- torchvision.ops.drop_block2d(input: Tensor, p: float, block_size: int, inplace: bool = False, eps: float = 1e-06, training: bool = True) Tensor [source]¶
Implements DropBlock2d from “DropBlock: A regularization method for convolutional networks” <https://arxiv.org/abs/1810.12890>.
input (Tensor[N, C, H, W]) – The input tensor or 4-dimensions with the first one being its batch i.e. a batch with
p (float) – Probability of an element to be dropped.
block_size (int) – Size of the block to drop.
inplace (bool) – If set to
True, will do this operation in-place. Default:
eps (float) – A value added to the denominator for numerical stability. Default: 1e-6.
training (bool) – apply dropblock if is
The randomly zeroed tensor after dropblock.
- Return type:
Tensor[N, C, H, W]