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DML_ACTIVATION_HARDMAX1_OPERATOR_DESC structure (directml.h)

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Performs a hardmax function on each element of InputTensor, placing the result into the corresponding element of OutputTensor.

The operator computes the hardmax (1 for the first maximum value along the specified axes, and 0 for all other values) of each element in the given input.

reducedTensor = ReduceArgMax(InputTensor, axes = Axes, axisDirection = DML_AXIS_DIRECTION_INCREASING)
broadcastedTensor = Broadcast the `reducedTensor` to `InputTensor`
for each coordinate in OutputTensor
    if broadcastedTensor[coordinate] == reducedIndexOf(coordinate)   // reducedIndexOf(coordinate) is the index of the coordinate within reduced axes `axes`.
        OutputTensor[coordinate] = 1
    else
        OutputTensor[coordinate] = 0
endfor

Where ReduceArgMax(input = InputTensor, axis = Axes) is DML_REDUCE_OPERATOR with DML_REDUCE_FUNCTION_ARGMAX as a reduce function.

Important

This API is available as part of the DirectML standalone redistributable package (see Microsoft.AI.DirectML version 1.9 and later. Also see DirectML version history.

Syntax

struct DML_ACTIVATION_HARDMAX1_OPERATOR_DESC
{
    const DML_TENSOR_DESC* InputTensor;
    const DML_TENSOR_DESC* OutputTensor;
    UINT AxisCount;
    _Field_size_(AxisCount) const UINT* Axes;
};

Members

InputTensor

Type: const DML_TENSOR_DESC*

The input tensor to read from.

OutputTensor

Type: const DML_TENSOR_DESC*

The output tensor to write the results to.

AxisCount

Type: UINT

The number of axes to calculate reduce hardmax. This field determines the size of the Axes array.

Axes

Type: _Field_size_(AxisCount) const UINT*

The axes along which to reduce hardmax. Values must be in the range [0, InputTensor.DimensionCount - 1].

Examples

The following examples all use this same three-dimensional input tensor:

InputTensor: (Sizes:{2, 2, 2}, DataType:FLOAT32)
[
    [
        [  12, 0],
        [-101, 11],
    ],
    [
        [  3,  234],
        [  0, -101],
    ]
]

Example 1

AxisCount: 1
Axes: {1}
OutputTensor: (Sizes:{2, 2, 2}, DataType:FLOAT32)
[
    [               // max element in {12, -101} is 12 and in {0, 11} is 11
        [1, 0],
        [0, 1],
    ],
    [               // max element in {3, 0} is 3 and in {234, -101} is 234
        [1, 1],
        [0, 0],
    ]
]

Example 2

AxisCount: 1
Axes: {0}
OutputTensor: (Sizes:{2, 2, 2}, DataType:FLOAT32)
[
    [               // max element in {12, 3} is 12, in {0, 234} is 234, in {-101, 0} is 0 and in {11, -101} is 11
        [1, 0],
        [0, 1],
    ],
    [
        [0, 1],
        [1, 0],
    ]
]

Example 3

AxisCount: 2
Axes: {0, 2}
OutputTensor: (Sizes:{2, 2, 2}, DataType:FLOAT32)
[
    [               // max element in {12, 0, 3, 234} is 234 and in {-101, 11, 0, -101} is 11
        [0, 0],
        [0, 1],
    ],
    [
        [0, 1],
        [0, 0],
    ]
]

Remarks

This operator is equivalent to DML_ACTIVATION_HARDMAX_OPERATOR_DESC when AxisCount == 1, and Axes == {DimensionCount - 1}.

Availability

This operator was introduced in DML_FEATURE_LEVEL_5_1.

Tensor constraints

InputTensor and OutputTensor must have the same DataType, DimensionCount, and Sizes.

Tensor support

Tensor Kind Supported dimension counts Supported data types
InputTensor Input 1 to 8 FLOAT32, FLOAT16
OutputTensor Output 1 to 8 FLOAT32, FLOAT16

Requirements

   
Header directml.h

See also