anchor.diff:          for _ in 1 .. n do 
               res4 <- 
                   match dtype with 
  -                | Dtype.Int32 -> Int32Tensor.From(rawData :?> int32[])
  -                | Dtype.Int64 -> Int64Tensor.From(rawData :?> int64[])
  -                | Dtype.Float32 -> Float32Tensor.From(rawData :?> single[])
  -                | Dtype.Float64 -> Float64Tensor.From(rawData :?> double[])
  +                | Dtype.Int32 -> Int32Tensor.from(rawData :?> int32[])
  +                | Dtype.Int64 -> Int64Tensor.from(rawData :?> int64[])
  +                | Dtype.Float32 -> Float32Tensor.from(rawData :?> single[])
  +                | Dtype.Float64 -> Float64Tensor.from(rawData :?> double[])
                   | _ -> failwith "unknown dtype in perf testing"
   
       [<Benchmark; BenchmarkCategory("fromCpuData")>]
  
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:     member perf.matmul_TorchSharp() = 
          let n = perf.configure(Backend.Torch, 1) 
          for _ in 1 .. n do 
              res4 <- matrixTorchTensor.matmul(matrixTorchTensor)
  
      [<Benchmark; BenchmarkCategory("matmul")>]
      member perf.matmul_RawTensor_Torch() = 
  