Attributes#

Introduction#

Name

Target

Required

Mutable

AvgPoolPrecisionPreserved

Precision

No

Yes

IntervalsAlignment

Quantization interval

Yes

Yes

PrecisionPreserved

Precision

Yes

Yes

Precisions

Precision

Yes

Yes

QuantizationAlignment

Quantization granularity

Yes

Yes

QuantizationGranularity

Quantization granularity

Yes

No

Target attribute group defines attribute usage during model transformation for the best performance:

  • Precision - the attribute defines the most optimal output port precision.

  • Quantization interval - the attribute defines quantization interval.

  • Quantization alignment - the attribute defines quantization granularity in runtime: per-channel or per-tensor quantization.

  • Quantization granularity - the attribute is set by plugin to define quantization granularity: per-channel or per-tensor quantization.

Required attribute group defines if attribute usage is required to get an optimal model during transformation:

  • Yes - the attribute is used by all OpenVINO plugins for low-precision optimization.

  • No - the attribute is used in a specific OpenVINO plugin.

Mutable attribute group defines if transformation can update an existing attribute:

  • Yes - the attribute can be updated by the next transformations in the pipeline. But attribute update order is still important.

  • No - existing attribute can not be updated by the next transformation. Previous handled transformation has optimized a model according to the current value.

FakeQuantize decomposition is a mandatory part of low precision transformations. Attributes used during decomposition are mandatory. Optional attributes are required only for certain operations.

Attributes usage by transformations:

Attribute name

Created by transformations

Used by transformations

PrecisionPreserved

MarkupPrecisions, MarkupAvgPoolPrecisionPreserved

AlignQuantizationIntervals, AlignQuantizationParameters, FakeQuantizeDecompositionTransformation, MarkupAvgPoolPrecisionPreserved

AvgPoolPrecisionPreserved

MarkupAvgPoolPrecisionPreserved

Precisions

MarkupCanBeQuantized, MarkupPrecisions

FakeQuantizeDecompositionTransformation

PerTensorQuantization

MarkupPerTensorQuantization

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.