code: def get_sine_pos_embed(
      pos_tensor, num_pos_feats=128, temperature=10000, exchange_xy=True
  ):
      """generate sine position embedding from a position tensor
  
      Args:
          pos_tensor (Tensor): Shape as `(None, n)`.
          num_pos_feats (int): projected shape for each float in the tensor. Default: 128
          temperature (int): The temperature used for scaling
              the position embedding. Default: 10000.
          exchange_xy (bool, optional): exchange pos x and pos y. \
              For example, input tensor is `[x, y]`, the results will  # noqa
              be `[pos(y), pos(x)]`. Defaults: True.
  
      Returns:
          Tensor: Returned position embedding  # noqa
          with shape `(None, n * num_pos_feats)`.
      """
      scale = 2.0 * math.pi
      dim_t = 2.0 * paddle.floor_divide(
          paddle.arange(num_pos_feats), paddle.to_tensor(2)
      )
      dim_t = scale / temperature ** (dim_t / num_pos_feats)
  
      def sine_func(x):
          x *= dim_t
          return paddle.stack(
              (x[:, :, 0::2].sin(), x[:, :, 1::2].cos()), axis=3
          ).flatten(2)
  
      pos_res = [
          sine_func(x)
          for x in pos_tensor.split(pos_tensor.shape[-1], -1)
      ]
      if exchange_xy:
          pos_res[0], pos_res[1] = pos_res[1], pos_res[0]
      pos_res = paddle.concat(pos_res, axis=2)
      return pos_res
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import copy
  import math
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from ..bbox_utils import bbox_overlaps
label_desc: Use image node_id 10 for calling a global function with example usage: get_sine_pos_embed(pos_tensor, num_pos_feats, temperature, exchange_xy) and returns: pos_res, paddle