code: def __init__(
      self,
      num_pos_feats=64,
      temperature=10000,
      normalize=False,
      scale=None,
  ):
      super().__init__()
      self.num_pos_feats = num_pos_feats
      self.temperature = temperature
      self.normalize = normalize
      if scale is not None and normalize is False:
          raise ValueError(
              "normalize should be true is scale is not None"
          )
      if scale is None:
          scale = 2 * math.pi
      self.scale = scale
  
imports: import math
  import copy
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddleseg.models import layers
  from paddleseg.cvlibs import manager, param_init
  from paddleseg.utils import utils
  from paddleseg.core.train import check_logits_losses
label_desc: Use image node_id 1 to create a new PositionEmbeddingSine object from inherited base classes: nn with example: obj = PositionEmbeddingSine(num_pos_feats, temperature, normalize, scale)