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 __init__(
      self,
      in_channels,
      out_channels,
      kernel_size,
      stride=1,
      padding=0,
      dilation=1,
      groups=1,
      bias=True,
  ):
      super(Conv2dSameExport, self).__init__(
          in_channels,
          out_channels,
          kernel_size,
          stride,
          0,
          dilation,
          groups,
          bias,
      )
      self.pad = None
      self.pad_input_size = (0, 0)
  
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 1 to create a new Conv2dSameExport object from inherited base classes: nn with example: obj = Conv2dSameExport(in_channels, out_channels, kernel_size, stride, padding, dilation, groups, bias)