Versioned name: Maximum-1
Category: Arithmetic binary operation
Short description: Maximum performs element-wise maximum operation with two given tensors applying multi-directional broadcast rules.
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 should match
- numpy - numpy broadcasting rules, aligned with ONNX Broadcasting. Description is available in ONNX docs.
- Type: string
- Default value: "numpy"
- Required: no
Inputs
- 1: First input tensor of type T. Required.
- 2: Second input tensor of type T. Required.
Outputs
- 1: The result of element-wise maximum operation. A tensor of type T.
Types
- T: arbitrary type, which supports less/greater comparison.
Detailed description Before performing arithmetic operation, input tensors a and b are broadcasted if their shapes are different and auto_broadcast
attributes is not none
. Broadcasting is performed according to auto_broadcast
value.
After broadcasting Maximum does the following with the input tensors a and b:
\[ o_{i} = max(a_{i}, b_{i}) \]
Examples
Example 1
<layer ... type="Maximum">
<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="Maximum">
<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>