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Add conj with cost_and_gradient #99

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Add conj with cost_and_gradient #99

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fliingelephant
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Try fixing #98

  • Still FAIL to pass the "belief propagation on circle" test (ComplexF64 version), where BP fails to converge.
  • There are four parts involving cost_and_gradient and I only edited belief.jl, mar.jl and leave those in map.jl and mmap.jl remained the same.
  • I am not sure if it is correct to conjugate tensors when the datatype is neither Real nor Complex.

@fliingelephant fliingelephant marked this pull request as draft July 2, 2025 02:31
GiggleLiu
GiggleLiu reviewed Jul 2, 2025
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There is an extra gauge degree of freedom for complex numbers, so the message can be different by a phase.

test/belief.jl
@@ -46,7 +46,7 @@ end
@testset "belief propagation" begin
n = 5
chi = 3
mps_uai = TensorInference.random_tensor_train_uai(Float64, n, chi)
mps_uai = TensorInference.random_tensor_train_uai(ComplexF64, n, chi)
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Please test both Float64 and ComplexF64.

@GiggleLiu GiggleLiu mentioned this pull request Jul 2, 2025
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@fliingelephant
Fix test
04b7215 
Signed-off-by: 周唤海 <[email protected]>
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GiggleLiu commented Jul 2, 2025 •
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close in favor of #100

@GiggleLiu GiggleLiu closed this Jul 2, 2025
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@fliingelephant @GiggleLiu