Files
openvino/docs/ops/movement/Tile_1.md
Andrey Zaytsev 4ae6258bed Feature/azaytsev/from 2021 4 (#9247)
* Added info on DockerHub CI Framework

* Feature/azaytsev/change layout (#3295)

* Changes according to feedback comments

* Replaced @ref's with html links

* Fixed links, added a title page for installing from repos and images, fixed formatting issues

* Added links

* minor fix

* Added DL Streamer to the list of components installed by default

* Link fixes

* Link fixes

* ovms doc fix (#2988)

* added OpenVINO Model Server

* ovms doc fixes

Co-authored-by: Trawinski, Dariusz <dariusz.trawinski@intel.com>

* Updated openvino_docs.xml

* Updated the link to software license agreements

* Revert "Updated the link to software license agreements"

This reverts commit 706dac500e.

* Docs to Sphinx (#8151)

* docs to sphinx

* Update GPU.md

* Update CPU.md

* Update AUTO.md

* Update performance_int8_vs_fp32.md

* update

* update md

* updates

* disable doc ci

* disable ci

* fix index.rst

Co-authored-by: Andrey Zaytsev <andrey.zaytsev@intel.com>
# Conflicts:
#	.gitignore
#	docs/CMakeLists.txt
#	docs/IE_DG/Deep_Learning_Inference_Engine_DevGuide.md
#	docs/IE_DG/Extensibility_DG/Custom_ONNX_Ops.md
#	docs/IE_DG/Extensibility_DG/VPU_Kernel.md
#	docs/IE_DG/InferenceEngine_QueryAPI.md
#	docs/IE_DG/Int8Inference.md
#	docs/IE_DG/Integrate_with_customer_application_new_API.md
#	docs/IE_DG/Model_caching_overview.md
#	docs/IE_DG/supported_plugins/GPU_RemoteBlob_API.md
#	docs/IE_DG/supported_plugins/HETERO.md
#	docs/IE_DG/supported_plugins/MULTI.md
#	docs/MO_DG/prepare_model/convert_model/Convert_Model_From_Caffe.md
#	docs/MO_DG/prepare_model/convert_model/Convert_Model_From_Kaldi.md
#	docs/MO_DG/prepare_model/convert_model/Convert_Model_From_MxNet.md
#	docs/MO_DG/prepare_model/convert_model/Convert_Model_From_ONNX.md
#	docs/MO_DG/prepare_model/convert_model/Converting_Model.md
#	docs/MO_DG/prepare_model/convert_model/Converting_Model_General.md
#	docs/MO_DG/prepare_model/convert_model/Cutting_Model.md
#	docs/MO_DG/prepare_model/convert_model/pytorch_specific/Convert_RNNT.md
#	docs/MO_DG/prepare_model/convert_model/tf_specific/Convert_EfficientDet_Models.md
#	docs/MO_DG/prepare_model/convert_model/tf_specific/Convert_WideAndDeep_Family_Models.md
#	docs/MO_DG/prepare_model/convert_model/tf_specific/Convert_YOLO_From_Tensorflow.md
#	docs/doxygen/Doxyfile.config
#	docs/doxygen/ie_docs.xml
#	docs/doxygen/ie_plugin_api.config
#	docs/doxygen/ngraph_cpp_api.config
#	docs/doxygen/openvino_docs.xml
#	docs/get_started/get_started_macos.md
#	docs/get_started/get_started_raspbian.md
#	docs/get_started/get_started_windows.md
#	docs/img/cpu_int8_flow.png
#	docs/index.md
#	docs/install_guides/VisionAcceleratorFPGA_Configure.md
#	docs/install_guides/VisionAcceleratorFPGA_Configure_Windows.md
#	docs/install_guides/deployment-manager-tool.md
#	docs/install_guides/installing-openvino-linux.md
#	docs/install_guides/installing-openvino-macos.md
#	docs/install_guides/installing-openvino-windows.md
#	docs/optimization_guide/dldt_optimization_guide.md
#	inference-engine/ie_bridges/c/include/c_api/ie_c_api.h
#	inference-engine/ie_bridges/python/docs/api_overview.md
#	inference-engine/ie_bridges/python/sample/ngraph_function_creation_sample/README.md
#	inference-engine/ie_bridges/python/sample/speech_sample/README.md
#	inference-engine/ie_bridges/python/src/openvino/inference_engine/ie_api.pyx
#	inference-engine/include/ie_api.h
#	inference-engine/include/ie_core.hpp
#	inference-engine/include/ie_version.hpp
#	inference-engine/samples/benchmark_app/README.md
#	inference-engine/samples/speech_sample/README.md
#	inference-engine/src/plugin_api/exec_graph_info.hpp
#	inference-engine/src/plugin_api/file_utils.h
#	inference-engine/src/transformations/include/transformations_visibility.hpp
#	inference-engine/tools/benchmark_tool/README.md
#	ngraph/core/include/ngraph/ngraph.hpp
#	ngraph/frontend/onnx_common/include/onnx_common/parser.hpp
#	ngraph/python/src/ngraph/utils/node_factory.py
#	openvino/itt/include/openvino/itt.hpp
#	thirdparty/ade
#	tools/benchmark/README.md

