code: def take_along_axis(
      arr: paddle.Tensor,
      indices: paddle.Tensor,
      axis: int,
      /,
      *,
      mode: str = "fill",
      out: Optional[paddle.Tensor] = None,
  ) -> paddle.Tensor:
      if arr.ndim != indices.ndim:
          raise ivy.utils.exceptions.IvyException(
              "arr and indices must have the same number of dimensions;"
              + f" got {arr.ndim} vs {indices.ndim}"
          )
      indices = indices.cast("int64")
      if mode not in ["clip", "fill", "drop"]:
          raise ValueError(
              f"Invalid mode '{mode}'. Valid modes are 'clip', 'fill', 'drop'."
          )
      arr_shape = arr.shape
      if axis < 0:
          axis += arr.ndim
      if mode == "clip":
          max_index = arr.shape[axis] - 1
          with ivy.ArrayMode(False):
              indices = ivy.clip(indices, 0, max_index)
      elif mode in ("fill", "drop"):
          if "float" in str(arr.dtype) or "complex" in str(arr.dtype):
              fill_value = float("nan")
          elif "uint" in str(arr.dtype):
              fill_value = paddle.iinfo(arr.dtype).max
          elif "int" in str(arr.dtype):
              fill_value = -paddle.iinfo(arr.dtype).max - 1
          else:
              raise TypeError(
                  f"Invalid dtype '{arr.dtype}'. Valid dtypes are 'float', 'complex',"
                  " 'uint', 'int'."
              )
  
          with ivy.ArrayMode(False):
              indices = ivy.where(
                  (indices < 0) | (indices >= arr.shape[axis]),
                  -1,
                  indices,
              )
              arr_shape = list(arr_shape)
              arr_shape[axis] = 1
              fill_arr = ivy.full(
                  arr_shape, fill_value, dtype=arr.dtype
              )
              arr = ivy.concat([arr, fill_arr], axis=axis)
              indices = ivy.where(
                  indices < 0, arr.shape[axis] + indices, indices
              )
  
      if paddle.is_complex(arr):
          return paddle.complex(
              paddle.take_along_axis(arr.real(), indices, axis),
              paddle.take_along_axis(arr.imag(), indices, axis),
          )
      return paddle.take_along_axis(arr, indices, axis)
  
imports: from collections import namedtuple
  from typing import Iterable, Optional, Union, Sequence, Tuple, NamedTuple, List, Any, Literal, Callable
  from numbers import Number
  from ..None import backend_version
  from ivy.func_wrapper import with_supported_device_and_dtypes, with_unsupported_device_and_dtypes, with_supported_dtypes, with_unsupported_dtypes
  import paddle
  import ivy
  import ivy.functional.backends.paddle
  from ivy.functional.ivy.experimental.manipulation import _check_paddle_pad, _to_paddle_padding
label_desc: Use image node_id 18 for calling a global function with example usage: take_along_axis() and returns: paddle, paddle