sums¶

paddle.fluid.layers.tensor. sums ( input, out=None ) [source]

This function computes the sum of multiple input Tensors elementwisely.

Case 1, sum of 3 Tensors

           # Input Tensors
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.]]

# Output Tensor
out.shape = [2, 3]
out.data = [[111., 222., 333.],
            [444., 555., 666.]]

          

Parameters

input (list) – A list of Variables which hold input Tensors with the same data type and shape. Optional data types are: float32, float64, int32, int64.
out (Variable, optional) – Output Tensor. It can be any existing Variable. The default value is None, then a new Variable will be created and returned.

Returns

The sum of inputs. The shape and data type is the same with input.: If out is not None, the returned value is out .

Return type

Variable

Examples

           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)

# Sum of multiple Tensors, the result is stored to a new Variable sum0 (sum0=x0+x1+x2, the value is [[6, ..., 6], ..., [6, ..., 6]])
sum0 = fluid.layers.sums(input=[x0, x1, x2])

# Sum of multiple Tensors, sum1 and x3 represents the same Variable (x3=x0+x1+x2, the value is [[6, ..., 6], ..., [6, ..., 6]])
sum1 = fluid.layers.sums(input=[x0, x1, x2], out=x3)

          