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>
67 lines
2.8 KiB
Markdown
67 lines
2.8 KiB
Markdown
## OneHot <a name="OneHot"></a> {#openvino_docs_ops_sequence_OneHot_1}
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**Versioned name**: *OneHot-1*
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**Category**: Sequence processing
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**Short description**: *OneHot* sets the elements in the output tensor with specified indices to `on_value` and fills all other locations with `off_value`.
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**Detailed description**
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Taking a tensor with rank `N` as the first input `indices`, OneHot produces tensor with rank `N+1` extending original
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tensor with a new dimension at `axis` position in shape. Output tensor is populated with two scalar values: `on_value`
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that comes from the 3rd input and `off_value` that comes from the 4nd input. Population is made in the following way:
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output[:, ... ,:, i, :, ... ,:] = on_value if (indices[:, ..., :, :, ..., :] == i) else off_value
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where `i` is at `axis` position in `output` shape and has values from range `[0, ..., depth-1]`.
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When index element from `indices` is greater or equal to `depth`, it is a well-formed operation. In this case the corresponding row `output[..., i, ...]` is populated with `off_value` only for all `i` values.
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Types of input scalars `on_value` and `off_value` should match and can be any of the supported types. The type of output tensor is derived from `on_value` and `off_value`, they all have the same type.
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**Attributes**:
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* *axis*
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* **Description**: *axis* is a new axis position in the output shape to fill with one-hot values.
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* **Range of values**: an integer. Negative value means counting dimension from the end.
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* **Type**: `int`
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* **Default value**: None
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* **Required**: *yes*
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**Inputs**:
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* **1**: `indices`: input tensor of rank `N` with indices of any supported integer data type. Can be 0D. Required.
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* **2**: `depth`: scalar (0D tensor) of any supported integer type that specifies number of classes and the size of one-hot dimension.
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* **3**: `on_value`: scalar (0D tensor) of any type that is the value that the locations in output tensor represented by indices in input take.
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* **4**: `off_value`: scalar (0D tensor) of any type that is the value that the locations not represented by indices in input take.
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**Outputs**:
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* **1** Output tensor of rank `N+1`, where `N` is a rank of input tensor `indices`. A new axis of the size `depth` is inserted at the dimension `axis`.
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**Examples**
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```xml
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<layer ... type="OneHot" ...>
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<data axis="-1"/>
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<input>
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<port id="0"> <!-- indices value: [0, 1, 2] -->
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<dim>3</dim>
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</port>
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<port id="1"> <!-- depth value: 2 -->
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</port>
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<port id="2"> <!-- on_value 5 -->
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</port>
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<port id="3"> <!-- off_value 10 -->
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</port>
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</input>
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<output>
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<port id="0"> <!-- output value # [[5, 10], [10, 5], [10, 10]] -->
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<dim>3</dim>
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<dim>2</dim>
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</port>
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</output>
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</layer>
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``` |