code: def forward(self, x, mask):
      y_embed = paddle.cumsum(mask, 1, dtype="float32")
      x_embed = paddle.cumsum(mask, 2, dtype="float32")
  
      if self.normalize:
          eps = 1e-6
          y_embed = y_embed / (y_embed[:, -1:, :] + eps) * self.scale
          x_embed = x_embed / (x_embed[:, :, -1:] + eps) * self.scale
      dim_t = paddle.arange(self.num_pos_feats, dtype="float32")
      dim_d = paddle.expand(paddle.to_tensor(2), dim_t.shape)
      dim_t = self.temperature ** (
          2 * (dim_t / dim_d).astype("int64") / self.num_pos_feats
      )
  
      pos_x = paddle.unsqueeze(x_embed, [3]) / dim_t
      pos_y = paddle.unsqueeze(y_embed, [3]) / dim_t
  
      pos_x = paddle.flatten(
          paddle.stack(
              [
                  paddle.sin(pos_x[:, :, :, 0::2]),
                  paddle.cos(pos_x[:, :, :, 1::2]),
              ],
              axis=4,
          ),
          3,
      )
      pos_y = paddle.flatten(
          paddle.stack(
              [
                  paddle.sin(pos_y[:, :, :, 0::2]),
                  paddle.cos(pos_y[:, :, :, 1::2]),
              ],
              axis=4,
          ),
          3,
      )
  
      pos = paddle.transpose(
          paddle.concat([pos_y, pos_x], axis=3), [0, 3, 1, 2]
      )
  
      return pos
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import paddle.nn
  import paddle
  import math
label_desc: Use image node_id 2 for calling the PositionEmbeddingSine obj's underlying member method code with example usage: obj.forward(x, mask) and returns: pos