* Doc Migration from Gitlab (#1289) * doc migration * fix * Update FakeQuantize_1.md * Update performance_benchmarks.md * Updates graphs for FPGA * Update performance_benchmarks.md * Change DL Workbench structure (#1) * Changed DL Workbench structure * Fixed tags * fixes * Update ie_docs.xml * Update performance_benchmarks_faq.md * Fixes in DL Workbench layout * Fixes for CVS-31290 * [DL Workbench] Minor correction * Fix for CVS-30955 * Added nGraph deprecation notice as requested by Zoe * fix broken links in api doxy layouts * CVS-31131 fixes * Additional fixes * Fixed POT TOC * Update PAC_Configure.md PAC DCP 1.2.1 install guide. * Update inference_engine_intro.md * fix broken link * Update opset.md * fix * added opset4 to layout * added new opsets to layout, set labels for them * Update VisionAcceleratorFPGA_Configure.md Updated from 2020.3 to 2020.4 Co-authored-by: domi2000 <domi2000@users.noreply.github.com>
3.0 KiB
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
- Description: block_size specifies the size of the value block to be moved. The depth dimension size must be evenly divided by
-
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]
- blocks_first: the output depth is gathered from
- 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>