code: def max_pool2d_same(
      x,
      kernel_size: List[int],
      stride: List[int],
      padding: List[int] = (0, 0),
      dilation: List[int] = (1, 1),
      ceil_mode: bool = False,
  ):
      x = pad_same(x, kernel_size, stride, value=-float("inf"))
      return F.max_pool2d(
          x, kernel_size, stride, (0, 0), dilation, ceil_mode
      )
  
file_path: pytorch-image-models/timm/layers/pool2d_same.py
imports: import torch
  import torch.nn
  import torch.nn.functional
  from typing import List, Tuple, Optional
  from .helpers import to_2tuple
  from .padding import pad_same, get_padding_value
label_desc: Use image node_id 2 for calling a global function with example usage: max_pool2d_same(x, kernel_size, stride, padding, dilation, ceil_mode) and returns: F