stochastic_depth

torchvision.ops.stochastic_depth(input: torch.Tensor, p: float, mode: str, training: bool = True) → torch.Tensor

Implements the Stochastic Depth from “Deep Networks with Stochastic Depth” used for randomly dropping residual branches of residual architectures.

Parameters

• input (Tensor[N, ..]) – The input tensor or arbitrary dimensions with the first one being its batch i.e. a batch with N rows.

• p (float) – probability of the input to be zeroed.

• mode (str) – "batch" or "row". "batch" randomly zeroes the entire input, "row" zeroes randomly selected rows from the batch.

• training – apply stochastic depth if is True. Default: True

Returns

The randomly zeroed tensor.

Return type

Tensor[N, ..]