mindspore.nn.ReplicationPad1d

class mindspore.nn.ReplicationPad1d(padding)

Pad on W dimension of input x according to padding.

Parameters

padding (union[int, tuple]) –

The padding size to pad the last dimension of x .

• If padding is an integer, all directions will be padded with the same size.

• If padding is a tuple, uses $(pa{d}_{left},pa{d}_{right})$ to pad.

Inputs:

• x (Tensor) - 2D or 3D, shape: $(C,W_{in})$ or $(N,C,W_{in})$.

Outputs:

Tensor, after padding. Shape: $(C,W_{out})$ or $(N,C,W_{out})$, where $W_{out}=W_{in}+pa{d}_{left}+pa{d}_{right}$

Raises

• TypeError – If padding is neither a tuple nor an int.

• TypeError – If there is an element in padding that is not int.

• ValueError – If padding is tuple and the length of padding is not divisible by 2.

• ValueError – If padding is tuple and there is a dimension mismatch between the padding and the tensor.

Supported Platforms:

GPU

Examples

>>> import numpy as np
>>> import mindspore as ms
>>> pad1d = ms.nn.ReplicationPad1d(2)
>>> input = ms.Tensor(np.arange(0, 8).reshape(1, 2, 4), ms.float32)
>>> print(input)
[[[0. 1. 2. 3.]
  [4. 5. 6. 7.]]]
>>> out = pad1d(input)
>>> print(out)
[[[0. 0. 0. 1. 2. 3. 3. 3.]
  [4. 4. 4. 5. 6. 7. 7. 7.]]]
>>> pad1d = ms.nn.ReplicationPad1d((3, 1))
>>> out = pad1d(input)
>>> print(out)
[[[0. 0. 0. 0. 1. 2. 3. 3.]
  [4. 4. 4. 4. 5. 6. 7. 7.]]]