LogicalXor¶
Versioned name : LogicalXor-1
Category : Logical binary operation
Short description : LogicalXor performs element-wise logical XOR operation with two given tensors applying multi-directional broadcast rules.
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 should match
numpy - numpy broadcasting rules, aligned with ONNX Broadcasting. Description is available in ONNX docs.
Type : string
Default value : “numpy”
Required : no
Inputs
1 : A tensor of type T. Required.
2 : A tensor of type T. Required.
Outputs
1 : The result of element-wise logical XOR operation. A tensor of type T.
Types
T : boolean type.
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 :
Examples
Example 1
<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: broadcast
<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>