ConstantPad2d¶
- class torch.nn.ConstantPad2d(padding, value)[source][source]¶
Pads the input tensor boundaries with a constant value.
For N-dimensional padding, use
torch.nn.functional.pad()
.- Parameters
padding (int, tuple) – the size of the padding. If is int, uses the same padding in all boundaries. If a 4-tuple, uses (, , , )
- Shape:
Input: or .
Output: or , where
Examples:
>>> m = nn.ConstantPad2d(2, 3.5) >>> input = torch.randn(1, 2, 2) >>> input tensor([[[ 1.6585, 0.4320], [-0.8701, -0.4649]]]) >>> m(input) tensor([[[ 3.5000, 3.5000, 3.5000, 3.5000, 3.5000, 3.5000], [ 3.5000, 3.5000, 3.5000, 3.5000, 3.5000, 3.5000], [ 3.5000, 3.5000, 1.6585, 0.4320, 3.5000, 3.5000], [ 3.5000, 3.5000, -0.8701, -0.4649, 3.5000, 3.5000], [ 3.5000, 3.5000, 3.5000, 3.5000, 3.5000, 3.5000], [ 3.5000, 3.5000, 3.5000, 3.5000, 3.5000, 3.5000]]]) >>> # using different paddings for different sides >>> m = nn.ConstantPad2d((3, 0, 2, 1), 3.5) >>> m(input) tensor([[[ 3.5000, 3.5000, 3.5000, 3.5000, 3.5000], [ 3.5000, 3.5000, 3.5000, 3.5000, 3.5000], [ 3.5000, 3.5000, 3.5000, 1.6585, 0.4320], [ 3.5000, 3.5000, 3.5000, -0.8701, -0.4649], [ 3.5000, 3.5000, 3.5000, 3.5000, 3.5000]]])