(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.
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).
The columns of the tensor correspond one-by-one to the keys specified by the attributes. There must be as many columns as keys.
### Attributes
* **classlabels_int64s - INTS** :
The keys when using int keys.
One and only one of the 'classlabels_*' attributes must be defined.
* **classlabels_strings - STRINGS** :
The keys when using string keys.
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.