code: def forward(self, x):
      if self.training and self.drop > 0:
          y = (
              paddle.rand(shape=[x.shape[0], 1, 1])
              .__ge__(self.drop)
              .astype("float32")
          )
          y = y.divide(paddle.full_like(y, 1 - self.drop))
          return paddle.add(x, y)
      else:
          return paddle.add(x, self.m(x))
  
imports: import itertools
  import math
  import warnings
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddle.nn.initializer import Constant
  from paddle.nn.initializer import TruncatedNormal
  from paddle.regularizer import L2Decay
  from .vision_transformer import Identity
  from .vision_transformer import ones_
  from .vision_transformer import trunc_normal_
  from .vision_transformer import zeros_
label_desc: Use image node_id 2 for calling the Residual obj's underlying member method code with example usage: obj.forward(x) and returns: paddle, paddle