Intel® oneAPI Deep Neural Network Developer Guide and Reference
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SquaredDifference
General
SquaredDifference operation performs element-wise subtraction operation with two given tensors applying multi-directional broadcast rules, after that each result of the subtraction is squared.
Before performing arithmetic operation,  and
 and  are broadcasted if their shapes are different and auto_broadcast attributes is not none. Broadcasting is performed according to auto_broadcast value. After broadcasting SquaredDifference does the following with the input tensors:
 are broadcasted if their shapes are different and auto_broadcast attributes is not none. Broadcasting is performed according to auto_broadcast value. After broadcasting SquaredDifference does the following with the input tensors:
 
 
   Operation attributes
| Attribute Name | Description | Value Type | Supported Values | Required or Optional | 
|---|---|---|---|---|
| Specifies rules used for auto-broadcasting of input tensors. | string | none , numpy (default) | Optional | 
Execution arguments
The inputs and outputs must be provided according to below index order when constructing an operation.
Inputs
| Index | Argument Name | Required or Optional | 
|---|---|---|
| 0 | src_0 | Required | 
| 1 | src_1 | Required | 
Outputs
| Index | Argument Name | Required or Optional | 
|---|---|---|
| 0 | dst | Required | 
Supported data types
SquaredDifference operation supports the following data type combinations.
| Src_0 / Src_1 | Dst | 
|---|---|
| f32 | f32 | 
| bf16 | bf16 | 
| f16 | f16 |