sums

paddle.fluid.layers.sums(input, out=None)[源代码]

该OP计算多个输入Tensor逐个元素相加的和。

  • 示例:3个Tensor求和
输入:
    x0.shape = [2, 3]
    x0.data = [[1., 2., 3.],
               [4., 5., 6.]]
    x1.shape = [2, 3]
    x1.data = [[10., 20., 30.],
               [40., 50., 60.]]
    x2.shape = [2, 3]
    x2.data = [[100., 200., 300.],
               [400., 500., 600.]]

输出:
    out.shape = [2, 3]
    out.data = [[111., 222., 333.],
                [444., 555., 666.]]
参数:
  • input (list) - 多个维度相同的Tensor组成的元组。支持的数据类型:float32,float64,int32,int64。
  • out (Variable,可选) - 指定求和的结果Tensor,可以是程序中已经创建的任何Variable。默认值为None,此时将创建新的Variable来保存输出结果。

返回:输入的和,数据类型和维度与输入Tensor相同。若 outNone ,返回值是一个新的Variable;否则,返回值就是 out

返回类型:Variable

代码示例

import paddle.fluid as fluid

x0 = fluid.layers.fill_constant(shape=[16, 32], dtype='int64', value=1)
x1 = fluid.layers.fill_constant(shape=[16, 32], dtype='int64', value=2)
x2 = fluid.layers.fill_constant(shape=[16, 32], dtype='int64', value=3)
x3 = fluid.layers.fill_constant(shape=[16, 32], dtype='int64', value=0)

# 多个Tensor求和,结果保存在一个新建的Variable sum0,即sum0=x0+x1+x2,值为[[6, ..., 6], ..., [6, ..., 6]]
sum0 = fluid.layers.sums(input=[x0, x1, x2])

# 多个Tensor求和,sum1和x3是同一个Variable,相当于x3=x0+x1+x2,值为[[6, ..., 6], ..., [6, ..., 6]]
sum1 = fluid.layers.sums(input=[x0, x1, x2], out=x3)