class_docstr: This function implements dropout 2d. It randomly put zeros on
  entire channels.
  
  
  Arguments
  ---------
  dropout_rate : float
      It is the dropout factor (between 0 and 1).
  inplace : bool
      If True, it uses inplace operations.
  
  Example
  -------
  >>> drop = Dropout2d(drop_rate=0.5)
  >>> inputs = torch.rand(10, 50, 40)
  >>> output=drop(inputs)
  >>> output.shape
  torch.Size([10, 50, 40])
code: def __init__(
      self,
      drop_rate,
      inplace=False,
  ):
      super().__init__()
      self.drop_rate = drop_rate
      self.inplace = inplace
      self.drop = nn.Dropout2d(p=self.drop_rate, inplace=self.inplace)
  
imports: import torch
  import logging
  import torch.nn
label_desc: Use image node_id 1 to create a new Dropout2d object from inherited base classes: nn with example: obj = Dropout2d(drop_rate, inplace)