code: def conv_general_dilated(
      lhs,
      rhs,
      window_strides,
      padding,
      lhs_dilation,
      rhs_dilation,
      dimension_numbers,
  ):
      lhs_perm, rhs_perm, out_perm = _conv_general_permutations(
          dimension_numbers
      )
      if isinstance(padding, str):
          padding = padtype_to_pads(
              np.take(lhs.shape, lhs_perm)[2:],
              np.take(rhs.shape, rhs_perm)[2:],
              window_strides,
              padding,
          )
      trans_lhs = transpose(lhs, lhs_perm)
      trans_rhs = transpose(rhs, rhs_perm)
      out = conv_with_general_padding(
          trans_lhs,
          trans_rhs,
          window_strides,
          padding,
          lhs_dilation,
          rhs_dilation,
      )
      return transpose(out, np.argsort(out_perm))
  
imports: import builtins
  import collections
  import itertools
  import numpy
  import opt_einsum
  import scipy.special
  from jax._src import dtypes
  from jax._src import util
label_desc: Use image node_id 23 for calling a global function with example usage: conv_general_dilated(lhs, rhs, window_strides, padding, lhs_dilation, rhs_dilation, dimension_numbers) and returns: transpose