SpaceToDepth

Versioned name: SpaceToDepth-1

Category: Data movement

Short description: SpaceToDepth operation rearranges data from the spatial dimensions of the input tensor into depth dimension of the output tensor.

Attributes

• block_size
  • Description: block_size specifies the size of the value block to be moved. The depth dimension size must be evenly divided by block_size ^ (len(input.shape) - 2).
  • Range of values: a positive integer
  • Type: int
  • Default value: 1
  • Required: no
• mode
  • Description: specifies how the output depth dimension is gathered from block coordinates and the old depth dimension.
  • Range of values:
    • blocks_first: the output depth is gathered from [block_size, ..., block_size, C]
    • depth_first: the output depth is gathered from [C, block_size, ..., block_size]
  • Type: string
  • Default value: None
  • Required: yes

Inputs

• 1: data - input tensor of any type with rank >= 3. Required.

Outputs

• 1: permuted tensor with shape [N, C * (block_size ^ K), D1 / block_size, D2 / block_size, ..., DK / block_size].

Detailed description

SpaceToDepth operation permutes element from the input tensor with shape [N, C, D1, D2, ..., DK], to the output tensor where values from the input spatial dimensions D1, D2, ..., DK are moved to the new depth dimension. Refer to the ONNX* specification for an example of the 4D input tensor case.

The operation is equivalent to the following transformation of the input tensor data with K spatial dimensions of shape [N, C, D1, D2, ..., DK] to Y output tensor. If mode = blocks_first:

x' = reshape(data, [N, C, D1/block_size, block_size, D2/block_size, block_size, ... , DK/block_size, block_size])

x'' = transpose(x',  [0,  3, 5, ..., K + (K + 1), 1,  2, 4, ..., K + K])

y = reshape(x'', [N, C * (block_size ^ K), D1 / block_size, D2 / block_size, ... , DK / block_size])

If mode = depth_first:

x' = reshape(data, [N, C, D1/block_size, block_size, D2/block_size, block_size, ..., DK/block_size, block_size])

x'' = transpose(x', [0,  1, 3, 5, ..., K + (K + 1),  2, 4, ..., K + K])

y = reshape(x'', [N, C * (block_size ^ K), D1 / block_size, D2 / block_size, ..., DK / block_size])

Example

<layer type="SpaceToDepth" ...>
    <data block_size="2" mode="blocks_first"/>
    <input>
        <port id="0">
            <dim>5</dim>
            <dim>7</dim>
            <dim>4</dim>
            <dim>6</dim>
        </port>
    </input>
    <output>
        <port id="1">
            <dim>5</dim>    <!-- data.shape[0] -->
            <dim>28</dim>   <!-- data.shape[1] * (block_size ^ 2) -->
            <dim>2</dim>    <!-- data.shape[2] / block_size -->
            <dim>3</dim>    <!-- data.shape[3] / block_size -->
        </port>
    </output>
</layer>