code: def _pad_to_factor(self, x: Tensor, factor: int) -> Tensor:
      assert (
          x.dim() == 4
      ), f"expected x to be of dim [B, C, H, W], got {x.shape}"
      H, W = x.shape[-2:]
      H_padded = math.ceil(H / factor) * factor
      W_padded = math.ceil(W / factor) * factor
      pad_sizes = (
          0,
          W_padded - W,
          0,
          H_padded - H,
      )  # W then H! (pad is reverse)
      return F.pad(x, pad_sizes, mode=self.pad_mode)
  
file_path: NeuralCompression/projects/torch_vct/neural/patcher.py
imports: import math
  from typing import NamedTuple, Optional, Tuple, Union
  import torch
  import torch.nn
  import torch.nn.functional
  from torch import Tensor
label_desc: Use image node_id 3 for calling the Patcher obj's underlying member method code with example usage: obj._pad_to_factor(x, factor) and returns: F