DropBlock2d¶
- class dragon.vm.torch.nn.DropBlock2d(
 p=0.1,
 block_size=7,
 inplace=False
 )[source]¶
- Set the blocks to zero randomly. [Ghiasi et.al, 2018]. - The DropBlock function is defined as: \[\text{DropBlock}(x_{ijk}) = x_{ijk} * (r_{ik} \sim \mathcal{B}(1, 1 - \gamma)) \\ \quad \\ \text{where}\quad \gamma = \frac{p}{\text{block\_size}^{n}} \frac{\text{feat\_size}^{n}}{(\text{feat\_size} - \text{block\_size} + 1)^n} \]- Examples: - x = torch.ones(1, 3, 4, 4) m = torch.nn.DropBlock2d(block_size=3) y = m(x) - See also 
__init__¶
- DropBlock2d.- __init__(
 p=0.1,
 block_size=7,
 inplace=False
 )[source]¶
- Create a - DropBlock2dmodule.- Parameters:
- p (float, optional, default=0.1) – The dropping ratio.
- block_size (int, optional, default=7) – The size of a spatial block.
- inplace (bool, optional, default=False) – Whether to do the operation in-place.
 
 
