torch.nn.functional.dropout2d# torch.nn.functional.dropout2d(input, p=0.5, training=True, inplace=False)[source]# Randomly zero out entire channels (a channel is a 2D feature map). For example, the jjj-th channel of the iii-th sample in the batched input is a 2D tensor input[i,j]\text{input}[i, j]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 (float) – probability of a channel to be zeroed. Default: 0.5 training (bool) – apply dropout if is True. Default: True inplace (bool) – If set to True, will do this operation in-place. Default: False Return type Tensor
