oneflow.nn.ConstantPad1d¶
-
class
oneflow.nn.
ConstantPad1d
(padding)¶ Pads the input tensor boundaries with a constant value.
The interface is consistent with PyTorch, and referenced from: https://pytorch.org/docs/1.10/generated/torch.nn.ConstantPad1d.html.
For N-dimensional padding, use
torch.nn.functional.pad()
.- Parameters
padding (int, list, tuple) – the size of the padding. If is int, uses the same padding in both boundaries. If a 2-tuple, uses (\(\text{padding_left}\), \(\text{padding_right}\))
value (int, float) – The constant value used for padding. Defaults to 0.
- Shape:
Input: \((N, C, W_{in})\)
Output: \((N, C, W_{out})\) where
\(W_{out} = W_{in} + \text{padding\_left} + \text{padding\_right}\)
For example:
>>> import oneflow as flow >>> import numpy as np >>> input = flow.tensor(np.arange(8).reshape(2,2,2).astype(np.float32)) >>> m = flow.nn.ConstantPad1d(padding=[1, 2], value=9.9999) >>> output = m(input) >>> output tensor([[[9.9999, 0.0000, 1.0000, 9.9999, 9.9999], [9.9999, 2.0000, 3.0000, 9.9999, 9.9999]], [[9.9999, 4.0000, 5.0000, 9.9999, 9.9999], [9.9999, 6.0000, 7.0000, 9.9999, 9.9999]]], dtype=oneflow.float32)