anchor.diff:      member perf.addition_TorchSharp() = 
           let n = perf.configure(Backend.Torch, 10)
           for _ in 1 .. n do 
  -            res4 <- torchTensor.Add(torchTensor)
  +            res4 <- torchTensor.add(torchTensor)
   
       [<Benchmark; BenchmarkCategory("addition")>]
       member perf.addition_RawTensor_Torch() = 
  
positive.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")>]
  
negative.code:         for _ in 1 .. n do 
              res4 <- 
                  match dtype with 
                  | Dtype.Int32 -> Int32Tensor.randint(10L, [| int64 perf.tensorSize |] , enum (int Device.Default.DeviceType), Device.Default.DeviceIndex)
                  | Dtype.Int64 -> Int64Tensor.randint(10L, [| int64 perf.tensorSize |] , enum (int Device.Default.DeviceType), Device.Default.DeviceIndex)
                  | Dtype.Float32 -> Float64Tensor.rand([| int64 perf.tensorSize |] , enum (int Device.Default.DeviceType), Device.Default.DeviceIndex)
                  | Dtype.Float64 -> Float32Tensor.rand([| int64 perf.tensorSize |] , enum (int Device.Default.DeviceType), Device.Default.DeviceIndex)
                  | _ -> failwith "unknown dtype in perf testing"
  
      [<Benchmark; BenchmarkCategory("rand")>]
  