anchor.diff:      override t1.MaxPool3D(kernelSize, strides, paddings) = 
           let _batchSize, _channels, _inputDimensions, _kernelDimensions, _outputDimensions, outputShape =
               Shape.checkCanMaxpool3d dtype t1.Shape kernelSize strides paddings
  -        let struct (resultt, indicest) = tt.MaxPool3DWithIndices(int64s kernelSize, strides=int64s strides, padding=int64s paddings)
  +        let struct (resultt, indicest) = tt.max_pool3d_with_indices(int64s kernelSize, strides=int64s strides, padding=int64s paddings)
           
           // NOTE: DiffSharp currently expects indices as an Int32 tensor
           let indices = t1.MakeLike(indicest, shape=outputShape, dtype=Dtype.Int64).Cast(Dtype.Int32)
  
positive.code:         | Dtype.IntegralOrBool -> opNotSupported "PowT0T" dtype
          | _ -> 
          let t1 = t2.FullLike(Shape.scalar, t1)
          let result = t1.Expand(t2.Shape).TorchTensor.Pow(t2.TorchTensor)
          t2.MakeLike(result)
  
      override t1.PowTT0(t2:scalar) =
  
negative.code:         | Dtype.IntegralOrBool -> opNotSupported "PowTT0" dtype
          | _ -> 
          let t2v = toTorchScalar t2
          let result = tt.pow(t2v)
          t1.MakeLike(result)
  
      override t1.MatMulTT(t2) = 
  