class_docstr: An attention layer that allows for downscaling the size of the embedding
  after projection to queries, keys, and values.
class_docstr_tok: ["An","attention","layer","that","allows","for","downscaling","the","size","of","the","embedding","after","projection","to","queries",",","keys",",","and","values","."]
code: def _separate_heads(self, x, num_heads: int):
      b, n, c = x.shape
      x = x.reshape([b, n, num_heads, c // num_heads])
      return x.transpose([0, 2, 1, 3])
  
file_path: PaddleSeg/contrib/SegmentAnything/segment_anything/modeling/transformer.py
imports: import paddle
  from paddle import Tensor, nn
  import paddle.nn.functional
  import math
  from typing import Tuple, Type
  from common import MLPBlock
label_desc: Use image node_id 2 for calling the Attention obj's underlying member method code with example usage: obj._separate_heads(x, num_heads) and returns: x