class_docstr: 2D Convolutions like TensorFlow's 'SAME' mode, with the given input image size.
  The padding mudule is calculated in construction function, then used in forward.
class_docstr_tok: ["2D","Convolutions","like","TensorFlow","'s","'SAME","'","mode",",","with","the","given","input","image","size",".","The","padding","mudule","is","calculated","in","construction","function",",","then","used","in","forward","."]
code: def forward(self, x):
      x = self.static_padding(x)
      x = F.conv2d(
          x,
          self.weight,
          self.bias,
          self.stride,
          self.padding,
          self.dilation,
          self.groups,
      )
      return x
  
imports: import re
  import math
  import collections
  from functools import partial
  import torch
  from torch import nn
  from torch.nn import functional
  from torch.utils import model_zoo
label_desc: Use image node_id 2 for calling the Conv2dStaticSamePadding obj's underlying member method code with example usage: obj.forward(x) and returns: x