old_contents: # stdlib
  from uuid import UUID
  
  # third party
  from numpy import ndarray
  
  # syft absolute
  from syft.lib.python import Tuple
  
  # relative
  from ..tensor import AutogradTensor
  from .op import Op
  
  
  class TransposeOp(Op):
      """Repeat operation across a dimension"""
  
      def forward(self, x: AutogradTensor, *dims: Tuple[int]) -> AutogradTensor:  # type: ignore
          self.x = x
          self.dims = dims
  
          reverse_t_dims = {}
          for i, d in enumerate(self.dims):
              reverse_t_dims[d] = i
  
          l_dims = sorted(
              [(x[0], x[1]) for x in reverse_t_dims.items()], key=lambda x: x[0]
          )
          self.reverse_dims = [x[1] for x in l_dims]
  
          return AutogradTensor(x.child.transpose(*dims), requires_grad=x.requires_grad)
  
      def _backward(self, grad: ndarray, backprop_id: UUID) -> None:
  
          if self.x.requires_grad:
  
              grad = grad.transpose(*self.reverse_dims)
  
              self.x.add_grad(grad)
  
              if self.x.grad_fn:
                  self.x.backward(backprop_id=backprop_id)
  
new_contents: # stdlib
  from typing import Tuple
  from uuid import UUID
  
  # third party
  from numpy import ndarray
  
  # relative
  from ..tensor import AutogradTensor
  from .op import Op
  
  
  class TransposeOp(Op):
      """Repeat operation across a dimension"""
  
      def forward(self, x: AutogradTensor, *dims: Tuple[int]) -> AutogradTensor:  # type: ignore
          self.x = x
          self.dims = dims
  
          reverse_t_dims = {}
          for i, d in enumerate(self.dims):
              reverse_t_dims[d] = i
  
          l_dims = sorted(
              [(x[0], x[1]) for x in reverse_t_dims.items()], key=lambda x: x[0]
          )
          self.reverse_dims = [x[1] for x in l_dims]
  
          return AutogradTensor(x.child.transpose(*dims), requires_grad=x.requires_grad)
  
      def _backward(self, grad: ndarray, backprop_id: UUID) -> None:
  
          if self.x.requires_grad:
  
              grad = grad.transpose(*self.reverse_dims)
  
              self.x.add_grad(grad)
  
              if self.x.grad_fn:
                  self.x.backward(backprop_id=backprop_id)
  
subject: Fix bad import