code: def scaled_l2(self, x, codewords, scale):
      num_codes, channels = paddle.shape(codewords)
      reshaped_scale = scale.reshape([1, 1, num_codes])
      expanded_x = paddle.tile(x.unsqueeze(2), [1, 1, num_codes, 1])
      reshaped_codewords = codewords.reshape(
          [1, 1, num_codes, channels]
      )
  
      scaled_l2_norm = paddle.multiply(
          reshaped_scale,
          (expanded_x - reshaped_codewords).pow(2).sum(axis=3),
      )
      return scaled_l2_norm
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddleseg.cvlibs import manager
  from paddleseg.models import layers
  from paddleseg.utils import utils
label_desc: Use image node_id 2 for calling the Encoding obj's underlying member method code with example usage: obj.scaled_l2(x, codewords, scale) and returns: scaled_l2_norm