code: def conv3d_transpose(
      x: paddle.Tensor,
      filters: paddle.Tensor,
      strides: Union[int, Tuple[int, int, int]],
      padding: Union[str, Sequence[Tuple[int, int]]],
      /,
      *,
      output_shape: Optional[
          Union[ivy.NativeShape, Sequence[int]]
      ] = None,
      filter_format: str = "channel_last",
      data_format: Optional[str] = "NDHWC",
      dilations: Optional[Union[int, Tuple[int, 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 12 for calling a global function with example usage: conv3d_transpose() without return types