.. _l-onnx-doc-BitwiseNot:

==========
BitwiseNot
==========

.. contents::
    :local:


.. _l-onnx-op-bitwisenot-18:

BitwiseNot - 18
===============

**Version**

* **name**: `BitwiseNot (GitHub) <https://github.com/onnx/onnx/blob/main/docs/Operators.md#BitwiseNot>`_
* **domain**: **main**
* **since_version**: **18**
* **function**: False
* **support_level**: SupportType.COMMON
* **shape inference**: True

This version of the operator has been available
**since version 18**.

**Summary**

Returns the bitwise not of the input tensor element-wise.

**Inputs**

* **X** (heterogeneous) - **T**:
  Input tensor

**Outputs**

* **Y** (heterogeneous) - **T**:
  Output tensor

**Type Constraints**

* **T** in (
  tensor(int16),
  tensor(int32),
  tensor(int64),
  tensor(int8),
  tensor(uint16),
  tensor(uint32),
  tensor(uint64),
  tensor(uint8)
  ):
  Constrain input/output to integer tensors.

**Examples**

**default**

::

    node = onnx.helper.make_node(
        "BitwiseNot",
        inputs=["x"],
        outputs=["bitwise_not"],
    )

    # 2d
    x = np.random.randn(3, 4).astype(np.int32)
    y = np.bitwise_not(x)
    expect(node, inputs=[x], outputs=[y], name="test_bitwise_not_2d")

    # 3d
    x = np.random.randn(3, 4, 5).astype(np.uint16)
    y = np.bitwise_not(x)
    expect(node, inputs=[x], outputs=[y], name="test_bitwise_not_3d")

    # 4d
    x = np.random.randn(3, 4, 5, 6).astype(np.uint8)
    y = np.bitwise_not(x)
    expect(node, inputs=[x], outputs=[y], name="test_bitwise_not_4d")