Pad

class Pad(pad_width, mode='constant', constant_val=0.0)

Pads the input tensor.

Parameters:

• pad_width (Tuple[Tuple[int, int], ...]) – A tuple. Each element in the tuple is the tuple of 2-elements, the 2 elements represent the padding size on both sides of the current dimension, (front_offset, back_offset)

• mode (str) –

  One of the following string values. Default: 'constant'

  • 'constant': Pads with a constant value.

  • 'reflect': Pads with the edge values of tensor.

  • 'replicate': Pads with the reflection of the tensor mirrored on the first and last values of the tensor along each axis.

• constant_val (float) – Fill value for 'constant' padding. Default: 0

Examples

>>> import numpy as np
>>> inp = Tensor([[1., 2., 3.],[4., 5., 6.]])
>>> inp
Tensor([[1. 2. 3.]
 [4. 5. 6.]], device=xpux:0)
>>> m = M.Pad(pad_width=((1, 1),), mode="constant")
>>> m(inp)
Tensor([[0. 0. 0.]
 [1. 2. 3.]
 [4. 5. 6.]
 [0. 0. 0.]], device=xpux:0)
>>> m = M.Pad(pad_width=((1, 1),), mode="constant", constant_val=9)
>>> m(inp)
Tensor([[9. 9. 9.]
 [1. 2. 3.]
 [4. 5. 6.]
 [9. 9. 9.]], device=xpux:0)
>>> m = M.Pad(pad_width=((1, 1), (1, 2)), mode="reflect")
>>> m(inp)
Tensor([[5. 4. 5. 6. 5. 4.]
 [2. 1. 2. 3. 2. 1.]
 [5. 4. 5. 6. 5. 4.]
 [2. 1. 2. 3. 2. 1.]], device=xpux:0)
>>> m = M.Pad(pad_width=((1, 1), (1, 2)), mode="replicate")
>>> m(inp)
Tensor([[1. 1. 2. 3. 3. 3.]
 [1. 1. 2. 3. 3. 3.]
 [4. 4. 5. 6. 6. 6.]
 [4. 4. 5. 6. 6. 6.]], device=xpux:0)