> For the complete documentation index, see [llms.txt](https://docs.zama.org/concrete-ml/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.zama.org/concrete-ml/1.1/developer-guide/api/concrete.ml.onnx.onnx_utils.md).

# concrete.ml.onnx.onnx\_utils.md

[![](https://img.shields.io/badge/-source-cccccc?style=flat-square)](https://github.com/zama-ai/concrete-ml/blob/release/1.1.x/src/concrete/ml/onnx/onnx_utils.py#L0)

## module `concrete.ml.onnx.onnx_utils`

Utils to interpret an ONNX model with numpy.

### **Global Variables**

* **ATTR\_TYPES**
* **ATTR\_GETTERS**
* **ONNX\_OPS\_TO\_NUMPY\_IMPL**
* **ONNX\_COMPARISON\_OPS\_TO\_NUMPY\_IMPL\_FLOAT**
* **ONNX\_COMPARISON\_OPS\_TO\_NUMPY\_IMPL\_BOOL**
* **ONNX\_OPS\_TO\_NUMPY\_IMPL\_BOOL**
* **IMPLEMENTED\_ONNX\_OPS**

***

[![](https://img.shields.io/badge/-source-cccccc?style=flat-square)](https://github.com/zama-ai/concrete-ml/blob/release/1.1.x/src/concrete/ml/onnx/onnx_utils.py#L420)

### function `get_attribute`

```python
get_attribute(attribute: AttributeProto) → Any
```

Get the attribute from an ONNX AttributeProto.

**Args:**

* `attribute` (onnx.AttributeProto): The attribute to retrieve the value from.

**Returns:**

* `Any`: The stored attribute value.

***

[![](https://img.shields.io/badge/-source-cccccc?style=flat-square)](https://github.com/zama-ai/concrete-ml/blob/release/1.1.x/src/concrete/ml/onnx/onnx_utils.py#L432)

### function `get_op_type`

```python
get_op_type(node)
```

Construct the qualified type name of the ONNX operator.

**Args:**

* `node` (Any): ONNX graph node

**Returns:**

* `result` (str): qualified name

***

[![](https://img.shields.io/badge/-source-cccccc?style=flat-square)](https://github.com/zama-ai/concrete-ml/blob/release/1.1.x/src/concrete/ml/onnx/onnx_utils.py#L444)

### function `execute_onnx_with_numpy`

```python
execute_onnx_with_numpy(graph: GraphProto, *inputs: ndarray) → Tuple[ndarray, ]
```

Execute the provided ONNX graph on the given inputs.

**Args:**

* `graph` (onnx.GraphProto): The ONNX graph to execute.
* `*inputs`: The inputs of the graph.

**Returns:**

* `Tuple[numpy.ndarray]`: The result of the graph's execution.

***

[![](https://img.shields.io/badge/-source-cccccc?style=flat-square)](https://github.com/zama-ai/concrete-ml/blob/release/1.1.x/src/concrete/ml/onnx/onnx_utils.py#L475)

### function `remove_initializer_from_input`

```python
remove_initializer_from_input(model: ModelProto)
```

Remove initializers from model inputs.

In some cases, ONNX initializers may appear, erroneously, as graph inputs. This function searches all model inputs and removes those that are initializers.

**Args:**

* `model` (onnx.ModelProto): the model to clean

**Returns:**

* `onnx.ModelProto`: the cleaned model


---

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