code: def conv2d_output_shape(
      h_w, kernel_size=1, stride=1, pad=0, dilation=1
  ):
      h_w, kernel_size, stride, pad, dilation = (
          num2tuple(h_w),
          num2tuple(kernel_size),
          num2tuple(stride),
          num2tuple(pad),
          num2tuple(dilation),
      )
      pad = num2tuple(pad[0]), num2tuple(pad[1])
  
      h = math.floor(
          (
              h_w[0]
              + sum(pad[0])
              - dilation[0] * (kernel_size[0] - 1)
              - 1
          )
          / stride[0]
          + 1
      )
      w = math.floor(
          (
              h_w[1]
              + sum(pad[1])
              - dilation[1] * (kernel_size[1] - 1)
              - 1
          )
          / stride[1]
          + 1
      )
  
      return h, w
  
label_desc: Use image node_id 2 for calling a global function with example usage: conv2d_output_shape(h_w, kernel_size, stride, pad, dilation) and returns: h,  w