* Cherry-picked remove font-family (#8211)

* Cherry-picked: Update get_started_scripts.md (#8338)

* doc updates (#8268)

* Various doc changes

* theme changes

* remove font-family (#8211)

* fix  css

* Update uninstalling-openvino.md

* fix css

* fix

* Fixes for Installation Guides

Co-authored-by: Andrey Zaytsev <andrey.zaytsev@intel.com>
Co-authored-by: kblaszczak-intel <karol.blaszczak@intel.com>
# Conflicts:
#	docs/IE_DG/Bfloat16Inference.md
#	docs/IE_DG/InferenceEngine_QueryAPI.md
#	docs/IE_DG/OnnxImporterTutorial.md
#	docs/IE_DG/supported_plugins/AUTO.md
#	docs/IE_DG/supported_plugins/HETERO.md
#	docs/IE_DG/supported_plugins/MULTI.md
#	docs/MO_DG/prepare_model/convert_model/Convert_Model_From_Kaldi.md
#	docs/MO_DG/prepare_model/convert_model/tf_specific/Convert_YOLO_From_Tensorflow.md
#	docs/install_guides/installing-openvino-macos.md
#	docs/install_guides/installing-openvino-windows.md
#	docs/ops/opset.md
#	inference-engine/samples/benchmark_app/README.md
#	inference-engine/tools/benchmark_tool/README.md
#	thirdparty/ade

* Cherry-picked: doc script changes (#8568)

* fix openvino-sphinx-theme

* add linkcheck target

* fix

* change version

* add doxygen-xfail.txt

* fix

* AA

* fix

* fix

* fix

* fix

* fix
# Conflicts:
#	thirdparty/ade

* Cherry-pick: Feature/azaytsev/doc updates gna 2021 4 2 (#8567)

* Various doc changes

* Reformatted C++/Pythob sections. Updated with info from PR8490

* additional fix

* Gemini Lake replaced with Elkhart Lake

* Fixed links in IGs, Added 12th Gen
# Conflicts:
#	docs/IE_DG/supported_plugins/GNA.md
#	thirdparty/ade

* Cherry-pick: Feature/azaytsev/doc fixes (#8897)

* Various doc changes

* Removed the empty Learning path topic

* Restored the Gemini Lake CPIU list
# Conflicts:
#	docs/IE_DG/supported_plugins/GNA.md
#	thirdparty/ade

* Cherry-pick: sphinx copybutton doxyrest code blocks (#8992)

# Conflicts:
#	thirdparty/ade

* Cherry-pick: iframe video enable fullscreen (#9041)

# Conflicts:
#	thirdparty/ade

* Cherry-pick: fix untitled titles (#9213)

# Conflicts:
#	thirdparty/ade

* Cherry-pick: perf bench graph animation (#9045)

* animation

* fix
# Conflicts:
#	thirdparty/ade

* Cherry-pick: doc pytest (#8888)

* docs pytest

* fixes
# Conflicts:
#	docs/doxygen/doxygen-ignore.txt
#	docs/scripts/ie_docs.xml
#	thirdparty/ade

* Cherry-pick: restore deleted files (#9215)

* Added new operations to the doc structure (from removed ie_docs.xml)

* Additional fixes

* Update docs/IE_DG/InferenceEngine_QueryAPI.md

Co-authored-by: Helena Kloosterman <helena.kloosterman@intel.com>

* Update docs/IE_DG/Int8Inference.md

Co-authored-by: Helena Kloosterman <helena.kloosterman@intel.com>

* Update Custom_Layers_Guide.md

* Changes according to review  comments

* doc scripts fixes

* Update docs/IE_DG/Int8Inference.md

Co-authored-by: Helena Kloosterman <helena.kloosterman@intel.com>

* Update Int8Inference.md

* update xfail

* clang format

* updated xfail

Co-authored-by: Trawinski, Dariusz <dariusz.trawinski@intel.com>
Co-authored-by: Nikolay Tyukaev <nikolay.tyukaev@intel.com>
Co-authored-by: kblaszczak-intel <karol.blaszczak@intel.com>
Co-authored-by: Yury Gorbachev <yury.gorbachev@intel.com>
Co-authored-by: Helena Kloosterman <helena.kloosterman@intel.com>
2021-12-21 20:26:37 +03:00

3.2 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>