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...precision_transformations/quantization/pipelines/fake_quantize_decomposition.md
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| # OpenVINO™ Low Precision Transformations: FakeQuantizeDecompositionTransformation pipelines | ||
| ## Table of Contents | ||
| 1. [Introduction](#introduction) | ||
| 2. [Pipeline #1: FakeQuantize decomposition](#pipeline-1-fakequantize-decomposition) | ||
| 3. [Pipeline #2: Concat per-tensor quantization](#pipeline-2-concat-per-tensor-quantization) | ||
| 4. [Pipeline #3: Concat multi-channels quantization](#pipeline-3-concat-multi-channels-quantization) | ||
| 5. [Pipeline #4: FakeQuantize connects neighbor cascade Concat operations](#pipeline-4-fakequantize-connects-neighbor-cascade-concat-operations) | ||
| 6. [Pipeline #5: AvgPool precision propagation](#pipeline-5-avgpool-precision-propagation) | ||
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| ## Introduction | ||
| `FakeQuantizeDecompositionTransformation` decomposes `FakeQuantize` operation on quantize (`FakeQuantize` with low precision output) and dequantization operations (`Convert`, `Subtract` and `Multiply`). `FakeQuantize` result output precision depends on: | ||
| 1. Next operation supported input precision. Customizable parameter `precisionsOnActivations` is used for identifying supported input precision. | ||
| 2. Operation output intervals. | ||
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| ## Pipeline #1: FakeQuantize decomposition | ||
| [NOT UPDATED] | ||
| Features: | ||
| 1. `FakeQuantize` on activations operation output intervals are signed, default precision should be `signed int8` which is not supported by `Convolution` bellow. | ||
| 2. Quantize and dequantize operations on activations are presented by one `Fakequantize` operation. | ||
| 3. Quantize and dequantize operations on weights are presented by one `Fakequantize` operation. | ||
| 4. There is no `FakeQuantize` between `AvgPool` and `Convolution`. | ||
| 5. `Convolution` weights are quantized. | ||
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| > TODO: if `Convolution` is not quantized then [[input] port] requirements are not set. <= WIP | ||
| > TODO: if operation is not precision preserved then `PRECISION_PRESERVED` attribute can be skipped. <= WIP: right now: created everywhere | ||
| ### Original model | ||
|  | ||
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| ### Markup precisions | ||
|  | ||
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| ### Markup AvgPool precisions (CPU/GPU specific) | ||
|  | ||
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| ### Propagate precisions | ||
|  | ||
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| ### Transformations | ||
|  | ||
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| ## Pipeline #2: Concat per-tensor quantization | ||
| [NOT UPDATED] | ||
| Features: | ||
| 1. `FakeQuantize` on activations operations output intervals are signed, default precision should be `signed int8` which is not supported by `Convolution` bellow. | ||
| 2. `FakeQuantize` on activations operations have different output intervals which will be aligned. | ||
| 3. Quantize and dequantize operations on activations are presented by one `Fakequantize` operation. | ||
| 4. Quantize and dequantize operations on weights are presented by one `Fakequantize` operation. | ||
| 5. There is no `FakeQuantize` between `AvgPool` and `Convolution`. | ||
| 6. `Convolution` weights are quantized. | ||
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| > TODO: `Convolution` operation defines `ConcatTransformation` behavior for each plugin and the behavior is not configurable. | ||
| > TODO: if `Convolution` is not quantized then `FakeQuantize` are not aligned <= WIP: `MarkupPrecisions` tranformation checks each operation quantization and add empty [input [port]] requirements if operation is not quantized. | ||
| > TODO: if `ConvolutionTransformation` is skipped ([input [port]] requirements are empty) then `FakeQuantize` are not aligned <= WIP | ||
| > TODO: if `Convolution` operation doesn't exist then `FakeQuantize` are not aligned <= WIP | ||
| ### Original model | ||
|  | ||
|
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||
| ### Markup precisions | ||
|  | ||
|
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||
| ### Markup AvgPool precisions (CPU/GPU specific) | ||
|  | ||
|
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| ### Propagate precisions | ||
|  | ||
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| ### Align concatization quantization | ||
|  | ||
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| ### Transformations | ||
|  | ||
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| ## Pipeline #3: Concat multi-channels quantization | ||
| [NOT UPDATED] | ||
| Features: | ||
| 1. Quantize and dequantize operations on activations are presented by one `Fakequantize` operation. | ||
| 2. There is no `FakeQuantize` between `AvgPool` and `Result`. | ||
|
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||
| ### Original model | ||
|  | ||
|
|
||
| ### Markup precisions | ||
|  | ||
|
|
||
| ### Markup AvgPool precisions (CPU/GPU specific) | ||
|  | ||
|
|
||
| ### Propagate precisions | ||
|  | ||
|
|
||
| ### Align concatization quantization | ||
|  | ||
|
|
||
| ### Transformations | ||
|  | ||
|
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| ## Pipeline #4: FakeQuantize connects neighbor cascade Concat operations | ||
| Features: | ||
| 1. Quantize and dequantize operations on activations are presented by one `Fakequantize` operation. | ||
| 2. There is `FakeQuantize` between two `Concat` subgraphs: the first uses multi-channel quantization, the second uses per-tensor quantization. | ||
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| > Source: `ConcatWithNeighborsWithConvolutionTransformation` functional test. | ||
| ### Original model | ||
|  | ||
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| ### Markup precisions | ||
|  | ||
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||
| ### Markup AvgPool precisions (CPU/GPU specific) | ||
|  | ||
|
|
||
| ### Propagate precisions | ||
|  | ||
|
|
||
| ### Align concatization intervals | ||
|  | ||
|
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||
| ### Align concatization quantization | ||
|  | ||
|
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| ### Transformations | ||
|  | ||
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| ## Pipeline #5: AvgPool precision propagation | ||
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| Features: | ||
| 1. There is `FakeQuantize` after `AvgPool`. | ||
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| > Source: `MarkupAvgPoolPrecisionsTransformation` functional test. | ||
| ### Original model | ||
|  | ||
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| ### Markup precisions | ||
|  | ||
|
|
||
| ### Markup AvgPool precisions (CPU/GPU specific) | ||
|  | ||
|
|
||
| ### Propagate precisions | ||
|  | ||
|
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||
| ### Align concatization quantization | ||
|  | ||
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| ### Transformations | ||
|  |
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