# tensorplay.functional.cumprod

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

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

Returns the cumulative product of elements of input in the dimension
dim.

For example, if input is a vector of size N, the result will also be
a vector of size N, with elements.

$$y_i = x_1 \times x_2\times x_3\times \dots \times x_i$$

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:

- dtype ([tensorplay.dtype](/docs/generated/tensorplay.DType.html#tensorplay.DType), optional) – the desired data type of returned tensor. If specified, the input tensor is casted to dtype before the operation is performed. This is useful for preventing data type overflows. Default: None.

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

Example:

```
>>> a = tensorplay.randn(10)
>>> a
tensor([ 0.6001,  0.2069, -0.1919,  0.9792,  0.6727,  1.0062,  0.4126,
        -0.2129, -0.4206,  0.1968])
>>> tensorplay.cumprod(a, dim=0)
tensor([ 0.6001,  0.1241, -0.0238, -0.0233, -0.0157, -0.0158, -0.0065,
         0.0014, -0.0006, -0.0001])

>>> a[5] = 0.0
>>> tensorplay.cumprod(a, dim=0)
tensor([ 0.6001,  0.1241, -0.0238, -0.0233, -0.0157, -0.0000, -0.0000,
         0.0000, -0.0000, -0.0000])
```