pad¶

dragon.vm.torch.nn.functional.pad(
  input,
  pad,
  mode='constant',
  value=0
)[source]¶

Pad the input according to the given sizes.

The padded dimension is computed as:

$$\text{Dim}_{out} = \text{Dim}_{in} + pad_l + pad_r$$

The pad should be a sequence of $(N, 2)$ values, where $N$ is the last n-dimensions to pad.

Parameters:

• input (dragon.vm.torch.Tensor) – The input tensor.
• pad (Sequence[int]) – The n-d padding sizes.
• mode ({'constant', 'reflect', 'replicate', 'circular'}, optional) – The padding mode.
• value (number, optional, default=0) – The value used in constant mode.

Returns:

dragon.vm.torch.Tensor – The output tensor.

See also

torch.nn.ConstantPad2d(…), torch.nn.ReflectionPad2d(…), torch.nn.ReplicationPad2d(…)