DML_MAX_POOLING1_OPERATOR_DESC structure (directml.h)

Computes the maximum value across the elements within the sliding window over the input tensor, and optionally returns the indices of the maximum values selected.

Syntax

struct DML_MAX_POOLING1_OPERATOR_DESC {
  const DML_TENSOR_DESC *InputTensor;
  const DML_TENSOR_DESC *OutputTensor;
  const DML_TENSOR_DESC *OutputIndicesTensor;
  UINT                  DimensionCount;
  const UINT            *Strides;
  const UINT            *WindowSize;
  const UINT            *StartPadding;
  const UINT            *EndPadding;
};

Members

InputTensor

Type: const DML_TENSOR_DESC*

An input tensor of Sizes { BatchCount, ChannelCount, Height, Width } if InputTensor.DimensionCount is 4, and { BatchCount, ChannelCount, Depth, Height, Weight } if InputTensor.DimensionCount is 5.

OutputTensor

Type: const DML_TENSOR_DESC*

An output tensor to write the results to. The sizes of the output tensor can be computed as follows.

OutputTensor->Sizes[0] = InputTensor->Sizes[0];
OutputTensor->Sizes[1] = InputTensor->Sizes[1];

for (UINT i = 0; i < DimensionCount; ++i) {
  UINT PaddedSize = InputTensor->Sizes[i + 2] + StartPadding[i] + EndPadding[i];
  OutputTensor->Sizes[i + 2] = (PaddedSize - WindowSizes[i]) / Strides[i] + 1;
}

OutputIndicesTensor

Type: _Maybenull_ const DML_TENSOR_DESC*

An optional output tensor of indices to the input tensor InputTensor of the maximum values produced and stored in the OutputTensor. These index values are zero-based and treat the input tensor as a contiguous one-dimensional array. When multiple elements within the sliding window have the same value, the later equal values are ignored and the index points to the first value encountered. Both the OutputTensor and OutputIndicesTensor have the same tensor sizes.

DimensionCount

Type: UINT

The number of spatial dimensions of the input tensor InputTensor, which also corresponds to the number of dimensions of the sliding window WindowSize. This value also determines the size of the Strides, StartPadding, and EndPadding arrays. It should be set to 2 when InputTensor is 4D, and 3 when it's a 5D tensor.

Strides

Type: _Field_size_(DimensionCount) const UINT*

The strides for the sliding window dimensions of sizes { Height, Width } when the DimensionCount is set to 2, or { Depth, Height, Width } when set to 3.

WindowSize

Type: _Field_size_(DimensionCount) const UINT*

The dimensions of the sliding window in { Height, Width } when DimensionCount is set to 2, or { Depth, Height, Width } when set to 3.

StartPadding

Type: _Field_size_(DimensionCount) const UINT*

The number of padding elements to be applied to the beginning of each spatial dimension of the input tensor InputTensor. The values are in { Height, Width } when DimensionCount is set to 2, or { Depth, Height, Width } when set to 3.

EndPadding

Type: _Field_size_(DimensionCount) const UINT*

The number of padding elements to be applied to the end of each spatial dimension of the input tensor InputTensor. The values are in { Height, Width } when DimensionCount is set to 2, or { Depth, Height, Width } when set to 3.

Remarks

When OutputIndicesTensor is set to NULL, this operator is equivalent to DML_MAX_POOLING_OPERATOR_DESC.

A newer version of this operator, DML_MAX_POOLING2_OPERATOR_DESC, was introduced in DML_FEATURE_LEVEL_2_1.

Availability

This operator was introduced in DML_FEATURE_LEVEL_2_0.

Tensor constraints

• InputTensor, OutputIndicesTensor, and OutputTensor must have the same DimensionCount.
• InputTensor and OutputTensor must have the same DataType.

Tensor support

DML_FEATURE_LEVEL_5_0 and above

DML_FEATURE_LEVEL_3_0 and above

DML_FEATURE_LEVEL_2_0 and above

Requirements