> 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.convert.md).

# concrete.ml.onnx.convert.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/convert.py#L0)

## module `concrete.ml.onnx.convert`

ONNX conversion related code.

### **Global Variables**

* **IMPLEMENTED\_ONNX\_OPS**
* **OPSET\_VERSION\_FOR\_ONNX\_EXPORT**

***

[![](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/convert.py#L17)

### function `get_equivalent_numpy_forward_and_onnx_model`

```python
get_equivalent_numpy_forward_and_onnx_model(
    torch_module: Module,
    dummy_input: Union[Tensor, Tuple[Tensor, ]],
    output_onnx_file: Optional[Path, str] = None
) → Tuple[Callable[, Tuple[ndarray, ]], GraphProto]
```

Get the numpy equivalent forward of the provided torch Module.

**Args:**

* `torch_module` (torch.nn.Module): the torch Module for which to get the equivalent numpy forward.
* `dummy_input` (Union\[torch.Tensor, Tuple\[torch.Tensor, ...]]): dummy inputs for ONNX export.
* `output_onnx_file` (Optional\[Union\[Path, str]]): Path to save the ONNX file to. Will use a temp file if not provided. Defaults to None.

**Returns:**

* `Tuple[Callable[..., Tuple[numpy.ndarray, ...]], onnx.GraphProto]`: The function that will execute the equivalent numpy code to the passed torch\_module and the generated ONNX model.

***

[![](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/convert.py#L67)

### function `get_equivalent_numpy_forward`

```python
get_equivalent_numpy_forward(
    onnx_model: ModelProto,
    check_model: bool = True
) → Callable[, Tuple[ndarray, ]]
```

Get the numpy equivalent forward of the provided ONNX model.

**Args:**

* `onnx_model` (onnx.ModelProto): the ONNX model for which to get the equivalent numpy forward.
* `check_model` (bool): set to True to run the onnx checker on the model. Defaults to True.

**Raises:**

* `ValueError`: Raised if there is an unsupported ONNX operator required to convert the torch model to numpy.

**Returns:**

* `Callable[..., Tuple[numpy.ndarray, ...]]`: The function that will execute the equivalent numpy function.


---

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