oneflow.nn.ConstantPad3d¶
-
class
oneflow.nn.
ConstantPad3d
(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.ConstantPad3d.html.
For N-dimensional padding, use
flow.nn.functional.pad()
.- Parameters
padding (int, list, tuple) – the size of the padding. If is int, uses the same padding in all boundaries. If a 6-tuple, uses (\(\text{padding_left}\), \(\text{padding_right}\), \(\text{padding_top}\), \(\text{padding_bottom}\), \(\text{padding_front}\), \(\text{padding_back}\))
value (int, float) – The constant value used for padding. Defaults to 0.
- Shape:
Input: \((N, C, D_{in}, H_{in}, W_{in})\)
Output: \((N, C, D_{out}, H_{out}, W_{out})\) where
\(D_{out} = D_{in} + \text{padding_front} + \text{padding_back}\)
\(H_{out} = H_{in} + \text{padding_top} + \text{padding_bottom}\)
\(W_{out} = W_{in} + \text{padding_left} + \text{padding_right}\)
Examples:
>>> import oneflow as flow >>> import numpy as np >>> input = flow.tensor(np.arange(8).reshape(1,1,2,2,2).astype(np.int32)) >>> m = flow.nn.ConstantPad3d(padding=1, value=9) >>> output = m(input) >>> output tensor([[[[[9, 9, 9, 9], [9, 9, 9, 9], [9, 9, 9, 9], [9, 9, 9, 9]], [[9, 9, 9, 9], [9, 0, 1, 9], [9, 2, 3, 9], [9, 9, 9, 9]], [[9, 9, 9, 9], [9, 4, 5, 9], [9, 6, 7, 9], [9, 9, 9, 9]], [[9, 9, 9, 9], [9, 9, 9, 9], [9, 9, 9, 9], [9, 9, 9, 9]]]]], dtype=oneflow.int32)