class_docstr: Tensorflow like 'SAME' wrapper for 2D max pooling
      
class_docstr_tok: ["Tensorflow","like","'SAME","'","wrapper","for","2D","max","pooling"]
code: def __init__(
      self,
      kernel_size: int,
      stride=None,
      padding=0,
      dilation=1,
      ceil_mode=False,
  ):
      kernel_size = to_2tuple(kernel_size)
      stride = to_2tuple(stride)
      dilation = to_2tuple(dilation)
      super(MaxPool2dSame, self).__init__(
          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 1 to create a new MaxPool2dSame object from inherited base classes: nn with example: obj = MaxPool2dSame(kernel_size, stride, padding, dilation, ceil_mode)