# tensorplay.functional.logcumsumexp

Source: https://www.tensorplay.cn/docs/generated/tensorplay.functional.logcumsumexp.html

```python
tensorplay.functional.logcumsumexp(input, dim, *, out=None) → Tensor
```

Returns the logarithm of the cumulative summation of the exponentiation of
elements of input in the dimension dim.

For summation index $j$ given by dim and other indices $i$, the result is

$$\text{logcumsumexp}(x)_{ij} = \log \sum\limits_{k=0}^{j} \exp(x_{ik})$$

Parameters:

- input ([Tensor](/docs/generated/tensorplay.Tensor.html#tensorplay.Tensor)) – the input tensor.

- dim ([int](https://docs.python.org/3/builtins/functions.html#int)) – the dimension to do the operation over

Keyword Arguments:

out ([Tensor](/docs/generated/tensorplay.Tensor.html#tensorplay.Tensor), optional) – the output tensor.

Example:

```
>>> a = tensorplay.randn(10)
>>> tensorplay.logcumsumexp(a, dim=0)
tensor([-0.42296738, -0.04462666,  0.86278635,  0.94622083,  1.05277811,
         1.39202815,  1.83525007,  1.84492621,  2.06084887,  2.06844475]))
```