Greater¶

Versioned name : Greater-1

Category : Comparison binary operation

Short description : Greater performs element-wise comparison 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 : A tensor of type T. Required.
2 : A tensor of type T. Required.

Outputs

1 : The result of element-wise comparison operation. A tensor of type boolean.

Types

T : arbitrary supported type.

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 Greater does the following with the input tensors a and b :

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

Examples

Example 1

<layer ... type="Greater">
    <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="Greater">
    <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>

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