mindspore.mint.nn.ZeroPad1d

class mindspore.mint.nn.ZeroPad1d(padding)[source]

Pad the last dimension of input tensor with 0 using padding.

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.

Inputs:

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

Outputs:

Tensor, the tensor after padding.

Raises

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 mindspore
>>> x = mindspore.mint.ones((1, 2, 3, 4))
>>> # padding is tuple
>>> padding = (0, 1)
>>> pad1d = mindspore.mint.nn.ZeroPad1d(padding)
>>> out = pad1d(x)
>>> out
Tensor(shape=[1, 2, 3, 5], dtype=Float32, value=
[[[[ 1.00000000e+00,  1.00000000e+00,  1.00000000e+00,  1.00000000e+00,  0.00000000e+00],
   [ 1.00000000e+00,  1.00000000e+00,  1.00000000e+00,  1.00000000e+00,  0.00000000e+00],
   [ 1.00000000e+00,  1.00000000e+00,  1.00000000e+00,  1.00000000e+00,  0.00000000e+00]],
  [[ 1.00000000e+00,  1.00000000e+00,  1.00000000e+00,  1.00000000e+00,  0.00000000e+00],
   [ 1.00000000e+00,  1.00000000e+00,  1.00000000e+00,  1.00000000e+00,  0.00000000e+00],
   [ 1.00000000e+00,  1.00000000e+00,  1.00000000e+00,  1.00000000e+00,  0.00000000e+00]]]])
>>> # padding is int
>>> padding = 1
>>> pad1d = mindspore.mint.nn.ZeroPad1d(padding)
>>> out = pad1d(x)
>>> out
Tensor(shape=[1, 2, 3, 6], dtype=Float32, value=
[[[[ 0.00000000e+00,  1.00000000e+00,  1.00000000e+00,  1.00000000e+00,  1.00000000e+00,  0.00000000e+00],
   [ 0.00000000e+00,  1.00000000e+00,  1.00000000e+00,  1.00000000e+00,  1.00000000e+00,  0.00000000e+00],
   [ 0.00000000e+00,  1.00000000e+00,  1.00000000e+00,  1.00000000e+00,  1.00000000e+00,  0.00000000e+00]],
  [[ 0.00000000e+00,  1.00000000e+00,  1.00000000e+00,  1.00000000e+00,  1.00000000e+00,  0.00000000e+00],
   [ 0.00000000e+00,  1.00000000e+00,  1.00000000e+00,  1.00000000e+00,  1.00000000e+00,  0.00000000e+00],
   [ 0.00000000e+00,  1.00000000e+00,  1.00000000e+00,  1.00000000e+00,  1.00000000e+00,  0.00000000e+00]]]])