class_docstr: Median pool (usable as median filter when stride=1) module.
  
  Args:
       kernel_size: size of pooling kernel, int or 2-tuple
       stride: pool stride, int or 2-tuple
       padding: pool padding, int or 4-tuple (l, r, t, b) as in pytorch F.pad
       same: override padding and enforce same padding, boolean
code: def __init__(self, kernel_size=3, stride=1, padding=0, same=False):
      super(MedianPool2d, self).__init__()
      self.k = to_2tuple(kernel_size)
      self.stride = to_2tuple(stride)
      self.padding = to_4tuple(padding)  # convert to l, r, t, b
      self.same = same
  
file_path: pytorch-image-models/timm/layers/median_pool.py
imports: import torch.nn
  import torch.nn.functional
  from .helpers import to_2tuple, to_4tuple
label_desc: Use image node_id 1 to create a new MedianPool2d object from inherited base classes: nn with example: obj = MedianPool2d(kernel_size, stride, padding, same)