code: def conv2d(
      x: paddle.Tensor,
      filters: paddle.Tensor,
      strides: Union[int, Tuple[int, int]],
      padding: Union[str, int, Sequence[Tuple[int, int]]],
      /,
      *,
      data_format: str = "NHWC",
      filter_format: Optional[str] = "channel_last",
      x_dilations: Optional[Union[int, Tuple[int, int]]] = 1,
      dilations: Union[int, Tuple[int, int]] = 1,
      bias: Optional[paddle.Tensor] = None,
      out: Optional[paddle.Tensor] = None,
  ) -> paddle.Tensor:
      raise IvyNotImplementedException()
  
imports: from typing import Optional, Tuple, Union, Sequence
  import paddle
  import ivy
  from ivy.func_wrapper import with_unsupported_device_and_dtypes
  from ivy.utils.exceptions import IvyNotImplementedException
  from ivy.functional.ivy.layers import _handle_padding, _get_x_data_format, _deconv_length
  import ivy.functional.backends.paddle
  from .None import backend_version
label_desc: Use image node_id 8 for calling a global function with example usage: conv2d() without return types