class_docstr: ONNX export friendly Tensorflow like 'SAME' convolution wrapper for 2D convolutions
  
  NOTE: This does not currently work with torch.jit.script
code: def forward(self, x):
      input_size = x.size()[-2:]
      if self.pad is None:
          pad_arg = _same_pad_arg(
              input_size,
              self.weight.size()[-2:],
              self.stride,
              self.dilation,
          )
          self.pad = nn.ZeroPad2d(pad_arg)
          self.pad_input_size = input_size
  
      if self.pad is not None:
          x = self.pad(x)
      return F.conv2d(
          x,
          self.weight,
          self.bias,
          self.stride,
          self.padding,
          self.dilation,
          self.groups,
      )
  
imports: import collections.abc
  import math
  from functools import partial
  from itertools import repeat
  from typing import Tuple, Optional
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from .config import *
label_desc: Use image node_id 2 for calling the Conv2dSameExport obj's underlying member method code with example usage: obj.forward(x) and returns: F