BitwiseRightShift#

Versioned name: BitwiseRightShift-15

Category: Bitwise binary

Short description: BitwiseRightShift performs a bitwise right shift operation operation, applying multi-directional broadcast rules.

Detailed description: Before performing the operation, input tensors a and b are broadcasted if their shapes are different and the auto_broadcast attribute is not none. Broadcasting is performed according to the auto_broadcast value.

After broadcasting input tensors a and b, BitwiseRightShift performs a bitwise right shift operation for each corresponding element in the given tensors, based on the following equation:

o_{i} = a_{i} ≫ b_{i}

Note

If the number of shifts is negative, or if it equals or exceeds the total number of bits in the type T, the behavior can be undefined or implementation-defined (depends on the hardware).

Unsigned integer shift is always performed modulo 2^n where n is the number of bits in the type T.

When signed integer shift operation overflows (the result does not fit in the result type), the behavior is undefined.

Attributes:

auto_broadcast
- Description: specifies the 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, containing data to be shifted. Required.
2: A tensor of type T and arbitrary shape, with the number of shifts. Required.

Outputs

1: The result of element-wise BitwiseRightShift operation. A tensor of type T and the shape equal to the broadcasted shape of two inputs.

Types

T: any supported integer type.

Examples

Example 1: no broadcast

<layer ... type="BitwiseRightShift">
    <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: numpy broadcast

<layer ... type="BitwiseRightShift">
    <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>