# sum¶

paddle. sum ( x, axis=None, dtype=None, keepdim=False, name=None ) [source]

Computes the sum of tensor elements over the given dimension.

Parameters
• x (Tensor) – An N-D Tensor, the data type is bool, float16, float32, float64, int32 or int64.

• axis (int|list|tuple, optional) – The dimensions along which the sum is performed. If `None`, sum all elements of `x` and return a Tensor with a single element, otherwise must be in the range \([-rank(x), rank(x))\). If \(axis[i] < 0\), the dimension to reduce is \(rank + axis[i]\).

• dtype (str, optional) – The dtype of output Tensor. The default value is None, the dtype of output is the same as input Tensor x.

• keepdim (bool, optional) – Whether to reserve the reduced dimension in the output Tensor. The result Tensor will have one fewer dimension than the `x` unless `keepdim` is true, default value is False.

• name (str, optional) – Name for the operation (optional, default is None). For more information, please refer to Name.

Returns

Results of summation operation on the specified axis of input Tensor x, if x.dtype=’bool’, x.dtype=’int32’, it’s data type is ‘int64’, otherwise it’s data type is the same as x.

Return type

Tensor

Examples

```>>> import paddle

>>> # x is a Tensor with following elements:
>>> #    [[0.2, 0.3, 0.5, 0.9]
>>> #     [0.1, 0.2, 0.6, 0.7]]
>>> # Each example is followed by the corresponding output tensor.
>>> x = paddle.to_tensor([[0.2, 0.3, 0.5, 0.9],
...                       [0.1, 0.2, 0.6, 0.7]])
>>> out1
3.50000000)
>>> out2
[0.30000001, 0.50000000, 1.10000002, 1.59999990])
>>> out3
[1.89999998, 1.60000002])
>>> out4 = paddle.sum(x, axis=1, keepdim=True)
>>> out4
[[1.89999998],
[1.60000002]])

>>> # y is a Tensor with shape [2, 2, 2] and elements as below:
>>> #      [[[1, 2], [3, 4]],
>>> #      [[5, 6], [7, 8]]]
>>> # Each example is followed by the corresponding output tensor.
>>> y = paddle.to_tensor([[[1, 2], [3, 4]],
...                       [[5, 6], [7, 8]]])
>>> out5 = paddle.sum(y, axis=[1, 2])
>>> out5
[10, 26])
>>> out6 = paddle.sum(y, axis=[0, 1])
>>> out6
[16, 20])

>>> # x is a Tensor with following elements:
>>> #    [[True, True, True, True]
>>> #     [False, False, False, False]]
>>> # Each example is followed by the corresponding output tensor.
>>> x = paddle.to_tensor([[True, True, True, True],
...                       [False, False, False, False]])