class_docstr: Drop paths (Stochastic Depth) per sample.
docstr: Args:
      x (tensor): Input tensor.
docstr_tok: ["Args",":","x","(","tensor",")",":","Input","tensor","."]
code: def forward(self, x: torch.Tensor) -> torch.Tensor:
      """
      Args:
          x (tensor): Input tensor.
      """
      return drop_path(x, self.drop_prob, self.training)
  
imports: import torch
  import torch.nn
label_desc: Use image node_id 2 for calling the DropPath obj's underlying member method code with example usage: obj.forward(x) and returns: drop_path