anchor.diff:      member perf.matmul_TorchSharp() = 
           let n = perf.configure(Backend.Torch, 1) 
           for _ in 1 .. n do 
  -            res4 <- matrixTorchTensor.MatMul(matrixTorchTensor)
  +            res4 <- matrixTorchTensor.matmul(matrixTorchTensor)
   
       [<Benchmark; BenchmarkCategory("matmul")>]
       member perf.matmul_RawTensor_Torch() = 
  
positive.code:     member perf.addWithAlpha_TorchSharp() = 
          let n = perf.configure(Backend.Torch, 10) 
          for _ in 1 .. n do 
              res4 <- torchTensor.Add(torchTensor, alpha=torchScalar)
  
      [<Benchmark; BenchmarkCategory("addWithAlpha")>]
      member perf.addWithAlpha_RawTensor_Torch() = 
  
negative.code:         for _ in 1 .. n do 
              res4 <- 
                  match dtype with 
                  | Dtype.Int32 -> Int32Tensor.zeros([| int64 perf.tensorSize |] , enum (int Device.Default.DeviceType), Device.Default.DeviceIndex)
                  | Dtype.Int64 -> Int64Tensor.zeros([| int64 perf.tensorSize |] , enum (int Device.Default.DeviceType), Device.Default.DeviceIndex)
                  | Dtype.Float32 -> Float64Tensor.zeros([| int64 perf.tensorSize |] , enum (int Device.Default.DeviceType), Device.Default.DeviceIndex)
                  | Dtype.Float64 -> Float32Tensor.zeros([| int64 perf.tensorSize |] , enum (int Device.Default.DeviceType), Device.Default.DeviceIndex)
                  | _ -> failwith "unknown dtype in perf testing"
  
      [<Benchmark; BenchmarkCategory("zeros")>]
  