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_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 Multiply performs multiplication operation for the input tensors a and b using the formula below:
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>