ef45b5da8d
* 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>
3.3 KiB
3.3 KiB
Tile
Versioned name: Tile-1
Category: Data movement
Short description: Tile operation repeats an input tensor "data" the number of times given by "repeats" input tensor along each dimension.
- If number of elements in "repeats" is more than shape of "data", then "data" will be promoted to "repeats" by prepending new axes, e.g. let's shape of "data" is equal to (2, 3) and "repeats" is equal to [2, 2, 2], then shape of "data" will be promoted to (1, 2, 3) and result shape will be (2, 4, 6).
- If number of elements in "repeats" is less than shape of "data", then "repeats" will be promoted to "data" by prepending 1's to it, e.g. let's shape of "data" is equal to (4, 2, 3) and "repeats" is equal to [2, 2], then "repeats" will be promoted to [1, 2, 2] and result shape will be (4, 4, 6)
Attributes:
No attributes available.
Inputs:
- 1: "data" - an input tensor to be padded. A tensor of type T1. Required.
- 2: "repeats" - a per-dimension replication factor. For example, repeats equal to 88 means that the output tensor gets 88 copies of data from the specified axis. A tensor of type T2. Required.
Outputs:
- 1: The count of dimensions in result shape will be equal to the maximum from count of dimensions in "data" shape and number of elements in "repeats". A tensor with type matching 1st tensor.
Types
- T1: arbitrary supported type.
- T2: any integer type.
Detailed description:
Tile operation extends input tensor and filling in output tensor by the following rules:
\f[out_i=input_i[inner_dim*t]\f] \f[ t \in \left ( 0, \quad tiles \right ) \f]
Examples
Example 1: number elements in "repeats" is equal to shape of data
<layer ... type="Tile">
<input>
<port id="0">
<dim>2</dim>
<dim>3</dim>
<dim>4</dim>
</port>
<port id="1">
<dim>3</dim> <!-- [1, 2, 3] -->
</port>
</input>
<output>
<port id="2">
<dim>2</dim>
<dim>6</dim>
<dim>12</dim>
</port>
</output>
</layer>
Example 2: number of elements in "repeats" is more than shape of "data"
<layer ... type="Tile">
<input>
<port id="0"> <!-- will be promoted to shape (1, 2, 3, 4) -->
<dim>2</dim>
<dim>3</dim>
<dim>4</dim>
</port>
<port id="1">
<dim>4</dim> <!-- [5, 1, 2, 3] -->
</port>
</input>
<output>
<port id="2">
<dim>5/dim>
<dim>2</dim>
<dim>6</dim>
<dim>12</dim>
</port>
</output>
</layer>
Example 3: number of elements in "repeats" is less than shape of "data"
<layer ... type="Tile">
<input>
<port id="0">
<dim>5</dim>
<dim>2</dim>
<dim>3</dim>
<dim>4</dim>
</port>
<port id="1">
<dim>3</dim> <!-- [1, 2, 3] will be promoted to [1, 1, 2, 3] -->
</port>
</input>
<output>
<port id="2">
<dim>5</dim>
<dim>2</dim>
<dim>6</dim>
<dim>12</dim>
</port>
</output>
</layer>