00), (8.9194060692336816E-19,0.000000e+00), (1.0288069924389037E-18,0.000000e+00), (1.5872180940805351E-18,0.000000e+00)]> : tensor<36xcomplex>
%cst_1 = stablehlo.constant dense<(0.000000e+00,0.000000e+00)> : tensor<12x12xcomplex>
%0 = stablehlo.reshape %arg0 : (tensor<6x6xcomplex>) -> tensor<36xcomplex>
%1 = stablehlo.multiply %0, %cst_0 {enzymexla.symmetric_matrix = [#enzymexla]} : tensor<36xcomplex>
%2 = "stablehlo.scatter"(%cst_1, %c, %1) <{scatter_dimension_numbers = #stablehlo.scatter, unique_indices = true}> ({
^bb0(%arg1: tensor>, %arg2: tensor>):
stablehlo.return %arg2 : tensor>
}) {enzymexla.symmetric_matrix = [#enzymexla]} : (tensor<12x12xcomplex>, tensor<36x2xi64>, tensor<36xcomplex>) -> tensor<12x12xcomplex>
%3 = stablehlo.transpose %2, dims = [1, 0] : (tensor<12x12xcomplex>) -> tensor<12x12xcomplex>
%4 = stablehlo.fft %3, type = FFT, length = [12, 12] : (tensor<12x12xcomplex>) -> tensor<12x12xcomplex>
%5 = stablehlo.reshape %4 : (tensor<12x12xcomplex>) -> tensor<144x1xcomplex>
%6 = stablehlo.dot_general %cst, %5, contracting_dims = [1] x [0], precision = [DEFAULT, DEFAULT] : (tensor<6x144xcomplex>, tensor<144x1xcomplex>) -> tensor<6x1xcomplex>
%7 = stablehlo.reshape %6 : (tensor<6x1xcomplex>) -> tensor<6xcomplex>
return %7 : tensor<6xcomplex>
}
}
```
I'll send the code soon