93 lines
2.5 KiB
Markdown
93 lines
2.5 KiB
Markdown
# SquaredDifference {#openvino_docs_ops_arithmetic_SquaredDifference_1}
|
|
|
|
**Versioned name**: *SquaredDifference-1*
|
|
|
|
**Category**: *Arithmetic binary*
|
|
|
|
**Short description**: *SquaredDifference* performs element-wise subtract and square the result operation with two given tensors applying broadcasting rule specified in the *auto_broadcast* attribute.
|
|
|
|
**Detailed description**
|
|
As a first step input tensors *a* and *b* are broadcasted if their shapes differ. Broadcasting is performed according to `auto_broadcast` attribute specification. As a second step *Substract* and *Square* the result operation is computed element-wise on the input tensors *a* and *b* according to the formula below:
|
|
|
|
\f[
|
|
o_{i} = (a_{i} - b_{i})^2
|
|
\f]
|
|
|
|
**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 [Broadcast Rules For Elementwise Operations](../broadcast_rules.md)
|
|
* **Type**: string
|
|
* **Default value**: "numpy"
|
|
* **Required**: *no*
|
|
|
|
**Inputs**
|
|
|
|
* **1**: A tensor of type *T* and arbitrary shape. **Required.**
|
|
* **2**: A tensor of type *T* and arbitrary shape. **Required.**
|
|
|
|
**Outputs**
|
|
|
|
* **1**: The result of element-wise subtract and square the result operation. A tensor of type *T* with shape equal to broadcasted shape of two inputs.
|
|
|
|
**Types**
|
|
|
|
* *T*: any numeric type.
|
|
|
|
**Examples**
|
|
|
|
*Example 1 - no broadcasting*
|
|
|
|
```xml
|
|
<layer ... type="SquaredDifference">
|
|
<data auto_broadcast="none"/>
|
|
<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 broadcasting*
|
|
```xml
|
|
<layer ... type="SquaredDifference">
|
|
<data auto_broadcast="numpy"/>
|
|
<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>
|
|
```
|