code: def conv_general_dilated(
      x: Union[(None, mx.ndarray.NDArray)],
      filters: Union[(None, mx.ndarray.NDArray)],
      strides: Union[
          (int, Tuple[int], Tuple[(int, int)], Tuple[(int, int, int)])
      ],
      padding: Union[(str, int, Sequence[Tuple[(int, int)]])],
      /,
      *,
      dims: int = 2,
      data_format: str = "channel_last",
      feature_group_count: int = 1,
      x_dilations: Union[
          (int, Tuple[int], Tuple[(int, int)], Tuple[(int, int, int)])
      ] = 1,
      dilations: Union[
          (int, Tuple[int], Tuple[(int, int)], Tuple[(int, int, int)])
      ] = 1,
      bias: Optional[Union[(None, mx.ndarray.NDArray)]] = None,
      out: Optional[Union[(None, mx.ndarray.NDArray)]] = None,
  ) -> Union[(None, mx.ndarray.NDArray)]:
      raise IvyNotImplementedException()
  
file_path: ivy/ivy/functional/backends/mxnet/layers.py
imports: import mxnet
  from typing import Optional, Tuple, Union, Sequence
  import ivy
  from ivy.utils.exceptions import IvyNotImplementedException
label_desc: Use image node_id 8 for calling a global function with example usage: conv_general_dilated() without return types