code: def _normalize_batch(b:Tuple[Tensor,Tensor], mean:FloatTensor, std:FloatTensor, do_x:bool=True, do_y:bool=False)->Tuple[Tensor,Tensor]:
      "`b` = `x`,`y` - normalize `x` array of imgs and `do_y` optionally `y`."
      x,y = b
      mean,std = mean.to(x.device),std.to(x.device)
      if do_x: x = normalize(x,mean,std)
      if do_y and len(y.shape) == 4: y = normalize(y,mean,std)
      return x,f _normalize_batch(b:Tuple[Tensor,Tensor], mean:FloatTensor, std:FloatTensor, do_x:bool=True, do_y:bool=False)->Tuple[Tensor,Tensor]:
      "`b` = `x`,`y` - normalize `x` array of imgs and `do_y` optionally `y`."
      x,y = b
      mean,std = mean.to(x.device),std.to(x.device)
      if do_x: x = normalize(x,mean,std)
      if do_y and len(y.shape) == 4: y = normalize(y,mean,std)
      return x,y
docs: `b` = `x`,`y` - normalize `x` array of imgs and `do_y` optionally `y`.