oneflow.nn.functional.dropout2d¶
-
oneflow.nn.functional.
dropout2d
()¶ dropout1d(x: Tensor, p: float = 0.5, training: bool = True) -> Tensor
The documentation is referenced from: https://pytorch.org/docs/1.10/generated/torch.nn.functional.dropout2d.html.
Randomly zero out entire channels (a channel is a 2D feature map, e.g., the \(j\)-th channel of the \(i\)-th sample in the batched input is a 2D tensor \(\text{input}[i, j]\)) of the input tensor). Each channel will be zeroed out independently on every forward call with probability
p
using samples from a Bernoulli distribution.See
Dropout2d
for details.- Parameters
p – probability of a channel to be zeroed. Default: 0.5
training – apply dropout if is
True
. Default:True