class_docstr: Implement the PE function.
code: def __init__(self, dropout, dim, max_len=5000):
      super(PositionalEncoding, self).__init__()
      self.dropout = nn.Dropout(p=dropout, mode="downscale_in_infer")
  
      pe = paddle.zeros([max_len, dim])
      position = paddle.arange(
          0, max_len, dtype=paddle.float32
      ).unsqueeze(1)
      div_term = paddle.exp(
          paddle.arange(0, dim, 2).astype("float32")
          * (-math.log(10000.0) / dim)
      )
      pe[:, 0::2] = paddle.sin(position * div_term)
      pe[:, 1::2] = paddle.cos(position * div_term)
      pe = paddle.unsqueeze(pe, 0)
      self.register_buffer("pe", pe)
  
imports: import copy
  import math
  import paddle
  import paddle.nn
  import paddle.nn.functional
label_desc: Use image node_id 1 to create a new PositionalEncoding object from inherited base classes: nn with example: obj = PositionalEncoding(dropout, dim, max_len)