code: def conv_args(
      kernel_size: int,
      nout: int,
      padding: Optional[
          Union[ConvPadding, str, ConvPaddingInt]
      ] = ConvPadding.VALID,
  ):
      """Returns list of arguments which are common to all convolutions.
  
      Args:
          kernel_size: size of convolution kernel (single number).
          nout: number of output filters.
  
      Returns:
          Dictionary with common convoltion arguments.
      """
      stddev = objax.functional.rsqrt(
          0.5 * kernel_size * kernel_size * nout
      )
      return dict(
          w_init=functools.partial(objax.random.normal, stddev=stddev),
          use_bias=False,
          padding=padding,
      )
  
imports: import functools
  from typing import Callable, Sequence, Union, Optional
  from jax import numpy
  import objax
  from objax.constants import ConvPadding
  from objax.nn import Conv2D
  from objax.typing import JaxArray, ConvPaddingInt
label_desc: Use image node_id 1 for calling a global function with example usage: conv_args(kernel_size, nout, padding) and returns: dict