nn.functional.dropout1d¶
The dropout1d function randomly zeroes entire channels of the input tensor with a probability p during training.
Function Signature¶
def dropout1d(input_: Tensor, p: float = 0.5, training: bool = True) -> Tensor
Parameters¶
- input_ (Tensor):
The input tensor of shape (N, C, L), where N is the batch size, C is the number of channels, and L is the length.
- p (float, optional):
Probability of an element to be zeroed. Default: 0.5.
- training (bool, optional):
Apply dropout if True; do nothing if False. Default: True.
Returns¶
- Tensor:
A tensor of the same shape as the input, with entire channels randomly zeroed with probability p if training is True.
Examples¶
Applying dropout1d during training:
>>> input_ = Tensor([[[1.0, 2.0], [3.0, 4.0]]]) # Shape: (1, 2, 2)
>>> out = F.dropout1d(input_, p=0.5, training=True)
>>> print(out)
# Example output: Tensor([[[0.0, 0.0], [3.0, 4.0]]])