> 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/0.4/developer-guide/api/concrete.ml.common.check_inputs.md).

# concrete.ml.common.check\_inputs

[![](https://img.shields.io/badge/-source-cccccc?style=flat-square)](https://github.com/zama-ai/concrete-ml/blob/release/0.4.x/src/concrete/ml/common/check_inputs.py#L0)

## module `concrete.ml.common.check_inputs`

Check and conversion tools.

Utils that are used to check (including convert) some data types which are compatible with scikit-learn to numpy types.

***

[![](https://img.shields.io/badge/-source-cccccc?style=flat-square)](https://github.com/zama-ai/concrete-ml/blob/release/0.4.x/src/concrete/ml/common/check_inputs.py#L16)

### function `check_array_and_assert`

```python
check_array_and_assert(X)
```

sklearn.utils.check\_array with an assert.

Equivalent of sklearn.utils.check\_array, with a final assert that the type is one which is supported by Concrete-ML.

**Args:**

* **`X`** (object): Input object to check / convert

**Returns:** The converted and validated array

***

[![](https://img.shields.io/badge/-source-cccccc?style=flat-square)](https://github.com/zama-ai/concrete-ml/blob/release/0.4.x/src/concrete/ml/common/check_inputs.py#L33)

### function `check_X_y_and_assert`

```python
check_X_y_and_assert(X, y, *args, **kwargs)
```

sklearn.utils.check\_X\_y with an assert.

Equivalent of sklearn.utils.check\_X\_y, with a final assert that the type is one which is supported by Concrete-ML.

**Args:**

* **`X`** (ndarray, list, sparse matrix): Input data
* **`y`** (ndarray, list, sparse matrix): Labels
* **`*args`**: The arguments to pass to check\_X\_y
* **`**kwargs`**: The keyword arguments to pass to check\_X\_y

**Returns:** The converted and validated arrays


---

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