pad_constant_like

paddle.fluid.layers.pad_constant_like(x, y, pad_value=0.0, name=None)[源代码]

该OP使用 pad_value 填充 y ,填充到每个维度值的数量由x和y的形状而指定,((0,x.shape[0] - y.shape[0]), ..., (0, x.shape[i] - y.shape[i]), ..., (0, x.shape[n] - y.shape[n]))是每个维度填充的宽度,对于维度i,填充宽度 (0, x.shape[i] - y.shape[i]) ,表示在y的第i维开头不填充,而在末尾填充 x.shape[i] - y.shape[i] 个位置。该OP要求y与x具有相同的秩,并且对每个维度i, y.shape[i] <= x.shape[i]

样例

Given:
    X = [[[[ 0,  1,  2],
           [ 3,  4,  5]],
          [[ 6,  7,  8],
           [ 9, 10, 11]],
          [[12, 13, 14],
           [15, 16, 17]]],
         [[[18, 19, 20],
           [21, 22, 23]],
          [[24, 25, 26],
           [27, 28, 29]],
          [[30, 31, 32],
           [33, 34, 35]]]]
    X.shape = (2, 3, 2, 3)

    Y = [[[[35, 36, 37]],
          [[38, 39, 40]],
          [[41, 42, 43]]]]
    Y.shape = (1, 3, 1, 3)

and
    pad_value = 0.

Output is:
    out = [[[[35, 36, 37],
             [0, 0, 0]],
            [[38, 39, 40],
             [0, 0, 0]],
            [[41, 42, 43],
             [0, 0, 0]]],
           [[[0, 0, 0],
             [0, 0, 0]],
            [[0, 0, 0],
             [0, 0, 0]],
            [[0, 0, 0],
             [0, 0, 0]]]]
    out.shape = [2, 3, 2, 3]
参数:
  • x (Variable)- 多维Tensor
  • y (Variable)- 多维Tensor,与x具有相同的秩,而且对任意维度 i ,要求满足 y.shape[i] <= x.shape[i] 。数据类型为float32或float64
  • pad_value (float,可选) - 用于填充的常量值。默认值为0.
  • name (str | None) - (str|None) - 该参数供开发人员打印调试信息时使用,具体用法请参见 Name ,默认值为None。

返回:经过维度填充后的Tensor,与x具有相同的shape,与y具有相同的数据类型

返回类型: Variable

示例代码

# x是秩为4的tensor, x.shape = (2, 3, 2, 3)
# y是秩为4的tensor, y.shape = (1, 3, 1, 3)
import paddle.fluid as fluid
x = fluid.layers.data(name='x', shape=[2,3,2,3], dtype='float32')
y = fluid.layers.data(name='y', shape=[1,3,1,3], dtype='float32')
out = fluid.layers.pad_constant_like(x=x, y=y, pad_value=0.)
# out是秩为4的tensor, out.shape = [2, 3 ,2 , 3]