class oneflow.nn.ConstantPad2d(padding: Union[int, tuple, list], value: Union[int, float] = 0)

This operator pads the input with constant value that user specifies. User can set the amount of padding by setting the parameter paddings.

The interface is consistent with PyTorch. The documentation is referenced from: https://pytorch.org/docs/1.10/generated/torch.nn.ConstantPad2d.html.

Parameters
• padding (int, tuple, list) – the size of the padding. If is int, uses the same padding in all boundaries. If a 4-tuple, uses ($$\mathrm{padding_{left}}$$, $$\mathrm{padding_{right}}$$, $$\mathrm{padding_{top}}$$, $$\mathrm{padding_{bottom}}$$)

• value (int, float) – The constant value used for padding. Defaults to 0.

Shape:
• Input: $$(N, C, H_{in}, W_{in})$$

• Output: $$(N, C, H_{out}, W_{out})$$ where

$$H_{out} = H_{in} + \mathrm{padding_{top}} + \mathrm{padding_{bottom}}$$ $$W_{out} = W_{in} + \mathrm{padding_{left}} + \mathrm{padding_{right}}$$

For example:

>>> import oneflow as flow
>>> import numpy as np

>>> m = flow.nn.ConstantPad2d((2, 2, 1, 1), 1)
>>> input = flow.tensor(np.arange(18).reshape((1, 2, 3, 3)).astype(np.float32))
>>> output = m(input)
>>> output.shape
oneflow.Size([1, 2, 5, 7])
>>> output
tensor([[[[ 1.,  1.,  1.,  1.,  1.,  1.,  1.],
[ 1.,  1.,  0.,  1.,  2.,  1.,  1.],
[ 1.,  1.,  3.,  4.,  5.,  1.,  1.],
[ 1.,  1.,  6.,  7.,  8.,  1.,  1.],
[ 1.,  1.,  1.,  1.,  1.,  1.,  1.]],

[[ 1.,  1.,  1.,  1.,  1.,  1.,  1.],
[ 1.,  1.,  9., 10., 11.,  1.,  1.],
[ 1.,  1., 12., 13., 14.,  1.,  1.],
[ 1.,  1., 15., 16., 17.,  1.,  1.],
[ 1.,  1.,  1.,  1.,  1.,  1.,  1.]]]], dtype=oneflow.float32)

__init__(padding: Union[int, tuple, list], value: Union[int, float] = 0)

Initialize self. See help(type(self)) for accurate signature.

Methods

 __call__(*args, **kwargs) Call self as a function. __delattr__(name, /) Implement delattr(self, name). __dir__() Default dir() implementation. __eq__(value, /) Return self==value. __format__(format_spec, /) Default object formatter. __ge__(value, /) Return self>=value. __getattr__(name) __getattribute__(name, /) Return getattr(self, name). __gt__(value, /) Return self>value. __hash__() Return hash(self). __init__(padding[, value]) Initialize self. __init_subclass__ This method is called when a class is subclassed. __le__(value, /) Return self<=value. __lt__(value, /) Return self