ZeroPad2D

class paddle.nn. ZeroPad2D ( padding, data_format='NCHW', name=None ) [source]

This interface is used to construct a callable object of the ZeroPad2D class. Pads the input tensor boundaries with zero.

Parameters

  • padding (Tensor | List[int] | int) – The padding size with data type int. If is int, use the same padding in all dimensions. Else [len(padding)/2] dimensions of input will be padded. The pad has the form (pad_left, pad_right, pad_top, pad_bottom).

  • data_format (str) – An string from: “NCHW”, “NHWC”. Specify the data format of the input data. Default is “NCHW”

  • name (str, optional) – The default value is None. Normally there is no need for user to set this property. For more information, please refer to Name.

Shape:

  • x(Tensor): The input tensor of zeropad2d operator, which is a 4-D tensor. The data type can be float32, float64.

  • output(Tensor): The output tensor of zeropad2d operator, which is a 4-D tensor. The data type is same as input x.

Examples

Examples are as follows.

import paddle
import paddle.nn as nn
import numpy as np

input_shape = (1, 1, 2, 3)
pad = [1, 0, 1, 2]
data = paddle.arange(np.prod(input_shape), dtype="float32").reshape(input_shape) + 1

my_pad = nn.ZeroPad2D(padding=pad)
result = my_pad(data)

print(result)
# [[[[0. 0. 0. 0.]
#    [0. 1. 2. 3.]
#    [0. 4. 5. 6.]
#    [0. 0. 0. 0.]
#    [0. 0. 0. 0.]]]]
forward ( x )

forward

Defines the computation performed at every call. Should be overridden by all subclasses.

Parameters

  • *inputs (tuple) – unpacked tuple arguments

  • **kwargs (dict) – unpacked dict arguments

extra_repr ( )

extra_repr

Extra representation of this layer, you can have custom implementation of your own layer.