class_docstr: Creates a stochastic depth layer.
class_docstr_tok: ["Creates","a","stochastic","depth","layer","."]
docstr: Initializes a stochastic depth layer.
  
  Args:
    stochastic_depth_drop_rate: A `float` of drop rate.
  
  Returns:
    a tensor of the same shape as input.
docstr_tok: ["Initializes","a","stochastic","depth","layer",".","Args",":","stochastic_depth_drop_rate",":","A","`","float","`","of","drop","rate",".","Returns",":","a","tensor","of","the","same","shape","as","input","."]
code: def __init__(self, stochastic_depth_drop_rate: float) -> None:
      """Initializes a stochastic depth layer.
  
      Args:
        stochastic_depth_drop_rate: A `float` of drop rate.
  
      Returns:
        a tensor of the same shape as input.
      """
      super().__init__()
      self._drop_rate = stochastic_depth_drop_rate
  
imports: from typing import Optional, Tuple
  import torch
  import torch.nn
  from torch import Tensor
label_desc: Use image node_id 1 to create a new StochasticDepth object from inherited base classes: nn with example: obj = StochasticDepth(stochastic_depth_drop_rate)