class_docstr: Tensorflow like 'SAME' convolution wrapper for 2D convolutions
      
code: def __init__(
      self,
      in_channels,
      out_channels,
      kernel_size,
      stride=1,
      padding=0,
      dilation=1,
      groups=1,
      bias=True,
  ):
      super(Conv2dSame, self).__init__(
          in_channels,
          out_channels,
          kernel_size,
          stride,
          0,
          dilation,
          groups,
          bias,
      )
  
file_path: pytorch-image-models/timm/layers/conv2d_same.py
imports: import torch
  import torch.nn
  import torch.nn.functional
  from typing import Tuple, Optional
  from .config import is_exportable, is_scriptable
  from .padding import pad_same, pad_same_arg, get_padding_value
label_desc: Use image node_id 1 to create a new Conv2dSame object from inherited base classes: nn with example: obj = Conv2dSame(in_channels, out_channels, kernel_size, stride, padding, dilation, groups, bias)