de53c40578
* bulk change `type T` to `type *T*` in spec * update all `T` which referee to type to use *T* pattern * get back with `T` where T is dimension * fix *T*1 -> *T1* * Make italic types where was no formating
2.6 KiB
2.6 KiB
Multiply
Versioned name: Multiply-1
Category: Arithmetic binary operation
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:
\f[ o_{i} = a_{i} * b_{i} \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,
- 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>