class_docstr: This class implements a variant of the inverted residual block with squeeze-excitation unit,
  as described in `MobileNetv3 <https://arxiv.org/abs/1905.02244>`_ paper. This variant
  includes stochastic depth, as used in `EfficientNet <https://arxiv.org/abs/1905.11946>`_ paper.
  
  Args:
      stochastic_depth_prob: float,
      For other arguments, refer to the parent class.
  
  Shape:
      - Input: :math:`(N, C_{in}, H_{in}, W_{in})`
      - Output: :math:`(N, C_{out}, H_{out}, W_{out})`
code: def __init__(
      self, stochastic_depth_prob: float, *args, **kwargs
  ) -> None:
      super().__init__(*args, **kwargs)
      self.stochastic_depth = StochasticDepth(
          p=stochastic_depth_prob, mode="row"
      )
  
imports: from torch import Tensor, nn
  from cvnets.layers import StochasticDepth
  from cvnets.modules import InvertedResidualSE
label_desc: Use image node_id 1 to create a new EfficientNetBlock object from inherited base classes: InvertedResidualSE with example: obj = EfficientNetBlock(stochastic_depth_prob)