code: def segment_padding(data, segment_ids):
      """
      Segment padding operator.
  
      This operator padding the input elements which with the same index in 'segment_ids' to a common length ,
      and reshape its into [uniq_segment_id, max_padding, dim].
      Args:
          data (tensor): a tensor, available data type float32, float64.
          segment_ids (tensor): a 1-d tensor, which have the same size
                              with the first dimension of input data.
                              available data type is int32, int64.
  
      Returns:
          output (Tensor): the padding result with shape [uniq_segment_id, max_padding, dim].
          seq_len (Tensor): the numbers of elements grouped same segment_ids
          index: The index of elements for gather_nd or scatter_nd operation
  
      Examples:
  
          .. code-block:: python
  
              import paddle
              import pgl
              data = paddle.to_tensor([[1, 2, 3], [3, 2, 1], [4, 5, 6]], dtype='float32')
              segment_ids = paddle.to_tensor([0, 0, 1], dtype='int64')
              output, seq_len, index = pgl.math.segment_padding(data, segment_ids)
      """
      idx_a = segment_ids
      idx_b = paddle.arange(paddle.shape(segment_ids)[0])
  
      temp_idx = paddle.ones_like(segment_ids, dtype="float32")
      segment_len = segment_sum(temp_idx, segment_ids).astype("int32")
  
      max_padding = paddle.max(segment_len)
  
      segment_shift = get_index_from_counts(segment_len)[:-1]
      segment_shift = paddle.gather(segment_shift, segment_ids)
  
      idx_b = idx_b - segment_shift
  
      index = paddle.stack([idx_a, idx_b], axis=1)
  
      shape = [
          paddle.shape(segment_len)[0],
          max_padding,
          data.shape[-1],
      ]
      output = paddle.scatter_nd(index, data, shape)
  
      return output, segment_len, index
  
file_path: PGL/pgl/math.py
imports: import paddle
  from pgl.utils.op import get_index_from_counts
label_desc: Use image node_id 7 for calling a global function with example usage: segment_padding(data, segment_ids) and returns: output,  segment_len,  index