# LogicalXor {#openvino_docs_ops_logical_LogicalXor_1}

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**Versioned name**: *LogicalXor-1*

**Category**: *Logical binary*

**Short description**: *LogicalXor* performs element-wise logical XOR operation with two given tensors applying multi-directional broadcast rules.

**Detailed description**: Before performing logical operation, input tensors *a* and *b* are broadcasted if their shapes are different and ``auto_broadcast`` attributes is not ``none``. Broadcasting is performed according to ``auto_broadcast`` value.

After broadcasting *LogicalXor* does the following with the input tensors *a* and *b*:

.. math::

   o_{i} = a_{i} \oplus b_{i}


**Attributes**:

* *auto_broadcast*

  * **Description**: specifies rules used for auto-broadcasting of input tensors.
  * **Range of values**:

    * *none* - no auto-broadcasting is allowed, all input shapes must match
    * *numpy* - numpy broadcasting rules, description is available in :doc:`Broadcast Rules For Elementwise Operations <openvino_docs_ops_broadcast_rules>`,
    * *pdpd* - PaddlePaddle-style implicit broadcasting, description is available in :doc:`Broadcast Rules For Elementwise Operations <openvino_docs_ops_broadcast_rules>`.

  * **Type**: string
  * **Default value**: "numpy"
  * **Required**: *no*

**Inputs**

* **1**: A tensor of type *T_BOOL* and arbitrary shape. **Required.**
* **2**: A tensor of type *T_BOOL* and arbitrary shape. **Required.**

**Outputs**

* **1**: The result of element-wise *logicalXor* operation. A tensor of type *T_BOOL* and the same shape equal to broadcasted shape of two inputs.

**Types**

* *T_BOOL*: ``boolean``.

**Examples**

*Example 1: no broadcast*

.. code-block:: cpp

   <layer ... type="LogicalXor">
       <input>
           <port id="0">
               <dim>256</dim>
               <dim>56</dim>
           </port>
           <port id="1">
               <dim>256</dim>
               <dim>56</dim>
           </port>
       </input>
       <output>
           <port id="2">
               <dim>256</dim>
               <dim>56</dim>
           </port>
       </output>
   </layer>


*Example 2: numpy broadcast*

.. code-block:: cpp

   <layer ... type="LogicalXor">
       <input>
           <port id="0">
               <dim>8</dim>
               <dim>1</dim>
               <dim>6</dim>
               <dim>1</dim>
           </port>
           <port id="1">
               <dim>7</dim>
               <dim>1</dim>
               <dim>5</dim>
           </port>
       </input>
       <output>
           <port id="2">
               <dim>8</dim>
               <dim>7</dim>
               <dim>6</dim>
               <dim>5</dim>
           </port>
       </output>
   </layer>


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