code: def full(
      shape: Union[ivy.NativeShape, Sequence[int]],
      fill_value: Union[int, float, bool],
      *,
      dtype: Optional[Union[ivy.Dtype, paddle.dtype]] = None,
      device: core.Place = None,
      out: Optional[paddle.Tensor] = None,
  ) -> paddle.Tensor:
      if dtype is None:
          dtype = ivy.default_dtype(item=fill_value)
      if not isinstance(shape, Sequence):
          shape = [shape]
      if isinstance(fill_value, complex):
          fill_value = paddle.to_tensor(fill_value)
          ret_real = paddle.full(
              shape=shape, fill_value=fill_value.real()
          )
          ret_imag = paddle.full(
              shape=shape, fill_value=fill_value.imag()
          )
          ret = paddle.complex(ret_real, ret_imag)
      else:
          dtype_ = (
              None
              if ivy.as_native_dtype(dtype) == paddle.int8
              else dtype
          )
          ret = paddle.full(
              shape=shape, fill_value=fill_value, dtype=dtype_
          )
      if ret.dtype != ivy.as_native_dtype(dtype):
          return ret.cast(dtype)
      return ret
  
imports: import struct
  from numbers import Number
  from typing import Union, List, Optional, Sequence, Tuple
  import numpy
  import paddle
  import ivy.functional.backends.paddle
  import ivy
  from ivy.func_wrapper import with_unsupported_device_and_dtypes
  from ivy.functional.ivy.creation import _asarray_to_native_arrays_and_back, _asarray_infer_device, _asarray_handle_nestable, _asarray_infer_dtype, NestedSequence, SupportsBufferProtocol, _asarray_inputs_to_native_shapes, _remove_np_bfloat16
  from .None import backend_version
  from paddle.device import core
label_desc: Use image node_id 8 for calling a global function with example usage: full(shape, fill_value) and returns: ret, ret