mindspore.mint.nn.ConstantPad1d

class mindspore.mint.nn.ConstantPad1d(padding, value)[source]

Pad the last dimension of input tensor using padding and value.

For more information, please refer to mindspore.mint.nn.functional.pad().

Warning

This is an experimental API that is subject to change or deletion.

Parameters

padding (Union[int, tuple, list]) – Specifies padding size.
value (Union[int, float]) – Specifies padding value.

Inputs:

input (Tensor) - shape is \((N, *)\), where \(*\) means, any number of additional dimensions.

Outputs:

Tensor, the tensor after padding.

Raises

TypeError – If padding is not an integer of a list or tuple of 2 integers.
TypeError – If input is not Tensor.
TypeError – If value is not int or float.
ValueError – If padding contains negative value.
ValueError – If padding is a tuple or list, and the length does not match the tensor dimension.

Supported Platforms:: Ascend

Examples

>>> import numpy as np
>>> import mindspore as ms
>>> x = np.ones(shape=(1, 2, 3, 4)).astype(np.float32)
>>> x = ms.Tensor(x)
>>> # padding is tuple
>>> padding = (0, 1)
>>> value = 0.5
>>> pad1d = ms.mint.nn.ConstantPad1d(padding, value)
>>> out = pad1d(x)
>>> print(out)
[[[[1.  1.  1.  1.  0.5]
   [1.  1.  1.  1.  0.5]
   [1.  1.  1.  1.  0.5]]
  [[1.  1.  1.  1.  0.5]
   [1.  1.  1.  1.  0.5]
   [1.  1.  1.  1.  0.5]]]]
>>> print(out.shape)
(1, 2, 3, 5)
>>> # padding is int
>>> padding = 1
>>> value = 0.5
>>> pad1d = ms.mint.nn.ConstantPad1d(padding, value)
>>> out = pad1d(x)
>>> print(out)
[[[[0.5 1.  1.  1.  1.  0.5]
   [0.5 1.  1.  1.  1.  0.5]
   [0.5 1.  1.  1.  1.  0.5]]
  [[0.5 1.  1.  1.  1.  0.5]
   [0.5 1.  1.  1.  1.  0.5]
   [0.5 1.  1.  1.  1.  0.5]]]]
>>> print(out.shape)
(1, 2, 3, 6)