(l-onnx-docai-onnx-ml-CategoryMapper)=

# ai.onnx.ml - CategoryMapper


(l-onnx-opai-onnx-ml-categorymapper-1)=

## CategoryMapper - 1 (ai.onnx.ml)

### Version

- **name**: [CategoryMapper (GitHub)](https://github.com/onnx/onnx/blob/main/docs/Operators-ml.md#ai.onnx.ml.CategoryMapper)
- **domain**: `ai.onnx.ml`
- **since_version**: `1`
- **function**: `False`
- **support_level**: `SupportType.COMMON`
- **shape inference**: `True`

This version of the operator has been available
**since version 1 of domain ai.onnx.ml**.

### Summary

Converts strings to integers and vice versa.<br>
Two sequences of equal length are used to map between integers and strings,
with strings and integers at the same index detailing the mapping.<br>
Each operator converts either integers to strings or strings to integers, depending
on which default value attribute is provided. Only one default value attribute
should be defined.<br>
If the string default value is set, it will convert integers to strings.
If the int default value is set, it will convert strings to integers.

### Attributes

* **cats_int64s - INTS** :

  The integers of the map. This sequence must be the same length as the 'cats_strings' sequence.

* **cats_strings - STRINGS** :

  The strings of the map. This sequence must be the same length as the 'cats_int64s' sequence

* **default_int64 - INT** (default is `-1`):

  An integer to use when an input string value is not found in the map.<br>One and only one of the 'default_*' attributes must be defined.

* **default_string - STRING** (default is `_Unused`):

  A string to use when an input integer value is not found in the map.<br>One and only one of the 'default_*' attributes must be defined.

### Inputs

- **X** (heterogeneous) - **T1**:

  Input data

### Outputs

- **Y** (heterogeneous) - **T2**:

  Output data. If strings are input, the output values are integers, and vice versa.

### Type Constraints

* **T1** in ( `tensor(int64)`, `tensor(string)` ):

  The input must be a tensor of strings or integers, either [N,C] or [C].
* **T2** in ( `tensor(int64)`, `tensor(string)` ):

  The output is a tensor of strings or integers. Its shape will be the same as the input shape.