drop_path¶
dragon.vm.torch.nn.functional.drop_path(
input,
p=0.2,
increment=0.0,
training=True,
inplace=False,
slot=None
)[source]¶Set the examples over input to zero randomly. [Larsson et.al, 2016].
The DropPath function is defined as:
\[\text{DropPath}(x) = x * \text{Bernoulli}(p=1 - prob) \]- Parameters:
- input (dragon.vm.torch.Tensor) – The input tensor.
- p (float, optional, default=0.2) – The dropping prob.
- increment (float, optional, default=0.) – The increment value to
p. - training (bool, optional, default=True) – The training flag.
- inplace (bool, optional, default=False) – Whether to do the operation in-place.
- slot (int, optional) – The optional slot index.
- Returns:
dragon.vm.torch.Tensor – The output tensor.
See also