Multiply

Versioned name : Multiply-1

Category : Arithmetic binary

Short description : Multiply performs element-wise multiplication operation with two given tensors applying broadcasting rule specified in the auto_broacast 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 Multiply performs multiplication operation for the input tensors a and b using the formula below:

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

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 multiplication 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="Multiply">
    <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="Multiply">
    <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>