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DOCS: Low Precision Transformations proofreading for 22.3 (#14511)
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* Attributes
* Update lpt_attributes.md
* defines-fix
* revert principle
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sgolebiewski-intel authored Dec 16, 2022
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# AvgPoolPrecisionPreserved attribute {#openvino_docs_OV_UG_lpt_AvgPoolPrecisionPreserved}
# AvgPoolPrecisionPreserved Attribute {#openvino_docs_OV_UG_lpt_AvgPoolPrecisionPreserved}

ngraph::AvgPoolPrecisionPreservedAttribute class represents the `AvgPoolPrecisionPreserved` attribute.

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# IntervalsAlignment attribute {#openvino_docs_OV_UG_lpt_IntervalsAlignment}
# IntervalsAlignment Attribute {#openvino_docs_OV_UG_lpt_IntervalsAlignment}

ngraph::IntervalsAlignmentAttribute class represents the `IntervalsAlignment` attribute.

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# PrecisionPreserved attribute {#openvino_docs_OV_UG_lpt_PrecisionPreserved}
# PrecisionPreserved Attribute {#openvino_docs_OV_UG_lpt_PrecisionPreserved}

ngraph::PrecisionPreservedAttribute class represents the `PrecisionPreserved` attribute.

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# Precisions attribute {#openvino_docs_OV_UG_lpt_Precisions}
# Precisions Attribute {#openvino_docs_OV_UG_lpt_Precisions}

ngraph::PrecisionsAttribute class represents the `Precisions` attribute.

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# QuantizationAlignment attribute {#openvino_docs_OV_UG_lpt_QuantizationAlignment}
# QuantizationAlignment Attribute {#openvino_docs_OV_UG_lpt_QuantizationAlignment}

ngraph::QuantizationAlignmentAttribute class represents the `QuantizationAlignment` attribute.

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# QuantizationGranularity attribute {#openvino_docs_OV_UG_lpt_QuantizationGranularity}
# QuantizationGranularity Attribute {#openvino_docs_OV_UG_lpt_QuantizationGranularity}

ngraph::QuantizationAttribute class represents the `QuantizationGranularity` attribute.

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Expand Up @@ -54,4 +54,4 @@ Attributes usage by transformations:
| IntervalsAlignment | AlignQuantizationIntervals | FakeQuantizeDecompositionTransformation |
| QuantizationAlignment | AlignQuantizationParameters | FakeQuantizeDecompositionTransformation |

> **NOTE**: The same type of attribute instances can be created in different transformations. This approach is the result of the transformation single-responsibility principle. For example, `Precision` attribute instances are created in `MarkupCanBeQuantized` and `MarkupPrecisions` transformations, but the reasons for their creation are different.
> **NOTE**: The same type of attribute instances can be created in different transformations. This approach is the result of the transformation single-responsibility principle. For example, `Precision` attribute instances are created in `MarkupCanBeQuantized` and `MarkupPrecisions` transformations, but the reasons for their creation are different.

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