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

# ai.onnx.ml - ZipMap


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

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

### Version

- **name**: [ZipMap (GitHub)](https://github.com/onnx/onnx/blob/main/docs/Operators-ml.md#ai.onnx.ml.ZipMap)
- **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

Creates a map from the input and the attributes.<br>
The values are provided by the input tensor, while the keys are specified by the attributes.
Must provide keys in either classlabels_strings or classlabels_int64s (but not both).<br>
The columns of the tensor correspond one-by-one to the keys specified by the attributes. There must be as many columns as keys.<br>

### Attributes

* **classlabels_int64s - INTS** :

  The keys when using int keys.<br>One and only one of the 'classlabels_*' attributes must be defined.

* **classlabels_strings - STRINGS** :

  The keys when using string keys.<br>One and only one of the 'classlabels_*' attributes must be defined.

### Inputs

- **X** (heterogeneous) - **tensor(float)**:

  The input values

### Outputs

- **Z** (heterogeneous) - **T**:

  The output map

### Type Constraints

* **T** in ( `seq(map(int64, float))`, `seq(map(string, float))` ):

  The output will be a sequence of string or integer maps to float.