(l-onnx-doc-CumProd)=

# CumProd


(l-onnx-op-cumprod-26)=

## CumProd - 26

### Version

- **name**: [CumProd (GitHub)](https://github.com/onnx/onnx/blob/main/docs/Operators.md#CumProd)
- **domain**: `main`
- **since_version**: `26`
- **function**: `False`
- **support_level**: `SupportType.COMMON`
- **shape inference**: `True`

This version of the operator has been available
**since version 26**.

### Summary

Performs cumulative product of the input elements along the given axis.
By default, it will do the product inclusively meaning the first element is copied as is.
Through an `exclusive` attribute, this behavior can change to exclude the first element.
It can also perform product in the opposite direction of the axis. For that, set `reverse` attribute to 1.

Example:
```
input_x = [1, 2, 3]
axis=0
output = [1, 2, 6]
exclusive=1
output = [1, 1, 2]
exclusive=0
reverse=1
output = [6, 6, 3]
exclusive=1
reverse=1
output = [6, 3, 1]
```

### Attributes

* **exclusive - INT** (default is `'0'`):

  If set to 1 will return exclusive product in which the top element is not included. In other terms, if set to 1, the j-th output element would be the product of the first (j-1) elements. Otherwise, it would be the product of the first j elements.

* **reverse - INT** (default is `'0'`):

  If set to 1 will perform the products in reverse direction.

### Inputs

- **x** (heterogeneous) - **T**:

  An input tensor that is to be processed.
- **axis** (heterogeneous) - **T2**:

  A 0-D tensor. Must be in the range [-rank(x), rank(x)-1]. Negative value means counting dimensions from the back.

### Outputs

- **y** (heterogeneous) - **T**:

  Output tensor of the same type as 'x' with cumulative products of the x's elements

### Type Constraints

* **T** in ( `tensor(bfloat16)`, `tensor(double)`, `tensor(float)`, `tensor(float16)`, `tensor(int32)`, `tensor(int64)`, `tensor(uint32)`, `tensor(uint64)` ):

  Constrain input and output types to numeric tensors.
* **T2** in ( `tensor(int32)`, `tensor(int64)` ):

  axis tensor can be int32 or int64 only