class_docstr: Drop paths (Stochastic Depth) per sample  (when applied in main path of residual blocks).
      
class_docstr_tok: ["Drop","paths","(","Stochastic","Depth",")","per","sample","(","when","applied","in","main","path","of","residual","blocks",")","."]
code: def __init__(self, drop_prob=None):
      super(DropPath, self).__init__()
      self.drop_prob = drop_prob
  
imports: import numpy
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddle.nn import Layer
  from paddle.nn import Linear
  from paddle.nn.initializer import Constant
  from paddle.nn.initializer import Normal
  from paddle.nn.initializer import TruncatedNormal
label_desc: Use image node_id 1 to create a new DropPath object from inherited base classes: nn with example: obj = DropPath(drop_prob)