Subtract

Versioned name: Subtract-1

Category: Arithmetic binary

Short description: Subtract performs element-wise subtraction operation with two given tensors applying broadcasting rule specified in the auto_broadcast attribute.

Detailed description Before performing arithmetic operation, input tensors a and b are broadcasted if their shapes are different and auto_broadcast attribute is not none. Broadcasting is performed according to auto_broadcast value. After broadcasting Subtract performs subtraction operation for the input tensors a and b using the formula below:

\[o_{i} = a_{i} - b_{i}\]

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 Broadcast Rules For Elementwise Operations,

    • pdpd - PaddlePaddle-style implicit broadcasting, description is available in Broadcast Rules For Elementwise Operations.

  • Type: string

  • Default value: “numpy”

  • Required: no

Inputs

• 1: A tensor of type T and arbitrary shape and rank. Required.

• 2: A tensor of type T and arbitrary shape and rank. Required.

Outputs

• 1: The result of element-wise subtraction operation. A tensor of type T with shape equal to broadcasted shape of the two inputs.

Types

• T: any numeric type.

Examples

Example 1

 <layer ... type="Subtract">
     <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: broadcast

 <layer ... type="Subtract">
     <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>